Impact of Socioeconomic and demography variable in...

Lund University Department of Economic HistoryMaster Programme in Economic History

Factors Determine the Infant Mortality in Punjab

( Haris Idrees )

[email protected]

EKHR02Independent ResearchMaster’s thesis (15 credits ECTS)

Supervisor: Examiner:Tommy Bengtsson Martin Dribe

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Acknowledgement

In the name of ALLAH, The Most Gracious, The Most Merciful

First of all I would like to thanks Almighty Allah who gives me strength and ability to do this

research work. I am very much thankful to my supervisor Mr. Tommy Bengtsson for his

guidance and valuable comments.

I would like to thanks my brothers and sister for providing me the moral support for this study

and special thanks to my parents. It is not possible to complete this work without their

motivation. Their love and affection always be the basic source of my inspiration.

At the end I would like to thanks Swedish Government for providing me this opportunity.

I dedicate this thesis to my beloved Family.

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Abstract (150-200) Infant mortality is an important indicator to observe the children and public health and also to

examine the health policies. It is also used as the best indicator to check the socioeconomic

development. It is also one of the major goal of United Nation to reduce infant mortality in

developing countries. Now a days it is also the biggest challenge for the policy makers and

demographers to introduce such a policy which reduce the infant mortality in developing

countries. In this paper the author is trying to find out the socioeconomic and demographic

determinants of infant mortality in rural area of Punjab. With the help of previous research and

Mosley Chen frame work socioeconomic and demography variables are selected. Logistic

regression were applied as a statistical tool on Demography and Health Survey data.

In this study birth distribution of women aged 15 to 49 sample of 10,466 sample from Rural

Punjab were used to analysis. Pakistan Demography and Health Survey (PDHS) 2006-07 is the

biggest survey with fully representative of 95441 household samples and 39,049 births sample

with good composition of questionnaires to get information from the respondents.

Key Words: Infant mortality ; Punjab ; Rural, Poverty ; Mother’s education ; Health

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CONTENTSAcknowledgement 2Abstract 3Table of contents 4List of Tables 6

1. Introduction 7

1.1. Aim and scope 11

1.2. Research question 12

1.3. Thesis Plan 13

2. Background 14

2.1. Previous research 14

2.2. Theoretical framework 14

2.2.1. Mother’s Education and infant mortality 14

2.2.2. Poverty, socioeconomic and infant mortality 16

2.2.3. Fertility and infant mortality 17

2.2.4. Diseases and infant mortality 17

2.2.5. Biological and infant mortality 18

2.3. Infant Mortality in the Punjab Area 19

3. Theoretical model 23

3.1. Mosley and Chen frame work 23

4. Empirical Model 27

4.1. Statistical Model 27

4.2. Application 28

4.3. Data source 28

4.4. Variables 31

4.4.1. Mother’s Education 31

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4.4.2. Social Economic Status 31

4.4.3. Mother’s working Status 31

4.4.4. Father’s Education 32

4.4.5. Drinking Water Supply 32

4.4.6. Sanitation Facility 33

4.4.7. Mother’s Age at Marriage 33

4.4.8. Mother’s Age at Birth 34

4.4.9. Birth Order 34

4.4.10. Birth Interval 34

4.4.11. Number of Siblings 35

5. Statistical Tools 36

5.1. Logistic regression 36

5.2. Dummy Variables 38

6. Results 42

7. Conclusion 55

References

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List of Tables

Table 5(a) Distribution of Socioeconomic and Demographic Dummy variables

Table 6(a)Percentage Distribution of Infant deaths in Rural urban of Punjab (Pakistan)

Table 6(b)Percentage distribution of population by socioeconomic and Demographic Variables in Rural Urban Punjab (Pakistan)

Table 6(c) Covariance Between Socioeconomic variables

Table 6(d) Covariance Between Demographic variables

Table 6(e) Results of Socioeconomic Variables in Determinant of Infant Mortality in Rural Areas Punjab (Pakistan) by Logistic regression.

Table 6(f) Analysis of Socioeconomic Variables in Determinant of Infant Mortality in Rural Areas Punjab (Pakistan)

Table 6(g) Results of Demographic Variables in Determinant of Infant Mortality in Rural Areas Punjab (Pakistan) by Logistic regression.

Table 6(h)Analysis of Demographic Variables in Determinant of Infant Mortality in Rural Areas Punjab (Pakistan)

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Chapter No 1

Introduction:

Children plays an important role in nation building as they are nation builders in future. Healthy

children will become into healthy nation. Infant and child mortality is the best indicator to

examine the children’s health and also best pointer for socioeconomic development. There is

inverse relationship between infant mortality and socioeconomic development as high infant

mortality indicates poor government health policies and low socio economic development.

Pakistan is also facing high infant mortality rate like others developing countries.

Infant mortality is normally known as the death of child at an age less than one year. The scale

used to count the mortality rate is called infant mortality rate. It tells the total number of child

deaths under the age of one for every 1000 births. There are two constituents in which the infant

mortality rate is broken relating to the death timing: neonatal and post neonatal. The number of

deaths in 28 days of the child’s birth for every 1000 live births is called neonatal mortality. In

some cases an unusual neonatal mortality is reviewed. The post neonatal mortality is known the

number of deaths that happen after 28 days development and before one year per every 1000 live

births. One should keep in view the difference between neonatal mortality and post neonatal

mortality, as there is a much higher risk of death at the time of delivery than later. Moreover the

reasons of the death at the time of delivery vary from the reasons of death later. For this reasons

various effective steps have to be taken to reduce child mortality depending on the ages of

children at death (Encyclopedia of Death and Dying, 2010).

Infant mortality has turn into a global, growing and crucial issue especially in developing

countries. About 423,000 children die every year in Pakistan. It is also among those countries to

face the high child mortality. According to the World Health Organization rank of Pakistan in

child mortality is 47th country. Major causes of Child mortality in Pakistan can be classified by

two major factors like biological and socioeconomic variables. Socioeconomic factors consist of

economic status, education, maternal health education, and breast feeding, culture, sanitation and

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drinking water facility. Biological factors consist of birth spacing, birth weight, no of siblings,

high fertility, births and infection diseases (Unicef, 2008). With the integration of socioeconomic

and biological variables like maternal education, good sanitation conditions, preventive checks

against diseases, family planning and availability of medical care centre, Pakistan has increased

immensely the health condition of their population and child mortality as well (Kalhore, 2009).

Overall in the world infant mortality rate was 57 per 1000 births in 2001 and it is reduced a lot

from 126 per 1000 births in 1960 but this infant mortality rate is still very high in low developed

countries, almost 10 times higher than the developed countries. IMR in Low developed countries

is 91 per 1000 births (infant mortality, 2011). From the last two and three decades, child

mortality has become a alarming issue for Pakistan’s administration even it have progress a lot in

child survival. Child mortality has declined from 153 per 1000 live births to 101 per 1000 in

2007. Whereas infant mortality has declined from 102 per 1000 live births in 1991 to 77 per

1000 in 2001. IMR is 71 per 1000 live births in 2009. International organizations like UNICEF,

USAID, WHO has introduce a lot of successive programs to improve female education and also

training programs for the birth attendance (USAID, 2009).

Pakistan is the poorest country in South Asia and lagged behind of its neighbors. High fertility

rates, lack of education, ignorance of family planning and lack of health care centre and births

attendance are contributing a lot in poor child health (PAIMAN(b), 2011). Infant mortality ratio

is higher in the women from the rural area of Pakistan as compared to the urban areas. This is

because of availability and easy access to the health facilities and healthy clean water. USAID

has introduced the program Pakistan Initiative for Mothers and Newborns (PAIMAN) in 2004.

The primary objective of this program is to improve health of maternal and new born child.

PAIMAN was working in12 regions of Pakistan like two regions of Federally Administrated

Tribal Area (FATA) and district of Swat in North West Frontier West (NWFP). PAIMAN not

only reduce the infant and maternal death by providing quality health care centre but also giving

information about the complication of pregnancy and safe deliveries to the women living in rural

areas of Pakistan(PAIMAN(a), 2011).

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According to the report of Population Council infant mortality was two times higher in lowest

class workers as compared to the proficient class in Pakistan. Different states have different

infant mortality rates like India and this is because of unequal economic growth distribution. In

this study it is stated that infant mortality is much higher in rural areas (Population Council

2005).

Source : Poverty in Pakistan : http://en.wikipedia.org/wiki/Poverty_in_Pakistan Wednesday, May

12, 2011; 02:48:01 AM.

