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Primary and Reproductive Health in the Slums of
Trivandrum City
I. Introduction
1.1
India is the first country to initiate a national
family planning programme, integrated in the Primary Health Care
system, to contain the rate of population growth. It started as family
planning program, expanded into family welfare, covering both maternal
and child health (MCH) care and family planning. After the
International conference on Population and Development (ICPD)of 1994 in
Cairo, it became reproductive and child health, which included services
of reproductive tract infection, sexually transmitted diseases and
HIV/AIDS. Besides the expansion of services in the post-ICPD era, the
basic strategy of the Indian programme changed from target-orientation
to a need- based approach, focusing on meeting the needs of the members
of the community rather than achievements of certain national
demographic goals. In other words, the philosophy of its implementation
has undergone a change; it has become a two-step process of assessment
of the community needs (CNA) as the first step, and meeting those
needs, as the second.
1.1.1 Mainly a rural country, India has 72 per
cent of its population living in rural areas (Census 2001a). It was
therefore natural that all developmental efforts including those
related to health and family welfare focused on rural areas right from
the beginning. Successive Five Year Developmental Plans expanded the
infrastructure and activities. Today, a reasonable network of health
infrastructure has been created in rural areas, providing both
reproductive and primary health care services. Focus on rural areas and
constraints of resources in the programme led to a slow progress of
reproductive and primary health care services in urban areas. It was
presumed that better economic status and greater awareness of the urban
population and better accessibility of services there will help them to
take care of their own health including reproductive health goals. This
expectation, fell far short for the slum population groups living in
urban areas. This group forms about 40 percent of the large
metropolitan areas. It is therefore important that reproductive and
primary health care services in the slums receive adequate emphasis.
With this backdrop it is felt necessary to undertake a well-designed
study on reproductive and primary health care services in urban slums,
covering both dimensions of the service needs of people and how they
are being met or unmet.. The emphasis of the study should be on
policies, programmes and their implementation, and acceptance or
non-acceptance by the people. It should ultimately help in
strengthening the reproductive and primary health care services in
urban areas for meeting the needs for the slum population groups in
India. This study was conducted in the city of Trivandrum (also spelt
Thiruvananthapuram), the capital of the state of Kerala in India.
1.1.2 India, with a population of one billion,
has 28 States administered by their own elected governments and seven
Union Territories administered by the Centre. Kerala in the southwest
corner of the country is a small state, which takes up 1.27 per cent of
the land area and 3.1 percent of the population. The state was formed
in 1956 when the states of the country were re-organised on linguistic
lines. Till then the state was in three distinct regions. The
southernmost region was called Travancore and was ruled by the Maharaja
of Travancore till 1947 when the country gained independence from the
British. The middle region called Cochin (Kochi) was ruled by another
Maharaja. Both these monarchs owed their allegiance to the British
monarch who had suzerainty over the whole of India. But the
northernmost region called Malabar was directly ruled by the British as
part of the Presidency of Madras.
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1.1.3 The state has many features
that make it different from the other states of the country. The most
striking is the settlement pattern of the people. They live in small
homesteads from one end of the state to the other without much of a
difference between rural and urban areas. The population density is 819
per Sq. Km. against 324 of India. It has a coastal line of about 600
Kms. along the Arabian Sea and a width of about 60 Kms., bounded by the
mountain range of Western Ghats. It has been called a rural-urban
continuum where the villages are only administrative boundaries and the
towns, a thicker concentration of houses. Most of the villages (85.3
per cent) are well connected by motorable roads against 36.8 per cent
in the country. Similarly nearly 95per cent of the Kerala villages have
a bus stop within 5 Kms. and a Post Office within 2 Kms. against 64.5
and 70.2 per cent respectively for the country. The difference is even
more striking when it comes to telephones. More than 85per cent of
Kerala villages have telephone facility within two Kms. whereas only
51per cent of the villages in the country have it (Shariff, 1999). The
development of the rural areas has been so good that the urban
population has actually declined from 26.39 per cent in 1991 to 25.97
in 2001 (Census 2001a)
1.1.4 The next feature that strikes a casual
visitor to the state is the mix of religions. While India’s population
is a mixture of 12 per cent Muslims and 2 per cent Christians, most of
the others being Hindus, in Kerala Muslims are 21per cent and
Christians 20 per cent according to the Census of 1991. On the
political front the state is reported to be the first in the world to
have an elected communist government. The origins of communism can be
traced to the spread of literacy among a people who suffered from the
yoke of feudal tyranny in the agrarian sector. Literacy itself owes its
origin to the liberal policies of the Monarchs of Travancore and Cochin
and the efforts of Christian missionaries. The World Bank’s World
Development Report of 1991 cites the Royal Rescript of the Maharani of
Travancore in 1817 that commits the state to “defray the entire cost of
the education of its people in order that there may be no backwardness
in the spread of enlightenment among them”. Initially education was the
prerogative of the upper caste Hindus. But social reform movements that
started as a protest against the institutionalisation of social
exclusion by the upper casts, began demanding education for the
backward communities (Vijayachandran 2001). Spread of education has
been the prime mover of the development of the state, leading to a
literacy level of 91per cent and a female literacy level of 88per cent
against the all India figures of 65.4 and 54.2 per cent respectively in
2001.
1.1.5 However, job opportunities in the State
are very meagre and large segments of the workforce go outside the
state and the country seeking employment. The remittances from these
non-resident Keralites are a great source of income for their families
at home and keep the economy afloat. In spite of this, it remains one
of the poorer states of the country, with a per capita income less than
the national average. The Government estimate of per capita income for
1999-2000 is Rs.19461, which works out to about US$ 423 at the current
exchange rate (GOK 2000a).
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1.1.6 According to the estimates
of poverty by the Planning Commission of Government of India for
1999-2000, the poverty in the state is concentrated in the urban areas
with 20.27 per cent of the population living below the poverty line.
This means that they do not have the required financial capacity to
purchase food, which will fetch 2100 calories for an individual in a
day. It is noteworthy that the figure of poverty in the rural areas of
Kerala is very low at 9.38 per cent. But for the country as a whole the
situation is just the reverse with 27.09 per cent in the rural areas
and 23.62 per cent in the urban areas (Narayana 2001). This is a
telling example of the quality of life in the rural areas of Kerala.
1.1.7 Though the State is poor, it leads all the
other states in every indicator of health. It has often been compared
with many advanced countries of the world in its health status. Table
1.1 below gives a picture of the quality of life in the state in
comparison with the rest of the country and some other countries of
Asia.
Table 1.1 Selected Indicators of Development for
Kerala and Some Asian Countries
| Country / State |
Population (million) 1994 |
GDP Per Capita PPS $ 1994 |
HPI value (%)
1996 |
Population below International Poverty line
1985 (one PPS $ /day) |
Female Literacy Rate (%) 1994 |
Gross enrolment ratio (1995) in Secondary
Schools |
Life Expectancy Year 1994 |
Total Fertility Rate |
IMR 1994 |
| 1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
| Kerala |
30.5 |
1618 |
15.0 |
NA |
86.3 |
103 |
71.7 |
108 |
13* |
| India |
918.6 |
1348 |
36.7 |
52.0 |
39.0 |
49 |
61.3 |
3.0 |
74 |
| Sri Lanka |
18.1 |
3277 |
20.7 |
4.0 |
86.9 |
75 |
72.2 |
1.7 |
16 |
| Thailand |
58.2 |
7104 |
11.7 |
0.1 |
90.7 |
55 |
69.5 |
1.8 |
29 |
| Malaysia |
19.7 |
8865 |
NA |
5.6 |
77.5 |
57 |
71.2 |
3.4 |
12 |
| Indonesia |
194.6 |
3740 |
20.8 |
14.5 |
77.1 |
48 |
63.5 |
2.5 |
53 |
| China |
1208.8 |
2604 |
17.5 |
29.4 |
70.9 |
67 |
68.9 |
1.8 |
43 |
* According to National Family Health Survey for
1998-99, the IMR for Kerala is 16.3.
Notes: HPI: Human Poverty Index. This takes into account (i) the
survival deprivation in terms of people not expected to survive to age
40, (ii) a composite index of deprivation in economic provisioning
indicated by (a) population without access to safe water, (b)
population without access to health services, and (c) underweight
children under the age of five.
Source: Kannan, 1999.
1.1.8 As can be seen in this table, Kerala with
less than a fifth of the income of Malaysia, has achieved about the
same levels of life expectancy and infant mortality. In fact in total
fertility and female literacy Kerala is much ahead. Only Thailand has a
lower Human Poverty Index than Kerala. The annual growth rate of
population in Kerala has come down from 2.33 per cent in 1951-71 to 0.9
in 1991-2001 (Census 2001b). With all these statistics UNDP put the
human development index for Kerala at 62.79, 20 notches above that for
India. Even for China and Egypt, two countries known for their high
physical quality of life, the figures are only 60.9 and 61.1
respectively (Srinivasan & Shariff 1997)
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1.1.9 The State has a fairly good
health infrastructure in the public sector. The All India pattern of
one sub-centre with an Auxiliary Nurse Midwife for 5000 population, one
Primary Health Centre (PHC) for 25,000-30,000, and a Community Health
Centre for 100,000 dots the Kerala landscape with these institutions. A
woman of Kerala has to travel typically only 1.5 Kms. to reach a sub
centre for antenatal care or for immunising her child, whereas in the
rest of the country the radial distance to a sub centre is 2.7 Kms. A
typical PHC in the country covers an area of 143.08 Sq. Kms. with a
radial distance of 6.8 Kms. and in Kerala 37 Sq. Kms. with a radial
distance of 3.4 Kms. All put together the Government runs 1317
institutions manned by 4367 doctors trained in the modern system of
medicine with 45684 beds (GOK 2000). If the institutions and beds in
the other systems of medicine (mainly Homeopathy and the Indian System
of Medicine called Ayurveda) are added it comes to 2672 institutions
and 48258 beds. That is about one bed for 650 persons in the public
sector alone. But if we add the facilities in the private sector for
all the three systems of medicine there are altogether 1529
institutions and 120182 beds for a population of 31 million which is
one bed for every 258 persons, something that not even many developed
countries can dream of (Vijayachandran 2001).
1.1.10 However health planners have long been
aware of the fact that in this state of high social development there
are pockets untouched by all these improvements where malnutrition,
poverty and low health status still prevail. Three such islands are
mentioned by writers, namely the hilly areas inhabited by tribes, the
coastal areas occupied by the fishing community and the slums of the
cities. (Ramachandran 1996) this study will explore whether this is
true of the slums of the city of Trivandrum.
1.1.11 The city of Trivandrum is situated in the
southern tip of the State. The city has a long history behind it. Some
historians say that it is mentioned in some literature of the 8th
century as the seat of a University. However the modern history of the
city starts in the 12th century when the King of Travancore took an
interest in the City. Even before that Sree Padmanabha Swami Temple,
which was the center of the City, was attracting attention of many
travelers. The city was elevated to the status of the official capital
of Travancore dynasty in the 18th century. Ever since then it has been
the capital of Travancore. When the state of Kerala was formed in 1956
it became its capital.
1.1.12 It has a population of 750,000 spread
over 142 sq. kms. The total literacy level for the city is 92.5 percent
and for the women 90 per cent. About 12,000 of its people live in 36
identified slums, making up 1.6 per cent of the population. The
literacy level in the slums is only 78 per cent. (Census 2001a&b)
In October 2000, five rural areas surrounding the city were added on to
its administrative limits. These areas, being rural, did not have
designated slums; but many slum like settlements.
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1.2 Health Infrastructure
1.2.1 The city is well served by
health facilities both by government and private enterprises. There are
25 hospitals in the public sector, the largest being the Trivandrum
Medical College, a teaching institution. With 1542 beds and 23
specialties it caters to the education of under graduates and
postgraduates in medicine, dentistry, nursing, pharmacy, medical
laboratory technology and public health. The women and children section
is a separate hospital with 732 beds. Likewise the ophthalmic hospital
and mental hospital are separate units. While this is meant for
teaching, there is a general hospital meant for clinical services with
747 beds. It has also 12 specialties. On the non-teaching side there is
also a separate women and children hospital with 422 beds. Together
with other hospitals run by government there are 5246 beds in the
public sector in the allopathic system of medicine (GOK 2000). There
are about 400 beds each in Homeopathy and Ayurveda. The private sector
also provides big and small hospitals in the city, their number being
35, in addition to 41 clinics. Some of these hospitals have specialties
of a rare nature and serve in effect as referral hospital to many other
institutions. However it may be mentioned here that these hospitals
cater not only to the city population but also for patients coming from
the rest of the district and the neighbouring districts. The Medical
College Hospital serves as a referral hospital for at least three
districts of Kerala with a combined population of 7 million. The people
from at least two districts of the neighboring state of Tamil Nadu also
use this as their referral hospital. Thus it serves about 10 million
people.
1.3. Studies on Health in Urban Slums
1.3.1 Some studies are available
on the slums of India, which cover several aspects of health care also.
The proceedings of a conference on `Health Care of the Villages and
Urban Slums’ held on Jan 22-24 1990 in Calcutta, India noted the
alarming growth of urban population, which was 3.78 percent per annum
between 1971 and 1981 against 2.19 percent of the general population.
As much as 47 per cent of the urban growth was constituted by transfer
from rural areas. It is the people who come to the city in search of
livelihood that squat in the land and create slums. That conference
noted that the size of the slum population is directly related to the
size of the city. The town with less than 50,000 people had only 10.04
per cent in slums, and as the size of the town went up it steadily
increased to 30.78 per cent in the cities over 1 million in 1981 (Sahni
& Xirasagar, 1990)
1.3.2 WHO and UNICEF had an interregional
consultation on `Primary Health Care in Urban Areas’ in July 1986 in
Manila. (UNICEF & EAPRO, 1986) That conference noted that a third
of the urban people in Asia lives on slums. It brought out five
constraints in dealing with Primary Health Care in slums, namely, (i)
the true facts about urban poor are hidden in the aggregated data, (ii)
lack of understanding of primary health care among the medical
profession, (iii) the policy and the planning capability at the city
level is weak, (iv) lack of appropriate community Organisation among
urban poor settlements, and (v) lack of resources.
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1.4 Objectives
1.4.1 No study specific to the
health care of the slums of Trivandrum could be located. This is
probably the fist attempt to study the various aspects of primary and
reproductive health care of the slums of Trivandrum city. The major
objectives of the study are as follows:
1. To determine what percentage of population in urban slums and
non-slum areas are able to meet their various reproductive and primary
health care needs and through what sources - public, voluntary and / or
private.
2. To understand reasons for preferring one or more of these sources;
more particularly, to know why free public sector program services are
not utilised.
3. To understand the quality of care they receive, particularly from
the public sector program.
4. To determine why reproductive and primary health care needs for
certain percentage for population remain unmet, and
5. To relate public sector program policies, programmes and its
implementation with its access, acceptance and quality of services and
identify gaps at different levels.
1.5 The Plan
1.5.1 The next chapter describes
the methodology followed in the survey explaining the sampling
procedure, the grouping of the questionnaire, the plan for interviews
and the data processing. The third chapter is about the household
characteristics of the slums, the non-slums and the suburban areas as
captured in the survey. It describes the age, sex distribution and
marital status of the sample and goes on to cover their religious
affiliation, educational level and occupation. It goes on to present
the housing conditions, the possession of durable goods and the basic
amenities in the house. An attempt is also made in the chapter to
classify the sample by the expenditure and income data, including
remittances from migrants.
1.5.2 In Chapter IV the prevalence, incidence
and pattern of morbidity are presented, covering also the type of
treatment and the expenses involved. An attempt is then made to
highlight the financial burden caused by the disease by describing the
source of money spent for treatment how it was raised and the loss of
wages due to illness. In the same chapter the mortality in the sample
population is described, finding out the age and cause of death. The
fifth chapter is about reproductive health of women, starting from
their menarche, going through marriage, conception, antenatal care,
delivery and contraception. While the women in the reproductive age
group are the main respondents in this chapter, it also captures some
aspects of reproductive health of adolescence girls. Chapter VI is
about Child Health. The aspects described are breast-feeding, birth
weight, immunisation and nutritional supplements. The story of
reproductive health continues in Chapter VII, which focuses on the
awareness of HIV/AIDS, sexually transmitted diseases and infections of
the reproductive tract. The awareness of mode of transmission, the
source of information and misconception about the diseases are covered.
Three groups of respondents are involved in this chapter, namely women
and men in the reproductive age group and adolescent girls.
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1.5.3 Chapter VIII is about the
utilisation of public facilities and the assessment of the quality of
service there. Responses on the choice of treatment facility and the
reasons for the choice given by various groups are put together in this
chapter and the determinants of client satisfaction are explained. In
Chapter IX the result of the in-depth interviews with community leaders
service providers, programme managers, NGOs, health activists and
policy planners are put together. Their suggestions for improvements
are grouped under various headings. The last chapter is a brief
description of the summary and conclusion.
II. Data and Methodology
2.1 Introduction
2.1.1 This is a two pronged study;
the first being a sample survey of residents of the study area and the
second, an in-depth enquiry with community leaders, service providers,
programme managers, NGOs in the field, health activists and planners
and policy makers. We felt that such a two level structure will enable
the study to meet our objective more meaningfully and policy
recommendations will emerge with better quality.
2.2 Sampling Procedure
2.2.1 The city of Trivandrum
consisted of 50 wards covering an area of 74.93 square kilometers till
October 2000. The areas outside the city consists of villages divided
into administrative units called Panchayats, which have an elected
local governments, like the city. Five such Panchayats surrounding the
city were added to the city in October 2000. These five Panchayats
(details in Annexure 1) were added as 31 wards to the city making the
total number of wards 81 and the area 141.74 sq km. The five added
Panchayats brought in an additional population of 350,091. The current
population of the city is 744,739 (Census 2001a). The old city area had
36 properly designated slums. The newly added areas, being rural in
nature till October 2000, did not have such a list. We went through the
development plans of these five Panchayats and found that there were
really poor areas with slum like conditions in terms of socio-economic
status and environmental conditions, some being worse off than the
slums of the city. These poor areas were found to be a distinct group,
different from the slums and non-slum areas of the old city. We thus
decided to treat them as a separate unit, and call them, for want of a
better expression, `Suburbs’.
2.2.2 In view of the constraints on resources
and the possibility of coming to commonly applicable findings we
decided to have a convenient sample of 1000 households from the three
areas viz., slums, non-slum areas and suburbs. As our main focus was on
the slums, we decided to select one half of the total sample i.e. 500
from there, 250 from the suburbs and for comparison, 250 from the
non-slum areas. A uniform sampling procedure was adopted in all the
areas. The 36 slums in the old city were divided into 6 groups based on
the size of the land area since the sizes of the slums are not uniform.
The formulation of the six groups is as follows.
| Group I |
Area <0.2 hectare |
| Group II |
0.2 - 0.49 hectare |
| Group III |
0.5 - 0.9 hectare |
| Group IV |
1.0 - 1.49 hectare |
| Group V |
1.5 – 4.99 hectares |
| Group VI |
5 hectares and above |
2.2.3 From each group, two slums were selected
using simple random sampling technique, making a total of 12. The total
population of each slum was available (given in Annexure I) and the
average household size was taken as 5 as this the household size in the
district of Thiruvananthapuram according to the Census of 1991. Using
this information, we estimated the number of households in each
selected slum. The sample size of each slum was determined by the
technique of probability proportional to size (PPS). [(Number of HH in
the index slum/ total HH) * 500]. The sample households were then
selected by systematic sampling method with random start.
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2.2.4 In the five `suburbs’, we
found 47 slum-like locations for our study. From each suburb, two
localities were selected randomly, making a total of ten. Twenty-five
households from each were selected using the same procedure as
mentioned earlier. Thus the sample size for the suburban area is 250
households.
2.2.5 Again, 250 non-slum households from the
study area were also selected. The corporation area consists of 81
wards currently (see Annexure I). From these wards, 10 were selected
randomly and each ward was divided into four segments using topographic
maps showing roads, by lanes etc. From these four segments, one was
selected randomly. From the selected 10 segments, 25 households were
taken using the same sampling procedure followed in the other cases.
2.2.6 As the second major component of our
study, apart from the sample of respondents from households, a
representative sample of 56 functionaries consisting of community
leaders, service providers, programme managers and planners and policy
makers were also interviewed for understanding their perceptions,
attitudes and suggestions for improving primary health care in slums.
(The list of those interviewed in Annexure II) This was done in a
hierarchical way. First, the data on qualitative aspects reported by
the household respondents were taken up with community leaders to
obtain their reactions. The opinions and perceptions of the leaders of
the community, NGOs, health activists and the service providers were
collected to discuss with the policy makers and programme managers how
to formulate and implement strategies for the improvement of health
care systems in the slums.
2.3 Questionnaire
2.3.1 The first phase of the
survey was intended to collect a variety of information about the
households and individuals to study the level of health status in
general and the Reproductive and Child Health (RCH) in particular along
with the utilisation of public health care system. The field survey
used 106 questions grouped into four: on the household, on the burden
of disease, on Reproductive and Child Health and on the quality of
Public health care service. The questionnaire was prepared in the local
language of Malayalam (English translation in Annexure III) and its
pretest was carried out in the study area.
2.3.2 The household questionnaire consisted of
four sections. In section 1, all usual residents, as reported by the
head or an elderly member of household in each sample were listed. For
each person, the survey collected information on age, sex, marital
status, religion, education, occupation, and relationship with the head
of the household. Section 2 collected information on the ownership of
the house, materials used for the house construction, electrification
of the house and the type of cooking fuel used. Section 3 covered the
environmental condition, asking about the toilet facility, the source
of drinking water and water for other needs and the provision for
wastewater disposal. In order to understand the overall economic status
of the sample, possession of household durables, the monthly
expenditure on food and other items in the family were elicited in
section 4. These points were covered in the first seventeen questions
and the 105th and 106th questions, which were the last, tried to obtain
information on income of the households including income from
remittances from members working outside the state and country.
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2.3.3 The next group of questions
was intended to assess the health status of the sample, the pattern of
morbidity and mortality and the burden of disease. The questionnaire
collected information on the prevalence of disease with a recall period
of one month prior to the survey date, the treatment taken, expenditure
on the treatment, source of money for that and the income loss due to
the disease for each member of the household. Then the questionnaire
gathered information on the death of any member in the household within
three years of the survey date. The information on age, sex and marital
status of the females of the household was used to identify the
respondents for administering the women's questionnaire.
2.3.4 The questionnaire on Reproductive and
Child Health which was the third group consisted of four sections. The
first section collected information from all ever-married women in the
reproductive age of 15-49 years. In order to understand the demographic
and health behaviour of the sample women, a series of questions (from
numbers 35 to 66) were included in this section. The background
characteristics such as age, education, occupation, religion etc. of
the couples were collected. The details of each pregnancy such as the
date of delivery, outcome of pregnancy, sex and survival status of each
child, date of death if not living, and details of miscarriages were
included in the questionnaire. Questions were also asked about the
onset of menstruation, present menstrual status, problems related to
menstruation and treatment taken. Details regarding last pregnancy
including its outcome, problems, antenatal, natal and postnatal care,
place of delivery and breast-feeding behaviour were also gathered. In
addition to this all currently married women were asked about their
current pregnancy status, use of contraceptives, problems related to
the use of a specific method and treatment taken and the reasons for
nonuse.
2.3.5 The second section in this group covered
Child Health, collecting the details of immunisation against six
vaccine preventable diseases and child care of the last child aged two
years or less at the time of survey. The age at the administration of
each vaccine, the number of doses, the date and place of administration
and the reasons for non-immunisation were asked. The details of Vitamin
A drops, Iron and Folic acid and Pulse Polio immunisation taken were
also collected through this interview schedule.
2.3.6 In the third section, questions were
included to assess the awareness of Reproductive Tract Infections
(RTI), Sexually Transmitted Infections (STI) and Acquired Immuno
Deficiency Syndrome (AIDS) among all ever married women of the selected
households and their knowledge about the curability of these diseases.
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2.3.7 The fourth section consisted
of questions on adolescent health of the females aged 13-18 years. They
were asked about their age at menarche, menstrual cycle, problems
related to menstruation, treatment taken, prevalence of white discharge
and the treatment for that, awareness of RTI/STI and HIV/AIDS and the
prevalence and treatment of RTI.
2.3.8 The fifth was about sexual health of males
between 13 and 54 years. Questions related to age, education, marital
status, total number of sons and daughters born and living were asked.
Then it went on to any problems of sexual health they had before or
after marriage, the treatment taken for these problems, reason for not
taking the treatment, the effectiveness of the treatment, knowledge
about STI and HIV/AIDS, transmission of the diseases and their
prevalence.
2.3.9 The last group of questions was about the
quality of government health services and client satisfaction.
Information on the visit of all ever-married women on any government
health facility for the last three months was collected. This
questionnaire gathered details of the presence of health staff in the
hospital at the time of respondent’s visit, their behaviour towards the
clients, availability of medicines, satisfaction about the treatment
received etc. Some questions related to client satisfaction of public
facilities were put to other respondents also in the context of the
burden of disease. But these were taken along with the data gathered in
this group for analysis.
2.4 Training and Fieldwork
2.4.1 In order to maintain uniform
survey procedure in all the selected areas, a 'Manual of Survey
Procedure' dealing with different aspects of the survey was prepared.
It consisted of instructions to the interviewers regarding interview
techniques, field procedure, method of asking questions and recording
answers. It also contained instructions to the editors and supervisors
of the survey. The methods for house listing and mapping were also
provided in the manual. Most of the interviewers were post-graduates in
Social Sciences with some prior experience in household data collection
although the minimum educational qualification fixed was a graduate
degree in social sciences. All field staff were given two weeks
training on the questionnaire, techniques of interviewing, mapping,
editing and other aspects of the study by the senior staff of the
Population Research Centre, University of Kerala, Thiruvananthapuram.
During the training, mock interviews were conducted between
participants and the pretest results were also evaluated. The field
survey was conducted during February - May 2001.
2.5 In-depth interviews
2.5.1 The second stage of the
study began by collecting information about the needs of the community
through in depth interview of the leaders of the community. Two
Research Assistants, one a Ph.D. in Social Demography and the other a
postgraduate in sociology and mass communication, both with several
years of experience in conducting such studies, interviewed the local
leaders and chiefs of nongovernmental organizations. They enquired with
the leaders about their assessment of the health problem of the
community, their expectations from the government programmes and what
role they played to alleviate these problems. Some of the NGOs
interviewed were also providers of some services. After getting a
picture of the health and reproductive health needs of the people, the
next stage was interviewing the providers of services. These were
Government functionaries in health at the cutting edge level, doctors
and paramedics of public and private hospitals both non-profit and for
profit. In the next stage the programme managers were interviewed with
the information collected from the first three groups. These were
government functionaries in the city health department and the Health
Services of the state who provided the services in the city area. This
was to understand program characteristics, program quality, program
management and policies and factors that affect them. The next group of
informants was health activists who had several ideas about cost
effective provisioning of services. All this information was used in
interviewing the planners and decision makers like the Mayor of the
City Corporation, District Medical Officer, Director of Health services
and the Principal Secretary to Government in the Health Department. The
information collected from these interviews is used in the appropriate
places in the study.
To Top
2.6 Data Processing
2.6.1 All completed questions were
edited in the field by the field editor and it was re-edited by the
field supervisor. The supervisor checked all skip sequences and
responses for consistency. Random checks were conducted by the Research
Assistant independently in the field. The data were coded after
assigning appropriate codes for open-ended questions. The coded data
were entered in computer and analyses was performed using the
Statistical Package for Social Sciences (SPSS).
III. Household Characteristics
3.1
This Chapter presents the major characteristics of
the sample household population such as age, sex composition, marital
status, income, expenditure, household conditions, possession of
durable goods, basic amenities and the socio-economic characteristics
of the usual residents. The main purpose of this Chapter is to describe
the environment in which the study population lives.
3.2 Age and Sex Composition
3.2.1 First we wanted to know the
age composition of our sample. The distribution of household population
by age and sex composition as recorded in the survey is shown in Table
3.1.
Table 3.1 Age and Sex Distribution of Household
Population
| Age Group |
Urban |
Suburban |
Total |
| Slums |
Non Slums |
| M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
| <1 |
1.1 |
0.9 |
1.0 |
0.6 |
1.3 |
1.0 |
0.8 |
1.3 |
1.0 |
0.9 |
1.1 |
1.0 |
| 1-4 |
8.8 |
5.8 |
7.2 |
3.8 |
4.6 |
4.2 |
7.4 |
7.4 |
7.4 |
7.2 |
5.9 |
6.5 |
| 5-9 |
9.2 |
9.1 |
9.2 |
7.6 |
7.1 |
7.3 |
7.6 |
6.8 |
7.2 |
8.4 |
8.1 |
8.2 |
| 10-14 |
8.2 |
8.1 |
8.2 |
10.4 |
6.3 |
8.3 |
8.0 |
9.4 |
8.7 |
8.7 |
8.0 |
8.3 |
| 15-19 |
7.6 |
10.8 |
9.3 |
8.6 |
8.2 |
8.4 |
10.3 |
8.5 |
9.4 |
8.5 |
9.6 |
9.1 |
| 20-24 |
9.8 |
9.8 |
9.8 |
7.4 |
8.8 |
8.1 |
10.5 |
11.1 |
10.8 |
9.4 |
9.9 |
9.6 |
| 25-29 |
7.9 |
9.4 |
8.7 |
7.2 |
7.9 |
7.5 |
10.5 |
7.0 |
8.7 |
8.4 |
8.5 |
8.4 |
| 30-34 |
5.9 |
7.5 |
6.8 |
7.0 |
8.8 |
7.9 |
8.7 |
9.2 |
9.0 |
6.9 |
8.2 |
7.6 |
| 35-39 |
9.2 |
9.4 |
9.3 |
8.2 |
8.8 |
8.5 |
7.2 |
7.4 |
7.3 |
8.5 |
8.8 |
8.6 |
| 40-44 |
6.7 |
5.5 |
6.1 |
6.6 |
5.7 |
6.2 |
6.3 |
6.3 |
6.3 |
6.6 |
5.7 |
6.1 |
| 45-49 |
6.7 |
5.1 |
5.9 |
5.0 |
5.6 |
5.3 |
5.3 |
5.5 |
5.4 |
5.9 |
5.3 |
5.6 |
| 50-54 |
5.8 |
5.8 |
5.8 |
3.2 |
9.2 |
6.3 |
2.7 |
7.7 |
5.2 |
4.4 |
7.1 |
5.7 |
| 55-59 |
4.3 |
4.4 |
4.4 |
9.4 |
6.5 |
7.9 |
7.6 |
5.0 |
6.3 |
6.4 |
5.0 |
5.7 |
| 60-64 |
2.5 |
3.2 |
2.9 |
4.4 |
4.4 |
4.4 |
2.9 |
2.8 |
2.8 |
3.1 |
3.4 |
3.2 |
| 65-69 |
3.1 |
2.0 |
2.5 |
4.8 |
3.3 |
4.0 |
2.3 |
1.7 |
2.0 |
3.3 |
2.2 |
2.7 |
| 70-74 |
1.6 |
1.9 |
1.8 |
3.0 |
1.9 |
2.4 |
1.5 |
1.1 |
1.3 |
1.9 |
1.7 |
1.8 |
| 75-79 |
0.8 |
1.0 |
0.9 |
2.4 |
0.2 |
1.3 |
0.4 |
0.6 |
0.5 |
1.1 |
0.7 |
0.9 |
| 80+ |
0.6 |
0.3 |
0.5 |
0.6 |
1.3 |
1.0 |
0.2 |
1.3 |
0.7 |
0.5 |
0.8 |
0.7 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
1060 |
1146 |
2206 |
501 |
522 |
1023 |
526 |
542 |
1068 |
2087 |
2210 |
4297 |
Median
age |
27.8 |
27.5 |
27.5 |
32.7 |
32.8 |
32.7 |
27.1 |
28.3 |
27.7 |
28.6 |
28.9 |
28.7 |
To Top
3.2.2 The total population
surveyed is 4297 distributed in 1000 households. The slum population of
the city is 11,667 (Census 2001a). The survey covered 2206 people in
the slum, making 18.9 per cent of the total slum population. There are
2087 males and 2210 females, making up a sex ratio of 1059 females for
every 1000 males. In a country with a sex ratio of 933, this is indeed
remarkable. But the State of Kerala has shown a sex ratio favourable to
females in the recent decades, the last being 1036 in 1991 and 1058 in
2001 (Census 2001b). It is significant that in the slums, this ratio is
even higher at 1081.
3.2.3 It can also be found that on the whole
children below one year comes to 0.9 percent per cent, 1.1 per cent and
1 per cent respectively among the male, female and the total
population. Also there is a smaller proportion of children under age
five than age five to nine (except suburban) which is in agreement with
the ongoing demographic transition in the state from high growth to low
growth, as we saw in chapter one. Children in the age group of 1-4 are
around 7 per cent in the slums and in the suburbs while they are only
4.2 per cent in the urban areas. The fact that there is no such
difference in the 0-1 age group in the three areas indicates that the
fertility decline took place earlier in the urban areas and the poorer
people in the slums and in the suburbs are only catching up.
3.2.4 Young population (0-14 years) constitutes
nearly one fourth (24 percent) of the total for both sexes. One has to
view this in the context of India and Kerala where the corresponding
figures are 36.1 per cent and 27.6.per cent respectively as revealed in
NFHS –2 (IIPS and ORC Macro 2001) . In the non-slum areas, the young
population constitutes 20.8 per cent, while it is much higher in the
suburbs at 24.3 per cent and slums at 25.6at 25.6 per cent. This adds
one more piece of evidence to the observation in the previous paragraph
that fertility decline has been delayed in the slums and suburban
areas. There is a larger number of the population in the younger age
group than in the older age groups of each sex in all the study areas.
