Mediating Causes for High Level of Infant Mortality Rate at Thondamuthur Block of Coimbatore District

Home , Health in India, Thondamuthur Block

MEDIATING CAUSES FOR HIGH LEVEL OF INFANT MORTALITY RATE AT THONDAMUTHUR BLOCK OF COIMBATORE DISTRICT

Submitted to

State Planning Commission Government of Tamilnadu

Dr. A. ARULRAJ Principal Investigator

P.G. & Research Department of Economics, Rajah Serfoji Government College (Autonomous), Thanjavur – 613 005.

March 2017 Executive Summary

The social and behavioural studies are playing a vital role in determining infant mortality rate in India. The State Planning Commission encourages for investigating the mediating cause for high level cause for the infant mortality at Thondamuthur Block in Coimbatore District. However, the project findings base on econometric models. Public health services (Practitioners services, hospital Services in Outpatients and Hospital Services in Inpatients) resulted insignificant impact on determining Infant mortality and health of the children at Thondamuthur Block. Hence it is not a factor for the high level cause for the Infant Mortality. Social Problems, Infrastructure facilities and economic problems dimensions resulted marginal impact on infant mortality. Since the state government provides various schemes for pregnant women during maternity period and also for improving child health. But the Social Problems, Infrastructure facilities and economic problems dimensions created psychological problems during maternity period. SEM empirically proved that psychological discomfort dimension is the mediated factor for the cause of high level cause for the infant mortality at Thondamuthur block in Coimbatore district. The present study scientifically proves that psychological discomfort factor is a medicating cause for the high level cause for the infant mortality at Thondamuthur Block in Coimbatore district. It means if there is any change in psychological discomfort factor then it will reflects immediately in Infant Mortality. Psychological Discomfort management alone the one and only solution for eradicating the infant mortality completely and the same has been scientifically proved with the help of structural equation model. Psychological Discomfort factor includes emotions of pregnant mothers, behaviour of husband, mother-in-law, friends and other relatives, lack of parents and friends support, sexual harassment in working place, varsity health hazards in informal sector, continuous sex inducement during the pregnancy time due to continuous drinking habit of the spouse and not proper interval between two babies. The policy makers, social science scientist, consultants and the Government should carefully make use of the said factor to eradicate the infant mortality at Thondamuthur Block in Coimbatore District. There is a need to create a committee to make ‘Effective Management of Psychological Discomfort’ factor to eradicate infant mortality completely.

TABLE OF CONTANTS Abbreviations List of Tables List of Figures Page No. Section - 1 Introduction 1 Section - 2 Reproductive and Child Health in Tamilnadu: 7 An Over View Section - 3 Infant Death in Coimbatore District: A Prelude 16 Section - 4 Mediating Causes for High Level of Infant Mortality 26 Rate: Findings from Field Survey Section - 5 Findings, Conclusion and Policy Recommendations 69 References Appendix - I a) Questionnaire - English b) Questionnaire – Tamil Appendix - II Village/Urban/Block level Data of Coimbatore District Appendix - III Bayesian Convergence Distribution for “MEDIATING CAUSES FOR HIGH LEVEL OF INFANT MORTALITY RATE” Regress Model Appendix - IV Bayesian Convergence Distribution for “MEDIATING CAUSES FOR HIGH LEVEL OF INFANT MORTALITY RATE” Structural Equation Latent Model Appendix - V Case Studies

ABBREVIATIONS

AD : Anno Domini AMOS : Analysis of Moment Structures FGD : Focus Group Discussion GDP : Gross Domestic Product HDI : Human Development Index HSCs : Health Sub-Centres ICDS : Integrated Child Development Services IGMSY : Indra Gandhi Mathirthva Sahyog Yojana IMR : Infant Mortality Rate NGO : Non-government Organisation PHCs : Primary Health Centres SEM : Structural Equation Modeling SIMA : Southern India Mills Association SPSS : Statistical Package for Social Sciences UPHCs : Urban Primary Health Centres

List of Tables

S. No. Particulars P. No. 2.1. Caesarean services are provided in 128PHCs - 8

2.2. Beneficiaries for the year 2013 – 2014 - 10

2.3. Immunization Performance during 2011-12, 2012-13 & - 10 2013-14

2.4. Dr.Muthulakshmi Reddy Maternity Benefit Scheme - 11

2.5. The Demographic Scenario of Tamil Nadu compared with - 13 India

2.6. The Infrastructure Facilities under Family Welfare - 13 Programme

2.7. Family Welfare Performance during 2013-14 - 13

2.8. Impact of Family Welfare Programme - 14

3.1. Public Health and Medical Services Rendered by - 17 Organisations and Individual year from 2012 to 2013

3.2. Details of the Beds Strength, Average Out patients and In - 17 patients in Coimbatore District year from 2013 to 2014