Figure 1 represents the percentage population on y-axis and rural urban areas of Pakistan on x-

axis and inform about the poverty issue in Pakistan. In rural areas poverty is very high 39.3 % in

2001 as compared to the urban areas 22.7 % in 2001. This poverty has reduced in 2005 but it is

still very high in rural areas almost 2 times higher than the poverty in urban areas..

Health issues and mortality of children cannot be cured separately, it is very much inter related

with carious socio economic circumstances as explained by Mahmood (1993). Issues related to

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http://en.wikipedia.org/wiki/Poverty_in_Pakistan

social component may b overlooked by the economical and financial aspects. Lower income of

the family has its own gory consequences for e.g. insufficient food, lower living standard,

shelter, housing facilities and recreational activities that might lay impact on the health of all the

members of the family. Besides all this the medical expenses might put the family under burden

and debt. This may lead to more decline in the living standard of the family. This can result in a

vicious circle for people generally from poor families. Infant mortality as a phenomenon is very

difficult to avoid and ignored due to its socio economic outcomes. Infant mortality rate of a

society in itself is the determinant of socio economic development of a society. Various factors

that play a significant task in the child health include house hold income, mother’ education,

occupation of father, living standard of family etc. Some demographic factors are also vital such

as birth interval, age of mother while bearing the child, health care facilities and immunization.

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1.1 Aim and scope:

Pakistan is one of those countries having very large population over 170 million and almost sixth

most populous countries. Punjab is the biggest province of Pakistan according to the population

approximately more than half of the population belong to the total population. Punjab has

contributed a lot in the development of Pakistan and its contribution in GDP is 59% in 2010

(Punjab, 2011).

The aim of this study is to investigate the socioeconomic and biological variables to determine

the infant mortality in the rural area of Punjab in Pakistan as infant mortality rate is very high in

Pakistan reflecting negative economic development at the end of 90’s. The poverty has increased

a lot and Almost one fourth of the population are categorized as poor in October 2006 and

17.2% of population are living under the poverty line (Poverty in Pakistan).

In this paper micro level socio economic, demography and biological variables of women aged

15-49 are analysis to examine the infant mortality in rural areas of Punjab. The aim of this paper

is to find out determinants of infant mortality in rural areas of Punjab. So this study will draw

attention of researchers and demographers to this area as it is the most populated area of

Pakistan. This study may be attain attention of policy makers as they are usually focus on the

fertility matters. In this study the author used Demography and Health Survey data for the year

of 2006-07.

One of the key policies to attain stability in population is the reduction of infant mortality rate.

There is great need of effort required to investigate socioeconomic and demography factors that

are determinants of infant mortality. In order to establish policies and programs for the reduction

of infant mortality and stability in population there has to be keen research on the factors

affecting it. Consequently, the sole purpose of this study was to investigate the determinant for

infant mortality. This study might be beneficial platform for the demographer, policy makers and

other students of the field to extend their research.

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1.2 Research Question:As it is mentioned above that the purpose of this paper is to find out the impact of socio

economic variables in determinants of infant mortality in rural areas of Punjab Pakistan. Under

five mortality rate is 94 per 1000 whereas infant mortality rate is 78 per 1000 in Pakistan. The

author is interested to analysis the determinants of infant mortality as most of the deaths in under

five belongs to the infant deaths.

Have a look on previous research and with the help of Mosley and Chen model a theoretical

model has established which provide a strong back up for analysis.

The following research questions are

What are the important determinants of infant mortality in Rural area of Punjab Pakistan?

Does Mother’s Education has significant role in infant mortality?

Which socioeconomic and demography variables having strong impact on infant

mortality?

With the help of statistic analysis these research question can be figure out and also point out the

determinants of infant mortality. These results can also be used for further studies on infant and

child mortality in Pakistan and other developing countries in South Asia.

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1.3 Thesis Plan

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Previous Research Background Theory

Methodology

Empirical Analysis

Results

Disscussion

Conclusion

Introduction

Research Questions

Theoretical Frame Work

Chapter No 2

Theoretical Background

2.1 Previous Research:Infant mortality is consider as an important measurement of population health. It is also the best

source for evaluation of the health programs and policies and very high in Pakistan. A lot of

research has been done to find out socioeconomic determinants in child mortality in different

countries but very few literatures were found in case of Pakistan and India. A very few studies

have done this before but these studies do not represent the demography and health survey data

at national level (Agha, 2000). In previous year I was found the demographic and socio-

economic determinants of infant mortality in Pakistan and now this study is an analysis of

demographic and socio-economic variables in determinant of infant mortality in Rural areas of

Punjab in Pakistan.

A lot of studies which was done before claimed that infant mortality is very much associated

with the socioeconomic and demography variables. So in this study all the socioeconomic

variables are examined through background and proximate variables

2.2 Theoretical Framework:

2.2.1 Mother’s Education:

Major women population of Pakistan is uneducated and most of them belong to the rural areas.

Infant and child mortality was found high in these rural areas and educated mothers brings a

large decline in child mortality as compared to the low level of mother’s education or uneducated

mother’s. Hence there exist a negative relationship between female education and child mortality

as educational brings positive attitude towards better health care (Ali S.M, 2001).

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Education play an important role in determinant of infant and child mortality. A large proportion

of female population is uneducated in Pakistan so uneducated mothers are also one of the main

reason of high child mortality. In rural areas of Pakistan it is believed that female should be

married at early age and also forbidden to discuss pregnancy complications. Whereas education

makes women more sensible to take care of their child and themselves as well Cochrane, 1980).

Alam found the strong negative association between mother’s education and infant mortality as

compare to the father’s education (Alam and Cleland, 1984).

Mother’s age at birth has a negative connection with the infant and child mortality. High child

mortality has found especially in teenage mothers because of less education, early pregnancies

and physically unable of child birth. So there should be awareness programs for mothers to

discourage the early age marriage and frequently pregnancy (Johansson, 2004).

In theory infant mortality is affected by education of mother. Very less attention has been

delivered to the fact that the educational status of the other women in the community might be of

significance. Social learning, direct mechanisms and social influence are the three factors that

might be relevant. When information and outlook are directly received from others in the

community through interaction and observation is referred as social learning. On the other hand

social influence is when a more submissive or reflexive behavior is shown to get approved

among people. Indirect mechanisms is referred when a society and its institutions are influenced

by others behavior, ideas and resources (Kravdal, n.d).

In 1996 the World Bank did an investigation that led to the result that child mortality among

families with non educational background is much higher. Here education is specifically defined

in terms of mother’s education. House and the commune traits also affect the child mortality.

House traits include individualistic characteristics of parents, their education, income and

livestock etc (World bank 1996).

Zerai (1996) in case of Zimbabwe analyzed various socio economic and other demographic

variables through a multi-level analytic construction. He studied socio economic variables and

determinants of child mortality through Cox regression analysis in case of 1988 Zimbabwe DHS

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data. One of the exclusive things he came up with was the more assertive influence of the

women’s education on child survival as compared to educational level of the mother alone. Thus

proving there is a unique roll of mass education on the life of the child and his survival.

2.2.2 Poverty and Socioeconomic variables on infant mortality:

Due to various exogenous and endogenous reasons child mortality tends to vary among

populations and different groups among populations. Among the rural areas or country side of

Pakistan there prevails a low standard of living. There is a huge issue of poor housing with

insufficient ventilation and over crowdedness. Moreover these houses often have their living on

animal stock so there are domestic animals like cattle as well in the houses. This leads to some

common respiratory disease among children. A society is affected in many ways due to a low

living standard. Various respiratory diseases, malnutrition, neonatal tetanus, malaria and

diarrheal illness are some common reasons for infant mortality. According to a survey almost

200,000 children die of diarrheal illness every year. The ratio of infant mortality varies from

other provinces of the country due to different biological, regional, socio economic and

demographic factors. Various endogenous factors include sex of child, sex preference for the

child, age of the mother at the time of birth and marriage and her health as well, breast feeding,

babies’ weight at birth, birth interval and use of contraceptives. On the other hand among

exogenous factors housing, region, education of parents, birth place, religiosity, livestock,

income, occupation, housing facilities especially toilet and water facility ( UNICEF, 2002).

High infant and child mortality are found in those families living below the poverty line. Ali in

his article found different infant and child mortality rates in different wealth status. As

socioeconomic status has also an important explanation of child mortality. Quality of clean

healthy drinking water and sanitation facility are consider a significant variables in

socioeconomic status as these variables have significantly associated with the child mortality. In

Pakistan a lot of diseases are born from unhealthy drinking water. If the availability of healthy

drinking water is provided then the life expectation will increase by two years (Ali, 2001).