Among the total population 55 per cent are in 15-49 age group. The
highest proportion (56.9 per cent) of this age group is in the suburban
area followed by slum (55.9 per cent) and non-slum (51.9 per cent).
Moreover women outnumber men at the oldest ages (80+) except with a
slight difference in the slum. Women are generally believed to be more
likely to survive to older ages leading to a higher expectation of life
for them. Though the difference appears negligible at present, it is
quite likely that the gap will widen in course of time when demographic
transition becomes universal.
3.2.5 The median age of the population shows the
youthful character of the population of the study area. For the total
population it is 28.9 years. The median age for females is higher by
0.3 years. This, again, is in tune with a higher expectation of life at
birth for females.
To Top
3.2.6 In order to find the dependency ratio in the
sample we extracted the data from Table 3.1 and put it in Table 3.2.
Table 3.2 Households by Age
| Age Group |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| < 15 |
25.5 |
20.8 |
24.3 |
24.1 |
| 15-64 |
68.9 |
70.5 |
71.2 |
69.8 |
| 65+ |
5.6 |
8.7 |
4.5 |
6.1 |
| Total |
100 |
100 |
100 |
100 |
| Dependary Ratio (%) |
45.1 |
41.8 |
40.4 |
43.3 |
3.2.7 The distribution of population by broad age
groups shows that the largest share of nearly 70 per cent is in the age
category of 15-64 years and the lowest share of 6 per cent is in the
age group 65 years and above. The age distribution of population in
suburban and slum are quite similar. The dependency ratio indicates
that for every person in the productive age group there are 0.4 persons
under age 15 or age 65 and above. The dependency ratio in the slums at
45.1 is higher than in the other areas.
3.3 Marital Status
3.3.1 Table 3.3 describes Marital Status of
household population at the time of the survey.
Table 3.3 Marital Status by Household Population
Marital
Status |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
| Single |
52.1 |
43.3 |
47.5 |
46.1 |
38.5 |
42.2 |
51.4 |
42.1 |
46.6 |
50.5 |
41.8 |
46.0 |
| Married |
44.7 |
40.9 |
42.7 |
49.3 |
45.2 |
47.2 |
44.9 |
42.8 |
43.8 |
45.8 |
42.4 |
44.0 |
| Widow |
1.8 |
11.9 |
7.0 |
3.2 |
10.7 |
7.0 |
2.8 |
10.7 |
6.5 |
2.4 |
11.3 |
7.0 |
| Divorced |
0.3 |
0.3 |
0.3 |
0.0 |
0.2 |
1.0 |
0.0 |
0.2 |
0.1 |
0.1 |
0.2 |
0.2 |
| Separated |
1.1 |
3.7 |
2.4 |
1.4 |
5.4 |
3.4 |
0.9 |
4.2 |
2.6 |
1.1 |
4.2 |
2.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
500 |
250 |
250 |
1000 |
3.3.2 It is observed that overall 44 per cent of
the population is currently married, 7 per cent widowed and another 3
per cent per cent divorced or separated. In all the three areas, males
outnumber females both in the never married and married categories.
However, in widowhood women outnumber men in all the three areas. In
the suburbs and slum areas, the proportion of never married was more
than married. But this trend was reversed in the non-slum area.
To Top
3.4 Household Composition
3.4.1 Table 3.4 provides the percent distribution
of households by sex of head of households and other members, size and
relationship structure.
Table 3.4 Household Composition
| Details |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
|
Household Headship
|
| Male |
76.6 |
83.6 |
78.4 |
78.8 |
| Female |
23.4 |
16.4 |
21.6 |
21.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Relationship |
M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
| Head |
36.1 |
10.2 |
22.7 |
41.7 |
7.8 |
24.4 |
37.3 |
9.9 |
23.4 |
37.7 |
9.6 |
23.3 |
| Wife |
0.0 |
31.6 |
16.4 |
0.0 |
37.0 |
18.9 |
0.0 |
33.7 |
17.1 |
0.0 |
33.4 |
17.2 |
| Husband |
0.4 |
0.0 |
0.2 |
0.4 |
0.0 |
0.2 |
0.9 |
0.0 |
0.5 |
0.5 |
0.0 |
2.5 |
| Son |
49.9 |
0.0 |
24.0 |
46.5 |
0.0 |
22.8 |
49.8 |
0.0 |
24.5 |
49.1 |
0.0 |
23.8 |
| Daughter |
0.0 |
34.2 |
17.8 |
0.0 |
39.3 |
20.0 |
0.0 |
35.2 |
3.6 |
0.0 |
35.7 |
18.3 |
| Grandchildren |
16.6 |
10.8 |
8.8 |
5.0 |
5.4 |
5.1 |
7.2 |
5.4 |
4.4 |
6.4 |
8.2 |
7.3 |
| Son-in-law |
4.3 |
0.0 |
2.1 |
4.6 |
0.0 |
2.2 |
3.4 |
0.0 |
2.7 |
4.2 |
0.0 |
2.0 |
| Daughter-in-law |
0.0 |
7.9 |
4.0 |
0.0 |
3.8 |
1.9 |
0.0 |
5.4 |
2.7 |
0.0 |
6.3 |
3.2 |
| Parent |
0.5 |
1.8 |
1.1 |
0.8 |
2.1 |
1.5 |
0.0 |
2.8 |
1.4 |
0.4 |
2.1 |
1.3 |
| Other |
2.2 |
3.4 |
6.6 |
1.0 |
4.6 |
2.9 |
1.4 |
7.6 |
4.7 |
1.6 |
4.6 |
3.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
1060 |
1146 |
2206 |
501 |
522 |
1023 |
526 |
542 |
1068 |
2087 |
2210 |
4297 |
3.4.2 As one would expect in a
typical household group in India, the large majority of households
(78.8 per cent) is headed by males. The proportion of female-headed
households is more in slums (23.4 per cent) compared to the suburbs
(21.6 per cent) and non-slum areas (16.4 per cent) areas. Female-headed
households would have limited resources, which would be one
contributory factor for the relative poverty of these areas. About 24
per cent of the population is sons and 18.3 per cent daughters of the
head of household. Grandchildren constitute 7.3 per cent.
3.4.3 On an average, there are 4.3 persons in a
household in our sample; 4.1 persons in non-slum households, 4.3 in the
suburbs and 4.4 in the slums. This compares with 5.1in Kerala State and
5.4 in India (NFHS -2).
To Top
3.5 Religion
3.5.1 India is predominantly a
Hindu country with 82 per cent of the population professing this faith,
12 per cent Islam, 2 per cent Christianity and 4 per cent others in
1991. Kerala throws up a different picture with 57 per cent Hindus, 21
per cent Muslims and 20 per cent Christians (Census, 1991). Our sample
shows yet another mix. Table 3.5 gives the distribution of households
by major religious groups.
Table 3.5 Distribution of Households by
Religious Affiliation (%)
| Religion |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Hindu |
46.6 |
70.4 |
82.0 |
61.4 |
| Muslim |
9.0 |
14.4 |
18.4 |
10.2 |
| Christian |
44.4 |
15.2 |
9.6 |
28.4 |
| Total |
100 |
100 |
100 |
100 |
| Number |
500 |
250 |
250 |
1000 |
3.5.2 Hindus are even higher than
in the state. But what is interesting is that the Christians constitute
the second largest religious community with 28.4 per cent. Muslims with
10.2 per cent are only about half the average of the state. Though
Hindus are the predominant group in all the three areas, the slums
present a different picture. There, Hindus and Christians are more or
less equally represented. One could venture an explanation in the fact
that many slums in our sample are inhabited by the fishing community
(not necessarily engaged in fishing) and there is a higher proportion
of Christians among them.
3.6 Education
3.6.1 Education has been
identified as the cornerstone of development as it affects almost all
aspects of human life and leads, among other things, to better health
outcomes. In a country with a total literacy rate of 54.16 per cent
(Census 2001b) Kerala flaunts itself as a 100 per cent literate state
and many writers attribute its high health outcomes and demographic
achievements to an early attainment of literacy especially among the
females.
3.6.2 The information on educational attainment
was collected for every member of the household. Since basic education
is starting at age six, only those above six have been considered here.
Table 3.6 provides the distribution of male and female household
members by the level of education obtained.
To Top
Table 3.6 Distribution of Population by
Education Level (%)
| Level of Education |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
| No Formal Education |
20.7 |
21.4 |
21.1 |
11.5 |
16.3 |
13.9 |
16.8 |
23.0 |
19.9 |
17.5 |
20.60 |
19.10 |
Primary
(Standards 1-4) |
18.3 |
18.0 |
18.1 |
8.9 |
8.1 |
8.5 |
14.8 |
18.1 |
16.5 |
15.2 |
15.60 |
15.30 |
Middle
(Standards 5-7) |
21.0 |
21.2 |
21.2 |
9.2 |
9.0 |
9.0 |
17.6 |
19.2 |
18.4 |
17.2 |
17.70 |
17.40 |
Secondary
(Standards 8 & 9)
|
21.9 |
27.7 |
24.8 |
11.6 |
12.5 |
12.1 |
26.7 |
27.6 |
27.2 |
20.5 |
24.00 |
22.30 |
| Matriculation |
12.9 |
8.1 |
10.4 |
23.3 |
18.8 |
21.0 |
15.2 |
6.0 |
10.5 |
16.0 |
10.20 |
13.00 |
| Under Graduate |
3.9 |
2.5 |
3.2 |
10.8 |
13.1 |
12.0 |
3.2 |
3.0 |
3.1 |
5.4 |
5.20 |
5.40 |
| Degree |
0.6 |
0.6 |
0.6 |
12.3 |
13.3 |
12.8 |
1.1 |
3.0 |
2.1 |
3.6 |
4.30 |
4.00 |
| PG and above |
0.7 |
0.4 |
0.6 |
12.3 |
8.9 |
10.6 |
4.6 |
0.0 |
2.3 |
4.6 |
2.40 |
3.50 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
945 |
1039 |
1984 |
471 |
480 |
951 |
475 |
496 |
971 |
1891 |
2015 |
3906 |
3.6.3 It shows that 19 per cent of the sample
did not have any formal education, 17.5 per cent males and 20.6 per
cent females. This does not mean that all of them are illiterate. Some
would have become literate as a result of the literacy mission, which
was a big movement in Kerala in the Nineties. Various reports of the
mission have shown that it had its impact in Trivandrum district also.
However the state figure for formal education is 92.8 percent for males
and 85.1 per cent for females. This figure is bettered in the urban
area with 88.5 per cent males and 83.7 per cent females (I-2). But when
it comes to our sample it is worse with 82.5 per cent for males and
79.4 per cent for females.
3.6.4 The overall level of education attained is
generally low among slum dwellers. On the whole a very small proportion
(7.5 per cent) of males and females have received higher education
leading to a university degree and above. Moreover, there is a notable
difference in educational attainment between the groups. People living
in non-slum areas have considerably more education than those living in
other areas. While 21 per cent of the non-slum areas have completed the
school education only 10.5 per cent in the suburbs and 10.4 per cent in
the slums have reached that stage. When it comes to women it is still
lower with 8 per cent in the slums and 6 per cent in the suburbs. Thus
one could say generally that the people in the slums are less educated
than their counterparts in the non-slum areas.
To Top
3.7 Occupation
3.7.1 After age, religion and
education, we probed into the nature of the occupation of the sample
population. Table 3.7 shows the distribution of occupational profile of
the sample household members.
Table 3.7 Distribution of Population by
Occupation (%)
Occupational
Status |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
M |
F |
Total |
| No Job |
19.4 |
17.6 |
18.5 |
23.9 |
16.6 |
20.1 |
10.2 |
18.4 |
14.4 |
18.2 |
17.6 |
17.9 |
| Govt. employee |
4.0 |
3.1 |
3.5 |
16.2 |
7.4 |
11.6 |
4.5 |
2.2 |
3.3 |
7.1 |
3.9 |
5.5 |
| Coolie |
6.4 |
5.0 |
5.7 |
2.3 |
0.7 |
1.5 |
12.5 |
11.5 |
12.0 |
6.9 |
5.5 |
6.2 |
Business
|
24.4 |
5.0 |
14.1 |
10.5 |
0.9 |
5.6 |
46.1 |
1.2 |
23.5 |
26.5 |
3.1 |
14.3 |
| Pensioner |
16.5 |
1.0 |
8.3 |
9.0 |
5.0 |
6.9 |
15.5 |
1.0 |
8.2 |
14.4 |
2.0 |
7.9 |
| Student |
5.1 |
19.5 |
12.7 |
21.9 |
17.1 |
19.4 |
3.0 |
17.7 |
10.4 |
8.7 |
18.5 |
13.8 |
| Housewife |
0.0 |
40.8 |
21.7 |
0.0 |
48.7 |
25.3 |
0.0 |
43.7 |
22.0 |
0.0 |
43.5 |
22.7 |
| Driver |
5.3 |
0.3 |
2.7 |
1.3 |
0.0 |
0.6 |
3.2 |
0.0 |
1.6 |
3.8 |
0.2 |
1.9 |
| Skilled |
5.5 |
4.0 |
4.6 |
5.4 |
1.9 |
3.6 |
4.0 |
2.9 |
3.5 |
5.1 |
3.2 |
4.1 |
| Non-skilled |
2.2 |
2.8 |
2.6 |
1.3 |
1.2 |
1.2 |
0.7 |
1.2 |
1.0 |
1.6 |
2.1 |
1.8 |
| Fishing |
11.2 |
0.7 |
5.6 |
8.2 |
0.5 |
4.2 |
0.2 |
0.0 |
0.1 |
7.6 |
0.4 |
3.9 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
770 |
873 |
1643 |
389 |
421 |
810 |
401 |
407 |
808 |
1560 |
1701 |
3261 |
To Top
3.7.2 Only those who were 15 years
and above were considered here. Of the total respondents nearly 18 per
cent reported that they have no work. Among non-slum population, this
is 20.1 per cent. Nearly 27 per cent of the male respondents are
engaged in business, much more (46 per cent) in the suburbs. Next to
business, the largest proportion of males (14.4%) is pensioners.
Government employees constitute 7.1 per cent of males. Nearly 8 per
cent are engaged in fishing. Around 7 per cent are coolies. We can
attempt to find the daily wage earners by adding three categories,
namely, coolies, non-skilled workers and those engaged in fishing. On
the whole 11.9 per cent of the people are daily wage earners, the slums
leading the pack with 13.9 per cent and the suburbs with 13.1 and
non-slums with 6.9 following.
3.7.3 Regarding female respondents, the largest
proportion (61.1 per cent) is either housewives or unemployed. 18.5 per
cent are students. Of the remaining, coolies came to 5.5 per cent,
government employees 3.9 per cent, business (petty vendors or running
small shops) 3.1 per cent and pensioners 2 per cent.
3.8 Condition of Housing
3.8.1 The household questionnaire
obtained the information on housing conditions and household
possessions. The data are helpful in assessing the standard of living,
the socio-economic status of the household and environmental conditions
in which the respondents live. Table 3.8 presents the distribution of
households by housing conditions like type of roof, wall, flooring and
the number of rooms apart from the details of ownership of the house.
Table 3.8 Distribution of Households by Housing
Characteristics (%)
| Characteristics |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
|
I. Ownership
|
|
| Ownership |
88.2 |
84.8 |
78.0 |
83.7 |
| Rent |
11.8 |
15.2 |
22.0 |
16.3 |
|
II. Roof
|
| Concrete |
24.4 |
59.6 |
21.2 |
32.4 |
| Tiled |
17.8 |
32.4 |
46.0 |
28.5 |
| Thatched |
45.4 |
4.8 |
25.6 |
30.3 |
| Sheet |
12.4 |
3.2 |
7.2 |
8.8 |
|
III. Wall
|
| Coconut leaves |
21.0 |
0.8 |
4.8 |
11.9 |
| Mud |
8.6 |
3.2 |
10.4 |
7.7 |
| Exposed Brick |
9.6 |
4.4 |
18.0 |
10.4 |
| Brick with Cement Plaster |
60.4 |
91.6 |
66.8 |
69.8 |
| Sack |
0.4 |
0.0 |
0.0 |
0.2 |
|
IV. Flooring
|
| Marble |
0.4 |
4.0 |
0.0 |
1.2 |
| Ceramic Tiles |
1.2 |
3.6 |
1.2 |
1.8 |
| Mosaic Tiles |
2.0 |
26.0 |
7.6 |
9.4 |
| Cement |
79.0 |
62.0 |
68.4 |
72.1 |
| Mud plastered with Cowdung |
13.4 |
4.0 |
20.4 |
12.8 |
| Exposed mud |
4.0 |
0.4 |
2.4 |
2.7 |
|
V. Number of Rooms
|
| One Room |
5.6 |
3.2 |
6.0 |
5.1 |
| Two Rooms |
23.0 |
1.6 |
6.4 |
13.5 |
| Three Rooms |
31.8 |
8.4 |
30.0 |
25.5 |
| Four or Five Rooms |
34.6 |
48.4 |
46.0 |
40.9 |
| Six and above |
5.0 |
38.4 |
11.6 |
15.0 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
500 |
250 |
250 |
1000 |
To Top
3.8.2 For the purpose of this
survey, the owner of a house is the person living in the house without
paying rent. Data indicate that among the total households 83.7 per
cent own their houses and the remaining 16.3 per cent pay rent. In the
urban area there were 15.2 per cent households who were paying rent for
their houses compared to 7.6 per cent in suburban and 11.8 per cent in
the slums. It may be noted here that there were instances where some
slum dwellers complained that they do not have title over the land they
occupy. But urban squatting, which is the major source of the creation
of slums, does not appear to be a major problem here unlike in the big
cities of India and the rest of the third world.
3.8.3 Coming to roofing, two materials, which
give permanent nature to it, are reinforced cement concrete and tiles.
By this standard 58.8 per cent of the houses in the sample have
permanent roofing, 32.4 per cent with concrete and 28.5 per cent with
tiles. 30.3 per cent had roofs thatched with cadjan coconut leaves,
which is a common roofing material for the poor in Kerala. Nearly 9 per
cent of the houses were roofed with sheets of various materials like
asbestos, aluminium and PVC. Only people with a reasonable means of
livelihood can afford to put concrete on top of their houses. Only 21.2
per cent in the suburban areas and 24.4 per cent in the slums could do
this while 60 per cent in the non-slums could afford it. Next in status
and cost would come tiled roofing. Transformation of roofing from tiles
to concrete is also an indication of the urbanization of the
households. This impression is borne out by the fact that 46 per cent
of houses in the suburbs have tiled roof while it is only 32.4 per cent
in the non-slums. But when it comes to the slums, the most popular
roofing material is coconut leaf thatch, covering 45.4 per cent of
houses as against 25.6 per cent in the suburbs and 4.8 per cent in the
non-slum areas. Houses that have sheet roof constitute 12.4 per cent in
the slums, 7.2 per cent in the suburbs and 3.2 per cent in the non-slum
areas. These two types of roofing are of a temporary nature and are
used by those who cannot afford the other two. Thus, 57.8 per cent of
the houses in the slums and about 33 per cent in the suburbs are of a
temporary nature, going by the roofing material. This can be taken as
an indicator of their access to resources.
3.8.4 Overall, the walls of a large proportion
of households are made up of bricks plastered with cement (69.8 per
cent). One out of ten houses have their walls made of bricks without
plastering. These two types of walls can be considered of a permanent
nature. Coconut palm leaves provide the walls of 12 per cent of the
houses and mud of 7.7 per cent. Sack is the wall material of 0.2 per
cent of the houses, all of which are in the slums. Thus 19.8 per cent
of the houses have temporary walls. While this constitutes only 4 per
cent of the houses in the non-slum area and 15.2 per cent in the
suburbs, it makes up a substantial 30 per cent of the houses in the
slums. It is safe to assume that the walls of a temporary nature with
materials like leaves, mud and sack do not have permanent roofing, as
it will not be supported by the walls. Thus out of the 57.8 per cent of
the houses in the slums with temporary roofing 30 per cent have
temporary walls also, making them insecure for living and liable to
perish in the heavy monsoons of the state. This also points to the
prevalence of poverty in the slums.
3.8.5 The type flooring used is another
indicator of the economic status of the occupant. Of the six types,
marble is the most expensive. No house in the slums has it. But 4 per
cent of the houses in the non-slum areas have it, while only a
negligible number (0.4 per cent) in the suburbs use it. The next
high-cost item is ceramic tiles, which is used by 3.6 per cent of the
houses in the non-slum area and only 1.8 per cent in the slums and
suburbs. The most commonly used flooring material is cement, covering
72 per cent of the houses. While nearly 92 per cent of the houses in
the non-slum areas are of this type, only 66.8 percent in the suburbs
and 60.4 per cent of the slums belong to this group. The traditional
flooring in the state is beaten earth covered with cow dung, which has
to be re-applied every now and then. This prevails to some extent in
the rural areas of the state. It is therefore not surprising that more
than 20 per cent of the houses in the suburbs have this kind of
flooring. This decreases to 13.4 per cent as we go to the slums and to
4 per cent in the non-slum areas of the city. But there are some people
who are too poor to afford even the cow dung covering for the mud
floor. They have just the beaten mud as their floor. Four per cent of
the houses in the slums and 2.4 per cent of the suburbs are of this
type. It is negligible in the non-slum areas.
3.8.6 The information on the number of rooms
that a household has, gives a measure of crowding. While most of the
respondents in urban areas (86.8 per cent) live in fairly adequate
space with four or more rooms, 53.2 per cent in the suburban areas and
much less (39.6 per cent) in the slums live with such convenience. On
the other hand, an overwhelming proportion of respondents in slums
(44.1 per cent) and in the suburban areas (42.4 per cent) live in
limited space with three rooms or less, against only 13.2 per cent in
the non-slum areas. The proportion of households that live in single
room and two-room tenements in the slums are 5.6 and 23 per cent
respectively, giving a picture of their overcrowding. With all these
features, it would not be far off the mark to infer that about 30 per
cent of the people in the slums are too poor to afford houses that keep
the minimum standards.
To Top
3.9 Household Durable Goods
3.9.1 In order to obtain
additional information on the economic status of households, the
respondents were asked about the possession of certain domestic items.
Table 3.9 shows the percentage of households having certain durable
goods.
Table 3.9 Distribution of Households by
Possession of Durable Goods (%)
| Possession |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Telephone |
14.4 |
56.8 |
16.4 |
25.5 |
| Refrigerator |
11.4 |
52.0 |
10.0 |
21.2 |
| Washing Machine |
2.0 |
26.0 |
0.0 |
7.5 |
| Television |
56.8 |
89.2 |
51.2 |
63.5 |
| VCR/VCP |
5.0 |
29.6 |
2.4 |
10.5 |
| Water pump |
3.6 |
11.2 |
1.6 |
5.2 |
| Grinder |
7.6 |
51.2 |
4.0 |
17.6 |
| Fan |
60.2 |
94.0 |
45.6 |
67.7 |
| Radio |
37.4 |
61.6 |
24.0 |
41.9 |
| Sewing Machine |
15.0 |
21.6 |
6.8 |
15.2 |
| Tape Recorder |
3.8 |
5.6 |
1.2 |
0.3 |
| Electric Mixer |
26.3 |
25.9 |
15.0 |
23.5 |
| Computer |
0.0 |
2.8 |
0.0 |
0.2 |
| Number |
500 |
250 |
250 |
1000 |
3.9.2 The data indicate that
almost 68 per cent of the households have fans (94 per cent in urban,
46 per cent in suburban and 60 per cent in slum) and 64 per cent own a
television (89 per cent in urban 51 per cent in suburban and 57 per
cent in slum). A little more than one fourth of the households have a
telephone. The proportion is high in the non-slum area (56.8 per cent)
than the suburbs (16.4 per cent) and slums (14.4 per cent). About one
fifth of the households also possess a refrigerator. The distribution
is more than half in the non-slum areas (52 per cent) followed by 11.4
per cent in the slums and 10 per cent in the suburbs. On the contrary,
it was observed that the percentage of households possessing electric
mixer is more in the slums (26.3 per cent) than in the other two areas.
But it may be noted that 51.2 per cent of the houses in the non-slum
areas have grinders. Probably the function of electric mixer is also
carried out by the grinders. Only 2.8 per cent of the households
possess a computer, none in the slums or suburbs. Ownership of
household durables varies tremendously between the areas. A comparison
of the extent of material possessions reveals that its degree is higher
in the non-slums than in the other two areas. The non-slum differential
is particularly strong for telephones, refrigerators, television,
VCR/VCP, fan and radio.
To Top
3.10. Ownership of Vehicles
3.10.1 Table 3.10 provides the
percentage of households owning certain vehicles.
Table 3.10 Distribution of Households by
Ownership of vehicles (%)
| Vehicle |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Car |
0.2 |
12.4 |
0.4 |
3.3 |
| Scooter |
9.2 |
33.2 |
16.4 |
17.0 |
| Auto rickshaw |
0.2 |
0.8 |
2.8 |
0.2 |
| Cycle |
22.2 |
24.4 |
13.6 |
21.5 |
| Boat with Engine |
1.0 |
0.0 |
0.0 |
0.1 |
| Number |
500 |
250 |
250 |
1000 |
3.10.2 Those who have one type of
vehicle or the other are less than half. More than a fifth of the
households own a bicycle (24.4 per cent in urban, 13.6 per cent in
suburban and 22.2 per cent in slums). Next to bicycle, scooter is the
most commonly owned mode of transport. On the whole 17 per cent of the
households possess a scooter. The proportion is 33.2 per cent in the
urban area, 16.4 per cent in the suburbs and 9.2 per cent in slums).
Overall only 3.3 per cent of households possess a car. Only one
household in the slum possesses a boat with engine, which is used for
the purpose of fishing.
3.11 Basic Amenities
3.11.1 Besides the nature of
houses, living conditions are influenced by the basic amenities
available. The presence of certain facilities affects the health as
well as the quality of life of the people. Here an attempt is made to
find out the availability of these amenities, which include
electricity, fuel, drinking water, water for other needs, toilet
facility, drainage facility etc. These physical characteristics of the
household have an important bearing on exposure to environmental
pollution as well as reflecting household economic condition. Table
3.11 provides information regarding the household amenities available.
To Top
Table 3.11 Households by Basic Amenities (%)
| Basic Amenities |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
|
I. Electricity
|
| Yes |
74.8 |
97.2 |
85.6 |
85.9 |
| No |
25.2 |
2.8 |
14.4 |
14.1 |
|
II. Fuel
|
| Wood |
75.4 |
32.0 |
84.0 |
66.7 |
| Kerosene |
9.0 |
2.0 |
1.6 |
5.4 |
| Gas (LPG) |
15.6 |
66.0 |
14.4 |
27.9 |
|
III. Drinking Water
|
| Tap at Home |
24.2 |
68.0 |
12.0 |
32.1 |
| Public Tap |
66.2 |
8.8 |
39.2 |
45.1 |
| Own Well |
8.6 |
23.2 |
30.0 |
17.6 |
| Public Well |
1.0 |
0.0 |
18.0 |
5.2 |
|
IV. Water for other needs
|
| Tap at Home |
22.0 |
66.0 |
11.2 |
30.3 |
| Public Tap |
51.8 |
9.2 |
26.0 |
34.7 |
| Own Well |
24.8 |
24.4 |
39.6 |
28.4 |
| Public well |
0.8 |
0.4 |
20.4 |
5.6 |
| Pond |
0.4 |
0.0 |
0.0 |
0.2 |
| Stream/River |
0.0 |
0.0 |
2.8 |
0.7 |
| Bore well |
0.2 |
0.0 |
0.0 |
0.1 |
|
V. Drainage Facility
|
| Without Cover |
20.0 |
4.4 |
2.4 |
11.7 |
| With Cover |
14.0 |
34.4 |
0.0 |
15.6 |
| Pit |
0.4 |
2.0 |
0.0 |
0.7 |
| No Facility |
65.6 |
59.2 |
97.6 |
72.0 |
|
VI. Stagnation of Water
|
| Yes |
23.6 |
7.6 |
23.2 |
19.3 |
| No |
76.4 |
92.4 |
76.8 |
80.7 |
|
VII. Toilet Facility
|
| No Facility |
34.6 |
1.6 |
24 |
23.6 |
| With Flush |
6.7 |
45.5 |
8.9 |
19.8 |
| Without Flush |
78.4 |
50.4 |
72.7 |
67.9 |
| Pit |
14.9 |
4.1 |
18.4 |
12.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
500 |
250 |
250 |
1000 |
|
No Facility
|
| Public Toilet |
46.2 |
0.0 |
10.0 |
36.3 |
| Open Ground |
53.8 |
100.0 |
90.0 |
63.7 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
173 |
4 |
16 |
237 |
3.11.2 Electricity is widely
available in the study area. Overall 85.9 per cent of the households
have this facility. Electricity is much more common in non-slums, 97.2
per cent of households having it, compared to 85.6 per cent in the
suburbs and 74.8 per cent in the slums. It is observed that about one
fourth of the households in the slums is deprived of electricity while
in the non slums it is less than 3 per cent.
3.11.3 Wood is the main source of fuel for
cooking. Overall 66.7 per cent of the households use this fuel, 27.9
per cent use LPG and 5.4 per cent kerosene. While two thirds of the
households in the non-slums have LPG as their fuel, wood is the fuel
for three fourths of the households in the suburbs and slums.
To Top
3.11.4 Access to water and
sanitation is an important determinant of disease free living. Water is
generally supplied to all by the Government. But only some have
plumbing in their homes. Others depend for drinking water on the public
tap in the street or on wells, some their own and some public. The
majority (45 per cent) depends on street tap, only a third (32.1 per
cent) having taps in their homes. But the position changes grossly when
we disaggregate this data. Sixty eight per cent of the non-slum people
have piped water in their homes while only 24 per cent of the slum
dwellers and 12 per cent of the suburbans have this luxury. As one
would expect in a rural like setting, 48 per cent of the households in
the suburbs depend on well water, 30 per cent on their own wells and 18
per cent on public wells. But even within the non-slum areas of the
city, 23.2 per cent of the households depend on wells for drinking
water. It is noteworthy that only 9.6 per cent of slum dwellers depend
on well water for drinking.
3.11.5 Availability of water for other needs is
also important. A variety of sources of water are available in the
study area. We have seen that 45 per cent of the people take their
drinking water from public taps. While this is the source of water for
other purposes also, the proportion is only 34.7 per cent. This is
probably because of the difficulty in fetching the water from the
street tap, or due to their reluctance to use unprotected water for
drinking. Only a negligible proportion of households is dependent on
other sources like public well, river, pond and bore well.
3.11.6 Another facility that has an equal
bearing on health and disease- free living is the drainage system for
wastewater. Table 3.11 provides information regarding the type of
drainage system in the study area. A majority of the households (72 per
cent) has no drainage system operating in their locality. It was found
that most of the of households (97.2 per cent) in the suburbs have no
drainage facility, followed by 65.6 per cent in the slums and 59.2 per
cent in the rest of the urban area.
3.11.7 The respondents were asked whether there
was any stagnation of water around their houses. On the whole, more
than 80 per cent said that there was no stagnation of water within the
premises of their houses and hence it was not a problem for them. This
is surprising in the face of the fact that 72 per cent of the houses do
not have drainage facility. The lack of stagnation is probably because
of the undulating terrain of the city. Trivandrum is fortunate enough
to have been built on a complex of hills. Most of the remaining 20 per
cent of the households which have the problem of water stagnation are
in the slums and suburbs. The proportion is almost similar in both
areas. Another factor that reduces the stagnation of water in the slums
is that many of the slums are close to the sea where the sandy soil
percolates the water down quickly. Only 7.6 per cent of the households
in urban area have the problem of water stagnation.
To Top
3.11.8 Table 3.11 also provides
the information on the kind of toilet facilities used by the sample
households. It is found that 76.4 per cent of the households have
toilet facility. It is to be noted that in the slums only 65.4 per cent
of the households have this, while 76 per cent have this in the suburbs
and nearly all in the urban area.
3.11.9 Nearly 88 per cent of households have
modern facility. Out of this only19.8 percent have flushing facility.
It is quite disturbing that in the slums and suburbs 14.9 per cent and
18.4 per cent of the households respectively use pit latrines. In the
crowded settlements of the slums where 10 per cent of the houses use
well water for drinking, 15 per cent using pit latrines is not a
healthy sign. A similar health hazard is posed by those who use the
open ground as toilets. The two surveys carried out by Kerala Sastra
Sahitya Parishat (KSSP) had revealed that the open defecation in the
state had come down from 51.1 per cent in 1987 to 27. 6 per cent in
1996 (Kunhikannan and Aravindan, 2000) But one would have expected this
to be nil in a city like Trivandrum which is known for its cleanliness.
Therefore it is surprising that more than 63 per cent of those who do
not have toilets use open ground as toilets. This is a whopping 15 per
cent of the households in the sample area where 22.8 per cent of the
people take drinking water from wells. However the use of open ground
is negligible in the urban area where the dependence on open wells for
drinking water is substantial (23.2 per cent). Fortunately only 48
households (9.6 per cent) in the slums use drinking water from the
wells where the use of open ground for toilet is by 93 houses (53.8 per
cent of houses with no facility), which makes 18.6 per cent of the slum
population. In the suburbs 21.6 per cent use open ground for toilet and
48 per cent depends on wells for drinking water.
3.11.10 The reluctance to use public toilets was
probed informally by the enumerators and covered in the interview with
community leaders. The common complaint is that the number of public
toilets is not adequate and their maintenance is also poor. The doors
of some of them are broken or missing. In the absence of Corporation
sweepers, they are not cleaned frequently. In some cases, slum dwellers
have employed their own sweepers and tried to keep the toilets clean.
Inadequate facilities for latrines and their overuse in the absence of
cleaning have made them not only unserviceable but also extremely
unhygienic. The practice of pay-and-use toilets adopted in some other
cities in India and abroad is worth trying here.
3.12 Monthly Household Expenditure
3.12.1Information has been
elicited on expenditure for measuring the economic status of the
household population.