3.3. Primary Health Centres with Sub-Centres year from 2013 to - 18 2014 3.4. Births and Deaths Registered in Coimbatore District year - 18 from 2013 to 2014 3.5. Birth, Death and Infant Mortality Rates in Coimbatore - 18 District year from 2013 to 2014

3.6. Infant Mortality Rate for India - 19

3.7. Infant Mortality Rate for Tamilnadu - 20

3.8. Infant Deaths for Coimbatore District - 21

3.9. Infant Death for Coimbatore Corporation - 22

3.10. Infant Death for Coimbatore Urban - 23 3.11. Infant Death for Coimbatore Rural - 24 3.12. Infant Death for Thondamuthur Block - 25 4.1 Age wise classification of Pregnant Women Households - 26 4.2. Educational Qualification of Pregnant Women Households - 28 4.3. Occupation of Pregnant Women Households - 30 4.4. Religious Classification of the Pregnant Women Households - 31 4.5. Income wise Classification of Pregnant Women Households - 32 4.6. Community wise Classification of Pregnant Women - 33 Households 4.7. Types of Family of Pregnant Women Households - 34 4.8. Residential Status of Pregnant Women Households - 35 4.9. Living conditions of Pregnant Women Households - 36 4.10. Size of Landholding of Pregnant Women Households - 37 4.11. Toilet Facilities of Pregnant Women Households - 38 4.12. Selection Preference of Hospitals by the Respondents - 39 4.13. Hospital Selection by the Respondents - 40 4.14. Medical Insurance of Pregnant Women Households - 41 4.15. Any Infant Death of Pregnant Women Households - 42 4.16. Summary of the Various Goodness of Fit Statistics and Other - 61 Values Corresponding to the “HIGH LEVEL OF INFANT MORTALITY RATE” Structural Equation Latent Model

List of Figures

S. Particulars Page No. No. 1.1. Proposed Conceptual Mediated Model for High Level cause for - 5 the Infant Mortality Rate at Thondamuthur Block in Coimbatore district 2.1. Trend Plot of Caesarean section delivery - 9 2.2. Trend plot for Dr.Muthulakshmi Maternity Scheme of Amount - 11 Disbursed 2.3. Trend plot for Dr.Muthulakshmi Maternity Scheme of No. of - 12 Beneficiaries 3.1. Trend Analysis Plot of Infant Mortality Rate for India from 2000 - 19 to 2012 3.2. Trend Analysis Plot of Infant Mortality Rate for Tamilnadu from - 20 2000 to 2012 3.3. Trend Analysis Plot of Infant Deaths for Coimbatore District - 21 from (2011-2012) to (2014-2015) 3.4. Trend Analysis Plot of Infant Death for Coimbatore Corporation - 22 from (2011-2012) to (2014-2015) 3.5. Trend Analysis Plot of Infant Death for Urban Total from (2011- - 23 2012) to (2014-2015) 3.6. Trend Analysis Plot of Infant Death for Rural Total from (2011- - 24 2012) to (2014-2015) 3.7. Trend Analysis Plot of Infant Death for Thondamuthur Block - 25 from (2011-2012) to (2014-2015) 4.1. Shows the AMOS Output with Regression Weights of - 50 “MEDIATING CAUSES FOR HIGH LEVEL OF INFANT MORTALITY RATE” Mediated Model 4.2. Posterior frequency Polygon distribution of the Mediating - 52 Factor (IMR) and (PD) Regression Weight (W13) 4.3. Posterior frequency Histogram distribution of the Mediating - 52 Factor (IMR) and (PD) Regression Weight (W13) 4.4. Posterior frequency Trace plot of the Mediating (IMR) and (PD) - 53 Regression Weight (W13) 4.5. Posterior frequency Autocorrelation plot of the Mediating - 53 Factor (IMR) and (PD) Regression Weight (W13) 4.6. Two-dimensional Surface plot of the marginal posterior - 54 frequency distribution of the mediating factor (PD with (IMR) and (HSI) Regression Weight (W9) and (W13) 4.7. Two-dimensional Histogram plot of the marginal posterior - 54 frequency distribution of the mediating factor (PD) with (IMR) and (HSI) Regression Weight (W9) and (W13) 4.8. Two-dimensional Contour plot of the marginal posterior - 55 frequency distribution of the mediating factor (PD) with (IMR) and (HSI) Regression Weight (W9) and (W13) 4.9. Shows AMOS path diagram output for the Overall Mediated for - 59 “HIGH LEVEL OF INFANT MORTALITY RATE” Structural Equation Latent Model 4.10 Posterior frequency Polygon distribution of the Mediating - 62 . Factor (PD) and (IMR) Regression Weight (W70) 4.11 Posterior frequency Histogram distribution of the Mediating - 62 . Factor (PD) and (IMR) Regression Weight (W70) 4.12 Posterior frequency Trace plot of the Mediating Factor (PD) - 63 . and (IMR) Regression Weight (W70) 4.13 Posterior frequency Autocorrelation plot of the Mediating - 63 Factor (PD) and (IMR) Regression Weight (W70) 4.14 Two-dimensional Surface plot of the marginal posterior - 64 frequency distribution of the mediating factor (PD) and (IMR) and (HSI) Regression Weight (W68) and (W70) 4.15 Two-dimensional Histogram plot of the marginal posterior - 65 frequency distribution of the mediating factor (PD) and (IMR) and (HSI) Regression Weight (W68) and (W70) 4.16 Two-dimensional Contour plot of the marginal posterior - 65 frequency distribution of the mediating factor (PD) and (IMR) and (HSI) Regression Weight (W68) and (W70) 5.1 Empirically Proved Conceptual Model for High Level of Infant - 71 Mortality Rate