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Different opportunities of the availability of basic health facilities like healthy drinking water,

sanitation and nutrition positively affect with child mortality. Political instability, poor

management and political powers in the region are the major causes of regional economic growth

so the regional discrimination also has an impact on child mortality. Child mortality is also

higher in those households living two or more per room (Cochrane, 1980).

2.2.3 Fertility and infant mortality:

Fertility and mortality are closely related to each other and considered the most interesting area

of demographic researchers. Population researchers are of the view that child mortality can play

an vital role in determine the fertility rate with the help of biological variables as child survivors

would increase the birth interval and provide better opportunity of lactation (T.P Schultz, 1972).

Fertility preferences in Asian countries also depend on the children composition. Pakistani

couple have desired of both gender male and female children but female child was found less

preference than male child and this is why male child has entertained a better take care, good

health and better nutrition facility. Around 65% of women in Pakistan are willing to have no

more children after three male children (Alauddin.et.al, 1976).

2.2.4 Diseases and infant mortality:

Some of the common reasons of infant mortality stated by WHO in 2009 are malaria, measles,

diarrhea, pneumonia and malnutrition. Every of these mentioned diseases are associated with the

socio economic circumstances of the child. Moreover it was added that if all the five killing

diseases are to be eradicated, poverty has to be lessen, less overcrowding, a significant rise in

health and education, a firm grip over population and reduction in malnutrition. Further mention

was the management of these ailments necessitates healthy breastfeeding, high quality sanitation,

clean water and time to time vaccinations. In developing countries diarrhea is major reason of

death following to it is pneumonia. According to a research in 2009 diarrhea seemed to have

caused near 1.5 million casualties in people less than 5 years of age and 1.1 million in people of

age 5 year or more. An average 4 to 5 million babies are born in Pakistan every year. Diarrhea is

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more common in under developed countries for the reasons of poor sanitation system and bad

hygiene. Most recent figures have revealed that and estimated 2.5 billion in world have low

quality sanitation and round about a billion of have no availability of safe and clean water. Such

unhygienic and unsanitary conditions facilitate the production and spread of diarrhea causing

germs. It is not sufficient to improve the sanitation alone because the child is still vulnerable to

disease and require a sufficient and satisfactory health care system as well. Facts have revealed

that children with a poor family background and low income are more prone to catch diarrhea

that prevails or comes repeatedly to them. This prolonged or repeated diarrhea acts as catalyst in

the condition where malnutrition and poor health are already on the go, thus creating death cycle

(WHO, 2009).

Upgrading in the sanitation to make water clean and safe parallel to betterment of hygiene

conditions can be useful in the prevention of diarrhea in children. As facts show that 88 percent

of the casualties caused by diarrhea are solely due to unsafe water, bad hygiene and insufficient

sanitation.

2.2.5 Biological Variables and infant mortality:

Beside these socioeconomic variables some biological factors also play an important role in

determinant of infant and child mortality. In Pakistan preventable diseases and misconception

about vaccinations are the challenges in child survival. The main diseases cause death between

children are measles, diarrhea, malaria, pneumonia, which can be prevented with the help of

proper hygiene, good sanitation conditions, nutrition and availability of medical health centers

38% of rural areas in Pakistan has not the access of sanitation facility and this increase rapidly

infection diseases. In rural district of Pakistan a lot of families have no idea about the benefits of

vaccination so they do not pay much attention to the cure and preventive checks.

Most of the demographers and their research show that the child mortality can be reduced up to

five million children per year with the help of antibiotics, nutrition supplements, breastfeeding

practice and better healthcare practice (WHO, 2006).

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Biological variables have also a strong impact in determinant of child mortality. Birth interval

has a negative relationship with the child mortality. If the birth interval has increased the

probability of child survival has increased. In Pakistan the probability of a child survives is two

times greater than the child having birth interval less than 4 years (PDHS, 06-07). Birth weight

has increased the probability of child death. A child with average birth size has 68% lower risk

of mortality than low birth weight. Lactation or failure of breast feeding is also attributed to the

child’s death. Mothers are failed to feed up their children with short birth interval or sibling

competition (Das Gupta, 1990).

Countries that are still under development like Pakistan have a very common tradition among

people to approach conventional practitioners for treatment. It is one of the main reasons for a

poor health of mother and child. This leads to a higher ratio of infant mortality and morbidity. A

research shows that that almost 47.5 percent of the women go to conventional birth attendants for

their delivery. On the other hand a much lesser ratio of women i.e. 35 percent went to doctors for

their delivery. The only possible way to get to a better quality of health status in Pakistan is to

have an easy and cheap access to high quality and modern health seeking systems. According to

the population report released by world fertility survey in the year 1985 out of 29 countries 19

showed that child mortality was higher in babies born fourth or later. And 25 out of 29 countries

showed higher mortality rate for children who were born in seventh or later (Akhtar et al,. 2005).

2.3 Infant Mortality in Rural Punjab (Pakistan)

Almost 70 percent of the Pakistani population is living in rural areas, therefore majority of the

child births are carried out there (Rashida 2000). In the very beginning of their life they are

associated with many disadvantages due to the overall condition of our villages. They easily get

victims to unhygienic conditions and malnutrition. In the northern region of country iodine

deficiency is quiet common. With the nourishment of child the nutrition of mother is equally

important. Under nourishment of the mother is the reason for high rate of low birth weight babies

i.e. 25 percent. Moreover, anemia, iron deficiency are the prevailing problems among child

bearing women.

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Frequent and short birth intervals are highly associated with high child mortality. Short birth

intervals are associated with child malnourishment. Breastfeed contains a lot of vitamins that a

child necessary need for survive and growth, which women cannot provide with short birth

interval.

Having recognizing this universal truth, human societies have thriving to reduce or postpone

death since the beginning. Countries that are developed have been very successful in achieving

this goal. On the other hand countries that are still on their way or are under developed have not

succeeded in reducing infant mortality rate. At the present the child mortality rate of Pakistan is

towering where every 11th child born alive dies before seeing the light of his very first day

(Cleland and Farooqui, 1998). Pakistan and all other under developed countries are trying their

level best for the reduction child mortality and mothers in the stages of pre natal and post natal.

Major causes of a high death rate in mothers are the increasing level of still birth and also the

trend of mentally and physically handicapped births. Moreover, scarcity of quality health

facilities and incapability to use these facilities even if available, repeated pregnancies, financial

inadequacies, bad environment and low level of nutrition are also responsible. Parallel to this the

old traditions of the country have also kept the people held back to get benefited from the

contemporary health care facilities. In the rural areas people are still not willing to get benefited

from modern hospitals and health care system. For these reasons both the mother and child are

severely affected and have high risk of catching disabilities and diseases. These issues have been

the cause for which the rural areas of Pakistan are now a serious challenge for all the

sociologists, planners, administrators and politicians as well who are trying to come up with the

solution for all these health issues specially combating the high rate of infant mortality (Akhtar et

al., 2005). As mentioned by UNICEF that every one of 10 children in Pakistan do not see the

light of their first day. These mortality rates differentiate greatly from class to class and region to

region in urban areas. However in poor families this rate is about 230 of 1000 children. Thus

rural areas or country side has high mortality rate than urban (UNICEF, 1992).

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Child mortality rate in under developing countries remains much high as compared to a notable

decline in the developed nations. World’s children state held that nearly 12.9 million children are

dying every year in the developing nations. The major reasons for the infant mortality are

respiratory diseases, measles, diarrhea, mal aria. In Nigeria there are many casualties among

children due to neonatal tetanus, tuberculosis, diarrhea, and bronchopneumonia. Socio economic

and biological factors are influencing the child mortality and morbidity. Bad hygiene of cooking

utensils and feeding bottles, unsafe and insufficient removal of house waste and poor quality of

water storage are the main reasons for diarrhea. Many still hold maternal education to b a vital

factor in the survival of child. In conventional Yoruba the virus attack of measles is associated

with many cultural beliefs that have no. Normally it is deemed that one has measles for the

reason of breaking the family taboos and norm. Moreover, it is considered an evil trait of

witches. For the reason that measles is related to witches in many backward families it is

believed that it has been done by the enemy and co- wives are always the suspects. On the other

hand diarrhea is considered as something which gets the bodily impurities (Ogunjuyigbe, 2004).