3.12.2Table 3.12 shows the distribution of the
sample households according to monthly expenditure.
Table 3.12 Monthly Expenditure of Households
| Monthly Expenditure (in Rs.) |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| <500 |
13.6 |
0.8 |
6.4 |
8.6 |
| 500-999 |
24.6 |
5.2 |
30.0 |
21.1 |
| 1000-1499 |
23.0 |
12.0 |
27.2 |
21.3 |
| 1500-1999 |
22.0 |
18.4 |
16.4 |
19.7 |
| 2000-2499 |
9.2 |
14.8 |
7.6 |
10.2 |
| 2500-2999 |
4.4 |
16.4 |
5.6 |
7.7 |
| 3000-3499 |
1.8 |
11.6 |
4.0 |
4.8 |
| 3500-3999 |
0.8 |
7.6 |
1.6 |
2.7 |
| 4000-4499 |
0.4 |
6.0 |
0.0 |
1.7 |
| 4500-4999 |
0.0 |
2.0 |
0.4 |
0.6 |
| 5000+ |
0.2 |
5.2 |
0.8 |
1.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
500 |
250 |
250 |
1000 |
| Median |
1257 |
2459 |
1250 |
1477 |
To Top
3.12.3 On the whole, the average
monthly expenditure of more than half of the households (51 per cent)
in the sample was below Rs.1500. Poverty line in the urban area is
defined as having enough to consume to get 2100 calories per day. The
amount required for that at current prices is Rs. 372 per capita per
month (Oommen, 1999). For the family size of 4.3, the expenditure
required to cross the poverty line is Rs.1600. However our data is in
intervals of Rs500 and we can take Rs1500 as the cut off expenditure.
If we follow this criterion we can see that as high as 61.2 per cent in
the slums and 63.6 per cent in the suburbs are below the poverty line,
while only 18 per cent in the non-slum area come in this category.
However we recognize that this data is only a quick measure of poverty,
which has other dimensions. Households with monthly expenditure above
Rs.1500 and below Rs.5000/- constitute about 47.4 per cent. The number
of households with expenditure more than Rs.5000 was extremely low
at1.6 per cent.. It can also be seen that the largest group of 18.4 per
cent in the non-slum areas spends in the range of Rs.1500 to Rs.2000,
whereas in the suburbs and slums it is 16.4 and 22 per cent
respectively. . If we take the expenditure below Rs500 as a rough and
ready measure of people living in abject poverty, there are 13.6
percent of the people absolutely poor in the slums and 6.4 per cent in
the suburbs whereas in the non-slums it is only less than one per cent.
The median expenditure for the sample is Rs.1477. For the slums it is
Rs.1257, for the suburbs Rs.1250 and for the non-slum area Rs.2459.
3.12.4 The questions on total expenditure were
not asked straight away. Item wise expenditure was asked and then added
to get the total. This gave more reliability to the data. The item wise
break up is given in Table 3.15.It reveals that the largest proportion
of the people in the slums (29.4 per cent) and in the suburbs (28 per
cent) spend in the range of Rs.1500 to Rs. 2000 on food. In the other
parts of the city the largest group (20.8 per cent) spent in the range
of Rs.3000 to Rs.3500 on food.
3.12.5 Coming to utilities, while all spent some
amount on fuel, nearly 63 per cent did not spend anything on water and
nearly 20 per cent did not spend on electricity. Most of the others in
all the three areas spent less than Rs.50 on water and less than Rs.150
on electricity. The expenditure on fuel also came to less than Rs.50
for most people.
3.12.6 But huge differential is noticed in the
expenditure towards rent. It is noteworthy that most of the people
(88.6 per cent) did not have to pay any rent. Ownership of houses seems
to be the ruling pattern across the three areas. The majority of those
who stay in rented buildings in the slums and in the suburbs pay less
than Rs.350 a month, while in the non-slum areas the majority pays more
than Rs.1050 per month. It is interesting that at least 2 families in
the slums also pay more than Rs.1050.
3.12.7 When it came to education more than half
the people did not have to spend anything. This could be due to a
variety of reasons like having no school-going children at the time of
the survey, getting the benefit of free education from the government
which is available for large sections of the population, support from
service organizations for books etc. Nearly a fifth of the households
in the slums and suburbs spent less than Rs.150 a month, while 22.8 per
cent in the non-slum areas spent up to Rs.350.
3.12.8 The next item queried was clothing. More
than a quarter of the households in the slums and suburbs spent only
less than Rs.50 a month on this item. More than half in these areas
spent up to Rs.150, whereas in the urban areas more than half spent up
to Rs.750 on clothing.
3.12.9 As far as expenditure on treatment is
concerned, 54.6 per cent of the total reported no expenditure. It is to
be noted that more than three fourth of the households in the non-slum
area did not have to spend anything on this. Nearly 30 per cent in the
slums and a fourth of the people in the suburbs spent less than Rs.150
a month on treatment. The expenditure on treatment for the episodes of
illness in the previous month is dealt with separately in Chapter IV.
3.12.10Thirty seven per cent in the slums and
40.4 per cent in the suburbs spent up to Rs.150 a month on travel,
while more than a third in the non-slum areas spent up to Rs.350. When
it came to entertainment, the picture changed. The vast majority (83
per cent) answered that they do not spend anything on entertainment.
Nearly 13 per cent spent below Rs.150 a month with some slight
variations across the areas. Probably they watch Television, nearly two
thirds having it at home (see Table 3.9). The expenditure on TV being
of a capital nature would not figure in the monthly expenditure. The
items grouped as miscellaneous include donations, gifts, charity etc.
Half the people do not have any expenditure on this and more than a
third spent less than Rs. 150 a month with some variations in the
areas.
To Top
Table 3.13 Distribution of Households by Item
wise Expenditure (%)
| Item wise Expenditure (in Rs.) |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
|
Food
|
| <500 |
2.8 |
2.0 |
2.4 |
2.5 |
| 500-999 |
10.4 |
1.2 |
11.6 |
8.4 |
| 1000-1499 |
9.6 |
4.0 |
9.2 |
8.1 |
| 1500-1999 |
29.4 |
10.4 |
28.0 |
24.3 |
| 2000-2499 |
14.8 |
12.0 |
16.4 |
14.5 |
| 2500-2999 |
1.8 |
6.8 |
1.2 |
2.9 |
| 3000-3499 |
24.0 |
20.8 |
18.0 |
21.7 |
| 3500-3999 |
1.8 |
8.4 |
4.4 |
4.1 |
| 4000-4499 |
1.0 |
9.6 |
1.2 |
3.2 |
| 4500-4999 |
2.6 |
8.8 |
3.6 |
4.4 |
| 5000+ |
1.8 |
16.0 |
4.0 |
5.9 |
|
Water
|
| <50 |
18.0 |
39.6 |
8.0 |
24.2 |
| 50-149 |
6.2 |
25.2 |
4.0 |
12.1 |
| 150-249 |
0.0 |
2.0 |
0.0 |
0.5 |
| 250-349 |
0.0 |
0.4 |
0.0 |
0.1 |
| 350-449 |
0.0 |
0.4 |
0.0 |
0.1 |
| 450+ |
0.0 |
0.4 |
0.0 |
0.1 |
| None |
75.8 |
32.0 |
88.0 |
62.9 |
|
Electricity
|
| <50 |
29.0 |
18.8 |
49.6 |
31.6 |
| 50-149 |
30.0 |
36.4 |
22.0 |
29.6 |
| 150-249 |
9.0 |
22.4 |
6.4 |
11.7 |
| 250-349 |
2.6 |
10.4 |
0.8 |
4.1 |
| 350-449 |
1.2 |
5.6 |
0.4 |
2.1 |
| 450-549 |
0.4 |
0.8 |
0.0 |
0.4 |
| 550-649 |
0.0 |
0.4 |
0.0 |
0.1 |
| 650-749 |
0.0 |
0.0 |
0.0 |
0.0 |
| 750+ |
0.4 |
2.0 |
0.4 |
0.8 |
| Not Paying |
27.4 |
3.2 |
20.4 |
19.6 |
|
Fuel
|
| <50 |
82.4 |
36.0 |
84.8 |
71.4 |
| 50-149 |
9.6 |
23.6 |
7.6 |
12.6 |
| 150-249 |
2.4 |
3.2 |
1.2 |
2.3 |
| 250-349 |
5.6 |
36.0 |
6.0 |
13.3 |
| 350-449 |
0.0 |
0.4 |
0.4 |
0.2 |
| 450-549 |
0.0 |
0.8 |
0.0 |
0.2 |
|
Rent
|
| <50 |
0.0 |
0.0 |
0.0 |
0.0 |
| 50-149 |
2.6 |
0.0 |
0.0 |
1.3 |
| 150-249 |
1.6 |
0.4 |
0.8 |
1.1 |
| 250-349 |
2.6 |
1.2 |
2.8 |
2.3 |
| 350-449 |
1.2 |
0.8 |
1.2 |
1.1 |
| 450-549 |
1.0 |
0.8 |
0.0 |
0.7 |
| 550-649 |
1.0 |
0.8 |
0.0 |
0.7 |
| 650-749 |
0.0 |
0.0 |
0.0 |
0.0 |
| 750-849 |
0.6 |
0.4 |
0.4 |
0.5 |
| 850-949 |
0.2 |
0.0 |
0.0 |
0.1 |
| 950-1049 |
0.6 |
1.6 |
1.2 |
1.0 |
| 1050+ |
0.4 |
9.2 |
0.0 |
2.5 |
| None |
88.2 |
84.8 |
93.2 |
88.6 |
|
Education of Children
|
| <50 |
5.2 |
0.0 |
6.8 |
4.3 |
| 50-149 |
14.4 |
7.2 |
11.2 |
11.8 |
| 150-249 |
9.2 |
9.2 |
8.4 |
9.0 |
| 250-349 |
5.8 |
6.4 |
2.4 |
5.1 |
| 350-449 |
2.2 |
6.8 |
2.8 |
3.5 |
| 450-549 |
1.6 |
8.4 |
3.2 |
3.7 |
| 550-649 |
0.8 |
2.0 |
0.4 |
1.0 |
| 650-749 |
0.4 |
0.8 |
0.0 |
0.4 |
| 750-849 |
0.6 |
1.6 |
0.4 |
0.8 |
| 850-949 |
0.4 |
0.0 |
0.0 |
0.2 |
| 950-1049 |
0.8 |
3.6 |
0.0 |
1.3 |
| 1050+ |
2.2 |
4.0 |
1.2 |
2.4 |
| None |
56.4 |
50.0 |
63.2 |
56.5 |
|
Cloth
|
| <50 |
26.4 |
5.6 |
26.8 |
21.3 |
| 50-149 |
33.0 |
9.2 |
34.4 |
27.4 |
| 150-249 |
21.8 |
6.0 |
9.6 |
14.8 |
| 250-349 |
9.4 |
9.2 |
11.2 |
9.8 |
| 350-449 |
3.0 |
11.2 |
3.2 |
5.1 |
| 450-549 |
3.0 |
5.2 |
2.4 |
3.4 |
| 550-649 |
0.0 |
2.4 |
0.8 |
0.8 |
| 650-749 |
0.4 |
3.6 |
0.8 |
0.8 |
| 750-849 |
0.6 |
22.4 |
4.4 |
7.0 |
| 850-949 |
0.0 |
0.0 |
0.0 |
0.0 |
| 950-1049 |
1.4 |
8.0 |
3.6 |
3.6 |
| 1050+ |
1.0 |
17.2 |
2.8 |
5.5 |
|
Treatment of Diseases
|
| <50 |
5.8 |
0.0 |
8.0 |
4.9 |
| 50-149 |
24.6 |
10.8 |
16.8 |
19.2 |
| 150-249 |
10.8 |
4.8 |
9.2 |
8.9 |
| 250-349 |
4.6 |
2.8 |
4.8 |
4.2 |
| 350-449 |
1.4 |
0.0 |
0.8 |
0.9 |
| 450-549 |
5.0 |
2.8 |
2.8 |
3.9 |
| 550-649 |
0.6 |
0.4 |
0.8 |
0.6 |
| 650-749 |
0.0 |
0.0 |
0.0 |
0.0 |
| 750-849 |
0.4 |
0.4 |
0.0 |
0.3 |
| 850-949 |
0.0 |
0.0 |
0.0 |
0.0 |
| 950-1049 |
1.2 |
1.2 |
0.8 |
1.1 |
| 1050+ |
1.0 |
1.2 |
2.4 |
1.4 |
| None |
44.6 |
75.6 |
53.6 |
54.6 |
|
Travel
|
| <50 |
5.0 |
0.0 |
6.4 |
4.1 |
| 50-149 |
32.0 |
11.2 |
34.0 |
27.3 |
| 150-249 |
7.2 |
10.4 |
10.0 |
8.7 |
| 250-349 |
6.6 |
13.2 |
6.0 |
8.1 |
| 350-449 |
1.4 |
1.6 |
0.4 |
1.2 |
| 450-549 |
3.8 |
16.8 |
4.0 |
1.2 |
| 550-649 |
0.8 |
0.8 |
0.8 |
0.8 |
| 650-749 |
0.2 |
0.0 |
0.0 |
0.2 |
| 750-849 |
0.4 |
0.0 |
0.0 |
0.2 |
| 850-949 |
0.2 |
0.4 |
0.0 |
0.2 |
| 950-1049 |
0.4 |
1.2 |
0.8 |
0.7 |
| 1050+ |
0.0 |
1.6 |
0.8 |
0.6 |
| None |
42.0 |
42.8 |
36.8 |
40.9 |
|
Entertainment
|
| <50 |
2.8 |
0.4 |
7.6 |
3.4 |
| 50-149 |
7.4 |
14.8 |
8.4 |
9.5 |
| 150-249 |
1.0 |
6.0 |
1.6 |
2.4 |
| 250-349 |
0.4 |
2.4 |
0.4 |
0.9 |
| 350+ |
0.6 |
1.6 |
0.0 |
0.7 |
| None |
87.8 |
74.8 |
82.0 |
83.1 |
|
Miscellaneous
|
| <50 |
19.2 |
0.0 |
12.8 |
12.8 |
| 50-149 |
19.6 |
31.2 |
22.4 |
23.2 |
| 150-249 |
5.6 |
13.2 |
4.0 |
7.1 |
| 250-349 |
2.4 |
5.2 |
2.4 |
3.1 |
| 350-449 |
0.4 |
0.8 |
0.4 |
0.5 |
| 450-549 |
0.8 |
2.0 |
0.4 |
1 |
| 550+ |
1.2 |
3.6 |
0.8 |
1.7 |
| None |
50.8 |
44.0 |
56.8 |
50.6 |
To Top
3.13 Monthly Household Income
3.13.1 Income is the most
difficult information to get in surveys as people have a feeling that
they will get some benefit if the income is reported low. This is not
surprising because many welfare schemes of the government are targeted
to low-income groups and there is no foolproof system of means testing.
In order to reduce this bias of understatement, the questions on
expenditure were put in the beginning of the survey and after covering
aspects like morbidity, reproductive and child health, quality of
government services etc, income was asked as the last question.
Table 3.14 Distribution of Households by Monthly
Income (%)
| Monthly Income |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| <1500 |
18.00 |
2.80 |
20.80 |
14.90 |
| 1500-2999 |
37.00 |
10.40 |
35.60 |
30.00 |
| 3000-4499 |
24.60 |
22.80 |
28.80 |
25.20 |
| 4500-5999 |
12.00 |
12.40 |
6.00 |
10.60 |
| 6000-7499 |
4.20 |
12.00 |
4.00 |
6.10 |
| 7500-8999 |
2.20 |
8.80 |
2.00 |
3.80 |
| 9000-10499 |
1.60 |
8.00 |
1.20 |
3.10 |
| 10500-11999 |
0.00 |
1.60 |
0.40 |
0.50 |
| 12000-13499 |
0.40 |
4.40 |
0.40 |
1.40 |
| 13500-14999 |
0.00 |
1.60 |
0.00 |
0.40 |
| 15000-16499 |
0.00 |
5.60 |
0.00 |
1.40 |
| 16500-17999 |
0.00 |
1.20 |
0.00 |
0.30 |
| 18000-19499 |
0.00 |
1.60 |
0.40 |
0.50 |
| 19500-20999 |
0.00 |
1.60 |
0.00 |
0.40 |
| 21000-22499 |
0.00 |
1.20 |
0.00 |
0.30 |
| 22500-23999 |
0.00 |
0.40 |
0.00 |
0.10 |
| 24000-25499 |
0.00 |
3.60 |
0.40 |
1.00 |
| 25500+ |
0.00 |
0.00 |
0.00 |
0.00 |
| Total |
100 |
100 |
100 |
100 |
| Number |
500 |
250 |
250 |
1000 |
| Median |
2797 |
6200 |
2730 |
4762 |
To Top
3.13.2 Monthly income of about 15
per cent of the members of the household is below Rs.1500/-. (Urban 2.8
per cent, suburban 20.8 per cent and in slum 18 per cent). 30 per cent
of the members have reported their monthly income is between Rs.1500
and Rs.3000/-. A little more than one fourth households have income
between Rs.3000 and Rs.4500/-. Only 1 per cent earn more than
Rs.24000/-. The data shows that the lowest monthly income of Rs.1500 or
less is found to be considerably more among the households in suburban
area (20.8 per cent) followed by slums (18 per cent) and the least in
the non-slums (2.8 per cent). These differences are significant and
reveal the gravity of economic problems prevailing in the slums and
suburbs. However, largest group of households that has a monthly income
ranging from Rs.1500 to Rs.3000 can be found in slum (37 per cent)
followed by suburban 35.6 per cent and urban 10.4 per cent. However it
is to be noted that nearly one fifth of the slum dwellers have income
above Rs. 4500 while in the suburbs it is only less than 15 per cent.
When the income slab goes up further, the number of houses in the
non-slum areas increase while the others decline. The median income is
Rs.4762 for the total, Rs.2797 for the slums, Rs. 2730 for the suburbs
and Rs. 6200 for the non-slum areas.
3.13.3 Questions were put on the source of
income, dividing it into land, business, salary, pension, wages, rent,
help from relatives and help from institutions. Data in Table 3.15
shows that the large majority of the households in the slums (75.6 per
cent) and in the suburbs (74.8 per cent) have their income from wages.
Salary and pension together constitute the majority (54 per cent) in
the urban areas. However it may be borne in mind that several
households have income from multiple sources.
Table 3.15 Distribution of Households by Source
of Income (%)
| Item |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Land |
0.6 |
5.6 |
2 |
2.2 |
| Business |
7.8 |
17.2 |
6.8 |
9.9 |
| Salary |
17.8 |
35.6 |
11.6 |
20.7 |
| Pension |
4.6 |
18.4 |
5.6 |
8.3 |
| Wages |
75.6 |
37.6 |
74.8 |
65.9 |
| Rent |
2.0 |
2.4 |
2.0 |
2.1 |
| Help from Relatives |
7.0 |
7.6 |
3.6 |
6.3 |
| Help from Institution |
1.0 |
0.5 |
0.8 |
1.0 |
| Number |
500 |
250 |
250 |
1000 |
Note: The percentages may add to more than 100 as
there are multiple sources of income
To Top
3.14 Migration
3.14.1 Migration has been noted by
many researchers as having a positive influence on the development
process of the State and its population growth. Every decade since 1950
witnessed decrease in the population growth rate in the state. The
impact of migration on the decrease has been steadily rising ever since
out migration from the state started exceeding in migration. As a
result of migration, the proportion of population below poverty line
has declined by 12 per cent. The number of unemployed persons has come
down by more than 30 per cent (Zacharia, 2000). However, the volume of
migration in the sample is very low, only 49 houses having migrants.
This section provides major socio economic and demographic
characteristics of the migrants of the study area. Table 3.16 presents
the percentage distribution of migrants in the households in the study
area.
Table 3.16 Distribution of Households by
Migrants (%)
| Number of Migrants |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| One |
73.3 |
93.3 |
100.0 |
81.6 |
| Two |
23.3 |
6.7 |
0.0 |
16.3 |
| Three |
3.3 |
0.0 |
0.0 |
2.0 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
30 |
15 |
4 |
49 |
3.14.2 Of the 1000 sample
households, 49 households (4.9 per cent) have members working outside
Kerala. Of the 49 households, 8 households have two migrants each and
one has three. Thus there are 59 migrants in total.
To Top
3.14.3 The background
characteristics of the migrants are presented in Table 3.17.
Table 3.17 Background Characteristics of
Migrants (%)
| Characteristics |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
|
I.Relationship with Head of Household
|
| Husband |
25.6 |
25.0 |
0.0 |
23.7 |
| Son |
41.0 |
31.3 |
75.0 |
40.7 |
| Daughter |
2.6 |
6.2 |
0.0 |
3.4 |
| Son-in-law |
30.8 |
25.0 |
0.0 |
27.1 |
| Brother |
0.0 |
6.2 |
25.0 |
3.4 |
| Sister-in-law |
0.0 |
6.2 |
0.0 |
1.7 |
|
II. Age
|
| <25 |
7.7 |
6.2 |
0.0 |
6.8 |
| 25-29 |
30.8 |
25.0 |
50.0 |
30.5 |
| 30-34 |
28.2 |
18.8 |
0.0 |
23.7 |
| 35-39 |
25.6 |
6.2 |
25.0 |
20.3 |
| 40-44 |
5.1 |
18.8 |
0.0 |
8.5 |
| 45-49 |
2.6 |
18.8 |
0.0 |
6.8 |
| 50+ |
0.0 |
6.2 |
25.0 |
3.4 |
|
III. Sex
|
| Male |
97.4 |
87.5 |
100 |
94.9 |
| Female |
2.6 |
12.5 |
0 |
5.1 |
|
IV. Education
|
| illiterate |
5.1 |
0 |
0 |
3.4 |
| 7th to 9th Standard |
25.7 |
6.2 |
0 |
18.6 |
| Matriculation |
46.1 |
37.5 |
25 |
42.4 |
| Under Graduate |
5.1 |
25 |
75 |
15.3 |
| Degree |
7.7 |
12.5 |
0 |
8.4 |
| Technical Qualification |
10.3 |
18.7 |
0 |
11.9 |
|
V. Occupation
|
| Government Service |
5.1 |
12.5 |
0 |
6.8 |
| Business |
35.7 |
25 |
25 |
32.2 |
| Driver |
17.9 |
18.8 |
50 |
20.2 |
| Servant |
5.1 |
0 |
0 |
3.4 |
| Salesman |
2.6 |
12.5 |
25 |
6.8 |
| Electrician |
12.8 |
18.8 |
0 |
13.6 |
| Semi-skilled |
18.1 |
6.2 |
0 |
13.6 |
| Others |
0 |
6.2 |
0 |
1.7 |
|
VI. Duration of Stay
|
| Less than 1 year |
7.7 |
0.0 |
25.0 |
6.8 |
| 1-5 years |
58.9 |
31.2 |
25.0 |
6.8 |
| 6-9 years |
12.9 |
25.0 |
0.0 |
15.2 |
| 10-15 Years |
12.8 |
18.8 |
25.0 |
15.2 |
| 16-20 years |
7.7 |
12.5 |
25.0 |
10.2 |
| Above 20 years |
0.0 |
12.5 |
0.0 |
3.3 |
|
VII. Monthly Remittance
|
| <1000 |
12.8 |
18.8 |
25 |
15.3 |
| 1000-2499 |
51.3 |
0 |
0 |
33.9 |
| 2500-3999 |
15.4 |
12.5 |
25 |
15.3 |
| 4000-5499 |
7.7 |
37.5 |
25 |
16.9 |
| 5500-6999 |
12.8 |
12.5 |
0 |
11.9 |
| 7000+ |
0 |
6.2 |
0 |
6.7 |
|
VIII. Place of Stay
|
| Europe |
0 |
6.2 |
25 |
3.4 |
| Middle East |
79.5 |
93.8 |
75.0 |
83.0 |
| South-East Asia |
7.7 |
0 |
0 |
5.1 |
| Outside State but within India |
12.8 |
0 |
0 |
8.5 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
39 |
16 |
4 |
59 |
To Top
3.14.4 Of the total population,
40.7 per cent of migrants are sons and 3.4 per cent are daughters of
the heads of households. Approximately, 23.7 per cent are husbands of
the head. About 27.1 per cent of the migrants are sons-in-law and 1.7
per cent sisters-in-law of the head of the family. Around 3 per cent
are brothers of the head of household.
3.14.5 Age distribution of the migrants reveals
almost one third (30.5 per cent) of migrants belong to 25-29 age group.
Nearly one fourth of the migrants (23.7 per cent) belong to 30-34 age
group. Another 20.3 per cent of the migrants are in the age group of
35-39 years. These age groups together constitute almost 75 per cent of
the total migrants. This shows the age selectivity of migration.
3.14.6 Regarding sex, there is a clear
predominance of males in migration. Of the total, 95 per cent are males.
3.14.7 Educational level of the migrants shows
that around 43 per cent of migrants are matriculates. More than 15 per
cent are under graduates and 8 per cent graduates. Nearly 12 per cent
have technical qualifications like Certificate or Diploma in
Engineering, Teachers Training Certificate or Computer Training. Only 2
persons(3.4 per cent) are illiterate.
3.14.8 Occupational breakdown of the total
migrants shows that the larger proportion of migrants (32.2 per cent)
is engaged in business. Next to business, the majority of migrants
(20.2 per cent) are employed as drivers. Similar proportion (6.8 per
cent) of migrants are working in Government service and as Salesmen.
Electricians and semi skilled workers constitute 13.6 per cent each.
More than three per cent work as servants.
3.14.9 Around 7 per cent of migrants have
duration of service less than one year. Almost 65 per cent have service
between one year and 10 years. More than one fourth has service between
10 years and 20 years. 3.3 per cent have worked more than 20 years.
3.14.10 Remittances, no doubt, improve the
standard of living of the migrants’ family. The survey also collected
information on the volume of remittances sent by migrants. Almost 34
per cent of the migrants sent between Rs.1000/- and Rs.2500/- monthly.
More than 15 per cent sent between Rs.2500 and Rs.4000. Nearly 17 per
cent sent between Rs.4000/- and 5500/-. Monthly remittance of only 5
per cent is Rs.10,000/- and above.
3.14.11 Table 3.17 also shows the place where
the migrants work at the time of survey. Countries of the Persian Gulf
occupy first place in receiving migrants from the study area, nearly 83
per cent working there. Around 5 per cent work in South East Asia and
3.4 per cent work in Europe. The remaining 8.5 per cent is employed
outside the state but within India.
To Top
3.15 Summary
3.15.1 The picture that emerges is
that the slums and the poor areas in the suburbs have many
characteristics in common, which make them distinct from the non-slum
areas. The slums have a sex ratio more favourable to the females than
the rest of the city and the state. The fertility decline has taken
place in the slums later than the other areas. There is a higher
dependency ratio in the slums. Generally males head the households. But
in the slums nearly one fourth of the households have female heads. The
religious mix shows that the study area has more Christians and less
Muslims than the state. In the slums the proportion of e Christians is
almost equal to Hindus. In the matter of education, the slums trail
behind the rest of the city. Only a tenth of the people in the slums
and suburbs completed high school education successfully. Business is
the most common occupation, the suburbs leading the other two groups.
About 12 per cent of those employed are daily wage earners, the slums
leading with 14 per cent. Nearly a third of the houses in the slums are
of purely temporary nature with thatched roof and walls, and only less
than a fourth has running water inside. More than a third of the houses
in slums do not have toilet facility and among them more than half use
the open field for this. About a fourth of the houses in the slums are
not electrified. Going by the expenditure data, more than 13 per cent
of the slum dwellers are absolutely poor which is not so in the suburbs
or the rest of the city. Another 25 per cent are moderately poor.
IV. Morbidity and Morality
4.1
The State of Kerala is well known for its fast
achievement of demographic and health transition among the states of
India. The low level of fertility and mortality, especially infant
mortality, compares well with many advanced countries. However, the
prevalence of morbidity is reported high in spite of continuing low
mortality. This apparent paradox has caught the attention of several
health economists and population scientists. Information on morbidity
and mortality is highly relevant for identifying population groups,
which require attention by health care planners. With this backdrop our
study aimed to collect data on the incidence of sickness and of death
in the sample.
4.1.1 To find out the incidence, prevalence and
pattern of morbidity, questions were put to the respondents. The
incidence of morbidity works out to 42 per thousand with the previous
month as the reference period . We limited the reference period to one
month in order to avoid recall lapse and related errors. This was
comparatively lower in the slums at 38 and higher in the suburbs at 49.
There is some difference in the prevalence of morbidity among the three
groups. Out of 500 households surveyed in the slums, 246 had at least
one member who was ill at the time of the survey. Out of the 250
surveyed in each of the other two areas, 129 in the non-slum areas and
111 in the suburban areas had one member sick. Some households had 2
and some three, making the total ill 282 in the slums, 148 in the
non-slum areas and 129 in the suburban areas. The sample sizes in the
three areas are is 2206, 1023 and 1068 respectively. Thus the
prevalence of morbidity works out to 127.8 per thousand in the slum
areas, 144.7 in the non-slum areas, 120.8 in the suburban areas and
130.1 in the entire study area. A comparison of this with the morbidity
of the state for different years available in other surveys is given in
Table 4.1
Table 4.1 Morbidity Rates in Kerala and
Trivandrum City
| Disease |
Kerala |
Trivandrum City 2001 |
| NSS 1974 |
KSSP 1987 |
KSSP 1996 |
NCAER 1993 (Urban) |
Urban |
Suburban |
Total |
| Slum |
Non Slum |
| Acute |
71.2 |
206.4 |
121.9 |
210.0 |
127.8 |
144.7 |
120.8 |
130.1 |
| Chronic |
83.7 |
138.0 |
114.6 |
Source: Kunhikannan & Aravindan (2000) for
columns 1 to 4
Shariff 1999 for column 5
Note:
The recall period of the three other surveys is two weeks.
To Top
4.1.2 In the present survey a
clear distinction between chronic and acute diseases has not been
attempted. However, the general picture that emerges is that the
prevalence of morbidity in Trivandrum City is not much different from
the state. Morbidity is the lowest in the suburban areas. This is
understandable as these were villages till recently and were added on
to the city for administrative convenience. They carry the
characteristics of a village in some respects and city in some others.
But it is surprising that more people in the non-slum areas fall ill
than in the slum areas. An explanation for this may have to be sought
in the perception of illness among people at different levels of social
development.
4.1.3 It is generally observed that among people
with low economic status and poor health indicators, the morbidity is
also very low. This is because the surveys look at the perceived
morbidity and poor people may not perceive some small episodes of
illness as significant enough to seek treatment and recall and report.
This question has been agitating some writers like Johanson S Ryan and
Riley. The latter who reviewed the morbidity trends in Japan, United
States, Britain and Hungary found that sickness prevalence has moved in
a direction opposite to the death rate for most of the age and sex
groups (Riley 1990). This is well illustrated in Indian states as well.
Surveys have shown repeatedly that Kerala which has very good health
indicators as we saw in Chapter I, has the highest prevalence of
morbidity. It was 163 per thousand in 1994 against an all India figure
of 94. A state like Bihar with an IMR of 67 and life expectancy of 60
had only the prevalence rate of 91 per thousand in the same survey
(NCAER 1994). The picture about major morbidity is not different,
showing Kerala with a major morbidity prevalence rate of 73.2, India
45.8 and Bihar 38.2 (Sharif 1999). When one bears this dimension in
mind it need not be surprising that the people with better education,
and income, living in the non-slum areas have a more intense perception
about morbidity, recall minor ailments which the slum dwellers might
ignore.
4.2 Pattern of Morbidity
4.2.1 Communicable diseases
constitute a major burden of disease in India, accounting for 50 per
cent of the burden compared to only 18 per cent in China, a country
very similar, and 43.8 per cent in low and middle income countries in
1998 (WHO, 1999). With this background, a specific question was put
whether the respondents had any communicable diseases during the recall
period. Only 9 out of the 4297 persons questioned reported that they
had communicable diseases. However as can be seen in Table 4.2, many
had fever, some of which like typhoid fever would be communicable. It
is quite likely that the respondents did not recognize them as
communicable. Therefore this data on communicable diseases is not
conclusive.
4.2.2 Out of the 559 people who were ill, 130
(23.3per cent) were down with fever, cold, headache etc. making the
incidence rate of this common complaint 232 per thousand. This omnibus
group is the largest group of ailments in the KSSP Survey also, being
118 in 1987 and 68 in 1996 over a two-week recall period. Not much
difference is observed among the three areas about the incidence of
this group of illnesses as can be seen from Table 4.2
To Top
Table 4.2 Nature of Disease (%)
| Disease |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Pneumonia Fever, Severe cold, Headache, Migraine,
Toothache etc. |
20.6 |
26.4 |
25.6 |
23.3 |
| Blood Pressure, Heart Problems |
24.8 |
16.9 |
10.9 |
19.5 |
| Asthma, Cough, Breathing Difficulty |
22.0 |
12.8 |
16.3 |
18.2 |
| Paralysis, Stroke, Arthritis, Rheumatism |
10.3 |
12.8 |
12.4 |
11.4 |
| Diabetes, Kidney Trouble, Urinary infection, Uterus
complaint |
3.9 |
13.5 |
7.0 |
7.2 |
| Dysentery, Gas Trouble, Vomiting Stomach ache, Ulcer in
the GI Tract, Jaundice Appendicitis |
5.7 |
5.4 |
6.2 |
5.7 |
| Allergy & Skin Diseases |
2.1 |
2.7 |
7.0 |
3.4 |
| Eye problem, Hearing impaired |
1.8 |
3.4 |
3.1 |
2.5 |
| Accident |
3.5 |
0.7 |
1.6 |
2.3 |
| Cancer, Tumour |
1.1 |
2.0 |
3.1 |
1.8 |
| Mental Problem, Retarded Growth, Epilepsy |
1.4 |
2.0 |
1.6 |
1.6 |
| Tuberculosis |
1.8 |
0.0 |
1.6 |
1.3 |
| Goiter, Thyroid problem |
0.7 |
0.7 |
0.8 |
0.7 |
| Filariasis |
0.4 |
0.0 |
0.8 |
0.4 |
| Measles |
0.0 |
0.7 |
0.8 |
0.4 |
| Chickenpox |
0.0 |
0.0 |
1.6 |
0.4 |
| Total |
100 |
100 |
100 |
100 |
| Number |
282 |
148 |
129 |
559 |
4.2.3 After fever,
cardio-vascular problems seem to be the highest, nearly 20 per cent
suffering from that. It is interesting to note that nearly 25 per cent
of the sick in slums suffer from this, while in the non-slum it is only
17 per cent and in the suburbs only 11 per cent. One would expect this
group of life style related ailments to be more prevalent among the
richer group of non-slums. But here the picture is different.