SECTION - 1

INTRODUCTION

1.1. Introduction

The Infant Mortality Rate (IMR) is one of the important indicators for the health status of a country. In developing countries, background characteristics such as mother’s literacy, urban/rural residence, and household economic status are likely to affect a child’s condition at birth as well as its environment, thus affecting infant and child mortality (Hobcraft, McDonald, and Rutstein 1984; Mosley and Chen 1984; United Nations 1985; 1991; 1998). Infant and child mortality are determined by biological endowment of the children at birth and after birth. The present study empirically examines the Mediating Cause for high level Infant Mortality Rate at Thondamuthur block in Coimbatore district, Tamilnadu. The main purpose of the study is to identify the mediating cause of High level infant mortality with the aid of socioeconomic characteristics of mothers and households, demographic characteristics of children and health care behaviours of mothers. There are many dimensions associated with variations in infant and child mortality rate. In the present study we made an attempt to isolate the effects of individual variables.

Maternal and child health services in India are designed to provide basic health services to vulnerable groups of pregnant women through programmes such as the Minimum Needs Programme, the Child Survival and Safe Motherhood Programme, and the Reproductive and Child Health Programme (IIPS 1995; Ministry of Health and Family Welfare 1998). These report discuses the estimated effects of women’s healthcare behaviour such as antenatal visits, tetanus immunization, and place of delivery on neonatal mortality and the same will be useful for evaluating current maternal and child health programmes. There are many dimensions influencing the high level cause for the infant mortality in the world. But, in India, the child sex dimension is most important factor for high level infant mortality rate. In most populations, male mortality is higher than female mortality at almost all ages (Heligman 1983; United Nations Secretariat 1988). In South Asia, however, female mortality is higher than male mortality at many ages (Ghosh 1987; Office of the Registrar General, India 1994; Pebley and Amin 1991;

Preston 1990), especially during the post neonatal and childhood periods. Excess female mortality at post neonatal and childhood ages in India and other South Asian countries is believed to result from son preference, which leads to differential treatment of sons and daughters in terms of food allocation, prevention of diseases and accidents, and treatment of illness (United Nations 1998).

In India, many researchers have documented evidence of son preference and discrimination in caring for sons and daughters (Basu 1989; Das Gupta 1987; Muhuri and Preston 1991). Studies on infant and child mortality in India also document large variations among states in the degree of son preference and associated excess female child mortality (Arnold, Choe, and Roy 1998; IIPS 1995; Mutharayappa et al. 1997). Their results show that excess female mortality tends to be higher in northern states, where the traditional family system is strongly patriarchal, than in southern states with less of a patriarchal tradition. The strong patriarchal tradition in northern India includes customs related to marriage, living arrangements and support for elderly parents, and funeral rituals that assign many privileges and duties exclusively to sons (Arnold, Choe, and Roy 1998; Caldwell, Reddy, and Caldwell 1989; Dyson and Moore 1983; Kapadia 1966; Karve 1965; Kishor 1995; Koenig and Foo 1992). At marriage, dowry payments impose a heavy financial burden on the parents of girls, while after marriage wives typically move in with their husbands’ families, weakening ties with their own parents. Such customs may cause parents to desire more sons than daughters and to discriminate against daughters, and this in turn may result in excess female post neonatal and child mortality. It will be difficult to eliminate son preference and associated excess female child mortality quickly in India because long standing traditions are slow to change. Some observers have noted, however, that the degree of son preference may be declining somewhat (Visaria 1994). Maternal and child health programmes that provide supple maternal nutrition and basic health care to all children, regardless of sex, may also help to reduce excess female child mortality (Pebley and Amin 1991). In Tamilnadu, few blocks were affected the said dimensions but the government has taken necessary steps to reduce the Infant mortality rate. The rest of the dimensions have not discussed and the same have been influenced on infant mortality which

are socio-economic factors, mother’s literacy, households heads religion and caste, exposure to mass media, access to a flush or pit toilet, birth order, mother’s age at childbirth, previous birth interval, mortality of an older sibling and psychological discomfort.