The opposite connection between the socioeconomic factors of the parents, children and the

infant mortality rate is recognized by various researches and is considered authentic regardless of

the mortality rate of any national population in totality. Studies have shown that there is

significant impact of parental education on a child’s mortality and health. The profession and

education of the father and mother both effect the child survival in independent ways especially

in developing countries. Moreover the economic structure of any family or household proves out

to b a significant factor in elucidating the disparity in infant mortality. Economic conditions or

structure of any household of include various aspects of daily life such as access to pure diet,

clean water, medical facilities and trust worthy sanitary system. This contrast with the families

with a poor economic structure residing in densely populated areas with a poor water supply;

unhealthy sanitation, and housing facility with sheer hygiene problem thus more prone to get

infectious diseases. Various maternal factors also have a significant impact on a child birth and

its survival such as: birth interval, age of the mother while bearing a child, birth order etc. Babies

born to mother who have already had a child loss are at a higher risk of dying at some stage in

their infancy. Sex of the child also affects the infant and child mortality. For a newly born baby

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breastfeeding has some social, economic and bio demographic effects. Breastfeeding affects the

child and the mother both in health and nutritional aspects. It also has huge effect on the child in

post neonatal time. Curative and preventive measures are included in the health seeking

behavior. Vaccinations against diseases like tuberculosis, tetanus, measles, polio, small pox etc

are included in preventive measures. On the other hand curative measures comprise on carious

modern and conventional methods of treatment and care that are undertaken in explicit

conditions (Mahmood 2002).

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Chapter No :3

Theoretical Model

The main aspect of quantitative approach is to integrate the medical and social science and the

main objective of quantitative approach is to formulate hypothesis, build theoretical model, apply

statistical tools having some results and made conclusions. This approach is good for

socioeconomic research which provides bases for the researchers and demographers for social

development. This approach usually applied in education and social science field. In this study

the explanatory variables represents the socioeconomic, demography and biological variables

which are examined as this is the main aspect of this approach.

3.1 Mosley and Chen Frame Work

In the beginning of 1980’s there was a period of great cheerfulness about the child endurance in

countries with high mortality. A lot of research was being carried in that time. The phenomena of

primary health care defined in terms of essential health care, methods that were scientifically

sound and socially and morally accepted were made available to people at an affordable cost.

This all was sanctioned by Declaration of Alma-Ata in September 1978. Another research

brought it up that some of the countries with a low income have also been able to succeed in

getting low child mortality. With the help of these huge vaccination campaigns and new

technologies it was made possible to avoid infectious diseases in children. Malaria and diarrheal

illness could now be treated and prevented at a lower cost. Many international aid agencies

strived for providing cheap and effective inventions for the reduction of child mortality and

developing countries (Menken, 1987).

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To analyze child mortality from various point of views, there is a wide range of determinants in

the literature that somehow directly or indirectly affect the child mortality. Scholars have mostly

focused demographic, socio economic and biological factors in their research and viewpoints.

Firstly the debate was whether to what extent socio economic factors and technological

advancements have been able to improve child health and lessen the mortality rate in developing

countries, in midst of 20th century. Then it was analyzed that the mortality rate is decreased due

to the transference of medical advancement and knowledge which is not a part of socio economic

(Preston, 1975). Another research later brought up a different insight and focused on the socio

economic factors for e.g. mother’s education in case of child survival (Caldwell 1983).

Later in 1984 Henry Mosley and Lincoln Chen in their article disused that the researches carried

out in order to determine the cost effective use of health sector have weighed down because of a

poor conceptual model especially in case child survival and health. They found a considerable

inequality and disproportion between the social sciences research that mainly stressed on the

impact of socio economic and cultural factors in infant mortality and on the other had the

medical researches that solely focused on various diseases and held morbidity as the reason of

child death. The sole purpose of their research was to come up with a logical method that would

put together both the research methods and will lead to a single determinant that merged

morbidity and mortality both. The sole concept of their model was that all the socio economic

and cultural reasons act in an adjoining way which directly affects the menace of various

diseases and their outcomes.

There is an assumption in the analytical construction that endogenous and exogenous factors

both affect the health status of the child. Here socio economic factors are linked to the exogenous

factors and biomedical is related to the endogenous factors. The exogenous factors that are the

socio economic indirectly affect the child mortality as they function from the bio medical aspects

(Schultz, 1984).

The analytical constructions of both Mosley and Chen are similar to Davis and Blake. In the

frameworks cultural, socio economic and health variables impact on a thrifty but comprehensive

set of determinants which finally give a single variable. The researchers have identified five

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categories that comprise upon 14 proximate determinants: environmental pollution

(water/food/air/fingers/skin/inanimate objects/insect vectors/soil), maternal factors (birth

interval/age), nutrient deficiency (protein/calories/micronutrients), personal illness control

(medical treatment/personal preventive precautions) and injury (accidental, intentional). In above

mentioned groups four of them mention factors due to which children move from healthy to sick

and one of the groups mentions and impacts the rate through preventive measures and treatment.

This is a very comprehensive list of determinants because the child health will only change if one

of the determinants changes.

Thus this framework provides a conceptual model to all the researchers regardless they are

epidemiologists or social scientist working on the issue of infant mortality. After Mosley Chen a

number statistical ways have known to be more common: investigation of relation between

proximate determinants and background reasons for e.g. the investigation of reasons related to

the immunization of child; framework which include an ending capricious, mortality in general

with the background factors and proximate determinants both. This works in step by step way

first counting on the background factors and then including the proximate determinants.

There are various levels of socio economic determinants that explain how they exactly influence

child mortality.

a. Individual level

b. Household level

c. Community level

The variables at individual level mainly deal with the factors of individual productivity normally

known as health, time and skill. Educational level of mother and father of the child determine the

skill. In the urban cities education explains the relationship with household income and

occupation. Education of the father is a significant determinant of income and assets. There are

many examples in which father’s income and education show a relationship with health issues of

the child. This is due to the effect on the proximate determinants from income. Moreover father’s

education additionally affects the health of the child in case of the choice of the health facilities

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being provided to the child. In case of mothers situation is quiet varying as it lays more affect on

direct effect on the child’s health. Mother’s education has not that much correlation with assets

and the income of the family as it does in case of the other parent. This is because of the

biological relation between the child and mother as the in the time of pregnancy and

breastfeeding, nutritional and health status of the mother directly impacts child’s health. When

the mother is well educated she has good information about hygiene, nutrition, preventive

measures and other health related concerns. To give birth to healthy child and the sustain its

health also requires the some extra health care measures from the mother for e.g. keeping the

child in good hygiene, off and on visits to the clinics and feeding the child on healthy food.

Societies in which there is clear difference between the labors among the sexes a mother tend to

have more time foe the child. On the other hand modern societies where a mother is mostly busy

in earning income for the family her time for child care is automatically reduced. The economic

condition of the family is a determinant of the mother’s work. If the family is poor the mother

has to work that leads to neglecting of child on the other hand families with a high income or

rich families have mothers at home and can also hire a mistress for the child (Mosley and Chen,

1984).

In house level the variables are illustrated in terms of clean supply of water and food, clothing

and housing all lays an impact on the child’s health. Moreover the quality and the area of the

house is important as well. Houses that have poor ventilation system and are over populated lay a

bad impact on the health status of the child. According to Mosley and Chen Children who live in

houses with these facilities are less prone to dying. Anna. It is the proximate determinants

through which the quality of services and goods is operated at house hold level. Accessibility to

fresh food also influences the child health. Food with a high quality is more resistant to diseases.

Lack of hygiene, poor quality water and overcrowded housing are the major reasons of

environmental pollution. Food infection is caused because of the poor housing. It is mainly due

to the low quality storage system and poor sanitation. Poor quality of water also augments the

bacteria (Mosley and Chen, 1984).

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Last group of the socio economic factors discussed in the construction is community level.

Biological, social and political settings in which the child survives establish his health results.

Ecological or biological settings lay impact on the availability of income for the parents for e.g.

soil, rainfall, climate etc. Stability of political institutions and their quality are included in

political settings. Telephone, water supply, electricity also affect prices the prices of goods that

indirectly affects the health outcomes. These differences also exist at regional level in different

population of various countries. There are various cultural differences that exist in various

regions of Pakistan. In south Asian culture male children are considered more valuable for the

family therefore are given preferred and better health and nutritional facility (Das Gupta, 1987).

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Chapter No 4

Empirical Model:

4.1 Statistical Model:

In this analysis, independent variable is binary in nature as it represents the infant is survive or

die. To get good results logistic regression is the best option for this analysis which forecast the

probability of dependent variables reaction.