4.2.4 The next group of common ailments is
asthma, cough and breathing difficulty, afflicting about 18 per cent of
the ill. This, again, is more in the slums with 22 per cent, while it
is only about 13 in the non-slum areas and 16 in the suburbs. The
fourth group of ailments is nervous disorders like paralysis, stroke,
etc. affecting 11.4 per cent. In this, the slums are better placed with
only about a tenth suffering from this, against about an eighth in the
other areas. Another finding of interest is that though only 2.3 per
cent of the ill were accident victims, their proportion in the slums is
3.5 per cent against less than one in the non-slums and 1.6 in the
suburbs
To Top
4.3 Duration of illness
4.3.1 The intensity of illness is
indicated, among other things by its duration. The responses to the
questions on this are presented in Table 4.3.
Table 4.3 Duration of Illness (%)
| Duration |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 1 month and less |
29.8 |
29.1 |
40.3 |
32.0 |
| 2 months |
4.3 |
4.1 |
3.9 |
4.1 |
| 3 months |
3.5 |
2.7 |
2.3 |
3.0 |
| 4 months |
2.1 |
2.0 |
1.6 |
2.0 |
| 5 months |
1.1 |
0.7 |
1.6 |
1.1 |
| 6 months |
3.2 |
2.7 |
1.6 |
2.7 |
| 7 month |
0.7 |
0.7 |
1.6 |
0.9 |
| 8 months |
0.4 |
1.4 |
1.6 |
0.9 |
| 9 months |
0.4 |
0.7 |
1.6 |
0.7 |
| 10 months |
0.7 |
1.4 |
0.8 |
0.9 |
| 12 months |
2.8 |
3.4 |
0.8 |
2.5 |
| 4 Years |
20.6 |
22.3 |
19.4 |
20.8 |
| 9 Years |
14.5 |
12.2 |
8.5 |
12.5 |
| Above 10 years |
12.1 |
14.2 |
14.0 |
13.1 |
| Period not specified |
2.5 |
2.7 |
0.8 |
2.1 |
| No data. |
1.4 |
0.0 |
0.0 |
0.7 |
| Total |
100 |
100 |
100 |
100 |
| Number |
282 |
148 |
129 |
559 |
4.3.2 Out of the 559 persons
reported ill 32per cent were ill for less than a month and 48.5per cent
for more than a year. Illness lasting less than a month can be assumed
to be of a minor nature. The percentage of people with less than one
month’s illness in the slum is 29.8 and in the non-slums 29. However,
it is quite high at 40.3 per cent in the suburbs. This shows that more
of the sick in the suburbs suffered from illness of a minor nature.
This is in tune with our earlier observation that the incidence of
sickness in the suburbs is the lowest (Table 4.1). Those who were ill
for more than a year is 49.7 per cent in the slums 51.4 in non-slum
areas and 42.6 in the suburban areas. Here also the suburbans fare
better than the other two resident groups. Enquiries were also made to
find out whether the diseases are still prevailing and if not how long
it lasted. No significant difference could be noticed in this. (Table
not given)
To Top
4.4 Treatment
4.4.1 Most of those who were ill
(96.6 per cent) went in for treatment. There is very little variation
among the three areas in this. The reasons for not seeking treatment
are given in Table 4.4.
Table 4.4 Reasons for not Taking Treatment (%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 1. Financial cost |
55.6 |
66.7 |
50.0 |
57.9 |
| 2. Not believing in treatment |
1.1 |
0.0 |
0.0 |
5.3 |
| 3. Self-treatment |
33.3 |
33.3 |
50.0 |
36.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
9 |
6 |
4 |
19 |
4.4.2 More than a third (7
persons) resorted to self-treatment and 58 per cent did not go for
treatment because of the cost involved. However these are too small
numbers to draw any meaningful inference.
4.4.3 Most of those who took treatment resorted
to allopathic system and only 8.7 per cent of them chose other systems
like homoeopathy and Ayurveda . The percentage of non-slum ill who took
to other systems of medicine treatment is 14, whereas the percentage of
slum ill is only 5.5 and that of suburban ill 9.6.
Table 4.5 Type of Treatment (%)
| Type of Treatment |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Allopathy |
94.5 |
85.9 |
90.4 |
91.3 |
| Homeopathy |
1.8 |
8.5 |
2.4 |
3.7 |
| Ayurveda |
3.7 |
5.6 |
7.2 |
5.0 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
273 |
142 |
125 |
540 |
To Top
4.4.4 An interesting light is
shown on the health system seeking behavior of different groups.
Probably, the higher level of education among the non-slum people make
them more conscious of the side effects of modern medicine and willing
to experiment with the other systems. Generally, in India, reliance on
traditional system of medicine is very high among the rural poor
because of questions of physical and financial access. The survey shows
that once the barriers to access are removed, the poor people would
like to go for the sure shot of modern medicine. It is the better off
people who are more conscious of the side effects who would like to try
out alternate systems of medicine. In the Bellagio Conference on Good
Health at Low Cost (1985) the prevalence of traditional medicine is
identified as one of the common features of China, Sri Lanka and
Kerala, which were three of the four regions considered as models for
low cost health care (Halstead et al 1985). It appears that the poor
are apparently losing faith in the alternative systems. Perhaps they
cannot afford to spend more time on recovering from illness which the
alternate systems entail and would like to get back to their work as
early as possible as otherwise they would lose income. The gains in
preventive medicine and cost effective health care provided by the
alternate systems of medicine seem to be getting eroded. What this will
lead to and what are the implications on public health requires to be
further studied.
4.4.5 The type of hospital they went to and the
reasons why some did not go to public facilities are dealt with in
Chapter VIII.
4.4.6 Next we tried to find out if they had any
difficulty in accessing the facility for treatment. Out of the 540
patients, 6.7 per cent visited health facilities within a kilometer and
29 per cent within two kilometers as seen in Table 4.6.
Table 4.6 Distance to the Hospital (%)
| Distance in Km. |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| <1 |
9.1 |
3.5 |
4.8 |
6.7 |
| 1 |
19.7 |
32.6 |
15.2 |
22.0 |
| 2 and 3 |
23.8 |
18.4 |
14.4 |
20.1 |
| 4 to 9 |
26.1 |
21.3 |
32.8 |
29.3 |
| 10 |
14.6 |
15.6 |
14.4 |
14.8 |
| 11 to 19 |
4.8 |
6.4 |
13.6 |
7.2 |
| 20 plus |
2.2 |
2.1 |
4.0 |
2.6 |
| No Data |
0.0 |
0.0 |
0.8 |
0.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
273 |
142 |
125 |
540 |
To Top
4.4.7 More people in the slums
visited facilities within one kilometer, while those who went to
facilities within two kilometers are more in the non-slum areas (36 per
cent). In the suburban areas it is less at 20 per cent. However, the
fact that 25per cent of the patients had to travel more than 10 kms. to
the health facility in a city like Trivandrum is surprising. 1.7 per
cent had to travel more than 20 kms. But it has to be borne in mind
that this distance is to the hospital they chose to go to and not to
the nearest hospital.
4.4.8 The data on distance to the hospital of
choice is corroborated by the fact that 23.3 per cent of the patients
walked to the hospital (Table 4.7). This means a large majority of
those who went to the facility within two kms. did not have to engage
any means of transport.
Table 4.7 Mode of Conveyance (%)
| Mode |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| By Walk |
23.7 |
24.8 |
20.8 |
23.3 |
| By Bus |
48.9 |
2.6 |
55.2 |
48.7 |
| By Auto Rickshaw |
27.0 |
24.8 |
23.2 |
25.6 |
| By Car |
0.4 |
7.8 |
0.8 |
2.4 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
273 |
142 |
125 |
540 |
4.4.9 Only 2.4 percent had to go
by car. More than 22 percent did not have to spend anything at all on
transportation to the hospital, broadly corroborating the figure of 23
per cent who went by walk.
4.4.10 As seen in Table 4.10, 53 per cent had to
spend only less than Rs.15/- on transport to the hospital. This is a
very small amount. There is no significant difference among the three
groups in this regard.
Table 4.8 Expense for the Journey (%)
| Expense in Rs. |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Nil |
23.7 |
24.8 |
16.8 |
22.4 |
| 1-15 |
53.3 |
46.8 |
58.0 |
52.7 |
| 16-25 |
12.1 |
8.5 |
16.8 |
12.2 |
| 26-30 |
4.5 |
9.2 |
1.6 |
5.1 |
| 41-45 |
3.3 |
3.5 |
1.6 |
3.0 |
| 66-70 |
1.4 |
1.4 |
4.0 |
2.0 |
| 76+ |
1.8 |
5.7 |
1.6 |
2.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
273 |
142 |
125 |
540 |
To Top
4.5 Expenses for Treatment
4.5.1 Regarding the expenses for
treatment of the illnesses that occurred during the previous month, it
may be seen from Table 4.9 that, out of the 540 patients 451 (83.5 per
cent) incurred some expenditure.
Table 4.9 Expense for Treatment (%)
| Expenses in Rs. |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 1-100 |
34.6 |
28.2 |
40.6 |
34.4 |
| 101-200 |
20.2 |
19.7 |
15.1 |
18.8 |
| 201-300 |
11.8 |
8.5 |
8.5 |
10.2 |
| 301-400 |
6.1 |
11.1 |
6.6 |
7.5 |
| 401-500 |
8.3 |
15.4 |
5.7 |
9.5 |
| 501-600 |
2.2 |
5.1 |
3.8 |
3.3 |
| 601-700 |
0.0 |
2.6 |
5.7 |
2.0 |
| 701-800 |
1.8 |
2.6 |
5.7 |
2.0 |
| 801-900 |
0.4 |
0.0 |
0.0 |
0.2 |
| 901-1000 |
5.3 |
5.1 |
5.7 |
5.3 |
| 1001+ |
9.2 |
1.7 |
4.7 |
6.2 |
| Total |
100 |
100 |
100 |
100 |
| Number |
282 |
148 |
129 |
559 |
| Median expenditure in Rs. |
178 |
216 |
158 |
185 |
To Top
4.5.2 Out of the spenders, a third
spent only less than Rs.100 a month. The largest proportion of patients
in all the three areas belongs to this group. In the suburbs it is
nearly 41 per cent. Those who had to spend between Rs.100 and 200 are
nearly 19per cent. If we take these two groups together we can see that
the majority of the people (53.2 per cent) had to spend less than
Rs.200 on treatment. Nearly 55 per cent of the slum patients and 48 per
cent of the non-slum patients and 56 per cent of the suburban patients
belong to this group. Thus, overall, the expenses for treatment do not
appear to be high in the majority of cases. However, it is significant
that 9.2 per cent of the slum patients and 4.7 per cent of the
suburbans had to spend more than Rs.1000. The median expenses for
treatment work out to Rs.185 for the total. The fact that the non-slum
dwellers have a higher median expenditure implies, perhaps, a higher
burden of chronic diseases.
4.5.3 It may be noted that the expenditure for
treatment given in Chapter III refers to the average expenditure for
all households, whereas here we are dealing with the expenditure
incurred only by those who underwent treatment during the previous
month.
4.5.4 The total expenses as seen in Table 4.10
was gathered by adding up the expenses for the purchase of medicine,
fee for the doctor, the investigations and x rays and other
miscellaneous expenses. It would be interesting to find out the
expenses for the purchase of medicine alone. Table 4.12 shows that the
median expenditure for purchasing medicines is Rs.93, the highest being
in the non-slum areas with Rs.104. this is to be expected as they have
a higher burden of chronic disease.
Table 4.10 Expense for the Purchase of Medicine
(%)
| Expenses in Rs. |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Nil |
28.1 |
29.8 |
23.2 |
27.4 |
| 1-25 |
4.1 |
21.2 |
24.0 |
13.3 |
| 26-50 |
17.8 |
6.1 |
24.0 |
16.3 |
| 51-75 |
9.1 |
4.0 |
3.1 |
6.4 |
| 76-100 |
22.3 |
17.2 |
18.8 |
20.2 |
| 101-150 |
10.2 |
12.1 |
6.3 |
9.7 |
| 151-200 |
14.2 |
16.2 |
7.3 |
13.0 |
| 201-250 |
2.5 |
5.1 |
3.1 |
3.3 |
| 251-300 |
15.2 |
8.1 |
9.4 |
12.0 |
| 301+ |
4.6 |
10.1 |
4.2 |
5.9 |
| Total |
100 |
100 |
100 |
100 |
| Number |
197 |
99 |
96 |
392 |
| Median expenditure in Rs. |
97 |
104 |
67 |
93 |
To Top
4.5.5 Out of the 540 patients who
took treatment, 148 (27.4 per cent) did not have to spend anything at
all, 28per cent in the slums, nearly 30per cent in the non-slums and
23per cent in the suburbs. The patients who went to Government
hospitals are 67 per cent, as we will be seeing elsewhere in Chapter
VIII. The free distribution of drugs is only in the public facilities
and there is perennial complaint about its shortage in the Government
hospitals. In this study, we observe that while about two-thirds of the
patients go to Government hospitals, only a little over 27 per cent get
the medicines free. This means that only 40 per cent of those who go to
government hospitals get free medicine confirming the general
impression about the shortage of drugs in government hospitals. This
assumes that only government hospitals give medicines free. Another
interesting information is that 65 of the 540 patients (12 per cent)
paid some fees to the doctor. Private practice is allowed for
government doctors in the state. Very often there are complaints that
without paying fees to the doctor privately no proper treatment will be
available in government hospitals. In Kerala there is no practice of
levying separate fees by the doctor in private hospitals. Therefore one
could reasonably conclude that the payment was to government doctors in
their private consultation. Even then, it is not a sizable proportion
as more than two thirds went to government hospitals for treatment and
those who paid money to doctor are only 65 in number. On the assumption
that all this money was paid to government doctors, the percentage of
the patients who paid money to government doctors works out to 17 per
cent only. However some private doctors who run only outpatient clinics
and not hospitals would be collecting fees. Therefore the proportion of
patients who paid fees to government doctors is likely to be even less
than 17 per cent.
Table 4.11 Fee for Doctors (%)
| Expenses in Rs. |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 1-25 |
6.5 |
8.0 |
0.0 |
6.2 |
| 26-50 |
22.6 |
48.0 |
11.1 |
30.8 |
| 51-75 |
3.2 |
0.0 |
0.0 |
1.5 |
| 76-100 |
61.3 |
24.0 |
55.6 |
46.2 |
| 101-150 |
0.0 |
4.0 |
11.1 |
3.1 |
| 151-200 |
3.2 |
4.0 |
0.0 |
3.1 |
| 201-250 |
0.0 |
0.0 |
0.0 |
0.0 |
| 251-300 |
0.0 |
0.0 |
0.0 |
0.0 |
| 301+ |
3.2 |
12.0 |
22.2 |
9.2 |
| Total |
100 |
100 |
100 |
100 |
| Number |
31 |
25 |
9 |
65 |
To Top
4.5.6 Among those who paid, about
40 per cent paid only less than Rs.50, the proportion being more than
half in the non slum areas and much less in the other two. It may be
noted that most of them (84.7 per cent) paid Rs.100 or less as doctor’s
fee. An interesting piece of information is that it is in the slums
that more people paid between Rs. 75 and 100, followed by suburbs,
while in the non-slums more people paid between Rs 25 and 50. The
reasons for this are not clear.
4.5.7 The source of money was the next question
put to them.
Table 4.12 Source of the Money for Treatment
| Particulars |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| No. |
% |
No. |
% |
No. |
% |
No. |
% |
| No need for money |
26 |
9.5 |
18 |
12.8 |
33 |
26.4 |
77 |
14.3 |
| Own |
101 |
36.9 |
79 |
56.0 |
33 |
26.4 |
213 |
39.4 |
| Other Sources |
147 |
53.6 |
44 |
31.2 |
59 |
47.2 |
250 |
46.3 |
| Total |
274 |
100.0 |
141 |
100.0 |
125 |
100.0 |
540 |
100.0 |
4.5.8 Out of the 540 patients
who took treatment, only 39.4 per cent could find their own money and
46.3 per cent had to find money from other sources. The largest
proportion of those who had to find money from outside is in the slums
with 53.6 per cent. The suburbs with 47.2 per cent and non-slum with
31.2 follow it. Thus the proportion of ill in the slums who had to
raise money is much higher than in the other two groups. This speaks of
the high financial burden that a disease casts on the slum dwellers.
4.5.9 The heaviness of the burden becomes more
apparent when we look at the loss of wages due to illness.
Table 4.13 Wage Loss Due to Illness (%)
| Amount lost |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 1-150 |
2.4 |
10.5 |
7.7 |
4.9 |
| 151-300 |
8.8 |
0.0 |
2.6 |
5.6 |
| 301-450 |
1.2 |
0.0 |
5.1 |
2.1 |
| 451-600 |
8.2 |
15.8 |
15.4 |
11.2 |
| 601-750 |
4.7 |
0.0 |
7.7 |
4.9 |
| 751-900 |
1.2 |
0.0 |
0.0 |
0.7 |
| 901-1050 |
18.8 |
21.1 |
2.6 |
14.7 |
| 1051-1200 |
0.0 |
5.3 |
0.0 |
0.7 |
| 1201-1350 |
1.2 |
0.0 |
0.0 |
0.7 |
| 1351-1500 |
7.1 |
5.3 |
12.8 |
8.4 |
| 1501-3000 |
8.2 |
10.5 |
7.7 |
8.4 |
| 3001-4500 |
2.4 |
0.0 |
7.7 |
3.5 |
| 4501-6000 |
2.4 |
0.0 |
0.0 |
1.4 |
| 6001-7500 |
2.4 |
0.0 |
0.0 |
1.4 |
| 7501-9000 |
3.5 |
5.3 |
2.6 |
3.5 |
| 9001 |
2.4 |
26.3 |
2.6 |
5.6 |
| No Data |
25.9 |
0.0 |
25.6 |
22.4 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
85 |
19 |
39 |
143 |
To Top
4.5.10 Out of the 540 patients,
143 (26.5 per cent) suffered loss of wages due to illness that occurred
in the previous month. This is 31 per cent in the slums and suburbs.
But in the non-slum area this percentage is only 13.5. As can be seen
from Chapter III more people in the slums and suburban areas are daily
wage earners and, therefore, this is not surprising. Out of the 143
patients who suffered financial loss due to illness, 22.4 per cent
could not furnish any data about the amount of loss. The others
reported losing varying amounts of income. When the amounts were
grouped into intervals of Rs.150, the group that had the largest number
of people was found to be Rs.901 to Rs.1050/-. Nearly 15 per cent of
the patients suffered a loss in this range. While the proportion was 21
per cent in the suburbs and non-slums, it was nearly 19 per cent in the
slums. Some people had to lose more than Rs.9000/-. Those in the
non-slum area belonging to this category are 26.3 per cent. However, it
may be borne in mind that the sample size is very small.
4.5.11 Table 4.16 shows how the sick raised
money for treating themselves.
Table 4.14 How the Money was Raised (%)
| Particulars. |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Borrowed |
81.6 |
75.0 |
76.3 |
79.2 |
| Selling of land |
2.7 |
15.9 |
23.7 |
10.0 |
| Selling of Gold |
3.4 |
4.5 |
0.0 |
2.8 |
| Pledging of Gold |
4.8 |
4.5 |
0.0 |
3.6 |
| From Church |
2.0 |
0.0 |
0.0 |
1.2 |
| Help from relatives |
5.4 |
0.0 |
0.0 |
3.2 |
| Total |
100 |
100 |
100 |
100 |
| Number |
147 |
44 |
59 |
250 |
To Top
4.5.12 Nearly 80 per cent of
those who had to raise money from outside borrowed it, more in the
slums than in the other two areas. About one-eighth of the patients had
to liquidate assets like land and gold ornaments, 23.7 per cent of in
the suburbs, 20.4 per cent in the non-slum areas and only 6.1 per cent
in the slums. On the whole the slum dwellers could rely more on
borrowing and the need for liquidating assets was much less. Perhaps
they do not have much assets to liquidate. A total of 4.4 per cent
relied on help from relatives and religious organizations. It is
noteworthy that 5.4 per cent in the slums could get help from relatives
while none in the other two areas could manage it. Perhaps the slum
dwellers living closely together as a community has better access for
borrowing from friends and relatives.
4.5.13 A recent study by the World Bank has
shown that more than 40 per cent of the hospitalized Indians had to
borrow money or sell assets to meet the cost. (World Bank, 2001) Though
our study is not limited to hospitalization, the finding is not much
different. Out of the 540 persons who underwent treatment 250 had to
raise money from outside. If we leave the small proportion who got help
from relatives and religious institutions, the number of those who had
to borrow or sell assets is 239, making a percentage of 44.2. The World
Bank continued the enquiry and found that hospital expenses alone push
2.2 per cent of Indians below the poverty line. Our study did not have
in its scope this particular line of enquiry. However, we have seen in
Chapter III that 15 per cent of the people reported a monthly income of
less than Rs.1500, which is the amount, required for crossing the
poverty line. The proportion is substantially higher in the slums and
suburbs at 21 per cent and 18 per cent respectively. The ill in the
slums who had to spend upto Rs.200 for treatment are nearly 55 per cent
and in the suburbs more than 55. About a tenth of the people suffered a
wage loss upto Rs.300. Ignoring the small cost of transportation, these
two amounts will be pushing some people below the poverty line in the
slums and suburbs. It is certainly worth studying this separately.
4.6 Mortality
4.6.1 Mortality rate is often
considered a proxy for the health status of a community. The State of
Kerala has already achieved a low level of mortality with a crude death
rate of 6.4 per thousand and Infant Mortality Rate of 16 per thousand
live births (Census 2000b). Although our study does not permit the
computation of mortality rates, we have attempted to study the
mortality in the last three years and its causes.
4.6.2 During the last three years, the total
sample population experienced 92 deaths: 62 per cent men and 38 per
cent women. This ratio is maintained in the slums and non-slums and
slightly changed in the suburban areas as is evident in Table 4.15.
To Top
Table 4.15 Mortality within 3 Years (%)
| Particulars |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Male |
63.6 |
66.7 |
53.8 |
62.0 |
| Female |
36.4 |
33.3 |
46.2 |
38.0 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
33 |
33 |
26 |
92 |
4.6.3 A rough estimate of Crude
Birth Rate during the last three-year period works out to 7.3, which is
higher than the state average.
4.6.4 The age distribution of deaths shows that
most of the people died of old age, which is a reflection of population
aging. Table 4.16 shows that the total percentage of people who died
after 65 is 45.6 per cent.
Table 4.16 Age at Death (%)
| Age in Years |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 10-14 |
6.1 |
0.0 |
7.7 |
4.3 |
| 15-19 |
3.0 |
0.0 |
7.7 |
3.3 |
| 20-24 |
0.0 |
0.0 |
3.8 |
1.1 |
| 25-29 |
3.0 |
3.0 |
0.0 |
2.2 |
| 30-34 |
9.1 |
0.0 |
0.0 |
3.3 |
| 35-39 |
0.0 |
0.0 |
0.0 |
0.0 |
| 40-44 |
6.1 |
9.1 |
3.8 |
6.5 |
| 45-49 |
6.1 |
9.1 |
3.8 |
6.5 |
| 50-54 |
9.1 |
6.1 |
7.7 |
7.6 |
| 55-59 |
3.0 |
6.1 |
7.7 |
5.4 |
| 60-64 |
6.1 |
9.1 |
7.7 |
7.6 |
| 65-69 |
3.0 |
0.0 |
7.7 |
3.3 |
| 70-74 |
21.2 |
12.1 |
23.1 |
18.5 |
| 75-79 |
12.1 |
6.1 |
0.0 |
6.5 |
| 80-84 |
9.1 |
18.2 |
11.5 |
13.0 |
| 85-89 |
3.0 |
6.1 |
0.0 |
3.3 |
| 90+ |
0.0 |
9.1 |
3.8 |
4.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
33 |
33 |
26 |
92 |
| Mean age at death(Years) |
55.7 |
64.0 |
57.7 |
59.3 |
| Standard deviation |
20.89 |
17.91 |
22.03 |
20.6 |
To Top
4.6.5 The average life expectancy
of the state is 72 years. In our sample more than a fifth of the people
have lived beyond the age of 74. If we look at the proportion of people
who died in different age groups in the three areas, we can see that
the largest proportion (18.5per cent) died between 70 and 74 years.
More than 21 per cent of the deaths in the slums and more than 12 pr
cent in the non-slums and 23 per cent in the suburbs occurred in this
age group. Generally it is the people in the non-slum areas that live
longer, the mean age at death there being the highest at 64 followed by
suburbs at 57.7 and slums at 55.7. The tables do not include one infant
death that occurred in the slums.
4.6.6 Regarding the causes of death, in a little
over 3 per cent the cause was not diagnosed.
Table 4.17 Causes of Death (%)
| Cause |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Not Diagnosed |
6.1 |
3.0 |
0.0 |
3.3 |
| Geriatric ailments |
24.2 |
36.4 |
23.1 |
28.3 |
| B.P., Heart Attack |
15.2 |
24.2 |
19.2 |
19.6 |
| Suicide |
21.2 |
0.0 |
19.2 |
19.6 |
| Cancer |
6.1 |
12.1 |
7.7 |
8.7 |
| Diabetes, Kidney problems |
6.1 |
0.0 |
15.4 |
6.5 |
| Asthma |
6.1 |
9.1 |
3.8 |
6.5 |
| T.B. |
0.0 |
6.1 |
7.7 |
4.3 |
| Paralysis, Brain stroke |
3.0 |
3.0 |
3.8 |
3.3 |
| Jaundice |
6.1 |
0.0 |
3.8 |
3.3 |
| Ulcer |
3.0 |
3.0 |
0.0 |
2.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
33 |
33 |
26 |
92 |
4.6.7 It can be seen in Table 4.19
that 28.3 per cent of the deaths were due to geriatric ailments, the
highest proportion (36.4per cent) being in the non-slum areas. Though
cardio vascular diseases are the major cause of morbidity in the slums,
afflicting about 25 per cent of the sick, its fatal blow is felt more
in the non-slums with more than 24 per cent of the deaths caused by it.
This is much higher than the rate of 14.3 reported for the state in the
KSSP survey of 1996 (Kunhikannan and Aravindan 2000). It is quite
disturbing that suicide is the second largest killer in the slums,
accounting for 21.2 per cent of the deaths. It is nil in the non-slum
areas and less than 4 per cent in the suburbs. This is also much higher
than the state figure of 2.8 per cent of the KSSP study. This ought to
be a matter of serious concern. Kerala has one of the highest suicide
rates in the country with 28 per 100,000 against the country’s average
of 8 (various reports of the Kerala State Mental Health Authority). The
reasons for concentration of this in slum areas have to be investigated
without delay and interventions sought. We saw in Table 4.1 that the
morbidity due to accidents is the highest in the slums at 3.1 per cent
and it is only 1.6 per cent in the suburbs. However, the mortality due
to accidents is 5.4, almost the same as 5.7 in the KSSP study. It is
the highest in the suburbs at 11.5 per cent whereas in the other two
areas it is only 3 per cent. Diabetes and kidney problems accounted for
6.5 per cent of the deaths. If this is combined with blood pressure and
hearth attack, which commonly constitute the diseases of life style, we
can observe that 25.8 per cent of the deaths are due to this group of
diseases. In the slums it accounted for 21.3 per cent and in the
suburbs 34.6 per cent. In the non-slums there was no death due to
diabetes or kidney problem and therefore, the percentage is that of BP
and heart attack (24.2). Cancer caused 8.7 per cent of the deaths in
our study sample and almost the same in the state at 8.6 in the KSSP
study
To Top
4.7 Summary
4.7.1 We find that the incidence
of morbidity in the study sample is 130 per thousand and higher in the
non-slum areas. This is higher than the figure for the state reported
in various studies. But it is nothing to be alarmed about as we saw
that perceived morbidity goes up and not down with improved
development. Among the causes of morbidity, if we take away fever and
related common ailments, cardio vascular diseases take the highest
place in the slums afflicting more people there than in the other
areas. Acute respiratory infections are the most common disease among
the suburbans. Though the share of accidents is small, slums take the
lead in this.
4.7.2 About the duration of illness the
suburbans take the lead over the others with more short duration
illnesses. Most of them went for treatment, choosing the allopathic
system. Mostly they went to health facilities nearby, walking to it or
taking a ride by bus or auto rickshaw, spending small amounts for
transportation. Most of them had to spend some money for the treatment,
the amount being less than Rs.200 in the majority of cases with little
difference among the three resident groups. Only about 40 per cent of
those who went to government hospitals got all the medicine free. But
only 12 per cent of the patients had to pay fees to the doctor, the
amount being in the range of Rs.25 to 100 in the majority of cases.
Nearly half of those who spent money for treatment had to raise it from
other sources. Most of them borrowed it. Nearly a fourth in the suburbs
and a fifth in the non-slum areas had to sell their land or gold to
defray the expenses for treatment, while in the slums only a little
more than a twentieth had to do so. A little over a fourth of the sick
had to lose their wages also due to the illness. Thus the financial
burden caused by morbidity on the poor appears to be substantial,
calling for further investigation.
4.7.3 The Crude death rate for the sample is
found to be 7, not much different from the figure of 6.4 for the state.
A good number of people live longer than the average life expectancy of
72 for the state. Though the average age of death is 60, people in the
slums die younger at about 56 against 64 in the non-slums. Geriatric
ailments are, quite naturally, the most common cause of death. After
that, the greatest killer is cardio vascular disease, accounting for
about a fifth of the deaths. But in the slums this place is taken by
suicides.
To Top
V. Reproductive Health of Women
5.1 Introduction
5.1.1 India, the second most
populous country in the world crossing the one billion mark in May
2000, is one of the first to introduce programmes to control the
runaway growth of population. At the initiation of the programme in
1952 it was primarily a clinic-based family planning programme. This
was transformed into an extension programme in 1963 integrating it with
Maternal and Child Health care (MCH). 1992 saw the launching of the
Child Survival and Safe Motherhood (CSSM) programme with greater
emphasis on the reduction of maternal and infant mortality. Until 1996,
a target-oriented approach was followed so as to maximise the level of
family planning acceptance. After the International Conference on
Population and Development (ICPD) in Cairo 1994 the Population
Programme was given a different emphasis encompassing within its fold
the entire reproductive and Child Health of Women and Men. The
target-based approach has given way to the Community Needs Based
Assessment in India. The programme of Reproductive and Child Health
launched in 1996 puts this emphasis into practice. The New Population
Policy adopted by the Indian Parliament in February 2000 outlines the
strategy for achieving replacement level of fertility by 2010 and
stabilisation of population by 2045 (GOI 2000). This Survey had, as one
of its major components, questions about reproductive health status of
855 ever-married women between 15 and 49 years. Detailed probing was
done into the status of their reproductive health starting from puberty
and encompassing marriage, pregnancy, childbirth and contraception.
5.2 Menstrual Cycle
5.2.1 We began at the commencement
of the reproductive health with questions on puberty. Table 5.1 shows
the distribution of age at menarche of ever-married women between 15
and 49 years and adolescent girls by residential status.
Table 5.1 Age at Menarche (%)
| Age |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| EMW |
AG |
EMW |
AG |
EMW |
AG |
EMW |
AG |
| Less than 11 |
0.7 |
18.2 |
0.5 |
41.5 |
0.5 |
17.8 |
0.6 |
22.0 |
| 11-12 |
23.0 |
58.5 |
24.2 |
48.8 |
22.5 |
43.9 |
23.1 |
54.4 |
| 13 and Above |
76.3 |
20.8 |
75.3 |
9.8 |
77.0 |
39.0 |
76.3 |
22.1 |
| Not Started |
0.0 |
2.5 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
1.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
456 |
159 |
190 |
41 |
209 |
41 |
855 |
241 |
| Mean |
13.3 |
12.5 |
13.1 |
11.6 |
13.2 |
12.9 |
13.3 |
12.4 |
Note: EMW: Ever Married Women (15-49 years)
AG: Adolescent Girls ( 13 – 18 years)
To Top
5.2.2 One look at the table tells
the story of age at menarche advancing with the passage of time. While
only less than 1 per cent of the married women attained puberty before
11years, 22 per cent of the girls attained it at that time. This huge
differential persists irrespective of the area of residence. This is
probably due to the improved nutritional status of the girls compared
to women. This presumption gets strength when we note that in the
non-slum areas where the girls are likely to be better fed, 41.5 per
cent of them attained puberty before 11 while it is about 18 per cent
in the other two areas. More than half the girls attained puberty
between 11 and 12, while more than three fourths of the married women
attained it after 13. There is little difference among the areas in
this. But the upper age in the case of slum women went up to 19 years,
suburban to 18 years and non-slum to 17 years (data not shown). The
mean figure for the married women and the girls reconfirms the fact of
the latter attaining puberty earlier, the difference being about a year.
5.2.3 The next enquiry was about the regularity
of menstrual cycle and the problems during their periods. Both ever
married women and adolescent girls (AG) were separately asked about it.