According to the report of Save the Children, an international NGO, one-fifths of the world’s new born deaths occur in India. India also has the highest under-five mortality with over 2 million children dying before their fifth birthday. About 90% of these deaths are preventable. One-third of all malnourished children live in India and 46% of children under-3 years are underweight. A child’s chances of survival vary in different states. The infant mortality rate in Orissa is 96 per 1000 live births, in Kerala it is only 14 per 1000 live births.

The 11th plan (2007-12) has drawn attention to IMR in differences districts. Out of 32 districts, Dharmapuri, Krishnagiri, Villupuram, Thiruvannamalai and Perambalur were rated as the most backward districts based on Human Development Index (HDI). There are many indicators which form part of Human Development Index among them Infant Mortality Rate is one of the important indicator. There are many factors are associated with economic backwardness such as income, employment, productive assets especially land holding, percentage of people depending upon agriculture, land less labour, access to institutional credit, indebtedness etc. In addition, social factors are also determine the welfare of a society which consists of caste, gender, literacy, education, health, access to basic facilities like water and sanitation etc. It is not only known from many studies but also these social and economic factors influence each other and play an important role in determining the outcome of welfare programme. The present study investigates how economic and social factors influence the Infant Mortality Rate.

1.2. Economic Backwardness and Its Relationship influence High Level of IMR at Thondamuthur Block in Coimbatore District

Good health is necessary for empowerment. Rural healthcare services suffer from a shortage in public sector infrastructure. Majority of women from rural areas were working in an unorganised sector and they were paid less. They were suffering from many hazardous diseases and their health status is degrading year

by year. Healthcare services and programmes conducted by PHCs either directly or indirectly related to the health status of women. The present study empirically examines the mediating cause for high level infant mortality rate at Thondamuthur block in Coimbatore district.

1.3. Objectives of the study

1. To investigates the factors influencing high level Infant Mortality Rate at Thondamuthur Block in Coimbatore District; 2. To gain a better understanding about the mediating causes for high level Infant Mortality Rate and; 3. To explain the various dimensions influencing high level Infant Mortality Rate in the study area.

Based on the objectives of the study the following proposed conceptual model has been framed.

1.4. Proposed Conceptual Mediated Model for High Level of Infant Mortality Rate

There are eight dimensions were framed for the present study which are; i) Practitioners Services, ii) Hospital Services in Outpatients, iii) Hospital Services in Inpatients, iv) Social Problems, v) Infrastructure Facilities, vi) Psychological Discomfort, vii) Economics Problems and viii) High Level of Infant Mortality Rate.

The present study segregates dependent and independent variables. Dependent variables include Psychological Discomfort and High Level of Infant Mortality Rate and the independent variables consist of Practitioners Services, Hospital Services in Outpatients, Hospital Services in Inpatients, Social Problems, Infrastructure Facilities and Economics Problems. There is a need to study how and what extent the independent variables make changes in the dependent variable. The proposed conceptual research model shows the mediating cause for High level of Infant mortality rate for intensive understanding of the present study.

Figure 1.1: Proposed Conceptual Mediated Model for High Level cause for the Infant Mortality Rate at Thondamuthur Block in Coimbatore district

Practitioners Services

Hospital Services in Outpatients Demographic Variable

Hospital Services in Inpatients High Level of Infant Mortality Rate

Social Problems

Infrastructure Facilities Psychological Discomfort

Economic Problems

1.5. Methodology

The study has undertaken in two stages which are District/block level analysis based on secondary data and Field visit analysis based on primary data.

1.5.1. District/block level analysis based on secondary data:

We have taken district/block level data for analysing the mediating cause for high level of Infant Mortality Rate for that Data have been collected from the PHCs Thondamuthur Block, Anganwadis and District Planning Cell in Coimbatore District.

1.5.2. Field visit analysis based on primary data

1.5.2.1. Selection of Block

The detailed study has been made in Thondamuthur block since the block belongs to most backwardness in economic conditions and Higher Infant Mortality Rate levels.

1.5.2.2. Selection of villages

The field visit has been carried out in four villages namely Theethippalayam, Mathavarayapuram, Devarayapuram and Ikkarai Booluvampatti for collecting the

5 primary data. Focus group discussions (FGD) have been conducted with knowledgeable people in the villages and government officials with the help of detailed check list.

1.5.2.3. Primary survey

The primary survey of households with different economic background has been undertaken in the said four villages be part of 25 pregnant women households in each village. A detailed questionnaire (See Appendix – I) has been used to collect data to find out the mediating cause for the high level infant mortality rate in the study area.

1.5.2.4. Case studies under special schemes

In addition, case studies under special schemes have been undertaken in the said Blocks. For this purpose, the list of pregnant women Households has been procured from the concerned officers of the Departments of Health at the district level. There are five case studies (Appendix V) have been disclosed in this report.