Logit (P) = b0 + b1X1 + b2X2 + b3X3 + ....bnXn

In this model dependent variables consists of socio economic variables like infant gender,

mother’s education, wealth status, working status, father’s education, drinking water supply,

sanitation facility.

In this study there are two models

Infant Mortality = b0 + b1(Infant gender) + b2(Mother’s education) + b3(Mother’s employment

status) + B4(Wealth status) + B5(Father’s education) + B6(Drinking water supply) + B7

(Sanitation facility)

And the other model is

Infant Mortality = b0 + b1(Mother’s age at marriage) + b2(Mother’s age at birth) + b3(Birth order)

+ B4(Birth interval) + B5(Number of siblings)

If the regression coefficient are positive this means that it will increase the chances of outcome in

the same way if the regression coefficient are negative this mean that it will decrease the chances

of outcome. The author used STATA software to apply logistic regression and it calculate odds

ratio directly which is explained as the change in odd ratio for 1 unit change in independent

variables.

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4.2 Application:

The objective of this study is to measure the child mortality in rural urban area of Punjab in

Pakistan. For this logistic regression is applied on the micro data which is based on the

Demography and Health survey 2006-07.

Frequency Numeric Label

5837 1 = Urban

10466 2 = Rural

4.3 Data source:

In order to analysis the determinants of infant mortality in rural areas of Punjab, data taken from

Measured Demography and Health Survey (DHS) in 2006-07. The nationally representative

household data based on the public health issues and socioeconomic and demographic

information. DHS usually having more than 5000 samples and conducted after 5 years.

Demography and Health surveys are conducted by mix tools of survey i.e. questionnaires,

biomarkers and graphical information. Questionnaires in DHS are of three types like household

questionnaire, men’s questionnaire, women questionnaire. In the questionnaires of DHS topics

like diseases, Family planning, HIV, information about ill family members and their health are

discussed and translate this questionnaires from English to the local. In household questionnaires

is to get information about household members and socio economic status of household. In the

women’s questionnaires to get information about women aged 15 to 49 in which mostly

questions are about women’s education, working status and the maternal characteristics like

marriage, knowledge about family planning, reproductive status, infants nutrition, breast feeding

and fertility preference. In men’s questionnaire mostly question are about socio economic

variables like wealth status and level of education. In this analysis dataset are mostly taken from

the women’s questionnaires.

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Pakistan Demography and Health Survey is the largest survey with the sample of 95,441

households. PDHS collect these samples from all over the country. There are 39,049 samples of

women birth distribution between the ages of 15- 49 in which 16,303 are from the Punjab and

10466 of them belongs to the rural areas of Punjab. This survey was conduct by National

Institute of Population Studies (NIPS) with support of United States Agency International

Development (USAID) and technical support provided by the Measure Demography health

Survey Program.

World Health Organization (WHO) was examined DHS data set which resulted in

underestimation. Infant mortality rates are always lower in DHS dataset as compared to the

UNICEF dataset and this was because of non proper reported of children deaths and births.

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4.4 Variables4.4.1 Mother’s Education

Mother’s education is an important variable to determine the child mortality and fertility. If the

mother is educated then she is well known about the hygienic condition of the food and health

conditions of child. She also takes their children regular to the hospital for check up in order to

provide better health care as it is a necessary factor to control the child mortality. So with the

help of education between mothers we can reduce the child mortality. The variable can be

classified into further categories.

1. No education

2. Primary education

3. Secondary education

4. Higher education

4.4.2 Social Economic Status

Social economic status or wealth status is considered as an important variable in the study of

infant and child mortality. Poverty not only affects the child mortality directly but also indirectly.

The population of Punjab has different access to the health facilities so this variable has divided

into further categories.

1. Poorest wealth status

2. Poor wealth status

3. Middle wealth status

4. Rich wealth status

5. Richest wealth status

4.4.3 Woman Working Status

In this study we used women working status as dichotomous variable that consist of the value of

working and not working. Environment and work’s nature has a large influence on child

mortality. According to the Hobcraft women working status has a positive effects on the child

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mortality as if the woman is working as a result she has increase her standard of living and

provide better health and education to their children (Hobcraft et al, 1984). In Pakistan there is a

lot of risk of dying children under the age of 5 if their mothers are working. They have not

provide better health facilities to their children while when they are not at home and one thing

more working women always remain in stress (Ali, 2001). So this variable has divided into

further different categories.

1. Employed

2. Unemployed

4.4.4 Father’s Education

Education has itself very positive investment of a country. If the population of a country are

educated then hygienic level is also very high, people have much more knowledge about the

prevention of diseases (Das Gupta, 1990). Not only hygienic conditions are found better in the educated

household but also education help to increase income. There is a positive attitude of educated household

towards the health and nutrition status. This variable is divided into further categories.

1. No education

2. Primary education

3. Secondary education

4. Higher education

4.4.5 Drinking Water Supply

Drinking water supply means from where the water is coming for use, the facilities and

treatments to make it clean and be able to drink. Punjab have major different in drinking water

supply as in urban Punjab water coming from tap are mostly used whereas major parts of rural

areas are used water coming from tube well. This variable is divided into further categories.

1. Water Tap

2. Water tube well

3. Water pump

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4. Water surface

5. Water Unknown

4.4.6 Sanitation Facility

Sanitation facility means sewerage system, separate toilet facility and disposal of wastage in the

house. This variable is very important in this study as in Pakistan as there is no toilet facility in 3

out of 10 houses (PDHS, 2006-07). This variable directly affects infant health as if there is no

toilet facility and no proper disposal of wastage hence environment become polluted and risk of

diseases increased. This variable is divided into further categories.

1. Good Toilet Facility

2. Flush Toilet Facility

3. Pit Toilet Facility

4. No Toilet Facility

4.4.7 Mother’s age at Marriage

In Pakistan like religion country marriages are treated as the social and religious compulsion.

There is also a trend of female marriages at early ages. In Punjab there is an average difference

of 6 years between educated married women and uneducated married women. This variable is

divided into three categories.

1. 01 to 14 (years)

2. 15 to 17 (years)

3. 18 to 20 (years)

4. 21 to 23 (years)

5. 24 or more (years)

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4.4.8 Mother’s age at Birth

In Pakistan it is a trend of female marriage and first birth at early age. Female age at first birth

affects the child mortality a lot. Births at early ages not only increase child mortality but also

maternal mortality so this variable is divided into further categories.

1. 01 to 15 (years)

2. 16 to 19 (years)

3. 20 to 23 (years)

4. 24 or more (years)

4.4.9 Birth Order

Birth order is one of the important variables in determinant of child mortality. First and last birth

has a high mortality rates as compare to the child born among them. At early ages at the first

birth of a mother, it is difficult to manage and in the last birth women are not physical fit. So this

variable is divided into further three categories.

1. First birth

2. 2 to 4

3. 5 to 7

4. 8 or more

4.4.10 Birth Interval

Birth interval is also a critical variable to determine infant mortality. Infants have higher chances

of mortality if there is no birth interval as well as high birth interval. So this variable is divided

into further four categories.

1. Less than 1

2. 1 to 3

3. 4 to 6

4. 7 to 9

5. 10 or more

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4.4.11 Number of Siblings

The average number of person living a house is 7 persons. If the number of brothers and sisters

increases then the household faces a lot of problem about feeding them and to provide better

health care opportunity. It will also lead to the unhygienic conditions so as the number of sibling

increasing child mortality also increases.

1. No sibling

2. 1 to 4 children

3. 5 to 7 children

4. 8 or more children

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Chapter No 5

Statistical Tool

5.1 Logistic Regression Analysis :

In social science research analysis many time researchers have to predict against dichotomous

outcomes and in the past these question were answered by ordinary least square. But this

technique were found less effective in dichotomous outcomes due to the assumptions of ordinary

least square regression i.e. linearity, equal variance and normality. Logistic regression was

introduced between 1960 and 1970 to solve the problem with dichotomous outcomes. It is

specially introduce for the research questions in social sciences. Reference book ka

Logistic regression analysis applied in the techniques of those researches in multiple regressions

analysis in which the variables are in categorical outcomes. These categorical outcomes are very

common in practical life like success/failure or Yes/No. These outcomes are also known as the

dichotomous variables. The focus of this study is on the socioeconomic variables and mostly

outcomes of these variables are in categories.

In the study of child mortality in Punjab this technique is used for statistical method as this

analysis is observed most of the time in socioeconomic studies. In logistic regression it has the

same answer whether the dependent variables are discrete or dichotomous. There is no more

required the assumptions of ordinary least square in logistic regression and even this method is

useful when dependent variable is likely to be nonlinear with the independent variables ( David

and Stanley, 2000)

The aim of using logistic regression is to properly calculate outcomes with the help of a model.