The responses are presented in Table 5.2
Tables 5.2 Regularity of Menstrual Cycle (%)
| Regularity |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| EMW |
AG |
EMW |
AG |
EMW |
AG |
EMW |
AG |
| Regular |
80.3 |
92.8 |
91.6 |
96.5 |
83.3 |
97.2 |
83.5 |
94.1 |
| Irregular |
19.7 |
7.2 |
8.4 |
3.5 |
16.7 |
2.8 |
16.5 |
5.9 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Had Problem |
8.8 |
23.6 |
6.8 |
29.0 |
8.6 |
11.2 |
8.3 |
22.2 |
| No problem |
91.2 |
76.4 |
93.2 |
71.0 |
91.4 |
88.8 |
91.7 |
77.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
456 |
159 |
190 |
41 |
209 |
41 |
855 |
241 |
Note: EMW: Ever married Women ( 15- 49 years)
AG: Adolescent Girls ( 13- 18 years)
To Top
5.2.4 As one would expect, with
the advancement of age, more of the married women had irregular cycles
than the girls. However, one common feature is that the irregularity is
more in the slums than the other two areas, whether they are married
women or adolescent girls. This is one indicator which would suggest
that the female reproductive health status is lower in the slums.
Irrespective of the regularity of the cycle, some women had problems
associated with their periods. But about 92 per cent of the married
women and 78 per cent of the girls had no problem. The non-slum areas
lead the other two in this.
5.2.5 The majority of those with problems took
some treatment as can be seen in Table 5.3.
Table 5.3 Treatment for Menstrual Problems (%)
| Treatment Received |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| EMW |
AG |
EMW |
AG |
EMW |
AG |
EMW |
AG |
| Yes |
60.0 |
20.1 |
76.9 |
27.3 |
44.4 |
0.0 |
59.2 |
20.4 |
| No |
40.0 |
79.9 |
23.1 |
72.7 |
55.6 |
100.0 |
40.8 |
79.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
40 |
37 |
13 |
12 |
18 |
5 |
71 |
54 |
Note: EMW: Ever married Women ( 15- 49 years)
AG: Adolescent Girls ( 13- 18 years)
5.2.6 While only a fifth of the girls sought
treatment for their menstrual problems, about 60 per cent of the
married women did so. The suburban girls seem to take menstrual
problems in their stride, with none going for treatment. Even among
their women only 44.4 per cent went in for treatment. The facility they
visited for treatment is dealt with in Chapter VIII.
To Top
5.3 Marriage
5.3.1 The analysis of nuptiality
and associated factors are important because age at marriage has an
important bearing on family building activity and the level of
fertility. Presumably, a rise in the marriage age shortens the
reproductive span and implies a higher education before marriage. It is
true that upward shift in marriage age depresses fertility level and
increases average age of child bearing. One of the important factors
responsible for high population growth rates in most of the developing
countries today is the low level of age at marriage (Goyal, 1998). Age
at marriage has been found to be the most significant determinant of
declining fertility in Kerala (Zachariah, et al 1994). We tried to find
out the age at marriage of wives and husbands. The results are in
Tables 5.4 and 5.5.
Table 5.4 Age at Marriage of Wives (%)
| Age of marriage |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Less than 15 |
3.5 |
3.7 |
3.4 |
3.5 |
| 15-17 |
16.0 |
7.9 |
18.7 |
15.1 |
| 18 & 19 |
28.3 |
21.6 |
33.5 |
27.8 |
| 20-24 |
40.8 |
41.6 |
32.4 |
39.0 |
| 25-29 |
9.4 |
21.5 |
11.0 |
12.5 |
| 30+ |
2.0 |
3.7 |
1.0 |
2.1 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
456 |
190 |
209 |
855 |
| Median |
19.7 |
21.5 |
18.7 |
19.1 |
5.3.2 The table shows that 18.6
per cent of the marriages have taken place in the study area even
before the legal age of eighteen. This is higher in the slums at 19.5
percent, the highest being in the suburban area with 22.1 per cent. It
is not a happy state of affairs that in spite of a fairly high degree
of education among women, about a fifth of them contract marriages
which are illegal. Three and a half percentage has got married below
the age of 15 years among the three sample groups. This is less than
the figure of 5 per cent for the state (NFHS -2) 15-19 years seems to
be the most popular age for marriage for women, 42.9 per cent choosing
it. This is only 29.5 per cent in the non-slum areas, while it is 52.2
per cent in the suburbs and 44.3 per cent in the slums, probably an
effect of their higher education. We have seen in Table 3.6 that in the
non-slum area more than half the women are matriculates and above,
while in the other two areas they are only about 12 per cent. Only a
small percentage got married at the age of 30 and above. On the whole
the women in the suburbs get married very early as indicated in their
median age at marriage, which is 18.7. The next comes the slums with
19.7. The non-slum women have a median age of 21.5 They are the only
ones having a higher median age at marriage than the state for which
the median is 20.2. The other two groups can however, take consolation
in the fact that they have a higher median than the country’s, which is
16.4 according to NFHS –2.
To Top
Table 5.5 Age at Marriage of Husbands (%)
| Age of marriage |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 15-19 |
4.1 |
2.2 |
6.1 |
4.2 |
| 20-24 |
34.5 |
23.2 |
42.1 |
33.8 |
| 25-29 |
43.3 |
33.8 |
35.1 |
39.2 |
| 30-34 |
15.6 |
30.9 |
12.7 |
18.3 |
| 35-39 |
1.8 |
7.7 |
2.5 |
3.3 |
| 40+ |
0.7 |
2.2 |
1.5 |
1.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
456 |
190 |
209 |
855 |
| Median |
25.8 |
28.1 |
24.7 |
25.9 |
5.3.3 The most popular age for
marriage for men is 25 – 29 years, nearly 40 per cent of them getting
married in that interval. However, this holds good only in the slums
and non-slum areas with 43.3 per cent and 33.8 per cent respectively.
In the suburbs the popular age is 20 – 24 years, more than 42 per cent
getting married at that age interval. The non – slum areas show their
preference for higher age at marriage among the men also, with about 10
per cent getting married after 35, while in the suburbs it is only 4
per cent and in the slums only 2.5.This is in tune with the general
impression that age at marriage in the urban areas is high. At the all
India level while urban men get married at 26.5 years, rural men get
married at 24.2 years on an average (NFHS - 2) The median ages at
marriage of husbands show the same relationship as in the case of
wives. The present age of husbands and wives were also taken. But the
tables are not given, as they do not seem to be of any material
significance for our study. The median current ages of wives and of
husbands are 23.5 and 38.7 respectively, showing a difference of about
15 years. (Table not given).
To Top
5.4 Conception
5.4.1 The next question asked to
ever-married women in the reproductive age was about their conception.
Table 5.6 Conception (%)
| Whether Conceived |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| At least once |
90.5 |
87.9 |
92.3 |
90.9 |
| Not conceived |
9.5 |
12.1 |
7.7 |
9.1 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
456 |
190 |
209 |
855 |
5.4.2 As can be seen in the
table, 9.1 per cent of them did not conceive. Among the total number of
women, 90.5 per cent had experienced at least one birth, 67.8 percent
had two births and 28.2 had three births. Out of the total births,
about 2 per cent were stillbirths. The incidence of stillbirths is
slightly higher in the slums. Overall, no sex preference is observed in
the distribution of live births irrespective of birth order (data not
given.)
5.4.3 After enquiring about the onset of
pregnancy, the next probing was about the incidence of abortions, both
induced and spontaneous. Out of the sample of 855 women, 123 had
abortions. Table 5.7 gives the details of abortions that occurred to
ever-married Women.
Table 5.7 Abortions (%)
| Abortion if any |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Yes |
12.3 |
15.8 |
17.7 |
14.4 |
| No |
87.7 |
84.2 |
82.3 |
85.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
456 |
190 |
209 |
855 |
|
Number of abortion
|
| One |
57.1 |
83.3 |
62.2 |
65.0 |
| Two |
39.3 |
10.0 |
32.4 |
30.1 |
| Three |
3.6 |
6.7 |
2.7 |
4.1 |
| Four |
0.0 |
0.0 |
2.7 |
0.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
56 |
30 |
37 |
123 |
To Top
5.4.4One out seven women had at
least one abortion in their lifetime. However among slum dwellers only
one out of eight had it.
5.4.5 When it comes to the number of abortions,
nearly two thirds of those who had abortions had only one. The non-slum
areas take the lead in this with more than 83 per cent. In the non-slum
area, the number of women who had more than one abortion is also quite
less. Only three women there had two abortions and two had three. In
the slum area, out of 56 women who had abortion, 22 had two abortions
and two women had three.
5.4.6 Altogether 123 women had 173 abortions,
implying an average of 1.4 abortions per woman. Forty-three of them had
2, six had 3 and one had 4 abortions. We did not find much difference
in the months of occurrence of different order of abortions. Therefore
all the abortions were put together in one table to show their months
of occurrence.
Table 5.8 Months of Occurrence of Abortions (%)
| Month |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| First |
20.7 |
2.6 |
13.2 |
14.4 |
| Second |
36.6 |
44.7 |
26.4 |
35.3 |
| Third |
31.7 |
34.2 |
39.6 |
34.7 |
| Fourth |
6.1 |
10.5 |
9.4 |
8.1 |
| Fifth |
4.9 |
7.9 |
7.6 |
6.4 |
| Sixth |
0.0 |
0.0 |
3.8 |
1.1 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
82 |
38 |
53 |
173 |
5.4.7 Out of 173 abortions, 70
per cent have taken place in the second and third months of pregnancy.
The fact that 6.4 per cent of the abortions took place in the fifth
month should invite the concern of health providers. There were two
abortions in the sixth month, one of it was first abortion and the
other was the second for the same woman.
5.4.8 Information on the problems related to
abortion shows that nearly 12 per cent had some kind of problems
associated with it.
To Top
Table 5.9 Problems Associated with Abortion (%)
| Problems if any |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Yes |
16.1 |
3.3 |
13.5 |
12.2 |
| No |
83.9 |
96.7 |
86.5 |
87.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
56 |
30 |
37 |
123 |
|
Problems
|
| Back pain |
44.5 |
100.0 |
40.0 |
46.6 |
| Lower abdominal pain |
33.3 |
0.0 |
60.0 |
40.0 |
| Excess Bledding |
11.1 |
0.0 |
0.0 |
6.7 |
| High Fever |
11.1 |
0.0 |
0.0 |
6.7 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
9 |
1 |
5 |
15 |
5.4.9 Most of the women had no
problems associated with abortion. Out of 123 who had abortions only 15
had problems, one in the non-slum area, 5 in the suburbs and 9 in the
slums. In the problem cases 47 per cent had back pain. Three each in
the suburbs and slums suffered from lower abdominal pain. One woman
suffered from excessive bleeding and another from high fever.
5.4.10 The next probing was about any
stillbirths they would have had. It came out that only 8.2 per cent of
the sample had stillbirths.
Table 5.10 Stillbirths (%)
| Still Birth |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Yes |
12.3 |
6.3 |
1.0 |
8.2 |
| No |
87.7 |
93.7 |
99.0 |
91.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
456 |
190 |
209 |
855 |
5.4.11 The proportion of women who
had stillbirths is 12 percent in the slums, and 6 percent in non-slum
areas. The higher proportion in the slums is perhaps an indication of
the lower nutritional status of women, especially in the light of the
fact that antenatal care was adequate among them as we see in the
following section. The suburban women had the lowest number of
stillbirths at 1 percent.
To Top
5.5 The last Pregnancy
5.5.1 The ever-married women were
questioned in detail about their last pregnancy. If they were pregnant
at the time of questioning, the previous pregnancy was taken as the
last.
5.5.2 Antenatal checkup refers to pregnancy
related health care provided by a doctor or a health worker in a health
facility or at home. The safe motherhood initiative proclaims that all
pregnant women must receive basic, professional antenatal care. All
pregnant women are expected to have physical check up before delivery.
ANC can reduce maternal morbidity and mortality. A minimum of three
checks up is recommended by the health department so as to ensure safe
pregnancy and delivery.
Table 5.11 Antenatal Care (%)
| Antenatal checkup during
pregnancy taken |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Yes |
92.6 |
92.1 |
89.4 |
91.7 |
| No |
7.4 |
7.9 |
10.6 |
8.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
408 |
164 |
189 |
761 |
5.5.3 The table reveals that 92
per cent in the total had received ante-natal checkup during their
pregnancy, the same per cent in the slums and non-slums and 89 per cent
in the suburbs. As for the reasons for not going for check up see Table
5.12.
To Top
Table 5.12 Reasons for Not Availing of ANC (%)
| Reason |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Lack of Knowledge of Service |
30.0 |
0.0 |
5.0 |
15.9 |
| Did not feel necessary |
36.7 |
69.2 |
70.0 |
53.9 |
| Not customary |
0.0 |
7.7 |
0.0 |
1.6 |
| Financial cost |
30.0 |
15.4 |
10.0 |
20.6 |
| Distantly located |
0.0 |
7.7 |
0.0 |
1.6 |
| Not permitted to go |
0.0 |
0.0 |
10.0 |
3.2 |
| Others |
3.3 |
0.0 |
5.0 |
3.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
30 |
13 |
20 |
63 |
5.5.3 More than half the mothers
who did not go for antenatal checkup felt it to be unnecessary. This
points to the need for strengthening IEC activities in this area.
About16 percent of them reported lack of knowledge of service as the
reason, and nearly 21 per cent financial cost. Thirty per cent of the
slum mothers reported lack of knowledge and another 30 per cent
financial problems. It is important to note that two suburban women
were not allowed to go for antenatal check up by their families. One in
the non-slum area did not do antenatal check up, as it is not customary.
5.5.4 The survey further investigated the time
of antenatal check up and its components. The timing of the visits for
the antenatal care is given in Table 5.13.
Table 5.13 Timing of Antenatal Care (%)
| Month of first ANC |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| First |
7.4 |
9.3 |
10.7 |
8.6 |
| Second |
15.6 |
26.5 |
8.3 |
16.2 |
| Third |
38.6 |
48.3 |
45.0 |
42.3 |
| Fourth |
15.9 |
6.6 |
16.0 |
13.9 |
| Fifth |
11.9 |
4.7 |
13.5 |
10.8 |
| Sixth |
2.4 |
2.0 |
1.8 |
2.2 |
| Seventh and above |
8.2 |
2.6 |
4.7 |
6.0 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
| Mean month of starting ANC |
3.5 |
3.0 |
3.4 |
3.3 |
To Top
5.5.5 More than 42 percent of the
overall sample had their first visit for ANC in the third month of
pregnancy, 48 per cent in the non-slums, nearly 39 per cent in the
slums and 45 per cent in the suburbs. It speaks well of the awareness
of the pregnant women that nearly a fourth of them had their first
checkup before the end of the second month of pregnancy with some
differences showing in the three areas. As one would expect, more
expectant mothers in the non-slum area went earlier for checkup than in
the other areas. However it is to be noted that even in the slums
nearly two thirds of the expectant mothers had gone for checkup before
the end of third month. The mean month of first ANC is 3 or 3 plus in
all the areas. But about 23 per cent of slum women had started their
antenatal visit in the fifth month only. This also calls for concerted
action by the health providers among the underprivileged sections of
the society.
5.5.6 The number of antenatal checks up and the
timing of the first check up are important for the health of the mother
and the outcome of pregnancy. The conventional recommendation for
normal pregnancies is that once pregnancy is confirmed ante natal check
up should be scheduled at four weeks intervals during the first seven
months, then every two weeks until the last month and weekly thereafter
(MacDonald and Pritchard, 1980). Four ante natal checks up, one each
during the third, sixth and ninth month of pregnancy have been
recommended as the minimum necessary (Park and Park, 1989). Table 5.14
provides the information on the number of visits for ANC.
Table 5.14 Number of Visits for ANC (%)
| Number |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 1-3 |
9.3 |
4.6 |
9.5 |
8.3 |
| 4-6 |
31.5 |
12.6 |
33.1 |
27.0 |
| 7-9 |
46.3 |
30.5 |
46.7 |
43.0 |
| 10-12 |
12.2 |
36.4 |
6.5 |
16.1 |
| 13-15 |
0.5 |
15.2 |
3.6 |
4.4 |
| 16-18 |
0.2 |
0.7 |
0.6 |
0.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
| Mean |
6.9 |
9.5 |
6.7 |
7.4 |
To Top
5.5.7 Forty three percent of the
expectant mothers had between 7 and 9 visits, but in the non-slum area
more than 36 per cent had 10 to 12 visits. The proportion that had only
1 to 3 visits is very low at 8.3 per cent in the overall sample and
more than 9 in the slums and suburbs. Twenty seven per cent of all the
expectant mothers had 4 to 6 visits. More than 12 visits are rare,
coming to less than 5 per cent; but quite high at 15.2 per cent in the
non-slums. The mean visits are high for non-slum women than the other
two areas.
5.5.8 Regarding the components of ANC, we asked
the mothers about four items, namely measuring the weight, checking the
blood pressure, administering iron and folic acid tablets and tetanus
toxoid injections. The responses are presented in Table 5.15.
Table 5.15 Components of ANC (%)
| Weight measured |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Yes |
90.5 |
92.7 |
91.7 |
91.3 |
| No |
7.7 |
7.3 |
8.3 |
7.7 |
| Don't remember |
1.8 |
0.0 |
0.0 |
1.0 |
|
Blood Pressure checked or not
|
| Yes |
90.5 |
92.7 |
91.7 |
91.3 |
| No |
7.7 |
7.3 |
7.1 |
7.7 |
| Don't Remember |
1.8 |
0.0 |
1.2 |
1.0 |
|
Iron Folic Acid Received or not
|
| Yes |
98.4 |
100.0 |
98.8 |
98.9 |
| No |
1.6 |
0.0 |
1.2 |
1.1 |
|
TT Injection
|
| Yes |
91.6 |
91.1 |
92.3 |
91.5 |
| No |
8.4 |
8.9 |
7.7 |
8.5 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
5.5.9 It can be seen that most
of the expectant mothers who went for checkup had all the four
components done. More than 91 per cent had weight and blood pressure
taken, nearly 99 per cent were given iron and folic acid tablets and
91.5 per cent had anti-tetanus injections. Very little differential is
noticed among the three areas.
5.5.10 When we come to the breakup of the
components, we see the number of iron and folic acid tablets and TT
injections given in Table 5.16.
To Top
Table 5.16 Intake of Iron and Folic Acid Tablets
and TT (%)
| Number of Tablets |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| 10-50 tablets |
22.5 |
14.3 |
23.6 |
20.8 |
| 51-100 tablets |
65.7 |
60.7 |
54.3 |
62.1 |
| 101-150 tablets |
3.7 |
15.0 |
10.7 |
8.0 |
| 151-200tablets |
4.1 |
10.0 |
5.3 |
5.6 |
| 201 and above |
4.0 |
0.0 |
6.1 |
3.5 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
372 |
151 |
167 |
690 |
|
Number of TT Injection given
|
| One |
2.4 |
1.4 |
5.0 |
2.8 |
| Two |
24.2 |
23.4 |
26.2 |
24.5 |
| Three |
71.8 |
75.2 |
67.4 |
71.5 |
| Four Times |
1.5 |
0.0 |
1.4 |
1.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
5.5.11 Sixty two per cent of the
expectant mothers had between 50 and 100 tablets of iron and folic acid
and 71.5 per cent had 3 TT injections. It may be borne in mind that the
requirement is 100 tablets and at least two TT injections. The area
wise figures show that the highest was in the non-slum areas followed
by slums and suburbs.
5.5.12 The expectant mothers were asked about
the health problem they had during pregnancy. The result is in Table
5.17.
Table 5.17 Problems During Pregnancy (%)
| Problem |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Yes |
9.9 |
6.5 |
11.3 |
9.5 |
| No |
90.1 |
93.5 |
88.7 |
90.5 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
To Top
5.5.13 Nearly 91 per cent did
not have any health problem. However 11.3 per cent in the suburbs and
nearly 10 per cent in the slums had some problems. The nature of the
problem is given in Table 5.18.
Table 5.18 Nature of the Problem During
Pregnancy (%)
| Nature of Problem |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| High B.P. |
27.0 |
60.0 |
14.2 |
29.5 |
| Bleeding |
32.4 |
20.0 |
42.8 |
32.8 |
| Pain in the abdomen |
8.1 |
0.0 |
0.0 |
4.9 |
| Urinary infection |
0.0 |
10.0 |
7.3 |
3.3 |
| Vomiting |
16.2 |
0.0 |
14.2 |
13.1 |
| Suffocation |
8.1 |
0.0 |
14.2 |
8.2 |
| Associated with contraception failure |
8.1 |
10.0 |
7.3 |
8.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Consulted Doctors/Health workers |
85.7 |
100.0 |
87.5 |
88.5 |
| Number |
37 |
10 |
19 |
66 |
5.5.14 As can be seen from the
table, nearly a third of those who had problems had bleeding and about
30 per cent high blood pressure. The latter occurred to 60 per cent of
the sample in the non-slum areas. All of them in the non-slums
consulted doctors or health workers and less than 90 per cent in the
slums and suburbs.
5.6 Delivery
5.6.1 As far as delivery is
concerned, the most important question was if it took place in an
institution or at home. Table 5.19 shows that 93.4 per cent of the
deliveries took place in the institutions. This is the same figure for
the State as a whole as revealed in NNFHS -2. However the corresponding
all India figure is only 34 per cent (IIPS &ORC Macro 2001).
Table 5.19 Place of Delivery
| Place of Delivery |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Institution |
90.9 |
96.1 |
96.2 |
93.4 |
| Home |
9.1 |
3.9 |
3.8 |
6.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
5.6.2 In the slums institutional
deliveries are 91 per cent, in the suburbs and non-slums 96 per cent.
It is a matter of concern that in the slums, 9.1 per cent of the
deliveries took place at home.
To Top
5.6.3 However nearly 61 per cent
of the home deliveries in the slums were attended by trained personnel
such as doctor, nurse, ANM and Trained Birth Attendant (TBA). Only 23
per cent of the home deliveries in slums were attended by relatives and
friends, whereas it was 50 per cent in the non-slum area.
Table 5.20 If Home Delivery, Who Attended
| Attended by |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Doctor |
39.3 |
0.0 |
0.0 |
33.3 |
| Nurse/ANM |
12.5 |
0.0 |
0.0 |
10.6 |
| TBA |
8.9 |
50.0 |
0.0 |
12.1 |
| Untrained TBA |
16.1 |
0.0 |
0.0 |
13.6 |
| Relatives/ Friends |
23.2 |
50.0 |
100.0 |
30.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
34 |
6 |
6 |
46 |
5.6.4 Regarding the nature of
the delivery, 83 per cent had natural delivery with very little
variation among the three areas. The remaining 16.6 needed some
assistance.
Table 5.21 Nature of Delivery and Problems (%)
| Nature of Delivery |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Normal |
82.0 |
83.0 |
87.3 |
83.4 |
| Assisted |
18.0 |
17.0 |
12.7 |
16.6 |
| Total |
100 |
100 |
100 |
100 |
|
Problem during delivery
|
| Yes |
11.4 |
7.8 |
12.5 |
10.8 |
| No |
88.6 |
92.2 |
87.5 |
89.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
5.6.4 Of the total deliveries,
10.8 per cent had some medical problems, 12.5 per cent in the suburbs,
7.8 per cent in the non-slums and 11.4 in the slums.
To Top
5.6.5 The largest group (31 per
cent) had the problem of premature labour. None in the non-slum area
had it, while 42 per cent in the slums and 15 per cent in the suburbs
suffered from this problem. Prolonged labour was the next, covering
nearly 24 per cent.
Table 5.22 Nature of the Problems During
Delivery (%)
| Nature of the Problem |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Premature labour |
42.2 |
0.0 |
15.0 |
30.9 |
| Obstruced labour |
7.8 |
15.4 |
5.0 |
8.3 |
| Prolonged labour |
20.3 |
30.8 |
30.0 |
23.7 |
| Breach presentation |
7.8 |
23.1 |
25.0 |
13.9 |
| Excessive bleeding |
14.1 |
7.7 |
10.0 |
12.4 |
| Umbilical cord around neck |
1.6 |
0.0 |
0.0 |
1.0 |
| B.P. |
6.2 |
23.1 |
15.0 |
10.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
43 |
11 |
21 |
75 |
5.6.6 The outcome of the last
pregnancy is shown in Table 5.23.
Table 5.23 Outcome of the Last Pregnancy (%)
| Outcome |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Live Birth |
97.8 |
91.6 |
96.5 |
96.1 |
| Still Birth |
1.0 |
1.1 |
0.5 |
0.9 |
| Induced Abortion |
0.5 |
2.8 |
1.0 |
1.1 |
| Spontaneous Abortion |
0.7 |
4.5 |
2.0 |
1.9 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
417 |
179 |
196 |
792 |
5.6.6 Outcome of the last
pregnancy shows that 96 per cent ended in live births, nearly one per
cent ended in stillbirth, another one per cent in induced abortion and
two per cent in spontaneous abortion. It is noticed that the non-slum
women had more induced abortions than the others. It may be noted that
the data here is only about the last pregnancy whereas the data
previously given about abortions and stillbirths pertain to all women
in the reproductive age group.
To Top
5.6.7 We asked those who had
induced abortions why they did so. The answers are given in Table 5.24.
Table 5.24 Reasons for Termination of Last
Pregnancy (%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Child is too young |
50.0 |
60.0 |
0.0 |
44.4 |
| Can't afford another child |
50.0 |
40.0 |
100.0 |
55.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
2 |
5 |
2 |
9 |
5.6.8 The table shows that 60 per
cent of the non-slum women had done it because their child was too
young. Five of the nine women who had terminated their last pregnancy
did it due to the fact that they could not afford another child.
5.6.9The month at which the last pregnancy was
terminated is in Table 5.25.
Table 5.25 Month of Termination of Pregnancy (%)
| Month in which terminated |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| One |
50.0 |
0.0 |
50.0 |
22.2 |
| Two |
0.0 |
20.0 |
50.0 |
22.2 |
| Three |
0.0 |
20.0 |
0.0 |
11.1 |
| Four |
50.0 |
40.0 |
0.0 |
33.3 |
| Five |
0.0 |
20.0 |
0.0 |
11.1 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
2 |
5 |
2 |
9 |
5.6.10 It shows that 60 per cent
of the non-slum women had terminated their last pregnancy at fourth
month or onwards and 40 per cent terminated it in the second and third
month of gestation. One woman in slum did it in the fifth month of
gestation. Only two women (one in non slum and one in slum) reported
that they had some problem related to termination of pregnancy.
However, the sample is too small to attempt any inferences. The
non-slum woman suffered from excessive bleeding and the slum woman
suffered from back pain/body pain. Only one of the two went for
treatment (data not given).
To Top
5.7 Current Pregnancy
5.7.1 Besides asking the
ever-married women about their last pregnancy we also asked if any were
pregnant at the time of the survey. Thirty of the samples of 855 were
pregnant, 20 in the slums and five each in the other areas. We asked
them if they had antenatal check up. The result is in Table 5.26.
Table 5.26 ANC of Current Pregnancy (%)
| Whether consulted for checkup |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Yes |
90.0 |
80.0 |
100.0 |
90.0 |
|
Number of checks up
|
| 1-2 |
22.2 |
50.0 |
80.0 |
37.0 |
| 3-4 |
33.3 |
0.0 |
0.0 |
22.2 |
| 5-6 |
38.9 |
25.0 |
20.0 |
33.3 |
| Above 6 |
5.6 |
25.0 |
0.0 |
7.4 |
|
Month of first check up
|
| 1st Month |
44.4 |
50.0 |
80.0 |
51.9 |
| 2nd Month |
16.7 |
25.0 |
20.0 |
18.5 |
| 3rd Month |
27.8 |
25.0 |
0.0 |
22.2 |
| 4th Month |
5.6 |
0.0 |
0.0 |
3.7 |
| 5th Month |
5.6 |
0.0 |
0.0 |
3.7 |
|
Taken T.T. Injection or not
|
| Yes |
65.0 |
40.0 |
40.0 |
56.7 |
|
How many T.T. Injections
|
| One |
30.8 |
0.0 |
100.0 |
35.3 |
| Two |
53.9 |
100.0 |
0.0 |
52.9 |
| Three |
15.4 |
0.0 |
0.0 |
11.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
20 |
5 |
5 |
30 |
5.7.2 All the suburban women and
90 and 80 per cent of the slums and non-slums had had their checks up.
Regarding the number of checks up, 50 per cent of the non-slum women,
80 per cent of the suburban women and 22.2 per cent of the slum women
had 1-2 checks up. About a third of the slums had 3-4 checks up. Taking
up the month in which they had gone for consultation, 50 per cent of
the non-slum women, 80 per cent of the suburban and 44.4 per cent of
the slum have had their check up at the first month of their pregnancy.
5.7.3 Among the pregnant women, 40 per cent each
in the non-slum and suburban had taken T.T. injection and 65 per cent
in the slums. All of them in the non-slum area took two TT injections
and all of suburban region had one dose, while in the slum, 30.8 per
cent had taken one injection, 53.9 per cent two injections and 15.4 per
cent three injections.
To Top
5.8 Contraceptive Use
5.8.1 In the early years of the
population programme in India, the most popular contraception was
vasectomy. As female sterilisation came into vogue, the use shifted to
that, nearly two thirds of current contraception in India depending on
it (IIPS & ORC Macro 2000).
5.8.2 The focus of this section is our enquiry
into various aspects of contraceptive practice adopted by currently
married women like current and previous use of contraception, duration
of use, reasons for non-use, discontinuation, etc.
5.8.3 Of the total 813 currently married women,
30 are pregnant and thus have no need for contraception at the time of
the survey. Table 5.27 shows the percentage distribution of the others
by current use of contraception.
Table 5.27 Contraceptive Prevalence (%)
| Status |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Current Users |
61.2 |
48.9 |
65.1 |
59.4 |
| Non-users |
38.8 |
51.1 |
34.9
|
40.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
415 |
176 |
192 |
783 |
5.8.4 Of the 783 women who
constitute the potential for the need for contraception, 59.4 per cent
have adopted it. This Contraceptive Prevalence Rate of 59.4 per cent is
lower than the prevalence rate of 66 per cent in the urban areas of the
state as revealed in NFHS -2 (IIPS & ORC Macro 2001). But it is
noteworthy that the prevalence rate in the slums (61.2 per cent) is
higher than non-slum areas (48.9), and that the highest is in the
suburbs (65.1). This speaks well of the awareness of the women in the
poorer sections of the society.
5.8.5 When we probed the reasons for nonuse of
contraception, the answers we obtained are presented in Table 5.28.
Table 5.28 Reasons for Non Use of Contraception
(%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Want children |
58.6 |
65.5 |
76.0 |
64.8 |
| Desire for male child |
6.8 |
8.9 |
6.0 |
7.2 |
| Desire for female child |
6.8 |
6.7 |
3.0 |
6.0 |
| Fear about operation |
3.1 |
2.2 |
0.0 |
2.2 |
| Fear about side effects |
10.6 |
10.0 |
3.0 |
8.8 |
| Costs too much |
0.0 |
4.4 |
3.0 |
1.9 |
| Youngest too young |
10.6 |
0.0 |
3.0 |
6.0 |
| None to care after |
1.2 |
0.0 |
0.0 |
0.6 |
| eligious objection |
1.2 |
2.2 |
6.0 |
2.5 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
161 |
90 |
67 |
318 |
To Top
5.8.6 Two thirds of the women do
not use contraception because they want children. Probably this answer
is given by those who do not have any children yet or the desired
number. What is significant in this table is that only 7.2 per cent
gave the desire for a male child as the reason. This is matched by 6
per cent who want a female child. This is another proof to the fact
that there is no significant sex preference for children in the state,
unlike in the rest of the country where stories of female foeticide
abound, in spite of the law against sex determination of foetus. Nearly
9 per cent cited the fear about side effects as the reason. There is
need for health workers to play a better role in doing away with this
fear.
5.8.7 We probed the popularity of the different
methods of contraception. The distribution of women by the method used
is given in Table 5.29.
Table 5.29 Current use of Contraceptive Method
(%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Female Sterilisation |
97.6 |
94.1 |
96.0 |
96.6 |
| IUD |
0.8 |
1.2 |
1.6 |
1.1 |
| Oral pill |
0.0 |
0.0 |
0.8 |
0.2 |
| Condom |
0.0 |
2.3 |
0.8 |
0.6 |
| Rhythm/ Periodic abstinence |
1.6 |
2.3 |
0.8 |
1.5 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
254 |
86 |
125 |
465 |
5.8.8 Among the current users 98.5
per cent are using methods like sterilisation, IUD, oral pills and
condoms, which are, classified as modern methods. Female sterilisation
is the most popular method, with 96.6 per cent of the women preferring
that. It is much higher than the preference of 76 per cent by the women
users in the state and 71 per cent in the country (IIPS &ORC Macro
2001). This preference is the highest in the slums at 97.6 per cent
followed by the suburbs with 96 per cent. In the non-slum areas there
are some couples, though very few, preferring IUD, condoms and rhythm,
which are quite unpopular in the slums and suburbs. It is not
surprising that the poorer couples in the slums and suburbs opt for a
terminal method. This is in tune with the NFHS–2 data for the state,
which showed an inverse relationship between standard of living and
preference for female sterilisation (IIPS & ORC Macro 2001).
5.8.9 Sterlisation is not only popular but also
being adopted at an early age as seen in Table 5.30.