Data analysis were performed with Statistical Package for Social Sciences (SPSS) using techniques that included descriptive statistics, correlation analysis and AMOS package for Structural Equation Modeling (SEM) and Bayesian estimation and testing.

SECTION – 2

REPRODUCTIVE AND CHILD HEALTH IN TAMILNADU: AN OVER VIEW

Tamilnadu has emerged as a model state in India for providing health services. The Government hospitals are providing good services for urban poor. Arulraj. A & Rethinasivkumar. G (2012) examined the services quality of government hospitals in Tamilnadu. The results reveal that the government of Tamilnadu provided the best service quality for the preceding five years. The Government of Tamilnadu is also at the forefront of communicable and non-communicable diseases. Tamilnadu is one of the best performing state in the country for implementing the reproductive and child health schemes.

Public Health and Preventive Medicine Department was formed during 1923 in Tamil Nadu which is engaged in protecting and promoting the health of the people by immunization, health education, application of hygiene and sanitary measures, monitoring of drinking water quality and environmental hazards thereby reducing the burden of morbidity, infant mortality and disability in the State. Primary Health Centres and Health Sub-centres are playing an important role in providing Health services.

2.1. Primary Health Centres (PHCs)

Primary Health Centres have been brought under the control of the Director of Public Health and Preventive Medicine from 1st March 1996. A Primary Health Services in rural areas are established for a population of about 20,000 in hill areas and 30,000 in other areas. There are 1751 Primary Health Centres (PHCs) including 402 upgraded PHCs and 134 Urban Primary Health Centres (UPHCs) which are providing health services for the rural population. These centres are providing health services for the rural population as there are universal immunizations, reproductive and child health, vector Borne Diseases control and school health programme. All PHCs are functioning on 24X7 bases. During the Year 2013-2014, 91936470 out-patients at an average rate of 142 per day per PHC and 1532915 in-patients at an average rate of 72 in patients per month per primary health centre were getting treatments in the PHCs.

2.2. Health Sub Centres (HSCs)

A Health Sub Centres (HSCs) are established for population up to 3,000 in hill areas and 5000 in other areas. Each centre is named as Village Health Nurse (VNH). There are 8706 Health sub centres which are functioning very effectively for quality of health of the People in Tamilnadu. The health sub centres are playing a vital role in improving the quality of health services to pregnant women in rural areas.

2.3. Deliveries conducted at PHCs

HSCs and PHCs ensure that every woman is tracked and provided intuitional care and services during ante natal, natal and Post natal period. The Village Health Nurse at the HSC level and the sector health nurse at higher level followed 24x7 nursing provisions in the PHCs and also ensured that 2.5 lakh deliveries occurred in the PHCs. Improvements in PHCs facilities, upgrading all PHCs as 24x7 PHCs, introduction of birth companion scheme, provision of ultrasonogram machines, upgradation of PHCs with 30 beds with operation theatre, enhancement of Dr.Muthulakshmi Reddy Maternity Benefit Scheme assistance from Rs 6,000 to Rs. 12,000, provision of diet for antenatal mothers, organizing maternity picnics to PHCs, drop back for delivered mothers and establishment of birth waiting homes are responsible for the quantum increase in PHCs deliveries.

2.4. Caesarean services provided by PHCs

Table 2.1: Caesarean services are provided in 128 PHCs S.No Year Deliveries 1 2007-2008 366 2 2008-2009 1285 3 2009-2010 2694 4 2010-2011 4962 5 2011-2012 8320 6 2012-2013 8649 7 2013-2014 11435 Source: (Annual Report Of Health And Family Welfare, 2014 -2015 Govt. Of Tamilnadu)

Figure 2.1: Trend Plot of Caesarean services provided by 128 PHCs

Trend Analysis Plot for Caesarean section delivery Linear Trend Model Yt = -2264 + 1913*t

12000 Variable Actual 10000 Fits Accuracy Measures MAPE 40 8000 MA D 585 MSD 404957 6000

4000

2000 Caesarean section delivery 0

2008 2009 2010 2011 2012 2013 2014 Year

Trend analysis figure 2.1 reveals the Caesarean services provided by Primary healthcare centres. The trend plot that shows the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = -2264+1913*t. The Caesarean services provided by 128 PHCs data shows a general upward trend, though with an evident cyclic factor. The trend model appears to fit well to the overall trend. Trend analysis clearly stated that caesarean services provided by 128 PHCs from 2007- 2008 to 2013 - 2014. It indicates the upward trend which means the caesarean deliveries have been increased year by year.

2.5. Establishment of Urban Primary Health Centres

During 2012–2013, Government has issued orders for the establishment of 135 Urban Primary Health Centres in small urban areas of Tamil Nadu under the administrative control of the Director of Public Health and Preventive Medicine. Subsequently, two Urban PHCs were sanctioned. Among 137 Urban PHCs, three Urban PHCs were handed over to Chennai Corporation.