So to achieve the best results, a model is formed in which all the independent variables include

that make a sense, useful and helpful for the prediction of the dependent variable. There are two

types of strategies to build a regression model (Logistic regression).

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In Stepwise regression variables are entered in the model according to the order define by the

researchers. Logistic regression test the goodness of model after the variables is deleted or added.

One thing is more to explain here that stepwise regression is often used in the exploratory

research. The aim of the exploratory research is to explore the new relationship and required no

priori assumptions between variables.

In Backward logistic regression indicates that the testing of the previous theories and testing the

hypothesis which explain the previous relationship between variables. If the model begins with

full and all the explanatory variables then backward logistic regression are always preferred and

then the variables are eliminated even the model is fit for the data analysis (Logistic Regression

2002).

When the outcomes of independent variables are binary or dichotomous logistic regression

model use the probability of response.

g(x) = β0 + β 1X1 + β 2X2 + β 3X3..... + β pXp

Where

g(x) = Logit (log odds) of dependent variable

b0 = intercept term

There are p independent variables.

The logistic regression coefficients β0, β1, β2……. Βp are called parameter estimates

Suppose there are p independent variables and the conditional probability of the outcome occur

is denoted by

π( x ) = P(Y =1|x)

So the logistic model is

π( x ) = eg(x) /(1+eg(x))

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5.2 Dummy Variables:

Dummy variables are the numerical value usually used in regression to analysis the subgroup in

the study. In the research of social sciences dummy variables are usually used to treat different

groups and they are normally assigned the 0 and 1 values. 0 represents that this is in the manage

group and 1 represents that this is in the treated group. Dummy variables represent the multiple

subgroups in a single regression equation and Researchers have no need to write different

regression equation of the same model.

In the study of determinants of Infant mortality in rural urban area of Punjab the dependent

variable classified as there is a infant mortality and independent variables are classified into

different categories to dummy variables.

Y = 1 ,Yes0 , No

Table 5 (a) : Distribution of Socioeconomic and Demographic Dummy variables

Dummy Variables of Independent (socioeconomic and demography) variables are explained into

the following table.

Socio- Economic Variables

Mother's Education No of values

No education No education (1) 8112 Others (0) 2354 Primary education Primary education (1) 1521 Others (0) 8945 Secondary education Secondary education (1) 682 Others (0) 9784

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Higher education Higher education (1) 151 Others (0) 10315Working Status Employed Employed (1) 3522 Un Employed Un Employed (1) 6944Wealth Index Poorest Poorest (1) 2538 Others (0) 7928 Poor Poor (1) 2441 Others (0) 8025 Middle Middle (1) 2689 Others (0) 7777 Rich Rich (1) 1764 Others (0) 8702 Richest Richest (1) 2510 Others (0) 7956Father’s education (years) No education No education (1) 4606 Others (0) 5860 Primary education Primary education (1) 1914 Others (0) 8552 Secondary education Secondary education (1) 5119 Others (0) 5347 Higher education Higher education (1) 2080 Others (0) 8386Drinking Water Supply Facility Water Tap Water Tap (1) 2169 Others (0) 8297 Water Tube well Water Tube well (1) 7472 Others (0) 2994 Water Pump Water pump (1) 107 Others (0) 10359 Water Surface Water Surface (1) 322 Others (0) 10144 Water Unknown Water Unknown (1) 390 Others (0) 10076Sanitation Facility

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Good Toilet Good Toilet (1) 898 Others (0) 9568

Flush Toilet systemFlush ToiletSystem (1) 5009

Others (0) 5457 Pit Toilet Pit Toilet (1) 263 Others (0) 10203 No Toilet No Toilet (1) 3990 Others (0) 6476

Demographic Variables Mother's Age at Marriage

No of Values

Less than 15 Less than 15 (1) 1919 Others (0) 8547 15 to 17 15 to 17 (1) 3669 Others (0) 6797 18 to 20 18 to 20 (1) 2828 Others (0) 7638 21 to 23 21 to 23 (1) 1213 Others (0) 9253 24 or more 24 or more (1) 837 Others (0) 9629 Mother's Age at Birth Less than 16 Less than 16 (1) 1023 Others (0) 9443 16 to 19 16 to 19 (1) 4162 Others (0) 6304 20 to 23 20 to 23 (1) 3548 Others (0) 6918 24 or more 24 or more (1) 1733 Others (0) 8733Birth Order First Child First Child (1) 2334 Others (0) 8132 2 to4 2 to4 (1) 5107 Others (0) 5359 5 to 7 5 to 7 (1) 2345

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Others (0) 8121 8 or more 8 or more (1) 680 Others (0) 9786Birth Interval Less than 1 Less than 1 (1) 1828 Others (0) 8638 1 to 3 1 to 3 (1) 2785 Others (0) 7681 4 to 6 4 to 6 (1) 2034 Others (0) 8432 7 to 9 7 to 9 (1) 1687 Others (0) 8779 10 or more 10 or more (1) 2132 Others (0) 8334Number of siblings No sibling No sibling (1) 310 Others (0) 10156 1 to 4 1 to 4 (1) 2847 Others (0) 7619 5 to 7 5 to 7 (1) 4466 Others (0) 6000 8 or more 8 or more (1) 2843 Others (0) 7623

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Chapter No 6

Results:

Table 6(a) : Percentage Distribution of Infant deaths in Rural urban of Punjab (Pakistan)

Infant death Rural Urban

Child death during the first 12 months 1234 (11.80) 553 (09.45)

Child survive during the first 12 months 9232 (88.20) 5284 (90.55)

Total 10466 5837

………………………………………………………………………………………………………………………………………………………………….

The percentage of infant deaths in rural area is greater than the percentage infant deaths in urban areas. This shows the public health status in rural areas is not good.

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Table 6(b) : Percentage distribution of population by socioeconomic and Demographic Variables in Rural Urban Punjab (Pakistan)

Rural Area Urban Area(Population distribution) (Population distribution) (n= 10466) (n= 5837)

Sex of ChildMale 52.3 51.8Female 47.7 48.2

Mother's education (years)No education 77.5 48.8Primary education 14.5 17.3Secondary education 6.6 23.5Higher education 1.4 10.4

Working StatusEmployed 33.7 73.9Un-employed 66.3 26.1

Wealth IndexPoorest 24.2 3.6Poor 23.3 5.9Middle 25.6 17.0Rich 18.9 30.2Richest 7.0 43.3

Father’s education (years)No education 44.0 27.09Primary education 18.2 15.71Secondary education 31.0 38.53Higher education 6.8 18.67

Drinking Water Supply FacilityWater Tap 20.7 42.3Water tube well 71.3 39.5Water pump 1.1 8.7Water surface 3.1 5.7Water Unknown 3.8 3.8

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Sanitation FacilityGood toilet 8.6 6.2Flush toilet system 47.8 85.2Pit toilet 2.7 5.6No toilet 38.1 4.4Unknown toilet 2.8 3.6

Mother's Age at Marriage1 to 14 18.3 14.715 to 17 35.1 31.018 to 20 27.0 28.721 to 23 11.5 15.424 or more 8.1 10.2

Mother's Age at Birth1 to 15 9.7 8.616 to 19 39.7 38.520 to 23 33.9 34.124 or more 16.7 18.8

Birth OrderFirst Child 22.3 24.42 to4 48.7 51.85 to 7 22.4 19.38 or more 6.6 4.5

Birth IntervalLess than 1 17.4 13.91 to 3 26.6 21.14 to 6 19.4 17.87 to 9 16.1 17.910 or more 20.5 29.3

No of siblingNo sibling 2.9 3.01 to 4 27.2 36.55 to 7 42.6 40.88 or more 27.3 19.7

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This table 6(b) shows the considerable difference in independent variables such as Infant gender,

mother’s education, employment status, socio economic status, Father’s education, drinking

water facility and sanitation facility in rural and urban areas of Punjab. Around 52% of births in

rural area of Punjab are male. Urban population of Punjab consists 51.8% of male compared to

52.3% male in rural areas. In rural Punjab 33.6% of women are employed while 66.3% of

women are unemployed. Nearly 73.9% of birth are in employed women whereas 26% of birth

belong to unemployed women in urban areas of Punjab. Women’s working status shows

different trend in rural/urban areas of Punjab.