Table 5.30 Women’s Sterilisation by Age (%)
| Age |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| <19 |
4.4 |
3.7 |
5.0
|
4.4 |
| 20-24 |
43.1 |
33.3 |
41.6 |
41.0 |
| 25-29 |
32.7 |
44.4 |
40.0 |
36.7 |
| 30-34 |
10.9 |
17.3 |
10.0 |
11.8 |
| 35-39 |
6.5 |
1.2 |
1.7 |
4.2 |
| 40-44 |
2.4 |
0.0 |
1.7 |
1.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
248 |
81 |
120 |
449 |
| Mean |
23.7 |
25.9 |
24.0 |
24.1 |
To Top
5.8.10 It shows that 82 per cent
of those who adopted sterlisation are less than 30 years old with not
much difference in the three areas. A greater proportion of women in
the slums (43.1 per cent) and the suburbs (41.6 per cent) belong to the
age group of 20–24, while in the non-slums 44.4 per cent belong to the
age group of 25–29. This confirms the impression that the poor sections
go for terminal methods very early in their reproductive span. This
impression gets reinforced when we look at the mean age of
sterilisation, which is 23.7 and 24 in the slums and suburbs
respectively, whereas it is 25.9 in the non-slum areas.
5.8.11 The current users were also asked about
their previous use of contraceptive methods. The response is given in
Table 5.31.
Table 5.31 Previous Use of Contraceptives by
Current Users (%)
| Method |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| IUD |
95.0 |
50.0 |
83.3 |
82.4 |
| Oral pill |
5.0 |
12.5 |
0.0 |
5.9 |
| Condom |
0.0 |
0.0 |
16.7 |
2.9 |
| Rhythm/ Periodic abstinence |
0.0 |
12.5 |
0.0 |
2.9 |
| Withdrawal |
0.0 |
25.0 |
0.0 |
5.9 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
20 |
8 |
6 |
34 |
5.8.12 The most important
information from the table is that out of the 465 current users, only
34 (7.3 per cent) had any previous experience of contraception. This
implies that most of the women (92.7 per cent) go for the terminal
method of sterilisation as soon as the need for preventing further
birth is felt. There is some slight variation in the three regions in
the proportion of women who used contraception previously, it being 7.9
per cent in the slums, 9.3 in the non-slums and 4.8 in the suburbs (not
in the table). The interesting point is that 82.4 per cent of the
previous users had preferred IUD. The pattern appears to be that most
of the women go for female sterilisation as soon as they feel the need
for limiting the family size and most of the others try out IUD first
and then opt for sterilisation. However, there is some preference for
oral pill and rhythm in the non-slum areas and for condoms in the
suburbs among previous users.
5.8.13 This surmise can be further verified if
we look at the age of women who used contraception previously
To Top
Table 5.32 Age of Women Who Used Contraception
Previously (%)
| Age |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| <19 |
5.0 |
0.0 |
0.0 |
2.9 |
| 20-24 |
60.0 |
50.0 |
66.6 |
58.9 |
| 25-29 |
35.0 |
37.5 |
0.0 |
29.4 |
| 30-34 |
0.0 |
12.5 |
16.7 |
5.9 |
| 35-39 |
0.0 |
0.0 |
16.7 |
2.9 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
20 |
8 |
6 |
34 |
5.8.14 It can be seen from this
table that those between 20 and 24 years who did not directly go for
sterlisation but tried out a temporary method first are more in the
poorer areas of the slums and suburbs.
5.8.15 We can also check how long the women used
temporary methods before coming to the terminal method in table 5.33
Table 5.33 Duration of Previous Use of Temporary
Methods (%)
| Duration |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| One month |
0.0 |
5.0 |
0.0 |
2.9 |
| Two month |
0.0 |
5.0 |
0.0 |
2.9 |
| Three month |
12.5 |
5.0 |
16.7 |
8.9 |
| One year |
12.5 |
25.0 |
16.7 |
20.6 |
| Two year |
37.5 |
15.0 |
33.3 |
23.5 |
| Three year |
25.0 |
35.0 |
33.3 |
32.4 |
| Four year |
12.5 |
5.0 |
0.0 |
5.9 |
| Five year |
0.0 |
5.0 |
0.0 |
2.9 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
8 |
20 |
6 |
34 |
| Mean months |
24.9 |
25.9 |
21.5 |
24.5 |
5.8.16 This table adds one more
element to the story, namely, that most women who used temporary
methods prior to sterlisation try it out for a period of three years.
It has to be remembered that the effect of an IUD insertion would
normally last for five years. The IUD users seem to be discontinuing it
before the end of its effective period.
5.8.17 When it comes to the reasons for
abandoning the previous use, the desire to have another child stands
out as the most prominent.
To Top
Table 5.34 Reasons for Discontinuation of
Contraceptive Method by Previous Users (%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Effectiveness over |
15.0 |
0.0 |
16.7 |
11.8 |
| Want next child |
40.0 |
75.0 |
33.3 |
47.0 |
| Side effects |
30.0 |
12.5 |
33.3 |
26.5 |
| Became pregnant |
5.0 |
0.0 |
16.7 |
5.9 |
| Bleeding |
10.0 |
12.5 |
0.0 |
8.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
20 |
8 |
6 |
34 |
5.8.18 The next major reason is
side effects, which 26.5 per cent reported. This is an important
pointer. Did the IUD users remove the insertion prematurely because of
the side effects? But it is worth pursuing this question, as it will
point to the effectiveness of IUD as a contraceptive. Though the size
of the sample here is very small, it throws some light on the behaviour
of contraceptive use of the women who currently have adopted
contraception, mainly sterilisation.
5.9 Source of Motivation
5.9.1 Motivation and it source are
important factors in the realm of family planning programmes. The data
on the sources of motivation of contraception from our sample are
presented in Table 5.35.
Table 5.35 Distribution of Women by Source of
Motivation (%)
| Source |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Self |
57.7 |
63.0 |
66.1 |
61.0 |
| Husband |
33.6 |
29.8 |
26.6 |
30.9 |
| Relatives |
3.7 |
3.6 |
2.4 |
3.3 |
| Friends |
2.9 |
1.2 |
4.0 |
2.9 |
| Doctor/ANM/Health worker |
2.0 |
1.2 |
0.8 |
1.6 |
| Media |
0.0 |
1.2 |
0.0 |
0.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
254 |
86 |
125 |
465 |
5.9.2 It speaks highly of the
women’s awareness of the need to limit the size of families that most
of them (61 per cent) were motivated by their own desire, slightly less
in the slums. We have seen in Chapter III that most of them have a
fairly high level of education. Approximately 31 per cent of the women
were motivated by their husbands, more in the slums than in the other
two areas. Thus the decision to go in for contraception mostly ends in
the family, the husband and wife taking it together in about 92 per
cent of the cases. It is to be noted that motivation by the health
staff is only 1.6 per cent.
To Top
5.10 Summary
5.10.1 On the whole we see a
fairly good status of reproductive health among the sample women. It is
only slightly lower in the slums and suburbs than the non-slum areas of
the city. Starting with menstrual cycle we note that there is not much
of a difference in the age at menarche. However, so far as the
regularity of menstrual cycle is concerned, more women have irregular
cycles in the slums and suburbs than in the non-slum areas. Though the
number of women with problems in their periods is very small in the
three regions, more of them in the non-slums go for treatment.
Regarding the age at marriage comparatively more women in the slums and
suburbs get married before the legal age of 18. Generally, women in
these two areas get married earlier than in the non-slum areas. The
median age of women is, obviously higher in the non-slum areas, that
is, 21.5 years, as against 19.7 and 18.7 respectively in slums and
suburbs.
5.10.2 There is not much difference in the
number of conceptions among women in the three areas. But abortions,
whether spontaneous or induced, are highest in the suburbs followed by
the non-slums. But among those who had abortions, a higher number of
women in the slums had more than one. In the timing of abortion the
suburban women are worse off than in the other areas with the number in
the fourth, fifth and sixth months higher. More women in the slums and
suburbs had problems with abortion than in the non-slums. But in the
matter of stillbirths, the suburban women have the lowest problems. It
is a matter of concern that the outcome of one eighth of the
pregnancies in the slums ended in stillbirths.
5.10.3 Antenatal check up is a widely prevalent
practice in all the three areas, though slightly less in the suburbs.
The very few who did not avail themselves of ANC cited lack of
knowledge of the service and not feeling the need as the major reasons.
In the timing of ANC and its components there is not much difference
among the areas. But in the number of visits non-slums take the lead
with an average of 9.5 over the others with about 7. It is to be noted
that it is in the slums that the least number experienced problems with
their pregnancies.
5.10.4 Institutional delivery appears to be the
norm, with only 6.6 per cent taking place in the homes. This is higher
in the slums. However, the saving grace is that the home deliveries in
the slums were mostly attended by doctors or other trained personnel.
Most deliveries were normal in all the three areas. But more in the
slums and suburbs had medical problems like premature or prolonged
labour.
5.10.5 As far as the outcome of the last
pregnancy is concerned, most of them had live births in all the areas.
But induced and spontaneous abortions were more in the non-slums.
Talking about current pregnancy, it is noteworthy that it is the
suburbs that take the lead in going for ANC, followed by the slums.
5.10.6 Thus the slum women are not behind the
others in matters of reproductive health. In fact in the matter of
current use of contraception they fare even better. More women in the
slums and suburbs are current users than in the non-slums. Most of the
non-users gave desire for children as the reason. There is very little
gender preference for children in our study area. Most of the women
have adopted a permanent method of sterilization as in the rest of the
state and country. Only a very small proportion of these women had used
contraception previously. Among those who had, there was a preference
for IUD. Other temporary methods are popular only in the non-slum areas
with a small proportion preferring condoms in the suburbs. The terminal
method is adopted by more women in the slums and suburbs before the age
of twenty-four, whereas the popular age in the non-slums is between 25
and 29. The decision to adopt contraception seems to be taken between
the wife and husband, the former getting self-motivated in a majority
of the cases.
5.10.7 The picture that we get is of a set of
women who are quite aware of their reproductive health needs and who
get the needs met when they decide. . But the slum and suburban women
are slightly behind their better educated counterparts in the non-slums
in a few aspects, though in the use of contraception they are ahead.
To Top
VI. Child Health
6.1 Introduction
6.1.1 Child Health is one of the
key indicators of the health status and quality of life of a country.
In most of the developing countries, the level of child health is not
satisfactory as indicated by high deaths among infants and children
below five years, which constitute half of the total deaths in these
countries. Hence improvement of child health is an important aspect of
any country’s health care system. The most quoted indicator of child
health is infant mortality rate. While it has steadily improved for the
country to 68 per thousand from 112 in, the States other than Kerala
have to go a long way to reach its figure of 16. In the matter of child
mortality (under 5) also the state leads with 18.8 per thousand whereas
the country lags behind with 94.9 (Misra et al, 2001).
6.1.2 We have seen in Chapter V that most of the
deliveries in the study area take place in the hospitals and even when
it takes place in the homes it is mostly attended by doctors or trained
paramedical personnel. This ensures, to a great extent, the survival of
the mother and child. Out of 792 last pregnancies in our sample, 24
ended in abortions either induced or spontaneous and 7 in still births.
Thus the sample size of children we have is 761.
6.2 Birth Weight
6.2.1 The first point of enquiry
was about the weight of the baby, whether it was taken and, if so,
whether there were low birth weight babies. The results are presented
in Table 6.1.
Table 6.1 Birth Weight (%)
| Birth weight taken |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Yes |
87.9 |
94.1 |
93.3 |
90.6 |
| No |
12.1 |
5.9 |
6.7 |
9.4 |
|
Weight of the Baby
|
| < 2500 gram |
29.0 |
18.6 |
39.4 |
29.1 |
| 2500-2999 |
> 44.8 |
36.3 |
29.1 |
39.0 |
| 3000-3499 |
17.8 |
27.4 |
17.0 |
19.9 |
| 3500 and above |
8.5 |
17.7 |
14.6 |
12.0 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
408 |
164 |
189 |
761 |
To Top
6.2.2 The birth weight was taken
for most of the children immediately after the birth. This is not
surprising as institutional deliveries are the norm. But in the urban
areas of the state all babies born within three years prior to 1998-99
were weighed according to NFHS - 2, a great improvement on 76 per cent
of NFHS – 1 of 1992-93. Thus the figure is lower in the city. It is no
consolation that in urban India only 60 per cent was weighed, according
to NFHS II – 2 (IIPS & ORC Macro 2000 and 2001 and IIPS – 1995).
The figure is even lower in the slums with 88 per cent.
6.2.3 Low birth weight is a major cause of
childhood morbidity and mortality. The desired minimum birth weight
being 2500 grams, the proportion of low birth weight babies is 29.1 per
cent. This is higher than the figure for Kerala, which was estimated to
be 13 per cent by KSSP (Kunhikannan and Aravindan–2000). 18 per cent by
NFHS – 2 (IIPS & ORC Macro 2001). In our study only the non-slum
data agrees with the state data. In the other two areas the percentage
of LBW babies seems to be much higher than the state figure and even
the figure of 21 per cent for urban India (IIPS & ORC Macro 2000).
It is alarmingly high at 39.4 per cent in the suburbs. This is a matter
of concern and calls for immediate intervention. However it would
appear that no intervention is possible in this regard. Ramankutty
(2001) who conducted an exploratory study about the reasons for the
high prevalence of low birth weight babies in Kerala supported the
assumption that the demographic causes of LBW such as teenage
pregnancies, high birth order (beyond three), very short birth interval
and pregnancy among elderly women have been eliminated on account of
the demographic transition that has taken place in the state. He
concludes that the principal risk factors relate to the mother’s
nutritional status before pregnancy: her weight and height, the
tendency of first born children carrying an inherent chance for LBW,
premature birth etc. are the possible reasons. Therefore long term
measures are required to improve the nutritional status of adolescent
girls and eliminate the causes of premature delivery.
6.3 Breast Feeding
6.3.1 The next question was about
the practice of breast feeding. The responses are presented in Table
6.2.
Table 6.2 Details Regarding Breast Feeding (%)
| Breast Feeding Started |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Same day |
95.0 |
96.1 |
95.2 |
95.3 |
| 1-3 days |
3.1 |
3.3 |
3.0 |
3.1 |
| No breast feeding |
2.0 |
0.6 |
1.8 |
1.6 |
|
Whether feeding at present
|
| Yes |
1.9 |
0.6 |
2.4 |
1.8 |
|
Duration of breast feeding
|
| Less than 12 months |
14.2 |
14.4 |
15.4 |
14.3 |
| 12-17 months |
2.0 |
0.0 |
0.6 |
1.2 |
| 18-23 months |
72.2 |
83.0 |
77.2 |
74.8 |
| 24-29 months |
10.2 |
2.6 |
6.8 |
7.5 |
| 30+ months |
1.4 |
0.0 |
0 |
0.7 |
| Total |
100 |
100 |
100 |
100 |
| Number |
408 |
164 |
189 |
761 |
To Top
6.3.2 Breast feeding appears to
be the norm with more than 95 per cent of the mothers doing it the same
day. According to NFHS -2, only 42.9 per cent of the mothers in the
state and 15.8 per cent in the country started breast feeding the child
within one hour of birth. However those who started the same day is 92
per cent in the state and 37.1 per cent in the country (NFHS-2). Thus
there is not much difference between the state and the city whether it
is the slums, the non-slum areas or the suburbs. Adding those who
started it within three days of birth, it comes to 98.4 per cent.
Little difference is noticed between the areas.
6.3.3 Regarding the durations of breast feeding
two years appears to be the most popular one with nearly 75 per cent of
the mothers breast feeding their babies for that period. More mothers
in the non-slum areas did so. However the proportion of mothers
stopping at one year is not very small, it being a little over 14 per
cent. There are more mothers in the slum than in the other two areas
who breastfed their babies for more than two years.
6.4 Immunisation
6.4.1 In India, child immunisation
is an important component of child survival programme. The National
Policy Document of children accepts the responsibility of the State to
children both before and after birth and during the period of growth to
ensure their full physical, mental and social development. The Expanded
Programme of Immunisation was started in 1978 with the objective of
providing free immunisation services to all eligible children and
expectant mothers. Immunisation against polio was introduced in the
programme in 1979-80. BCG immunisation against Tuberculosis was also
brought under the Expanded Programme of Immunisation in 1981-82. The
latest addition to the programme was vaccination against measles in
1985-86. In order to step up the pace of immunisation, the Universal
Immunisation Programme was introduced in 1985-86 and is being
implemented in the state through the existing network of the primary
health care system.
6.4.2 An important means of improving the
survival of young children consists of immunising them against the
principal child diseases – tuberculosis, diphtheria, pertussis,
tetanus, poliomyelitis and measles. Hence, it would be significant to
study in this survey the immunisation services utilised by the children
of the sample households.
To Top
6.4.3 One dose of BCG and
measles vaccines and three doses of polio and DPT vaccines are needed
to establish immunity to the above major childhood diseases. BCG
Vaccination protects children against tuberculosis. This vaccination is
given at birth or at six weeks. DPT is administered in 3 doses at 45
days interval from birth. This protects them against diphtheria,
pertussis and tetanus. To protect the children against poliomyelitis
Oral Polio Vaccine (OPV) is given at birth as zero dose and three times
later every 45th day. Antimeasles vaccine is given in the ninth month.
The latest wisdom is that a child can be considered fully immunised
only if he has been given all the prescribed doses and the booster
doses which for polio and DPT goes on till the fifth year. This means
that only after 5 years of age we can assess the immunisation status.
However the primary immunisation is completed by the ninth month by
which time the measles vaccine and all the doses of polio and DPT
vaccines are given, except the booster doses.
6.4.4 Generally the surveys of immunisation
status are about the primary immunisation only and for that they cover
all the children from 12 to 24 months. They exclude the 0-12 months age
group since most of them would not have completed all the required
doses. However, we decided to capture the details of partial coverage
of immunisation also in the study area by including children of 0-12
months. We collected information on whether each living child within
the age group of 0-24 months ever received a vaccination during the
reference period. There were 95 children in this age group. The details
were obtained either from the immunisation cards available or from the
statements of the respondents.
6.4.5 For finding out the full coverage of
primary immunisation we grouped the children into two categories, those
below 9 months and those above as the ninth month is the cut off point
for completing all the doses of primary immunisation. Table 6.3 gives
the immunisation coverage of all children in the age group of 9-24
months. There were 73 children in this group. Children were classified
as fully immunised if all available vaccines in the required doses were
received.
Table 6.3 Distribution of Children (9–24 months)
by Immunisation Coverage (%)
| Immunised |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Full |
72.2 |
68.8 |
66.7 |
69.9 |
| Partial |
27.8 |
31.2 |
33.3 |
30.1 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
36 |
16 |
21 |
73 |
6.4.6 From the table it can be
seen that, only 70 per cent of the children in the age group of 9-24
months have been fully immunised. According to NFHS-2, 79.7 per cent of
children between 12 and 23 months in Kerala have received all doses of
all vaccines. This variation can be explained partly by the difference
in the age group considered here.
6.4.7 When it comes to partial immunisation the
picture is shown in table 6.4.
To Top
Table 6.4 Immunisation Status (%)
| Status |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| BCG |
96.3 |
100.0 |
100.0 |
97.9 |
| DPT |
1st Dose |
59.2 |
78.9 |
79.2 |
68.0 |
| 2nd Dose |
59.2 |
78.9 |
79.2 |
68.0 |
| 3rd Dose |
48.1 |
57.9 |
58.3 |
52.6 |
| POLIO |
1st Dose |
75.9 |
89.5 |
87.5 |
81.4 |
| 2nd Dose |
75.9 |
89.5 |
87.5 |
81.4 |
| 3rd Dose |
74.1 |
78.9 |
83.3 |
77.3 |
| Measles |
90.7 |
94.7 |
91.7 |
91.7 |
| Number |
53 |
18 |
24 |
95 |
6.4.10 All the children had
received BCG Vaccination except 2 in the slum. Thus BCG vaccination is
almost complete. It may be due to the fact that it is a single dose and
is administered soon after birth. Even then in the state only 96.2 per
cent of the children have received BCG and in the country 71.6 per cent
(IIPS and ORC Macro 2001).
6.4.8 DPT is administered in 3 doses. Only 52.6
per cent of the children in the age group 0-24 months have received all
the three. But about 68 per cent have received two doses. It is
reasonable to assume that they will receive the final dose as they age.
6.4.9 However in the case of Polio, more than 77
per cent are fully immunised. Government of India in 1995 introduced
Pulse Polio Immunisation for achieving total eradication of
poliomyelitis from India by 2000. It envisaged the administration of
oral polio vaccine to all children 0-3 years of age on one single day.
This is repeated 4-6 weeks later. The intention is to eliminate the
virus from the community. Accordingly, the State Department of Health
Services with the assistance of UNICEF organised immunisation camps on
1st December 2000 and 21st January 2001. Mothers were asked if their
children were administered polio vaccine in the camps. Most of the
children (83.5 per cent), irrespective of previous immunisation status,
were again immunised in the above camps.
6.4.10 Measles can be a serious problem among
children. A child is expected to get measles vaccinations when it is
nine months old. About 89 children (91.7%) had received the vaccination
against measles. This is the only vaccination where the figure for the
city is better than the figure for the State, which was 84.6 per cent
as, reported in NFHS-2. 6.4.13 Reasons for not vaccinating at all are
or not completing the vaccination schedule were collected during the
survey. There were many reasons for not immunising a child. Table 8.4
presents the distribution of children in the age group of 0 - 24 months
at the reference period of the survey who did not receive immunisation
or not fully immunised by reason and type of immunisation.
To Top
Table 6.5 Reasons for Non-immunisation
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| No. |
% |
No. |
% |
No. |
% |
No. |
% |
| Child is too young |
1.3 |
30.2 |
6 |
66.7 |
9 |
56.2 |
28 |
41.2 |
| Not aware of all doses |
1 |
2.3 |
2 |
22.2 |
0 |
0.0 |
3 |
4.4 |
| Child is ill |
19 |
44.2 |
0 |
0.0 |
6 |
37.5 |
25 |
36.8 |
| Family problem |
0 |
0.0 |
0 |
0.0 |
0 |
0.0 |
0.0 |
0.0 |
| Vaccine not available |
0 |
0.0 |
0 |
0.0 |
0 |
0.0 |
0 |
0.0 |
| No specific reasons |
9 |
20.9 |
1 |
11.1 |
1 |
6.2 |
11 |
16.2 |
| Financial problem |
1 |
2.3 |
0 |
0.0 |
0 |
0.0 |
1 |
1.5 |
| Total |
43 |
100.0 |
9 |
100.0 |
16 |
100.0 |
68 |
100.0 |
Note: The total here will be more than the
partially immunised and non-immunised children in 6.3 as the same
parent would give different reasons for different doses.
6.4.11 The reasons for failure to complete the
immunisation schedule fully show that “child is too young” is the
foremost reason pointed out by 41.2% of the mothers. These children may
not have attained the age prescribed by the health authorities for
receiving the remaining doses. For 36.8% of the mothers, the leading
reason is “child is ill”. Some other reasons mentioned by mothers for
not completing the immunisation are “not aware of all doses” and
“financial problem”. More than 16% of the mothers have no specific
reason to mention.
6.4.12 It is the responsibility of health
personnel to advise mothers to give all types of immunisation to
children since mothers may tend to neglect vaccination, though it is
very important. We tried to probe what was the source of motivation for
getting the children immunised. It was found that a good majority
(87.6%) of the mothers were motivated by doctors or nurses to immunise
their children (table not given). The role of the health worker does
not seem to have been important.
To Top
6.5 Nutritional Supplement
6.5.1 After immunisation, the
other items of health care for the children are the administration of
vitamin-A and iron and folic acid tablets. Vitamin-A deficiency is a
leading cause of blindness. Moreover it is also linked with increased
susceptibility to severe infections and malnutrition. In order to
prevent Vitamin A deficiency, supplementation programmes are
implemented under National Programme on Prevention of Blindness in
which oral doses in the form of tablet/liquid of Vitamin-A are
administered every 6 months to vulnerable groups of age 1–5 and
lactating mothers. In our sample of children below 24 months, only
about 32% have received Vitamin-A drops. While the proportion is more
or less the same in the non-slum area and high at 41.7% in the suburbs
is quite low at 27.8% in the slums. The figure is much lower than that
for the entire state which was 43.6% for children below three years the
figure for the slums is lower than the all India figure of 29.7% (IIPS
& ORC Macro.2000).
Table 6.6 Administration Vit.A and IFA to
children (%)
| Details |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Vitamin-A |
27.8 |
31.6 |
41.7 |
31.9 |
| Don't know |
11.8 |
0.0 |
0.0 |
6.4 |
| IFA |
22.2 |
31.6 |
16.7 |
22.7 |
| Number |
54 |
19 |
24 |
97 |
6.5.2 Children are given Iron and
Folic Acid tablets for iron supplementation. It is found that around
31.6% of children in non-slum area 16.7% in suburban and 22.2% in slum
got IFA tablets/liquid. On the whole 22.7% of children are given IFA
tablets for iron supplementation.
To Top
6.6 Summary
6.6.1 Though the state boasts of
a very low infant mortality rate, the status of immunisation in the
city leaves much to be desired. This calls for concerted efforts on the
part of the health authorities. One of the reasons for the low figure
could be that the private hospitals may not be giving adequate emphasis
for this. This is the impression gathered in the interview with some
community leaders NGOs and providers of public services. There is scope
for a more meaningful partnership with the private sector in this.
VII. Awareness of RTI, STI and HIV/AIDS
7.1 Introduction
7.1.1 Among different dimensions
of Reproductive health care, Reproductive Tract Infections (RTI),
Sexually Transmitted Infections (STI) and HIV/AIDS occupy a distinct
position. AIDS fell as a bombshell on the Indian scene in 1986 when the
first aids case was discovered in a sex worker in Chennai (Madras). A
quick survey of more than a hundred female sex workers of that city
showed that more than 10 per cent of them were infected with HIV. Since
then other areas have been found and many cases discovered. The
National AIDS Control Organisation (NACO) estimates that 3.86 million
people in India are infected with HIV and 20304 full blown AIDS cases
have been officially reported (NACO 2002). Tamil Nadu, Maharashtra,
Karnataka, Andhra Pradesh, Manipur and Nagaland are the states where
the infection has crossed one per cent in antenatal women. According to
the sentinel surveillance of antenatal women of Kerala carried out in
August – October 2001 the prevalence rate among them is 0.09 per cent
(Information collected from the State AIDS Cell, Kerala). Based on
this, the experts estimate the HIV positive population of Kerala to be
70,000. In a population of 3.1 million, this works out a prevalence
rate of 0.26 per cent. This chapter deals with the awareness of RTI,
STI and HIV including their mode of transmission and the preventive
measures among married women, adolescent girls and men in the
reproductive age group. We have already dealt with the problems of
reproductive health of married women in chapter V.
7.1.2 The Governments both at the Centre and the
States have launched Information, Education and Communication (IEC)
programmes through mass media and other means to increase awareness
about these diseases. In the second section of this chapter, we try to
analyse the knowledge about RTI, STI and AIDS and the transmission and
preventable measures of these among ever-married women of all ages. In
the three study areas, 1262 women, 241 adolescent girls and 998 males
were interviewed. The responses about the three diseases are put
together in one table each to make it easy for comparison and to avoid
monotony.
To Top
7.2 Ever Married Women of all Ages
7.2.1 Altogether 633 married women
were questioned in the slums, 325 in the non-slum areas and 304 in the
suburbs.
7.2.2 This section deals with the awareness of
RTI, STI and HIV/AIDS among ever-married women, the sources of
knowledge, awareness of the modes of transmission and curability. Table
7.1 presents the level of awareness of the three conditions among them.
Table 7.1 Awareness of RTI, STI and HIV among
Married Women (%)
| Awarenees and Source of
Knowledge RTI, STI and HIV |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| RTI |
STI |
HIV |
RTI |
STI |
HIV |
RTI |
STI |
HIV |
RTI |
STI |
HIV |
| Awareness |
54.8 |
52.1 |
77.4 |
68.0 |
64.6 |
86.2 |
43.8 |
41.1 |
72.7 |
55.6 |
52.7 |
78.6 |
|
Source of Knowledge
|
| Television |
39.2 |
38.6 |
57.0 |
61.5 |
59.1 |
78.2 |
36.5 |
30.3 |
24.3 |
44.3 |
41.8 |
62.4 |
| Radio |
15.6 |
14.1 |
19.8 |
29.2 |
28.6 |
33.2 |
15.1 |
16.8 |
56.9 |
19.0 |
18.5 |
24.3 |
| Print Media |
21.0 |
21.0 |
30.9 |
75.1 |
76.0 |
92.9 |
57.2 |
16.1 |
23.3 |
33.9 |
34.0 |
45.1 |
| Slogans/Pamplets/Poster |
3.5 |
3.3 |
5.9 |
24.0 |
26.8 |
31.4 |
4.0 |
4.0 |
7.9 |
8.0 |
9.5 |
12.9 |
| Doctors |
3.0 |
2.8 |
3.8 |
4.0 |
3.7 |
5.2 |
3.3 |
2.6 |
4.3 |
3.3 |
3.0 |
4.3 |
| Health Worker |
4.7 |
4.6 |
6.8 |
0.9 |
0.9 |
0.9 |
0.7 |
0.7 |
1.0 |
2.8 |
2.7 |
3.9 |
| School Curriculum and Teacher |
0.8 |
1.0 |
2.4 |
3.7 |
2.5 |
3.4 |
2.6 |
2.6 |
8.9 |
1.9 |
1.8 |
4.2 |
| Community Meetings |
8.7 |
8.1 |
11.7 |
2.5 |
0.9 |
0.9 |
4.9 |
3.6 |
4.0 |
6.2 |
5.2 |
7.1 |
| Friends/Relatives |
12.3 |
11.7 |
20.7 |
22.2 |
19.4 |
23.7 |
9.5 |
8.9 |
17.8 |
14.2 |
12.7 |
20.8 |
| Husband |
1.9 |
1.7 |
2.8 |
1.9 |
2.8 |
3.1 |
1.6 |
2.0 |
3.0 |
1.8 |
2.1 |
2.9 |
| Number |
633 |
633 |
633 |
325 |
325 |
325 |
304 |
304 |
304 |
1262 |
1262 |
1262 |
To Top
7.2.3 Overall more than half the
married women are aware of RTI and STI and more than three fourth about
HIV/AIDS. We have seen in chapter III that nearly 80 per cent of the
women in the sample had formal schooling (Table 3.6) The female
literacy in Kerala is 87.86 per cent in 2001 (Census 2001b). The level
of awareness of diseases that infect the reproductive system is not
commensurate with the level of education and literacy. The awareness is
the poorest among the suburbs, the slums faring better, followed by the
non-slum areas. It is not a happy state of affairs to know that about
half of them in the slums and suburbs are not aware of RTI and STI and
nearly a quarter of them about HIV, though they are reasonably well
educated. They lack this information, which is crucial for their sexual
health. NACO has put in a massive effort in IEC activities on HIV and
that seems to have had its impact. But the IEC work on RTI and STI have
not been that intensive in spite of these being given importance in the
Reproductive and Child Health (RCH) programme launched by Government of
India and the State Governments. It is surprising how in the two
massive programmes run by the Government both with the help of World
Bank and other donors, one could be very effective and the other not
so. This points to the lack of co ordination among the people who run
the two programmes. While NACO is under the Department of Health in
Government of India, RCH programme is run by the Department of Family
Welfare. Though the Union Minster for Health and Family Welfare heads
both these Departments, two separate Secretaries run them. It is not
difficult to include RTI and STI in the IEC activities on HIV and make
it a campaign on sexual health. But probably the compartmentalization
of the two Departments stands in the way. Many researchers have pointed
out this lack of co ordination between the two. This is yet another
pointer to it.
7.2.4 While there is a multiplicity of sources
of knowledge for the same individual, Television appears to dominate
all the others. This is not surprising as nearly two thirds of the
households have TV sets, the percentages in the slums and suburbs being
56.8 and 51.2 (see Table 3.9). For nearly two thirds of the married
women the awareness about HIV/AIDS came from TV and for more than 40
per cent of them, about RTI and STI. The next is the print media, about
a third of the women giving credit to it for RTI and STI and about 45
per cent for HIV. In the suburbs this is the major source of
information for RTI with more than 57 per cent acknowledging it.
However for the other two diseases TV dominates even in the suburbs.
The social interaction between friends and relatives contribute only
nominally to the propagation of knowledge about these diseases, more in
the non-slum areas than in the other two areas. Schooling does not
appear to have done much to spread the awareness of these diseases.
Those who came to know of them from the school curriculum or the
teachers are only less than 2 per cent for RTI and STI and 4.2 for HIV.
It appears that the role of health workers is very weak in all the
three areas in providing knowledge, only less than 3 for RTI and STI
and less than 4 for HIV. Community meetings also contributed marginally
to the awareness, only about 6 or 7 per cent of the married women
getting the information through them. However it is noteworthy that in
the slums this has played a marginally bigger role than in the other
two areas, contributing more than 8 per cent for RTI and STI and more
than 11 per cent for HIV. There appears to be better community activity
in the Slums.
To Top
Table 7.2 Awareness of Transmission of RTI, STI
and HIV among Married Women (%)
| Awarenees of Mode of
Transmission of RTI, STI and HIV |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| RTI |
STI |
HIV |
RTI |
STI |
HIV |
RTI |
STI |
HIV |
RTI |
STI |
HIV |
| Aware of mode of Transmission |
68.4 |
68.4 |
68.4 |
83.1 |
83.1 |
83.1 |
61.2 |
61.2 |
61.2 |
71.7 |
71.7 |
70.9 |
| Hetero-Sexual Intercourse |
88.6 |
97.2 |
98.4 |
92.3 |
99.0 |
99.6 |
89.7 |
92.0 |
93.3 |
90.1 |
96.8 |
97.1 |
| Needles/Blades/Skin puncture |
35.4 |
38.5 |
59.4 |
62.8 |
74.6 |
78.1 |
51.3 |
52.7 |
54.6 |
48.4 |
54.3 |
64.0 |
| Transfusion of infected Blood |
26.8 |
27.5 |
48.0 |
51.7 |
61.7 |
70.3 |
29.9 |
31.3 |
38.3 |
36.3 |
40.5 |
52.2 |
| Mother to Child |
5.5 |
6.1 |
12.4 |
26.6 |
36.8 |
36.4 |
14.5 |
17.0 |
16.8 |
14.9 |
19.3 |
21.8 |
| Homo-sexual Intercourse |
0.8 |
1.2 |
2.8 |
1.0 |
1.5 |
1.9 |
14.5 |
15.2 |
12.9 |
3.6 |
4.1 |
5.9 |
| Lack of Personal Hygiene |
13.4 |
7.3 |
0.7 |
18.8 |
4.5 |
0.7 |
5.1 |
1.8 |
1.0 |
13.7 |
5.2 |
0.8 |
| Others |
0.0 |
0.0 |
0.0 |
1.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.3 |
0.0 |
0.0 |
| Number |
633 |
633 |
633 |
325 |
325 |
325 |
304 |
304 |
304 |
1262 |
1262 |
1262 |
7.2.5 A striking similarity is
observed about the proportion of married women knowing about the mode
of transmission of the three diseases, it being over 70 per cent in all
the three. But there are differences among the areas. Only about two
thirds of the married women in the slums and suburbs know how they are
transmitted while over 83 per cent in the non slum areas know it.