2.6. Menstrual Hygiene Programme

Under this scheme 18 packs of sanitary napkins (six pads per pack) in a year at the rate three packs for two months for each adolescent girl (10–19 years) in rural areas both school going and non school going girls are provided. Sanitary Napkins are delivered by the government institutions to post natal mothers at the

9 rate of seven packs each (six pads per pack). Sanitary Napkins are being given to each women prison inmate and to 525 female inpatients in the Institute of Maternal Health, Chennai at the rate of 18 packs (six pads per pack) in a year. While implementing the programme it was assessed that 80% of (10-19 yrs) girls have attained puberty and hence the target was revised as 3279028 adolescent girls.

Table 2.2: Beneficiaries for the year 2013 – 2014 Sl. Category Number of Total Type of Sanitary No. Sanitary Napkins Quantity Napkin Packs required per required year (Pack) 1 Adolescent girls 3279028 x 18 59022504 Belt less Rural Type (10-19 yrs) attained puberty 2 Post-natal Mothers 725770 x 7 5080390 Belt Type 3 Women Prison inmates 729 x 18 13122 Belt Type 4 Female inpatients in 525 x 18 9450 Belt Type IMH Chennai Source: Department of Public Health and Preventive Medicine (2014-2015)

2.7. Immunization Programme

Annually, around 11.52 lakhs pregnant women and 10.48 lakhs infants are being targeted under immunization programme. The State has reported more than 95 % coverage over the years.

Table 2.3: Immunization Performance during 2011-12, 2012-13 & 2013-14 Vaccine 2011 - 2012 2012 - 2013 2013 - 2014 Target Achievement % Target Achievement % Target Achievement % (Fig. In Lakhs) (Fig. In Lakhs) (Fig. In Lakhs) Tetanus 11.97 11.72 98 11.88 11.36 96 11.52 11.10 96 Toxiod (AN Mothers) DPT* 10.83 10.65 98 10.83 10.46 97 10.48 10.26 98 POLIO 10.83 10.65 98 10.83 10.49 97 10.48 10.30 98 BCG 10.83 10.56 98 10.83 10.42 96 10.48 10.19 97 MEASLES 10.83 10.62 98 10.83 10.54 97 10.48 10.30 98 JE 3.29 2.81 85 3.34 3.12 93 3.21 3.25 101 * From 2011-12 onwards, DPT was replaced with Pentavalent vaccination. Source: Department of Public Health and Preventive Medicine (2014-2015)

2.8. Dr.Muthulakshmi Reddy Maternity Benefit Scheme

The assistance under this scheme has been enhanced from Rs 6000 to Rs 12000 by our Hon’ble Chief Minister with effect from 01.06.2011. Assistance

under this scheme is disbursed in three instalments to poor pregnant women. The details of beneficiaries under this scheme are as follows:

Table 2.4: Dr.Muthulakshmi Reddy Maternity Benefit Scheme Sl.No Year Amount Allotted (Rs. Amount Disbursed No. of In Crore) (Rs. In Crore) Beneficiaries 1. 2006 - 2007 100.00 100.00 241095 2. 2007 - 2008 300.00 296.64 679831 3. 2008 - 2009 350.00 349.26 579821 4. 2009 - 2010 360.00 358.60 599126 5. 2010 - 2011 360.00 347.51 581790 6. 2011 - 2012* 660.00 515.11 673093 7. 2012 - 2013 716.77 639.54 670313 8. 2013 - 2014 716.77 652.16 6636623 *including beneficiaries who have availed enhanced assistance of Rs.12,000 each. Source: Department of Public Health and Preventive Medicine (2014-2015)

Figure 2.2: Trend plot for Dr.Muthulakshmi Maternity Scheme of Amount Disbursed

Trend Analysis Plot for Dr.Muthulakshmi Reddy Maternity Benefit Scheme of Amount Disbursed Linear Trend Model Yt = 82.4 + 72.2*t

700 Variable Actual 600 Fits Accuracy Measures MA PE 16.63 500 MA D 42.93 MSD 2809.65 400

300 Amount Disbursed 200

100

2007 2008 2009 2010 2011 2012 2013 2014 Year

Trend Analysis 2.2 stated that the increasing trend of amount disbursed under Dr.Muthulakshmi Reddi Maternity Benefit Scheme from 2006 – 2007 to 2013 – 2014. The trend plot that shows the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 82.4+72.2*t. The trend model appears to fit well to the overall trend. The trend plot clearly stated that Dr.Muthulakshmi Reddy maternity benefit scheme is a successful scheme hence the No. of beneficiaries have been increased year by year and the same disclosed in trend analysis 2.3. The Government of Tamilnadu has launched a revised Dr.Muthulakshmi Reddy maternity benefit scheme. This scheme ensures adequate ante natal, natal and post natal care and encourage institutional delivery, nutritional support and immunisation to the mother and child. The

maternity benefit is very useful during maternity period for rural poor pregnant women as an economic independent. The cash assistance is given in three instalments on conditional basis and restricted to two deliveries.