Births in rural areas are very high in uneducated mothers about 77.5% of rural births occur to

those mothers who had no education whereas 48.8% of birth is in urban mothers with no

education. The following table shows the negative effect of higher education and births. About

10.2% of infant births is in urban areas due to the higher education of women compared to the

1.4% in rural areas. This table shows not only the rural urban differentials but also the literacy

rate of women in rural areas of Punjab.

In rural Punjab 24.2% of births belong to poorest family status and 23.3% of births belong to the

poor family so almost half of the births are belong to the poor families whereas ¾ of total births

in urban area belong to the rich and richest families. This table shows that major portion of births

belong to rich family in urban areas while approximately 50% of births are belong to the poor

family in rural areas of Punjab.

Drinking water supply almost shows the same result in rural and urban areas. Water tap and

water tube well are major source in providing water supply in rural/urban areas of Punjab. More

than 80% of belong to water tap and water tube well. Fathers are more educated than the women

in Punjab. In urban areas of Punjab, 18.67% of births are from higher educated fathers while

there is only 10.27% in higher educated women. Nearly ¼ of births in urban areas are from

uneducated fathers whereas 43.56% of births in rural areas are from uneducated fathers only

9.46% of births occur in rural areas are from the fathers getting high education.

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A larger proportion 85.2 % of births are in urban areas while using flush toilet and it is 47.8% of

births with flush toilet system in urban areas of Punjab in Pakistan. In urban areas the ratio 4.4%

of no toilet facility is very low as compared to the 38.1% in rural areas of Punjab.

In Punjab there is trend to get married at early ages like mostly 18.3% of women married when

they are less than 14 which is very young age and that age female are not mentally fit for

marriage while 35% of female are married at the age between 15 to 17 in rural areas of Punjab.

Percentage marriage between the age 18 to 20 is 27 whereas female marriage at the age of 20 and

more then this age is only 20 percent in rural Punjab.

Mother’s age at birth less than 15 years is 8.6 % in urban areas while it is 10 % in rural areas of

Punjab, which is very high and at that age female are not mentally and physically fit for children.

Most of the births occurred to mother’s age between 16 to 19. Overall mother’s age at birth

having same trend in rural and urban area of Punjab but because of the mother’s are more

educated in urban areas so they prefer to delay their first birth as compared to the rural areas of

Punjab.

The distribution of birth interval in rural urban areas is very much similar trend to each other

only the difference is there frequencies. 17% of births are lies when there is less than 1 birth

interval in rural Punjab and in urban Punjab 29% of births lies when the birth interval is more

than 10 years. Most of the births in rural Punjab is in the birth interval between 1 to 3 whereas

urban area of Punjab when the birth interval is more than 10 years.

The rural areas women have more children than urban women. Rural areas 42% of women

having between 5 to 7 children while in approximately 27% of children fall in more than 8

siblings. The birth distribution of sibling in rural/urban areas is very much similar to each other

and most of the births belongs to the women having 5 to 7 children in rural urban area of Punjab.

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Table 6(c) : Covariance Between Socioeconomic variables

| female~d women_~u workin~s wealth father~u water_~y sanita~y

-------------+---------------------------------------------------------------

female_child | 1.0000

women_edu | -0.0048 1.0000

workingsta~s | 0.0079 -0.1186 1.0000

wealth | -0.0060 0.4314 -0.2182 1.0000

father_edu | 0.0025 0.0212 -0.0352 0.0405 1.0000

water_supply | -0.0024 0.0349 0.0032 -0.0430 0.0019 1.0000

sanitation~y | 0.0113 -0.0893 0.0314 -0.2914 -0.0059 0.6630 1.0000

-------------+---------------------------------------------------------------

Table 6(c) represents the covariance between socioeconomic variables. Too check whether the

socio economic variables are correlated to each other or not covariance is applied on the data and

find that there is covariance between these variables.

Table 6(d) : Covariance Between Demographic variables

| ageatm~e ageatb~h birtho~r birthi~l noofsi~g

-------------+---------------------------------------------

ageatmarri~e | 1.0000

ageatbirth | -0.0005 1.0000

birthorder | 0.0084 -0.1631 1.0000

birthinter~l | 0.0260 -0.1089 0.0387 1.0000

noofsibling | 0.0040 -0.2820 0.5783 0.0670 1.0000

-------------+---------------------------------------------

Table 6(d) represents the covariance between demographic variables. Too check whether the

variables are correlated to each other or not covariance is applied on the data and find that there

is covariance between demography and biological variables.

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Table 6(e) : Results of Socioeconomic Variables in Determinant of Infant Mortality in Rural Areas Punjab (Pakistan) by Logistic regression.

Number of obs = 10466

LR chi2(19) = 151.78

Prob > chi2 = 0.0000

Log likelihood = -3720.4549 Pseudo R2 = 0.0200

------------------------------------------------------------------------------

infant_mor~y | Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

female_child | -.0864988 .0613055 -1.41 0.158 -.2066554 .0336579

d_p_wedu | -.264158 .1011568 -2.61 0.009 -.4624217 -.0658943

d_s_wedu | -.5996909 .178058 -3.37 0.001 -.9486781 -.2507036

d_h_wedu | -.2381441 .3030088 -0.79 0.432 -.8320305 .3557423

workingsta~s | .2374181 .0512643 4.63 0.000 .1369419 .3378943

d_poor_wea~2 | -.0452606 .0858449 -0.53 0.598 -.2135135 .1229922

d_middle_w~3 | -.3260546 .1059761 -3.08 0.002 -.533764 -.1183453

d_rich_wea~4 | -.458169 .1289967 -3.55 0.000 -.7109979 -.2053401

d_richest_~5 | -.4540454 .1746484 -2.60 0.009 -.79635 -.1117407

d_m_p | .0627911 .0850969 0.74 0.461 -.1039957 .2295779

d_m_s | .0787139 .0717484 1.10 0.273 -.0619104 .2193382

d_m_h | -.062699 .1299812 -0.48 0.630 -.3174576 .1920595

water_pump | .0131548 .0822189 0.16 0.873 -.1479914 .1743009

water_well | -.1685731 .341867 -0.49 0.622 -.8386202 .501474

water_surf~_ | -.2038549 .201994 -1.01 0.313 -.5997559 .1920461

water_unkn~n | .4235339 .1602253 2.64 0.008 .1094981 .7375697

pit_toilet | -.2168887 .2087014 -1.04 0.299 -.6259359 .1921585

no_toilet | .0234011 .0892654 0.26 0.793 -.1515559 .1983581

good_toilet | -.4414466 .1371707 -3.22 0.001 -.7102962 -.172597

_cons | -1.739436 .1567183 -11.10 0.000 -2.046599 -1.432274

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Table 6(f) : Analysis of Socioeconomic Variables in Determinant of Infant Mortality in Rural Areas Punjab (Pakistan)

Mother's Education Catagories Odds Ratio P -Value No education 1.000 ------ Primary education -0.264 0.009 Secondary education -0.599 0.001 Higher education -0.238 0.432Working Status Un Employed 1.000 ------ Employed 0.238 0.000Wealth Index Poorest 1.000 ------ Poor -0.045 -0.598 Middle -0.326 0.002 Rich -0.458 0.000 Richest -0.454 0.009Father’s education (years) No education 1.000 ------ Primary education 0.062 0.461 Secondary education 0.078 0.273 Higher education -0.062 0.630Drinking Water Supply Facility Water Tap 1.000 ------ Water tube well -0.168 0.622 Water pump 0.013 0.873 Water surface -0.203 0.313 Water Unknown 0.423 0.008Sanitation Facility Flush toilet system 1.000 ------ Pit toilet -0.216 0.299 No toilet 0.023 0.793 Good toilet -0.441 0.001

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The general cause of infant mortality are malnutrition, measles, diarrhea and pneumonia. These

diseases are very much correlated to the socioeconomic living condition of the children.

Sanitation facility, polluted environments and drinking water supply allow different diseases to

spread and effect infant’s health. In the results of socioeconomic variables on infant mortality the

variable like drinking water coming from unknown source has a significant impact on infant

mortality at 10 % level of significance. The logistic regression coefficient is 0.423 which mean

that it is associated with increasing risk of infant mortality. Sanitation facility also has an impact

on infant mortality as good toilet facility has significant impact on the infant mortality at 5 %

level of significance. Logistic regression coefficient for good toilet facility is -0.441 which mean

that it is significantly associated with decreasing risk of infant mortality.