Heterosexual intercourse is the most commonly acknowledged mode, about
97 per cent crediting it for STI and HIV and over 90 per cent for RTI.
It is quite heartening to see about 98 per cent of the married women in
the slums acknowledging this as the mode for STI and HIV and 88.6 for
RTI. The second place for all the three diseases is taken up by
needles, blades and skin punctures; 64 per cent crediting it for HIV,
54.3 per cent for STI and 48.4 per cent for RTI. Transfusion of
infected blood occupies the third place with 52.2 per cent for HIV,
40.5 per cent for STI and 36.3 per cent for RTI. The similarity about
the mode of transmission among the diseases continues and transmission
from mother to child takes the fourth place. About 15 per cent state
that this is a mode of transmission of RTI and about 20 per cent of
STI. Only 21.8 per cent of the respondents acknowledged the
transmission of HIV from mother to child. Though the major mode of
transmission of HIV in India is heterosexual in the course, accounting
for 82.6 percent, at least 1.8 percent is accounted for by the prenatal
route (NACO 2002). It is known that the chances of an HIV infected
mother passing it on to the child are quite high. Therefore, one would
expect this to be mentioned as a mode by a large majority of educated
women. Even in the non slum areas only 36.4 per cent stated this as a
mode of transmission. Perhaps the IEC activities on HIV do not
emphasize this mode and that could be the reason. When it comes to
fifth place the similarity ends and quite rightly. Homosexual
intercourse is the fifth place in HIV. But only about 6per cent of
married women acknowledge this as a mode of transmission of HIV.
Probably the awareness of the married women of the existence of this
practice itself would be very limited, given the societal mores.
Workers in the AIDS prevention programmes have found it difficult to
locate practitioners of homosexuality in Trivandrum city as they are
very few (Various reports of State AIDS Cell and interview with
community leaders). Lack of personal hygiene occupies the sixth place
for the other two diseases. About all these modes the awareness seems
to be higher in urban non-slums than the slums and suburbs.
To Top
7.2.6 Even though many of them
are aware of HIV/AIDS and a part of them about the mode of
transmission, still there are certain misconceptions existing in the
society about this. An individual identified as HIV +ve is ignored and
isolated by everybody in the society and many of them do not touch or
even go near the patient due to the misconception that it may be
transmitted by touch, air, sharing clothes and vessels etc. Questions
were put about each of these commonly perceived misconceptions.
Table 7.3 Misconceptions about Mode of
Transmission of HIV/AIDS among Married Women (%)
| Misconception |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Shaking hands |
13.7 |
13.5 |
22.4 |
15.8 |
| Embracing |
14.4 |
13.5 |
22.7 |
16.2 |
| Kissing |
19.1 |
15.4 |
23.4 |
19.2 |
| Sharing Clothes |
16.1 |
14.8 |
22.0 |
17.2 |
| Sharing vessels |
15.8 |
14.5 |
22.4 |
17.1 |
| Through urine, faeces etc. |
17.7 |
16.6 |
24.3 |
19.1 |
| Insects like Mosquito |
23.9 |
21.2 |
25.4 |
23.6 |
| Number |
633 |
325 |
304 |
1262 |
7.2.7 Overall the misconception
appears to be harboured by only about a fifth of the women. This is a
great improvement on the state figure revealed by a survey on
behavioural surveillance conducted by NACO in 2001. According to that
survey 44.8 per cent of females in Kerala had no incorrect knowledge on
the transmission of HIV, suggesting that 55.2 per cent had correct
knowledge (NACO). The married women of Trivandrum appear to be much
better in this. Shaking hands as a mode of HIV transmission was
mentioned by 13.5 percent urban non-slum respondents, 22.4 percent
suburban respondents and 13.7 slum dwellers. Embracing and hugging an
HIV +ve patient is a misconception for 16.2 percent on the whole.
‘Transmission is possible through kissing’ was mentioned by 19.2
percent in total while it is 15.4 percent among urban non-slum women,
22.4 percent in the suburban and 16.1 percent slum respondents. Sharing
vessels and clothes do not have much difference in all the three areas
and it is almost the same (around 17) when taken as a whole. Chances to
get transmitted by contact with urine and faeces of the patient scored
19.1 percent in the total, 16.6 percent from the urban non-slum, 24.3
percent from sub-urban and 17.7 percent from slum areas. It is to be
noted that the misconception is the highest among the suburbans, each
of the modes scoring about 22 per cent points. Slums and non-slums do
not show much difference. The IEC activities seem to have had their
impact in the old city area with an even spread while in the newly
added suburbs the impact is not that strong. More intensive efforts are
called for removing the misconceptions.
7.2.8 HIV is a disease brought about by the
individual’s actions nearly in all cases. Though there is a no cure for
it, it is almost preventable. Therefore the knowledge about prevention
is of paramount importance in combating the infection. Questions were
put on this to the married women. Their response is tabulated in Table
7.4.
To Top
7.4 Knowledge of Prevention of HIV/AIDS among
Married Women (%)
| Knowledge about Prevention |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Using condoms during sexual intercourse |
8.1 |
19.0 |
17.7 |
13.4 |
| Safe Sex |
98.8 |
99.6 |
92.7 |
97.7 |
| Checking blood prior to transfusion |
41.7 |
67.6 |
41.2 |
49.7 |
| Sterilising needles, syringes before injection |
53.0 |
73.5 |
46.9 |
57.6 |
| Avoiding Pregnancy while having HIV |
4.8 |
15.8 |
9.4 |
9.0 |
| Avoid any type of relation |
0.7 |
0.4 |
0.5 |
0.6 |
| Do not know |
2.1 |
0.0 |
11.4 |
3.8 |
| Number |
633 |
325 |
304 |
1262 |
7.2.9 Most of the married women
seem to have adequate knowledge about the method of prevention as
nearly 98 per cent of them mentioned safe sex as the method. The 13 per
cent who mentioned use of condoms also would be included in this
category. There is not much difference among the three areas; In the
urban non-slum and slum areas all the women have this impression, while
in the suburbs it is nearly 93 per cent. Almost 19 per cent of women in
the urban non-slum said that condom usage can prevent HIV transmission
to a certain extent while only 8.1 per cent in the slum said so. It is
around 18 per cent in the suburban area. The next highest group nearly
58 percent mentioned sterilizing needles, syringes etc. Nearly half the
married women mentioned checking blood prior to transfusion. Almost 68
per cent in the urban non-slum area, 41.2 percent in the suburban and
41.7 per cent from the slums subscribe to this view. Avoidance of
pregnancy while having HIV was supported by 15.8, 9.4 and 4.8 per cent
of women in the urban non-slum, suburban and slum areas respectively.
Though there are misconceptions about HIV positive patients leading to
their ostracisation from the society, only a negligible proportion of
respondents stated that avoiding contacts would prevent HIV infection.
It is encouraging to find that most of the people, especially in the
slums have correct knowledge about the modes of prevention of HIV.
To Top
7.2.10 A crucial factor about
the campaign in HIV is the emphasis that the infection is not curable.
Very expensive drugs are available only for reducing the viral load in
the infected person’s blood thereby enabling him to live with the virus
reasonably free from opportunistic infections. Therefore the impression
about curability is very much a determinant in the adoption of
preventive measures. Questions were put on this to the married women
and it is quite shocking that nearly 15per cent said that it is curable
and only 54per cent said it is not curable, 31per cent being not sure.
Probably the advertisements from quacks about cure for AIDS have
contributed to this. This is especially surprising because nearly all
are aware of HIV and have nearly correct knowledge about the mode of
transmission and prevention. This shows the IEC activities have to go a
long way in emphasizing the non-curability of HIV. The slogan ‘not
curable but nearly 100per cent preventable’ does not appear to have
caught on.
Table 7.5 Knowledge of Curability of RTI, STI
and HIV among Married Women (%)
| Curability |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| RTI |
STI |
HIV |
RTI |
STI |
HIV |
RTI |
STI |
HIV |
RTI |
STI |
HIV |
| Curable |
36.8 |
39.3 |
14.8 |
54.2 |
57.8 |
9.3 |
33.5 |
37.8 |
20.6 |
40.6 |
43.7 |
14.7 |
| Not curable |
12.5 |
11.1 |
54.0 |
4.9 |
3.7 |
64.3 |
6.3 |
2.3 |
43.1 |
9.0 |
7.1 |
54.1 |
| Do not know |
50.7 |
49.6 |
31.2 |
40.9 |
38.5 |
26.4 |
60.2 |
59.9 |
36.3 |
50.4 |
49.0 |
31.0 |
| Number |
633 |
633 |
633 |
325 |
325 |
325 |
304 |
304 |
304 |
1262 |
1262 |
1262 |
7.2.11 About RTI and STI, nearly
half the married women said they do not know if these are curable or
not, more in the suburbs than slums or non-slums. Knowledge of modern
medicine’s ability to cure these diseases does not appear to have
spread among married women. But it is to be noted that only less than
10per cent said it is not curable. The misconception about curability
about RTI an STI is high among the suburban as in the case of HIV. This
again, points to the need for strengthening IEC activities in this
direction.
To Top
7.3 Female Adolescents
7.3.1 This section deals with the
reproductive health of adolescent females between the age group 13 and
18 years. The total number of respondents is 241, out of which 159 are
from slums and 41 each from non-slum and suburban areas. We have
already dealt with the age at menarche in Chapter V.
Table 7.6 Menstrual Problems among Adolescent
Girls ( %)
| Menstrual problems |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
|
Regularity of menstrual cycle
|
| Regular |
92.8 |
96.5 |
97.2 |
94.1 |
| Irregular |
7.2 |
3.5 |
2.8 |
5.9 |
| Discomfort during menstruation |
23.6 |
29.0 |
11.2 |
22.2 |
| Abdominal pain |
82.4 |
63.6 |
100.0 |
79.6 |
| Head Ache |
2.9 |
36.4 |
0.0 |
10.2 |
| Excessive bleeding |
14.7 |
0.0 |
0.0 |
10.2 |
|
Went for treatment
|
| Government Hospital/Consultation |
2.9 |
18.2 |
0.0 |
6.1 |
| No consultation |
79.9 |
72.7 |
100.0 |
79.6 |
| Percent who are taking Medicines |
20.6 |
18.2 |
50.0 |
22.4 |
| Number |
159 |
41 |
41 |
241 |
To Top
7.3.2 Most of adolescents (94
per cent) have their menstrual cycles regularly. Irregularity of the
cycles is rare, the highest being about 8 per cent, which is among the
slum dwellers. Discomfort during menstruation was reported by 22.2 per
cent of the total respondents. It was insignificant among slums and
suburban girls. Among the urban non-slum respondents it was felt by 29
per cent. So far as the nature of discomfort is concerned, nearly 80
percent of the respondents had abdominal pain. Excessive bleeding
constituted 10.2 per cent of the total.
7.3.3 It comes out that 79.6 percent of the
respondents who had discomfort did not undertake any treatment. Out of
the treatment-seeking respondents, 14.3 per cent went to Government
hospitals while 6.1 per cent consulted private doctors. About 18
percent of slum dwellers depended on Government hospitals as could be
expected, while an equal proportion in the urban non-slums consulted
private doctors. Almost 18 percent of urban non-slum girls took
medicines while 50 percent in the suburban area and 20.6 per cent in
the slums also took it.
7.3.4 The respondents were asked about other
problems of the reproductive tract. The only common problem encountered
by the adolescents was white discharge. Therefore questions were put on
this. The result is shown in Table 7.7.
Table 7.7 Adolescent Girls with Reproductive
Tract Problems (%)
| Problems |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Do not have problem |
40.0 |
15.6 |
15.8 |
32.3 |
| Have white discharge |
60.0 |
84.4 |
84.2 |
67.7 |
| Consulted doctor |
1.0 |
0.0 |
0.0 |
8.7 |
| Took medicine |
17.2 |
0.0 |
16.7 |
15.9 |
| Number |
159 |
41 |
41 |
241 |
7.3.5 About one third of the total
respondents have this problem, while in the slums the proportion is 40
per cent. In spite of this being a major reproductive health problem,
only less than one per cent went in for consultation and less than 16
per cent took any treatment.
7.3.6 It is important for adolescent girls to
know about STI and HIV. Questions were put to them about this. The
results are in Table 7.8.
To Top
Table 7.8 Awareness of STI among Adolescent
Girls (%)
| Awareness |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Aware of STI |
50.7 |
43.8 |
31.6 |
46.4 |
| Gonorrhea |
94.9 |
93.3 |
100.0 |
95.2 |
| Syphilis |
2.5 |
6.7 |
0.0 |
2.8 |
| Aware of Mode of Transmission |
87.2 |
93.3 |
76.9 |
86.8 |
| Sexual intercourse |
94.1 |
92.9 |
90.0 |
93.5 |
| Needle/Blades |
67.1 |
64.3 |
50.0 |
68.1 |
| Transfusion of infected Blood |
49.3 |
50.0 |
80.0 |
52.7 |
| Number |
159 |
41 |
41 |
241 |
7.3.7 Though only 46.4 per cent of
the girls are aware of STI, all of them have heard about HIV (see Table
7.9 below). This shows that while the IEC campaign has been effective
on HIV, its efficacy on STI has been far from satisfactory, as we saw
in the case of married women as well. But it is encouraging to note
that more than half the girls in the slums have heard about STI, while
not even 44 per cents in the non-slums areas have heard about it, and
not even a third in the suburbs. The awareness of STI consists almost
entirely of the awareness of gonorrhea, 95.2 per cent being aware of it
and only less than 3 per cent knowing about syphilis. Other infections
do not appear to have entered their realm of thinking.
7.3.8 Among those who have heard about STI, 86.8
percent know about the mode of transmission, which is constituted by
93.3 percent from urban non-slum, 76.9 percent from suburban and 87.2
percent from slum areas. Most of them (93.5 per cent) mentioned sexual
intercourse as a mode of transmission. Transmission through
needles/blades was acknowledged by 64.3 per cent urban non-slum
adolescents, 80 percent of suburban and 67.1 percent slum adolescents.
Spread of STI through transfusion of infected blood scored 52.7 percent
in the total constituted by 50 from urban non-slum, 80 percent from
sub-urban and 49.3 from slum areas. Only 7.7 percent of the total
respondents mentioned that transmission is possible from mother to
child, which was not mentioned by any respondent from the urban non
slum area. About 12 percent of suburban slum adolescents and 9 from
slum areas supported it. On the whole the knowledge about modes of
transmission is encouraging.
To Top
Table 7.9 Awareness of HIV among Adolescent
Girls (%)
| Awareness |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Aware of HIV |
100.0 |
100.0 |
100.0 |
100.0 |
| Aware of Mode of Transmission HIV |
67.3 |
65.9 |
65.9 |
66.8 |
| Sexual intercourse |
84.1 |
87.5 |
92.1 |
86.0 |
| Needle/Blades |
72.3 |
74.1 |
71.4 |
76.2 |
| Transfusion of infected Blood |
59.5 |
63.0 |
62.9 |
60.6 |
| Mother to Child |
9.0 |
0.0 |
11.1 |
7.7 |
|
Source of Knowledge of HIV
|
| School |
39.3 |
19.1 |
32.3 |
35.3 |
| Friends/Relatives |
5.4 |
0.0 |
9.7 |
5.5 |
| Television |
56.3 |
61.9 |
57.3 |
57.9 |
| Newspaper/ Magazines |
19.6 |
38.1 |
3.2 |
18.9 |
| Community Classes |
2.7 |
0.0 |
0.0 |
1.8 |
| Parents |
0.9 |
0.0 |
3.2 |
1.2 |
| Number |
159 |
41 |
41 |
241 |
7.3.9 Though all the girls have
heard about HIV, only two thirds of them are aware about the mode of
its transmission, the three areas showing not much difference. Among
those who know about the mode of transmission of HIV, only 86 per cent
acknowledged sexual intercourse as the mode, 87.5 percent in the
non-slum areas, and 84.1 percent in the slums. The suburban girls fare
better with 92.1 per cent. Transmission through needles and blades was
known to a little over three fourths of the girls and through blood
transfusion to less than a third of them, the three areas showing not
much variation. Mother to child transmission is acknowledged not even
by 8 per cent and by none in the non-slum areas. With the entire sample
knowing about HIV, one would expect all of them to know about its
transmission also. An awareness of HIV without its mode of transmission
is not very effective in preventing the infection. This again points to
the lack of focus in the IEC campaigns on HIV.
To Top
7.3.10 As in the case of married
women, Television dominated as the source of knowledge among adolescent
girls, but to a much less extent. Nearly 58 per cent acknowledged it
with very little variation among the areas. It is quite heartening to
see that the school has played an important role in creating the
awareness of HIV, more than a third giving credit to it. However, among
the non-slum girls only less than 20 per cent acknowledged it. Nearly a
fifth of the girls mentioned magazines as a source of information.
Kerala is a state where a large number of magazines get circulated.
Some of the largest circulating magazines in the country are in the
state’s language of Malayalam. (Various newspaper reports). It is
widely known that there is a great readership of these magazines among
women. Table 7.1has shown that more than 45 per cent of the married
women acknowledge the print media as a source. Therefore a fifth of the
girls acknowledging it is not a surprise. But the inter – area
difference calls for some surprise with only a little over 3 per cent
of the girls of the suburbs giving credit to it, while more than 38 per
cent in the slums did so. But the size of the sample being only 41 such
differences may not be significant. Another similarity with the women
is that in the slums the girls get information through community
classes, though only less than 3 per cent. This source is totally
absent in the other two areas. This confirms the view that there is
more community activity in the slums. Parents as a source information
contributed only 1.2 percent to all the girls. The suburban areas fared
better with 3.2 percent, while in the slums it is not even one percent.
Parents, especially mothers, can play a better role in educating the
children about HIV, especially in the face of the fact that more than
78 per cent of the married women are aware of HIV (See Table 7.1).
7.4 Men (13 – 54 years)
7.4.1 In order to know about the
sexual health and related aspects of the males, men from 13 to 54 years
from the sample households were interviewed. A total of 998 men were
interviewed out of which 149 were from urban non-slum areas, 262 from
the suburban areas and 587 from the slums. We have already seen the
characteristics of men of all ages in Chapter III. Here we study only
men in the reproductive age group.
To Top
Table 7.10 Education and Marital Status of Male
Respondents (%)
| Characteristics |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
|
Education
|
| No Schooling |
4.6 |
0.0 |
1.5 |
3.0 |
| Primary |
15.3 |
1.3 |
17.5 |
13.8 |
| Secondary |
27.4 |
14.2 |
28.5 |
25.8 |
| Matriculation |
45.4 |
51.5 |
49.8 |
47.5 |
| Undergraduates |
3.9 |
12.1 |
1.2 |
4.5 |
| Degree and above |
2.2 |
12.1 |
1.5 |
3.5 |
| Technical Diploma or Certificate |
0.7 |
7.5 |
0.0 |
1.4 |
| Professional |
0.5 |
1.3 |
0.0 |
0.5 |
|
Marital Status
|
| Single |
39.7 |
64.4 |
37.4 |
43.8 |
| Currently married |
58.8 |
35.5 |
61.8 |
56.1 |
| Widower |
0.2 |
0.0 |
0.0 |
0.1 |
| Divorcee |
0.3 |
0.0 |
0.0 |
0.2 |
| Separated |
1.0 |
0.0 |
0.8 |
0.8 |
| Number |
587 |
149 |
262 |
998 |
7.4.2 Men who had no schooling are
only 3 per cent while in the general population it is 19 per cent
(Table 3.6). This would suggest that it is the women who constitute the
bulk of this category. Nearly half the men are matriculates,
predominantly in the non-slums. About an eighth of the non-slum men are
degree holders where as it is only about 2 per cent in the other two
areas. The upper hand of the non-slum areas is seen in all the levels
of education.
7.4.3 Regarding marital status, the bulk of the
men (nearly 62 per cent) are currently married. The proportion of
married men in the general population is only 44 (Table 3.3), which is
natural as the men below 15 are also included in that.
To Top
7.4.4 Questions were put to the
respondents about their sexual health problems before and after the
marriage. The number who had problems is too small to give in a table.
Only 6 of the 998 respondents stated that they have or had sexual
health problems before marriage, three from the slums, two from suburbs
and one from the non-slums. The problems were, difficulty in urination,
fungal infection and sore on the penis. All these respondents had taken
treatment and it was effective. Incidence of sexual disease after
marriage was also rarely reported. Only 11 respondents had problems, 8
in the slums, 2 in the suburbs and one in the non-slum areas. Five in
the slums had infertility and one sexual disability. All others had
fungal infection. Out of the 11 who had problems 8 persons took
treatment, all of them from the slums.
Table 7.11 Awareness of STI and HIV among Males
(%)
| Awareness |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
|
Education
|
| Aware of HIV |
90.5 |
100.0 |
88.9 |
91.5 |
| Aware of STI |
77.2 |
94.0 |
79.8 |
80.4 |
| Syphilis |
7.5 |
32.9 |
14.5 |
13.2 |
| Gonorrhea |
4.6 |
22.9 |
5.7 |
8.1 |
| Fungal infection |
0.6 |
2.1 |
1.4 |
1.1 |
| Do Not know |
1.9 |
1.4 |
0.0 |
0.8 |
|
Aware of Mode of Transmission
|
| Sexual Intercourse |
68.4 |
94.3 |
58.9 |
70.5 |
| Sexual contact with sex workers |
14.4 |
8.6 |
16.8 |
14.0 |
| Sharing of needles/blood transfusion |
20.1 |
41.4 |
25.4 |
25.2 |
| Mother to child |
6.2 |
2.9 |
4.8 |
5.2 |
| Do not know |
13.9 |
10.7 |
10.5 |
12.5 |
|
Knowledge about prevention
|
| Avoid sexual intercourse with sex workers |
23.4 |
14.3 |
14.8 |
19.6 |
| No sharing of needles/syringes |
10.2 |
17.9 |
17.2 |
13.3 |
| Using condom |
28.3 |
53.6 |
24.4 |
31.7 |
| Safe Sex |
22.5 |
43.6 |
27.3 |
27.4 |
| Do not know |
20.3 |
21.4 |
19.6 |
20.3 |
|
Knowledge of place of treatment
|
| Government Hospital |
25.6 |
35.7 |
23.0 |
26.7 |
| Private hospital |
52.3 |
57.9 |
56.9 |
54.5 |
| Aids cell |
22.1 |
3.4 |
18.7 |
18.5 |
| Do not know |
0.0 |
0.0 |
1.5 |
0.4 |
| Number |
587 |
149 |
262 |
998 |
To Top
7.4.5 More men know about STI
than married women and adolescent girls. While the proportions among
the first two are 52.7 and 46.4 per cent respectively, among men it is
as high as 80.4. The same trend is seen about HIV also. More than 91
per cent men know about it, while the married women who know are only
78.6 per cent, though all the adolescent girls know about it. According
to the behavioural surveillance survey conducted by NACO in 2001 (NACO
2002), the proportion of men in the urban areas of Kerala who had ever
heard of HIV is 99.5 and women 98.6. Though this is variant with the
result of our study, the general trend is the same, namely, that a
substantially high percentage of men and women know about HIV. This is
probably due to the fact that they get information from the schools
also, which only some in the sample of men would get. Introduction of
awareness of HIV in the schools is a recent phenomenon. Among the three
areas of the study, urban non-slums with 94 per cent scores the highest
in the awareness of STI. Though the general awareness about STI is good
across the areas, when it comes to the awareness of particular diseases
like syphilis, gonorrhea or fungal infection the knowledge is confined
to a very small proportion; 13.2 per cent about syphilis, 8 per cent
about gonorrhea and only 1 per cent about fungal infection. It would
appear that generally men do not have adequate information to suspect
STI when they get some symptoms. More men in the urban non-slum areas
know about these than in the other two areas. This calls for more
intensive IEC activities on this front.
To Top
7.4.6 About the transmission of
STI and HIV, more than 70 per cent acknowledged sexual intercourse as
the mode, while among married women nearly 97 per cent selected this
(Table 7.2). Somehow the women appear to know more about STI and HIV
transmissions than men. Even in the non-slum area, only close to 95 per
cent men acknowledged this, while 99 per cent of married women did so.
More than 94 percent of the urban non-slum respondents, 58.9 percent of
the suburban and 68.4 percent of the slum respondents mentioned about
sexual intercourse. Only 8.6 percent in the urban non-slum area, 16.8
percent in the suburban and 14.4 percent in the slum areas mentioned
that it may be transmitted by having sexual intercourse with sex
workers. Since the major carriers of STI are sex workers, this again
calls for more intensive educational efforts Transmission through blood
transfusion and sharing of needles was reported by 41.4 percent urban
non-slum respondents, 25.4 percent suburban respondents and 20.1
percent in the slum areas. Mother to child transmission was known to
2.9 percent, 4.8 percent and 6.2 percent in the urban non-slum,
suburban and slum areas respectively. A good proportion have mentioned
that they do not know the mode of transmission. It is around 10.7
percent in the urban non-slum, 10.5 percent in the suburban and 13.9
percent in the slum regions.
7.4.7 The knowledge about preventive measures
appears to be inadequate among men. Not even a fifth of the respondents
mentioned avoiding sexual intercourse with sex workers. According to a
survey carried out by the State AIDS Society of Kerala, the HIV
prevalence among female sex workers of Trivandrum is 2.6 per cent
(Collected from State AIDS Cell Trivandrum). They being the major
source of infection, it is quite surprising that only less than 20 per
cent of the men suggested avoiding sex with them as a preventive
measure. Though the men in the slums fare better in this with more than
23 per cent suggesting it, not even 15 per cent in the other two areas
suggest this as a means of prevention. When it comes to the sharing of
needles and syringes, the ignorance is appalling. In spite of the
widely acknowledged fact that this is one sure way of spreading HIV,
only a little over 13 per cent of the men stated avoiding sharing of
needles and syringes as a means of prevention. In the slums, it is only
a tenth of the men who mentioned this. The slightly better figure for
the non-slums and suburbs do not help in reducing the shock. Though the
transmission through this in India is only 4.2 per cent (NACO, 2002)
the people are expected to know of it. The shock deepens when it comes
to safe sex and the use of condoms. Not even a third of the men
mentioned use of condoms and only a little over a fourth mentioned safe
sex in general. Though the distinction between these two is blurred,
the respondents did not take them to be mutually exclusive. Even if we
add up the two, giving the benefit of doubt, it is only less than 60
per cent. With more than 93 per cent of men aware of HIV this is not a
happy state of affairs. Equally shocking is the fact a fifth of the men
do not know how to prevent HIV and STI. The fairly intensive IEC
campaign on HIV does not appear to bring home the messages about
prevention among men, who are the main culprits in its spreading.
7.4.8 Responses on the knowledge about the place
of treatment for STI shows that 35.7 percent in the urban non-slum
area, 23 per cent in the suburban region and 25.6 per cent in the slum
areas mentioned Government Hospitals. A significant proportion have
mentioned private hospitals i.e. around 57.9 per cent in the urban
non-slum, 56.9 per cent in the suburban and 52.3 per cent in the slum
areas. Treatment through AIDS cell was reported by 6.4, 18.7 and 22.1
per cent respondents in the urban non-slum, suburban and slum region
respectively.
To Top
7.5 Summary
7.5.1 This part of the survey
reveals that the awareness about RTI, STI and HIV is fairly high among
married women, adolescent girls and men in the reproductive age group.
The awareness of HIV is substantially higher than that of STI among the
three groups. This shows that the IEC campaign of NACO could not carry
with it effectively the messages on STI as well. The lack of
coordination between the department of Health which overseas the work
of NACO and the department of Family Welfare which is responsible for
Reproductive and Child Health in the same Ministry is perhaps
responsible for this state of affairs. There are some variations in the
degree of awareness among the three groups and the three areas of the
study. Generally the awareness about HIV is the highest among girls
followed by men and married women. But in the case of STI the
adolescent girls are in the lowest rung, the first and second being
taken by men and women. Among all the three groups of individuals,
those living in the suburban area are slightly less aware than those in
the slums and non-slums. More women and girls living in the slums are
aware of these deceases than those living in the other two areas.
7.5.2 The similarity among the three groups
continues in the mode of transmission also, with the girls showing the
highest awareness about the transmission of STI and women about HIV.
More women living in the non-slum areas know about transmission than
those in the other areas. Only less than a fifth of the women harbour
misconceptions about the transmission of HIV. Though a higher
proportion of men are aware of STI and HIV than women, when it comes to
the preventive measures they woefully lag behind. Not even three fourth
of them recognize sexual intercourse as a mode, though nearly all the
women recognize it and though it accounts for 82.6 per cent of the
transmissions in India. It is indeed shocking that only less than the
fifth of the men mentioned avoiding intercourse with sex workers as a
method of prevention. Safe sex as a means of prevention has appealed
only to a little over a fourth of men As the main culprits of the
transmission of the infection, the men need to know much more about
prevention. IEC activities have a long way to go in this.
7.5.3 Speaking of IEC, the best source of
information is proven to be television. About two thirds of the women,
and more than half of the girls acknowledged this medium. The role of
the health worker in spreading the message appears to be marginal. Of
late, the contribution to awareness from the schools has become more
evident as more than a third of the girls have acknowledged it, though
among the elder women it is insignificant. Community meetings are a
source of information to a very small extent. This is better in the
slums showing better community activity there.
To Top
7.5.4 Coming to the reproductive
health of adolescent girls, the age at menarche is between 11 and 13
for more than half concentrated in the middle. Most of them have
regular periods and some have slight problems like abdominal pain and
some, white discharge. Only a few take treatment for this. Combined
with a generally high awareness of STI and HIV one could say that the
reproductive health of adolescent girls are generally satisfactory with
no significant variation among the three areas.
7.5.5 Most of the men in the sample have
completed their educations at various levels, higher in the non-slum
areas followed by the suburbs and slums. A majority of them are
married. Their general standard of reproductive health is fairly high.
Those who had problems before or after marriage are too small to be
considered. But with the wrong notions about the prevention of HIV,
they are in the danger of losing their standard of sexual health.
VIII. Utilization and Assessment of Quality pf
Public Facilities
8.1 Introduction
8.1.1 In India health care is
expected to be the responsibility of the Government. In the days of the
Kings, health care was a Dharma of the monarch, meaning his duty. But
the Sanskrit word Dharma has also the connotation of giving free as
charity. Health care is also supposed to be given free to the people by
the government, as the latter’s duty. But in modern times, when costs
are rising, this concept of duty and charity cannot be easily put into
practice. But still the general expectation is that it is the duty of
the government to provide health care to all at all times. The people
tend to adjudge the quality of services provided by public health
facilities against this expectation.
8.1.2 In the State of Kerala where there is a
higher awareness of health needs, there is also a higher demand for
quality services by the government. Among the states of India, Kerala
has been consistently spending more than the average on health on a per
capita basis. The average for all states in 1980-81 was Rs.24 when for
Kerala it was Rs.32 and in the budget estimates of all states in
2000-01 it was Rs.146 for all states and Rs.198 for Kerala (GOK,
2000a). Even then large sections of people resort to private health
care, as the public facilities do not come up to their expectation.
KSSP Survey of 1987 has revealed that 58 per cent of health seekers go
to the private facilities and 28.6 per cent to government, the balance
treating themselves (Kunhikannan and Aravindan, 2000).
8.1.3 With this background an attempt was made
to find out the degree of utilization of public health facilities in
the city of Trivandrum, the reasons for not utilizing it and the level
of satisfaction. Questions were put in different parts of the survey
questionnaire to the entire sample population on the treatment for
general illness and to ever married women on the treatment of
complaints specific to them
To Top
8.2 General Population
8.2.1 In Chapter IV we saw that
out of the 4297-sample population, 559 people were afflicted with
various ailments during the month prior to the survey and 540 of them
took treatment. They were asked where they went for treatment. Table
8.1 below shows that, contrary to the general impression, two thirds of
them went to the public facilities for treatment.
Table 8.1 Choice of Facility by General
Population (%)
| Facility |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government Hospital |
63.4 |
62.7 |
80.0 |
67.0 |
| Private Hospital |
33.7 |
35.9 |
19.2 |
30.9 |
| Doctor's Home |
1.8 |
1.4 |
0.8 |
1.5 |
| Mobile Hospital |
1.1 |
0.0 |
0.0 |
0.6 |
| Medical Store |
0.0 |
0.0 |
0.0 |
0.0 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
273 |
142 |
125 |
540 |
8.2.2 But it has to be noted that
in the slums, only about 63% of the ill-used public facilities, whereas
80% in the suburban areas did so. Trivandrum is a city well provided
with Government and private health facilities including well-reputed
super specialty hospitals. The total number of health facilities in the
private sector is 71 as reported by the Health Department of the City
Corporation. The people in the suburban areas seem to have greater
confidence in public health facilities than the others. It is
significant that none of the respondents went to medical store for
treatment, although 7 of them had taken self-treatment. With a large
number of medical stores in the city, one would have expected at least
some patients to go to medical stores and consult the pharmacists and
shop assistants on what drugs to take. In many backward states
consulting the Pharmacy Store Assistant on minor ailments is a common
practice. This does not appear to be the case in Trivandrum city. This
speaks well of the awareness of the people on health matters.