Figure 2.3: Trend plot for Dr.Muthulakshmi Maternity Scheme of No. of Beneficiaries

Trend Analysis Plot for Dr.Muthulakshmi Reddy Maternity Benefit Scheme of No. of Beneficiaries Linear Trend Model Yt = 416127 + 37769*t

Variable 700000 Actual Fits

Accuracy Measures 600000 MA PE 1.85265E+01 MA D 7.52079E+04 MSD 1.10998E+10 500000

400000 No . o f Be n e f ic ia r ie s 300000

200000 2007 2008 2009 2010 2011 2012 2013 2014 Year

Trend Analysis 2.3 shows that the increasing trend of Dr.Muthulakshmi Reddi Maternity Benefit Scheme from 2006 – 2007 to 2013 – 2014. The trend plot that shows the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 416127+37769*. The trend model appears to fit well to the overall trend. For the financial year 2013-14, Rs.716.77 crore allocated for the programme and Rs.652.16 crore disbursed to 6,63,623 mothers were benefited through this programme. From 1st October 2012, benefits under the scheme are distributed directly to the bank account of the beneficiaries through Electronic Clearing Systems (ECS). On an average, 6 lakh women benefit from the scheme every year.

2.9. Family Welfare Programme

The Department of Family Welfare was functioning only as a wing of the Medical and Public health Directorates. A separate Directorate of Family Welfare was formed during 1983. Subsequently, the Family Welfare Programme was implemented as a people's programme by involving all the other departments. The main objective of the Directorate is to stabilize the population growth as well as to improve the maternal and child health status thereby reducing the vital indicators such as the IMR and MMR. Today, Tamil Nadu is considered as a model

State for the other States in the country in the implementation of the Family Welfare Programme.

2.9.1. Demographic Scenario

The Demographic Scenario of Tamil Nadu and India are as follows:

Table 2.5: The Demographic Scenario of Tamil Nadu compared with India Sl.No. Indicator India Tamilnadu 1. Population 1210726932 72147030 2. Decennial Growth Rate (%) 17.7 15.6 3. Sex Ratio (female per 1000 males) 943 996 4. Density of Population (per sq. K.M.) 382 555 5. Literacy Rate (%) Male 86.8 80.9 Female 73.4 64.6 Source: 2011 Census

6. Crude Birth Rate (per 1000 population) 21.6 15.7 7. Crude Death Rate (per 1000 population) 7.0 7.4 8. Infant Mortality Rate (per 1000 live births) 42 21 9. Natural Growth Rate (%) 1.45 0.83 Source: SRS 2012

2.9.2. The Infrastructure Facilities under Family Welfare Programme

Table 2.6: The Infrastructure Facilities under Family Welfare Programme Sl.No. Medical Institutions Total 1. Primary Health Centres 1751 2. Health Sub-Centres 8706 3. Rural Family welfare Centres 382 4. Post Partum Centres 110 5. Urban Family 108 6. Urban Health Posts 193 7. Voluntary Organisations 27 8. Approved Private Nursing Homes 2040 Source: Department of Public Health and Preventive Medicine (2014-2015)

2.9.3. Family Welfare Performance during 2013-14 can be seen from the table below

Table 2.7: Family Welfare Performance during 2013-14 Sl.No. Programme 2013 - 2014 2013 - 2014 % of achievement Assigned ELD 1. Sterilisation 400000 323310 80.8 2. I.U.C.D. Insertion 433000 379152 87.6 3. C.C. Users 180000 91605 50.9 Source: Department of Public Health and Preventive Medicine (2014-2015)

2.9.4. Impact of Family Welfare Programme is given in the table below

Table 2.8: Impact of Family Welfare Programme 1. Contraceptive Prevalence Rate (NFHS-3) 2005 - 2006 60% 2. Sterilization Acceptors with two and less than two living children 77.2% 2013 - 2014 (up to February 2014) 3. Percentage of Higher Order Births (2012) 9.0 4. Mean age at acceptance of Sterilization (2012-2013) 27.2 5. Mean number of living children to the sterilization acceptors (2012 - 2.2 2013) Source: Department of Public Health and Preventive Medicine (2014-2015)