Infant mortality is associated with the level of mother’s education in rural Punjab. Mother’s

primary, secondary and high education regression coefficient’s represent negative impact on

infant mortality this mean that when mother’s education increased infant mortality decrease. As

primary, secondary and high level of education is associated with the decreasing risk of infant

mortality. Results shows that mother’s primary education is significantly associated with infant

mortality at 10% level of significance whereas mother’s secondary education also significantly

associated with infant mortality at 5% level of significance. Father’s education has not

significantly associated with infant deaths in rural Punjab. Father’s primary and secondary

education has a positive effect on infant deaths whereas only father’s high education has negative

impact on infant mortality but this impact is not significantly associated.

Infant mortality is associated with the women’s working status. Results shows that it was found a

positive correlation between women’s working status and infant deaths. Regression coefficient

0.23 mean that it is significantly associated with increasing risk of infant deaths.

In rural Punjab infant mortality is very low in wealthy families. The results shows that poor

families have a negative impact on infant mortality but this impact is not significant whereas

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families belong to middle wealth status, rich and richest wealth status has a significant negative

impact on infant mortality. Middle and rich wealth status have significant associated with

decreasing risk of infant mortality at 5% level of significance. Richest wealth status has

significantly associated with increasing risk of infant mortality at 10% level of significance.

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Table 6(g) : Results of Demographic Variables in Determinant of Infant Mortality in Rural Areas Punjab (Pakistan) by Logistic regression.

Number of obs = 10466

LR chi2(17) = 246.99

Prob > chi2 = 0.0000

Log likelihood = -3672.8499 Pseudo R2 = 0.0325

------------------------------------------------------------------------------

infant_mor~y | Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

d_15to17_m~e | .0182435 .0871668 0.21 0.834 -.1526003 .1890873

d_18to20_m~e | -.0352992 .0924211 -0.38 0.703 -.2164412 .1458427

d_21to23_m~e | -.121404 .1169173 -1.04 0.299 -.3505578 .1077497

d_24ormore~r | -.0618639 .1308426 -0.47 0.636 -.3183108 .194583

d_16to19_b~e | -.0226171 .1007504 -0.22 0.822 -.2200841 .17485

d_20to23_b~e | -.3651146 .1079325 -3.38 0.001 -.5766585 -.1535707

d_24ormore~e | -.2996282 .125375 -2.39 0.017 -.5453586 -.0538978

d_2to4_order | -.4227657 .0783068 -5.40 0.000 -.5762442 -.2692872

d_5to7_order | -.755278 .0966968 -7.81 0.000 -.9448003 -.5657557

d_8ormore_~r | -1.031442 .1451037 -7.11 0.000 -1.31584 -.7470437

d_1to3_bir~r | -.2270734 .0935706 -2.43 0.015 -.4104683 -.0436785

d_4to6_bir~r | -.1478049 .0984993 -1.50 0.133 -.34086 .0452503

d_7to9_bir~r | -.2820671 .1053723 -2.68 0.007 -.488593 -.0755412

d_9ormore_~r | -.3730384 .1025058 -3.64 0.000 -.5739461 -.1721307

d_1to4_sib | .2308886 .2258635 1.02 0.307 -.2117957 .6735729

d_5to7_sib | .8336736 .2240055 3.72 0.000 .3946308 1.272716

d_8ormore_~b | 1.408622 .2287588 6.16 0.000 .9602634 1.856981

_cons | -2.039722 .2436052 -8.37 0.000 -2.517179 -1.562265

------------------------------------------------------------------------------

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Table 6(h) : Analysis of Demographic Variables in Determinant of Infant Mortality in Rural Areas Punjab (Pakistan).

Mother's Age at Marriage Categories Odds Ratio P -Value 1 to 14 1.000 ------ 15 to 17 0.018 0.834 18 to 20 -0.035 0.703 21 to 23 -0.121 0.299 24 or more -0.061 0.636Mother's Age at Birth 1 to 15 1.000 ------ 16 to 19 -0.022 0.822 20 to 23 -0.365 0.001 24 or more -0.299 0.017Birth Order First Child 1.000 ------ 2 to4 -0.422 0.000 5 to 7 -0.755 0.000 8 or more -1.031 0.000Birth Interval Less than 1 1.000 ------ 1 to 3 -0.227 0.015 4 to 6 -0.147 0.133 7 to 9 -0.282 0.007 10 or more -0.373 0.000Number of siblings No sibling 1.000 ------ 1 to 4 0.230 0.307 5 to 7 0.833 0.000 8 or more 1.408 0.000

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This results shows that woman’s age at marriage is not significantly associated with the infant

mortality but it has a negative associated with the infant mortality only marriage age between 15

to 17 years is positive associated with the infant mortality.

Usually it is considered that the child birth at young mothers aged less than 20 years and at older

years aged above 40 have at high risk of infant mortality as compared to the birth to the mothers

aged between 20 to 39. The results shows that birth age between 20 to 23 and birth age more

than 24 years are significantly negatively associated with the decreasing risk of infant mortality.

Birth age between 16 to 19 is negatively correlated with the infant mortality but it is not

significant effects on infant mortality.

Birth order has an important and significant determinant of infant mortality in rural Punjab. Birth

order 2 to 4 and birth order 5 to 7 are associated with decreasing risk of infant mortality. Birth

order more than 8 is also associated with decreasing risk of infant mortality but the logistic

regression coefficient is greater than 1 which means that birth order more than 8 have a large

negative impact on infant mortality.

Birth interval has a negative relation with the infant mortality as the interval between birth

increased infant mortality decreased. Birth interval 1 to 3, 4 to 6 and more than 10 years have

significantly associated with the decreasing risk of infant mortality.

No of siblings have a positive effect on infant mortality in rural Punjab as number of siblings

increased the chances of infant mortality also increased. Sibling between 5 to 7 and 8 or more

have positively significantly associated with the infant mortality this mean that these variables

are significantly associated with increasing risk of infant mortality. Regression coefficient of

sibling having more than 8 (1.40) represents have a high effect on infant mortality.

This result explain that the birth order Mother’s age at birth, birth interval, birth order and

number of siblings are the key determinants of infant mortality.

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Chapter No 7Conclusion

Moreover, this study was devised to analyze the socio economic and demographic determinants

of infant mortality and infant survival in sphere of medical sociology. The key objectives of this

study were to devise the prevailing patterns of infant mortality domain of demographic and socio

economic perspectives.

The results in this paper has shown that no education has very much associated with the infant

deaths and educated mother’s are less involved in infant’s death. These mother’s are very much

interested to accept family planning methods to delay the birth hence increased birth intervals.

So to reduce infant mortality, it is very much necessary for the policy makers and researchers to

increase education among mothers. It is also necessary to introduce new techniques for

increasing birth interval and family planning programs for mothers and infant’s health. Mother’s

education can not only increase infant’s health but also increase family health. It is to be

considered that many of the women might be get education if their parents are encouraged so this

will also help to reduce infant mortality in the long run.

In this paper the results has shown that mother’s education and mother’s working status have a

significantly associated with infant mortality. In rural areas of Punjab majority of the women

have no education hence less knowledge of health care and medical facilities. Women’s

education enable her to make quick and good decision for the better health of infant in uncertain

situation. In this paper the author have found that mother’s education, working status and social

status have very much significant factors in socioeconomic factors for determine the infant

mortality in rural areas of Punjab. The author found same variables like mother’s education and

social economic status was also very important and significant in determinant of infant mortality

in Punjab. Hence these variables are the basic cause of infant mortality so researchers should

introduce such a policy to treat these variables at first. Agha in his paper also found that mother’s

education was one the most important variable in determinant of infant mortality as 92 % of rural

births occurred in those women having no education between the period of 1982 to 1991 (Agha,

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2000). Anna analysis that region of residence, family income and father’s social status are the

important determinants of infant mortality and child mortality in Kenya. Hence for the better

employment opportunities, such a policies are required to increase the parent’s education (Anna,

2009).

Mother’s age at birth, birth order, birth interval and number of siblings have significantly

affected the infant mortality. It is found in rural areas where women get married at very early age

results in early pregnancies and birth in early age so it is required to discourage early marriages.

Birth interval and birth order have very much significance associated with the infant mortality.

Hence birth order is the most important factor to determine the infant mortality in biological

determinants. As it is very much common in rural population that infant mortality in terms of

first child is much higher as compared to the later births, and it is more frequent in rural Punjab

as there is a general trend of early marriages in these areas.

At the end of this paper the author conclude that almost all the socioeconomic and demographic

variables have very much relationship with each other so multiple policies are required to deal

with these variables. It is also important to give knowledge to the mothers to overcome uncertain

situations for the better health of infant’s.

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