To Top
8.2.3 When queried as to why
they did not make use of public facilities, nearly half of them
mentioned poor quality (mentioned as good quality in private facilities
and lack of confidence in Government facilities) as the reason, as seen
in Table 8.2. This is the reason given by 52 per cent of the slum ill,
59 per cent of the non-slum ill and only by 33 per cent of the suburban
ill. This strengthens the impression that the suburban people have
better faith in public facility.
Table 8.2 Reasons for Not Resorting to Public
Facilities by General Population (%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| No Confidence |
25.0 |
15.7 |
20.8 |
21.5 |
| Distance |
35.9 |
27.5 |
41.7 |
34.1 |
| Lack of cleanliness |
0.0 |
3.9 |
0.0 |
1.2 |
| To avoid delay |
1.1 |
2.0 |
12.5 |
3.0 |
| Heavy rush |
1.1 |
9.8 |
4.2 |
4.2 |
| Good quality in Private |
27.2 |
37.3 |
16.7 |
28.7 |
| Known Doctor in Private |
2.2 |
0.0 |
0.0 |
1.2 |
| Bribery in Govt. Hospital |
2.2 |
2.0 |
0.0 |
1.8 |
| Relatives influence |
3.3 |
0.0 |
4.2 |
2.4 |
| Medicines to be taken from outside |
2.2 |
2.0 |
0.0 |
1.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
92 |
51 |
24 |
167 |
About one third of them chose the private facility
because of the proximity to their homes.
8.2.4 The general population were also asked
about mortality and the results were given in Chapter IV. We saw in
that chapter that all were given some treatment before their death,
either at home or in one of the hospitals. This was followed up by a
question on the type of hospital they were taken to whether it was
private or public. The result is shown in Table 8.3.
To Top
Table 8.3 Choice of Facility for Treatment for
Fatal Illness by General Population (%)
| Facility |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government |
42.4 |
9.1 |
19.2 |
23.9 |
| Private |
45.5 |
57.6 |
57.7 |
53.3 |
| Home |
9.1 |
30.3 |
23.1 |
20.7 |
| Abroad |
3.0 |
3.0 |
0.0 |
2.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
33 |
33 |
26 |
92 |
All those who died had undergone treatment for
fatal illness; nearly 24 per cent in Government hospitals, 54.3 percent
in private hospitals and 20.7 per cent at home.
8.2.5 We have seen in Table 8.1 that when people
were sick, about two thirds went to government hospitals; but in the
mater of treatment which ultimately led to death only 24 per cent went
to government hospitals. In the latter case the illness would have been
grave. This indicates that they do not trust government hospitals when
the complaints are of a serious nature. However, a larger proportion in
the slums (42.4 per cent) took their seriously ill patients to the
government hospitals. In the non-slum area only less than 10 per cent
did that and in the suburbs nearly 20.
8.3 Ever Married Women of All Ages
8.3.1 This study has a specific
focus on Reproductive and Child Health. The ever married women (EMW) of
all ages were questioned in detail about their general and reproductive
health. It may be noted here that the recall period with EMW was three
months and not one month as in the case of the general sample, since
one month recall was not felt sufficient to capture the reproductive
health status adequately. The total sample size of ever-married women
of all ages was 1262. Out of them, 398 went in for treatment for some
ailment or the other. It is noteworthy that, not withstanding the
common complaint about public facilities, 278 of them went there for
treatment, making about 70 per cent.
Table 8.4 Choice of Facility by Ever Married
Women of All Ages for General Illness (%)
| Facility |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government |
71.9 |
50.0 |
78.0 |
69.8 |
| Private |
28.1 |
50.0 |
22.0 |
30.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
221 |
68 |
109 |
398 |
To Top
As in the case of general population, the
popularity of public facilities is the greatest in the suburbs followed
by slums. In the non-slum area only half the EMW made use of them for
their general illness.
8.3.2 Most clients judge a health facility by
the quality of overall service they receive – how they are treated and
what they experience during their visit. The dissatisfied clients would
hesitate to visit the same health facility again. Several factors which
can give satisfaction to the clients like a well equipped health
facility manned by trained medical personnel, with less waiting time,
with the patient examined in a place of privacy, with supportive staff,
sufficient medicines provided with right advice of how to administer
etc. play a key role in deciding the pattern of utilisation of health
services. If 70 per cent of the women seek treatment in government
hospitals, there could be only two reasons: either they are satisfied
with the services or, even if dissatisfied, they cannot afford to go to
a private facility. We saw in Chapter III that the majority of the
people are not so poor as not to be able to afford treatment for their
illness. Therefore, the fact that they went to government hospitals can
only show that they are not unhappy with the services available there.
In order to understand the client satisfaction, the components of
satisfaction were broken down into a series of questions and were posed
to the clients. Table 8.5 reveals the factors that influence client
satisfaction.
Table 8.5 Determinants of Client Satisfaction of
Ever Married Women who used Public Facilities (%)
| Determinants |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Service time convenient |
Yes |
93.1 |
100.0 |
95.3 |
94.6 |
| No |
6.9 |
0.0 |
4.7 |
5.4 |
| Easy to reach |
Yes |
90.6 |
76.5 |
81.2 |
86.0 |
| No |
9.4 |
23.5 |
18.8 |
14.0 |
| Whether Doctor/ Nurse Available |
Yes |
96.9 |
100.0 |
97.6 |
97.5 |
| No |
3.1 |
0.0 |
2.4 |
2.5 |
| Privacy |
Yes |
67.9 |
88.2 |
84.7 |
75.5 |
| No |
32.1 |
11.8 |
15.3 |
24.5 |
| Staff supportive/friendly |
Good |
82.4 |
100.0 |
95.3 |
88.5 |
| Poor |
17.6 |
0.0 |
4.7 |
11.5 |
| Quick attention |
Yes |
21.4 |
29.4 |
32.9 |
25.9 |
| Long wait |
78.6 |
70.6 |
67.1 |
74.1 |
| Availability of medicine |
Yes |
32.7 |
20.6 |
30.6 |
30.6 |
| No |
67.3 |
79.4 |
69.4 |
69.4 |
Received Instructions to use
medicine |
Yes |
96.9 |
100.0 |
98.8 |
97.8 |
| No |
3.1 |
0.0 |
1.2 |
2.2 |
| Treatment effective |
No |
13.2 |
8.8 |
12.9 |
12.6 |
| Can't say |
36.5 |
32.4 |
34.2 |
35.3 |
| Consulting fee paid |
Yes |
17.6 |
20.6 |
8.2 |
15.1 |
| No |
82.4 |
79.4 |
91.8 |
84.9 |
| Good enough to recommend to others |
Yes |
84.3 |
97.1 |
94.1 |
88.8 |
| No |
15.7 |
2.9 |
5.9 |
11.2 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
159 |
34 |
85 |
278 |
To Top
8.3.3 The data above indicate
that as high as 95 per cent found the timing to be convenient, 86 per
cent the facility to be within easy reach, the proportion being the
highest in the slums (90.6 per cent), and about 98 per cent found the
nurse and doctor to be available when they visited the health facility.
About three fourths were satisfied about privacy in the examination
room, 89 percent about the behaviour of the staff and 98 per cent about
the instructions given by the staff for taking medicine. A majority
(52.3 per cent) found the treatment to be effective. In spite of the
common complaint that the Doctors in government hospitals would not
give proper attention without paying fees, the data reveal that 85 per
cent did not pay fees to the doctor. A whopping 89 per cent would
recommend public facilities to others. As far as negative feedbacks are
concerned, around three fourth (74.1 per cent) found the waiting time
to be long andnearly 70 per cent did not get all the medicines.
8.3.4 The survey also collected information on
the reasons for not seeking medical help from public health facility.
Out of the sample of 1262 women 398 sought treatment and, as stated
above, only 120 of them went to private hospitals, making 30 per cent.
These persons were asked the reasons for not going to public
facilities. The response is given in Table 8.6.
Table 8.6 Reasons for Not Using Public facility
by Ever Married Women
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Not conveniently located |
19.4 |
17.7 |
20.8 |
19.2 |
| Timings not convenient |
4.8 |
0.0 |
0.0 |
2.5 |
| Poor quality of service |
38.8 |
14.7 |
29.1 |
30.0 |
| Heavy rush |
6.4 |
2.9 |
8.3 |
5.8 |
| Non-availability of Doctors |
0.0 |
0.0 |
0.0 |
0.0 |
| Rare availiability of Doctors |
0.0 |
0.0 |
4.2 |
0.8 |
| Doctors do not examine properly |
4.8 |
8.8 |
4.2 |
5.8 |
| Medicines not/rarely given |
3.2 |
0.0 |
8.3 |
3.3 |
| Medicines are of bad quality |
1.6 |
2.9 |
4.2 |
2.5 |
| Doctor/staff do not behave properly |
0.0 |
0.0 |
0.0 |
0.0 |
| Services are charged |
3.2 |
0.0 |
12.5 |
4.2 |
| Prefer Private Doctors |
17.8 |
52.9 |
4.2 |
25.0 |
| Others |
0.0 |
0.0 |
4.2 |
0.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
62 |
34 |
24 |
120 |
To Top
8.3.5 The largest group (30 per
cent) was driven to the private hospital by the poor quality in public
facilities, more in the slums (39 per cent) than in the other two
areas. This is not much different from the general population where
this group was found to be 34 per cent (Table 8.2 above). It is to be
noted that only about 15 per cent in the non-slums gave poor quality as
the reason. The next largest group is 25 per cent who simply prefer
private doctors, a very high proportion (53 per cent) in the non-slum
areas. This can be compared with the group of 21 per cent of the
general population who expressed lack of confidence in public
facilities. Nearly 20 per cent were driven by the distance, less in the
non-slums, whereas among the general population it was 34 per cent.
Heavy rush has driven only 5.8 per cent of the women to the private
facility and 4.2 per cent of the general population.
8.4 Ever-Married Women (15-49 Years)
8.4.1 So far we have considered
the question whether public facilities met the needs for general
ailments by all and by Ever Married Women of all ages. As our focus
narrows to reproductive health we also narrow the sample to Ever
Married Women in the reproductive ages. The questioning on reproductive
health started with their menstrual problems. We saw in Chapter V that
out of the total of 855 only 71 women had menstrual problems and out of
them only 42 went for treatment. It is noteworthy that 31 of them (73.8
per cent) went to public facilities.
To Top
Table 8.7 Choice of Facility for Menstrual
Problems (%)
| Facility |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government |
66.7 |
80.0 |
87.5 |
73.8 |
| Private |
33.3 |
10.0 |
12.5 |
23.8 |
| Others |
0.0 |
10.0 |
0.0 |
2.4 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
24 |
10 |
8 |
42 |
8.4.2 The reasons why others did
not go are in Table 8.8. The size of the sample is too small to draw
inferences.
Table 8.8 Reasons for Not Choosing Public
Facilities for Menstrual Problems (%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Not nearby |
12.5 |
0.0 |
0.0 |
9.0 |
| Poor quality |
37.5 |
50.0 |
100.0 |
45.5 |
| Others |
50.0 |
50.0 |
0.0 |
45.5 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
8 |
2 |
1 |
11 |
8.4.3 We also saw in Chapter V
that 761 of the sample could be asked about their last pregnancy and
found that 698 had gone for antenatal check up. As can be seen in Table
8.9, public facilities were the choice of 81 per cent of women.
To Top
Table 8.9 Place of Ante-Natal Check up (%)
| Facility |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government Hospital |
84.1 |
57.0 |
92.9 |
80.3 |
| Government Dispensary |
0.8 |
0.0 |
0.0 |
0.4 |
| Government Sub center |
0.5 |
0.0 |
0.0 |
0.3 |
| Private Doctor/Hospital |
14.6 |
43.0 |
5.9 |
18.7 |
| Doctor's House |
0.0 |
0.0 |
1.2 |
0.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
8.4.4 This again shows that
public facilities are quite popular. When we probed the reasons for not
using public facilities the answers we obtained show that the largest
group (42.4 per cent) did so due to the poor quality in public
facilities. We can reasonably club this with the 16.7 per cent of them
who gave the better quality in the private facility as the reason.
Together this makes 59.1 per cent. In the non-slums it is nearly 57 per
cent. This is higher than the previous two samples. Inconvenient
location was the factor that drove 21.2 per cent of the pregnant women
to the private sector for antenatal check up.
Table 8.10 Reasons for Not Going to Public
Facility for Antenatal Check up (%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Not conveniently located |
25.9 |
18.4 |
15.4 |
21.2 |
| Poor quality of Service |
51.9 |
69.2 |
38.4 |
59.1 |
| Fees should be remitted |
22.2 |
3.1 |
7.7 |
11.4 |
| Non-availiabilty of service |
0.0 |
0.0 |
7.7 |
0.7 |
| Did not feel necessary |
0.0 |
3.1 |
23.1 |
3.8 |
| Unhygienic condition |
0.0 |
6.2 |
7.7 |
3.8 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
54 |
65 |
13 |
132 |
To Top
8.4.5 Generally, the reasons are
not much different from those put forward for general ailments by men
and ever-married women. However, a new reason has come up, namely `fees
have to be remitted`. On further probing this answer was found to mean
the long procedure and the waiting for remitting the fees rather than
the amount of fees, which is quite small.
8.4.6 Some women had other health problems
during pregnancy. A total of 64 of them went in for consultations. As
can be seen in Table 8.11 about two thirds of them went to government
doctors and facilities. The reasons for going to others were not
probed.
Table 8.11 Consultation for Problems During
Pregnancy (%)*
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government Doctors and facilities |
69.0 |
40.0 |
78.6 |
68.0 |
| Private Doctor |
31.0 |
50.0 |
21.4 |
32.1 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
36 |
10 |
18 |
64 |
Note: One person (10 per cent) in the non-slum
visited doctor at home. Adding this, it will be 100 per cent. But many
in the other categories visited doctors at home also, which is not
included in the table.
8.4.7 We continued this probing on the
utilization of public services into the next step, namely deliveries.
Here also the proportion was substantial, with nearly three fourths
utilizing them.
Table 8.12 Place of Delivery (%)
| Place of Delivery |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government Hospital |
76.1 |
63.4 |
83.7 |
74.9 |
| Private Hospital |
14.8 |
32.7 |
12.6 |
18.4 |
| Home |
9.1 |
3.9 |
3.8 |
6.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
378 |
151 |
169 |
698 |
8.4.8 The reasons for not going to
government facilities are the same as in the other cases, poor quality
and distance dominating them.
To Top
Table 8.13 Reasons for Not Going to Government
Hospital for Delivery (%)*
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Not conveniently located |
30.7 |
24.0 |
52.2 |
31.7 |
| Poor quality of Service |
33.3 |
62.0 |
39.1 |
44.9 |
| Delivery attended by male |
11.1 |
2.0 |
0.0 |
5.9 |
| Costs involved |
15.9 |
0.0 |
0.0 |
7.4 |
| Unhygienic conditions |
0.0 |
6.0 |
0.0 |
2.2 |
| Others |
9.6 |
6.0 |
8.7 |
8.1 |
| Total |
100.6 |
100.0 |
100.0 |
100.2 |
Interestingly, about 6 per cent opted out of
government facility because the delivery is attended to by male
doctors, more than 11 per cent in the slums. Nearly 16 per cent in the
slums mentioned the costs involved as the reason. This would refer to
the informal payments to be made to the staff and the expenses for
buying medicine etc and the procedure for payment. It is not that
public facilities are costlier than private ones.
8.4.9 Out of the total of 855 ever married
women, 813 were currently married. Thirty of them were pregnant. The
remaining 783 were asked about their contraceptive use and the results
are discussed in Chapter V. A total of 449 currently married women have
undergone sterilization. Of them 425 accepted it in public facilities
and 24 in private hospitals (Table 8.14). The percentage of women who
did not use public facilities is only 5.3.
Table 8.14 Place of Sterilisation (%)
| Facility |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government |
98.0 |
82.7 |
95.8 |
94.7 |
| Private |
2.0 |
17.3 |
4.2 |
5.3 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
248 |
81 |
120 |
449 |
8.4.10 As for the reasons for not
going to public facilities, the picture is not much different from the
other uses. Nearly 71 per cent were deterred by the distance, 16.6 per
cent by the unhygienic conditions and about an eighth by poor quality.
To Top
Table 8.15 Reasons for not using Public Facility
for Sterilization (%)
| Reason |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Poor quality of service |
20.0 |
7.1 |
20.0 |
12.5 |
| Not convenient |
80.0 |
64.2 |
80.0 |
70.8 |
| Unhygienic |
0.0 |
28.6 |
0.0 |
16.6 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
5 |
14 |
5 |
24 |
8.5 Children Below 2 Years
8.5.1 The only question pertaining
to public facility probed about children was the place of immunization.
A total of 95 children were immunized (fully and partly), 68 of them in
public facilities, the percentage being 71.5. The reasons for not
seeking public facilities were not probed in this case.
Table 8.16 Place of Immunisation (%)
| Reasons |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government Hospital |
63.5 |
63.2 |
66.7 |
64.2 |
| Primary Health Centre |
3.8 |
0.0 |
8.3 |
4.2 |
| Immunisation Camp |
3.8 |
0.0 |
0.0 |
2.1 |
| Sub Centre |
1.9 |
0.0 |
0.0 |
1.0 |
| Private Hospital |
25.0 |
36.8 |
20.8 |
26.3 |
| Don't Know |
1.9 |
0.0 |
4.2 |
2.1 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
52 |
19 |
24 |
95 |
To Top
8.6 Summary of Choice
8.6.1 If we summarise the
responses from these various groups on where they went for their health
needs and why, we can see that a large majority of them went to public
facilities.
Table 8.17 Summary of Choice of Treatment
Facility (%)
| Group |
Number |
Government |
Private |
Others |
| All samples for general illness |
540 |
67.0 |
30.9 |
2.1 |
| All samples for treatment for fatal illness |
92 |
23.9 |
53.3 |
22.9 |
| Ever married women of all ages for general illness |
398 |
69.8 |
30.2 |
0.0 |
| Ever married women (ages 15-49) with menstrual problems |
42 |
73.8 |
23.8 |
2.4 |
| Ever married women (ages 15-49) for antenatal check up |
698 |
81.0 |
19.0 |
0.0 |
| Ever married women (ages 15-49) with problems during
pregnancy |
64 |
68.0 |
32.0 |
0.0 |
| Ever married women (15-49) for delivery |
698 |
74.9 |
18.4 |
6.6 |
| Ever married women (15-49) for sterilisation |
449 |
94.7 |
5.3 |
0.0 |
| Children for immunisation |
95 |
71.5 |
26.3 |
2.1 |
| Total |
3076 |
75.3 |
22.0 |
2.7 |
8.6.2 It reiterates the inference
that public facilities are quite popular. Except for illnesses which
ultimately led to death, more than three fourths of the sample and its
sub groups have gone to public facilities for general illnesses and
problems of reproductive health. It is as high as 95 per cent for
female sterilization. Overall about three fourths used public
facilities. This negates the general impression that public facilities
are run badly and people would avoid them. In fact when the women were
asked whether they were satisfied about the services provided by public
facilities, nearly three fourths of them answered in the affirmative
(Table 8.18). Even most of the others were partially satisfied.
To Top
Table 8.18 Level of Satisfaction by Ever Married
Women of All Ages (%)
| Level |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Fully satisfied |
71.0 |
73.5 |
79.1 |
73.3 |
| Partially satisfied |
25.8 |
23.5 |
20.8 |
24.2 |
| Not satisfied |
3.2 |
3.0 |
0 |
2.5 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
62.0 |
34.0 |
24.0 |
120.0 |
8.6.3 However, a rider is in place
here. Trivandrum is the capital of the state and is better served,
medically. The Government runs a super specialty teaching hospital with
about 1200 beds and four other big general hospitals, 1154 beds in two
facilities out of this are exclusively for women and children. It is
not like a rural area where there is only a sub centre with an
Auxiliary Nurse-Midwife for a population of 5000, a Primary Health
Centre with at least one doctor for 25,000 and a Community Health
Centre with at least four doctors for 100,000. Some of this
infrastructure is also available in the City. For finding out the type
of public facility used we asked the ever-married women of all ages
what type of facility they went to. More than 91 per cent answered that
they went to Hospitals. Only about 9 per cent used the other rural-like
infrastructure, as can be seen in the table below. Therefore the
response in this survey cannot be taken as the representative opinion
of consumers of public health facilities in the State.
Table 8.19 Choice of Public Facility for General
Illness by EMW of All Ages (%)
| Place of Treatment |
Urban |
Suburban |
Total |
| Slum |
Non-slum |
| Government Hospital |
93.7 |
91.2 |
84.7 |
90.7 |
| Community Health Centre |
1.2 |
0.0 |
3.5 |
1.8 |
| Primary Health Centre |
3.1 |
8.8 |
11.8 |
6.5 |
| Sub Centre |
1.9 |
0.0 |
0.0 |
1.1 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
159 |
34 |
85 |
278 |
To Top
8.6.4 We tried to find out
whether it is poverty that drives people to public health facilities
where the services are practically free. But we saw in Chapter III that
if we go by expenditure pattern, those who spent below Rs.500 a month
are only 8.6 per cent. If we go by income, only 15 per cent are with
less than Rs.1500 per month. As about three fourths of the people use
public facilities, the reason would not be lack of affordability. In
fact, we saw in Table 8.18 that most of the women are satisfied with
the quality of services and about 90 per cent would recommend it to
others Thus, there appears to be genuine reasons of acceptance for
using public facilities. However there is a significant proportion of
people who do not go to public facilities and for them distance and
poor quality are the two major reasons. The factor of distance, as
appearing in various tables, should be considered cautiously. The
perception on distance is relative and can vary among different
population groups such as total population, ever married women of all
ages and of reproductive age.
Table 8.20 Summary of Reasons for Choice of
Facilities
| Reason |
All sample |
EMW for all illness |
Menstrual Problem |
ANC |
Delivery |
Sterilisation |
| Disrtance |
34.1 |
19.2 |
9.0 |
21.2 |
31.7 |
70.8 |
| Poor quality |
28.7 |
30.0 |
45.5 |
59.1 |
44.9 |
12.5 |
| No confidence |
21.0 |
25.0 |
0.0 |
0.0 |
0.0 |
0.0 |
| Lack of cleanliness |
1.2 |
0.0 |
0.0 |
3.8 |
2.2 |
16.6 |
| Others |
15.0 |
25.7 |
45.5 |
15.9 |
21.2 |
0.0 |
| Total |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
100.0 |
| Number |
167 |
120 |
10 |
132 |
128 |
24 |
8.6.5 Lack of cleanliness and lack
of confidence in the ability of the facility to cure the patients form
the next two reasons. Other reasons vary among the groups and include
items like heavy rush, bribery, relatives’ influence, non-availability
of medicine etc as given in the individual tables in the relevant
paragraphs. In the next chapter we deal with the suggestion for the
improvement that came up in the in-depth interviews with community
leaders, health activists etc.
To Top
IX. Suggestions forImprovement of Public Health
Facilities
9.1
This study envisaged in-depth interviews with
community leaders, providers, programme managers, health activists and
decision makers also with a view to validating the data on qualitative
aspects provided by the household respondents and to enlist the
opinions as well as suggestions of the former. In this endeavour, the
information from various groups of respondents from households was used
as the reference material. There were several suggestions and opinions
commonly expressed by belonging to different groups. We have analysed
various suggestions and collated them under specific issues.
9.2 Shortage of Drugs
9.2.1 The community leaders were
of the impression that because of the general dissatisfaction with
public health facilities, slum dwellers were not going to the nearby
Government hospitals and health Centres for treatment. They were
surprised to know that the vast majority of slum dwellers and others
went to public facilities and that most of the women expressed
satisfaction about the services there. Some community leaders even
doubted the veracity of the responses. It took an explanation of the
methodology and of the detailed fieldwork involved, to convince them.
But one suggestion they all had in common was that more medicines
should be made available in the government facilities. When this was
taken up with the Director of Health Services and the Principal
Secretary to Government for Health and Family Welfare they both pointed
to the perennial shortage of funds in the Department. The Health
Department spends about Rs.500 million on the purchase of drugs alone.
But due to the ways and means position of the Government, they are not
able to release this fund (like all other departments) in time and
therefore the drug suppliers are not being paid their bills. This
interrupts the supplies.
9.2.2 Some of those interviewed doubted whether
shortage of funds is the only problem. According to them, sometimes
drugs lie undistributed in the medical stores while there is acute
shortage in the hospitals. According to them, this is more of a problem
in the rural areas. The logistics of distribution have to be
streamlined. Some of the leaders pointed out the system in the
neighbouring state of Tamil Nadu where a separate corporation has been
formed by the Government for drug distribution. But the Principal
Health Secretary to Government stated that the success of the Tamil
Nadu system depended on the funds for drug purchase being given to this
corporation at the beginning of the year itself. No doubt, there are
many things in the Tamil Nadu system that can be introduced in Kerala.
But unless funds are made available no system will work. Thus the crux
of the problem is the financial crisis the state is passing through.
To Top
9.3 Shortage of Manpower
9.3.1 The second major deficiency
pointed out by the community leaders, providers and programme managers
is the shortage of manpower in hospitals and other facilities. The
shortage is so acute that sometimes one nurse has to cater to more than
one ward and samples have to be taken to the private labs outside for
investigation. Many of those interviewed stated that the visits to
public facilities by patients will be even higher if there are doctors,
lab technicians and nurses in adequate number. While probing to find
out the reasons, it came out that the procedure of recruiting manpower
through an independent statutory body is a long drawn out one. The time
lag between requisitioning the staff and getting them in position is
2-3 years. Advance planning can be done only for vacancies caused by
retirement. But a large number of people go on leave. The practice of
granting leave upto fifteen years for taking up other jobs abroad and
even within the country came in for very sharp criticism from the
health activists. This practice may be appropriate in other sectors
where there are plenty of people to work. But in the health sector
where there is a perennial shortage of doctors, nurses, lab
technicians, pharmacists etc, this is totally illogical. But in spite
of the political leaders agreeing with the illogicality0 of granting
leave in the face of shortages, successive governments by different
political affiliations have done nothing about it. Thinking people
pointed out that pressure from the unions of employees is the reason.
9.4 Environmental Issues
9.4.1 The third issue that came up
is the need to emphasize on preventive care. Many of those who
interviewed brought to light the health hazards to which present day
living in crowded environment exposes people. Many suggestions came up
on this. The foremost was the need to provide drainage, sanitation,
waste removal and protected water in the slums. We saw in Chapter III
that 72 per cent of the households do not have drainage facility,
nearly two-thirds of the houses in the slums, nearly 60 per cent in the
non-slum areas and almost all in the suburbs. Trivandrum used to be
called the cleanest city in the country earlier. However the claim to
this distinction looks dubious in the face of the lack of drainage. It
is due to the topography of the land that there is not much stagnation
of water. The danger of outbreak of epidemics cannot be ruled out. A
priest near one of the slums in the coastal area brought to our
attention the outbreak of malaria in that locality in the first half of
1996. The cases were initially imported but soon it spread to large
areas threatening to blow into an epidemic. It was the concerted effort
of the health department, the Church and other non-governmental
agencies that put an end to this. Such situations can develop again in
the city with such poor drainage.
To Top
9.4.2 We also saw in Chapter III
that 24 per cent of the households do not have latrines, 35 per cent in
the slums. The majority of them use open ground as toilets, the use of
public toilets being confined to a third of them. The community leaders
blamed the city authorities for the bad upkeep of public toilets.
However, some health activists suggested that it would be better to
introduce pay-and-use toilets, which have been found to be very
successful in some other parts of the country. This is worth pursuing.
9.4.3 Waste removal was pointed out by the
respondents, the community leaders and by nearly all others as the
major problem in sanitation. Nearly every respondent complained about
it. The city authorities stated that they have found a solution to this
problem by erecting a garbage treatment plant nearby. However, the
residents around the newly erected plant have been objecting to the
transportation of garbage to that area and its treatment there as it
poses a health hazard to them. The current position is that this
expensive new plant does not get enough garbage, which continues to
accumulate in the streets and slums, and the removal is as
unsatisfactory as before.
9.5 Safe Drinking Water
9.5.1 The next suggestion for
preventive care was the provision of protected water in all the homes.
We saw in Chapter III (Table 3.11) that only a third of the houses have
running water inside and two-thirds of the houses in slums bring water
from the public tap in the street. This situation can be remedied only
by investment in a water augmentation scheme.
To Top
9.6 Strengthening of Primary Centres
9.6.1 The major problem in
government hospitals pointed out by all, is the heavy rush of patients.
This is more so in the specialty hospitals. At the same time the
utilization of centers for maternity care and primary health care is
very poor. The people tend to rush to tertiary hospitals and overcrowd
them. Many leaders said that this is because the quality of service in
the primary centers is very poor. The answer is to staff them
adequately, make drugs available and keep them clean. After doing this,
the specialty hospitals can be made truly and strictly referral
hospitals facilitating a two-way reference for the patients.
9.7 Cost Recovery
9.7.1 A question arises whether
the Government can provide all services to all free. If there is
improvement in quality, the people who get attracted to public
facilities are those who have been paying for their care in private
facilities. At the same time the quality cannot be kept low for fear of
serving the rich. This can be described as the Public Health Conundrum.
Purely from an objective standpoint, poor quality is a self-targeting
mechanism as only those who cannot afford better quality will go to a
poor facility. But it is totally an anti-egalitarian move as the poor
have an equal right to good quality services as the rich. The only way
out of the conundrum is to charge the rich who use public facilities.
The Principal Health Secretary pointed out the attempts have been made
by the health department for charging fees from those who can afford
and keeping the money in the Hospital Development Committee for
improving the facilities in the hospital. While a proper mechanism for
means testing is still to be evolved, this system has helped in
stretching the health budget and providing improvements not possible
under the budget. He showed the example of the teaching hospital in the
city, which has a Hospital Development Committee where political
parties and public men are represented. They are allowed to collect
user fee and keep it with them. They also run a medical store. The
money collected has been used for improving facilities like putting up
a Cardiac Catheter Lab, appointing security staff, etc. The budgeted
expenditure for running this hospital in 1998-99 was Rs.330 million and
the income of Hospital Development Committee was about 30 million. The
state Government intends to make the other hospitals follow this
example.
9.7.2 However the need for support from the
state budget was emphasized by all. They reminded us of the importance
given by the Monarchs of the state for health and education which is
the primary reason for the present high status in both. But there is
some complacency now and the share of health in the state budget has
steadily come down from 16.27 per cent in 1974-75 (Panikar and Soman,
1984) to 11.41 in 200-01 (GOK, 2000b). Our subjects here took strong
exception to this. This is a dangerous trend and has the potential of
undoing the gains of the past. They are of the view that at least the
status quo ante should be restored. After all, the need of the hour in
a state like Kerala is to improve the quality of population, especially
the health status of women and
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9.8 Partnership with Private Sector
9.8.1 In the context of the
declining share of health in the state’s budget and the rising
expectation of the people about modern healthcare, some pointed to the
need for seeking a partnership with the private sector. In India, more
than 80 per cent of the health expenditure is in the private sector and
the picture in Kerala is not different. Instead of keeping such a major
provider of health care at arms length, the government should rope in
their help in public health programmes as well as in general health
care. However, many also spoke of the need for regulating the conduct
of the private sector when it touches the boundaries of ethics.
9.9 Geriatric Care
9.9.1 The need for geriatric care
was emphasized by many. With a successful demographic transition, the
number of the elderly has risen fast in the state. Against an all India
figure of 7.9 per cent, Kerala has 10.0 per cent of its people above 60
(IIPS and ORC Macro 2001) The population above 70 has gone up from 3.41
per cent in 1991 to 4.95 in 2001 in the State (Rajan 2000) Families
have become nuclear and with 2.05 million people working outside the
state (Zacharia et al.1999), the elderly are left to fend for
themselves. There is need for old age homes, geriatric wards and
starting geriatric medicine as a speciality in the medical curriculum.
There is also the need for encouraging NGOs to provide home nursing for
the elderly.
9.10 Organisational Aspects
9.10.1 The next problem raised by
city leaders and program managers is the dichotomy in the organization
of health services in the city. The responsibility of health care in
the city is with the Director of Health Services who runs the general
and other hospitals and the Director of Medical Education who runs the
teaching hospital. The city corporation which has a health department
headed by a medical doctor is more or less confining its health
activity to sanitation. Some of the city councilors who were
interviewed were of the opinion that the city can take care of the
health of the people in its entirety. But the health administration in
the state Government and the health activists who were interviewed were
of the view that such a change in the organization of public health
provisioning is not called for as it will not bring any benefit to the
public.
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9.11 Autonomisation of Hospitals
9.11.1 Another important
suggestion was about the need of introducing greater autonomy to the
major hospitals in fund utilisation and generation. Currently, the
Superintendents of hospitals have to go through a cumbersome procedure
for purchase equipments and consumables. It is so long- drawn that in
many years, huge chunks of allocated funds go unutilized.
9.11.2 If the heads of the departments of major
hospitals and the medical superintendents are given more autonomy in
the utilisation of funds, this could be avoided. Each department can be
made a budget centre and they can also be permitted to recover costs as
much as possible without impinging on social equity. Such an innovative
step could go a long way in motivating them in generating the much
needed additional resources. A successful case is that of the Regional
Cancer Centre Trivandrum, which was originally the Radiotherapy
department of the Government Medical College and was transformed into
an autonomous society in 1981. Though the bulk of the finances still
come from the state budget, it now raises substantial resources
externally from agencies like WHO and research organizations and
internally from patients who can afford payment. More than half of its
running cost is r | 