2.10. Integrated Child Development Services

The overall goal of the ICDS is to improve the nutritional and health status of preschool children, pregnant and nursing women. Hence, the State Government has initiated various proactive measures to create the present environment for strengthening and restructuring of Integrated Child Development Services Scheme towards addressing nutrition challenges among children under six, adolescent girls and mothers. ICDS has been the centre-piece of the comprehensive strategies for providing a continuum of care in a life-cycle approach aimed towards impacting mother and child development. Integrated Child Development Services Scheme covers 35.37 lakh direct beneficiaries (nutrition) and 43.36 lakh indirect beneficiaries i.e. children availing health services, weight monitoring, counselling etc., through 54,439 Child Centres (comprising 49,499 Main Anganwadi Centres and 4,940 Mini Anganwadi Centres) functioning in 434 Child Development Blocks. As per National Family Health Survey NFHS-3 Data 2006, in Tamilnadu33.2% of children in the age group of 0 to 3 years were under the underweight category and it has been reduced to 17.23 % by March 2014. ICDS Data as on March 2014 indicates that 82.78 % (19.69 lakh) are normal children, 17.13 % (4.07 lakh) are moderately underweight children and 0.10% (2,489) only are severely underweight (SUW) children. During the 12th Five Year Plan (2012-2017), ICDS schemes has been restructured to carry out programmatic management and instructional reforms in a phased manner where Anganwadi Centres are repositioned as a “ Vibrant early childhood development centre” to become the first outpost for learning, health and nutrition by providing additional human resources and infrastructure. Nevertheless, in the study area ICDSs are playing a vital role to improve the health services for pregnant women.

2.11. Indira Gandhi Mathirthva Sahyog Yojana (IGMSY)

IGMSY Scheme (Conditional maternity benefit scheme) is being implemented in synergy with Dr. Muthulakshmi Reddy Maternity Benefit Scheme for pregnant women and lactating mothers by providing cash incentive to maintain them healthy and to manage loss of income during the period of conception and convalescence. The state is providing more schemes for child health care. The schemes are effectively implementing for ensuring the child health care in rural and urban areas. Hence, the state got the second lowest one among the major states in the country for the indicators.

SECTION - 3

INFANT DEATH IN COIMBATORE DISTRICT: A PRELUDE

The section indicates the Infant Mortality Rate in Country level, State level, District Level and Block level.

3.1. Coimbatore District – General Profile

The third largest city of the state, Coimbatore, is one of the most industrialized cities in Tamil Nadu, known as the textile capital of South India or the Manchester of the South, the city is situated on the banks of the river Noyyal, Coimbatore existed even prior to the 2nd or 3rd century AD by Karikalan, the first of the early Cholas. Among its other great rulers were Rashtrakutas, Chalukyas, Pandyas, Hoysalas and the Vijayanagara kings. When Kongunadu fell to the British along with the rest of the state, its name was changed to Coimbatore and it is by this name that it is known today, except in Tamil, in which it is called Kovai.

In the rain shadow region of the Western ghats, Coimbatore enjoys a very pleasant climate all the year round, aided by the fresh breeze that flows through the 25 kms long Palakkad gap. The rich black soil of the region has contributed to Coimbatore's flourishing agriculture industry and it is in fact the successful growth of cotton that served as a foundation for the establishment of its famous textile industry. The first textile mills came as far back as 1888 but there are now over a hundred mills. The result has been a strong economy and a reputation as one of the greatest industrial cities in South India.

There are more than 25,000 small, medium, large sale industries and textile mill. Coimbatore is also famous for the manufacture of motor pump sets and varied engineering goods. The development of Hydro electricity from the Pykara Falls in the 1930 led to a cotton boom in Coimbatore. Coimbatore serves as an entry and exit point to neighbouring Kerala and the very popular hill station of Udhagamandalam (Ooty) is 70 kms from Coimbatore. It is the disembarking point for those who want to take the Mountain train that runs from Mettupalayam just 35 kms away from Coimbatore, regular bus services also available daily from Coimbatore to Ooty and other districts, towns and major cities.

The growth of textiles naturally led to the inception of textile machinery manufacturing. Today, some of the best known global brands in textile machinery and component manufacturing are home grown enterprises. Even in the late 1800s, Coimbatore district had cotton cleaning and pressing factories and was exported to Mumbai (then Bombay) and England. A spinning mill was established around this time and even back then, the textile industry employed over 300 people. The Southern India Mills' Association (SIMA) was established in 1933, is very active in the Coimbatore region and governs most of the textile industry in South India. SIMA has a membership spread across the southern states and protects the interests of the textile mills and its workers.

3.1.1. Public Health Profile in Coimbatore District

Table 3.1: Public Health and Medical Services Rendered by Organisations and Individual year from 2012 to 2013 Sl.No. Items Numbers 1. Hospitals 1161 2. Dispensaries 253 3. Sanitary Centres 24 4. Nursing Home 414 5. Maternity & Child Welfare Clinic 210 6. Allopathic 1460 7. Ayurvedic 62 8. Unani 18 9. Homeopathy 85 Source: Directorate of District HEALTH, Coimbatore

Table 3.2: Details of the Beds Strength, Average Out patients and In patients in Coimbatore District year from 2013 to 2014 Place Type Beds Average Average OP/Day IP/Day Annur NTK* 30 691 29 Kottur NTK* 56 364 23 Mettupalayam TK** 116 1039 113 Periyanayakkanpalayam NTK 10 335 35 Pollachi HQRS*** 170 1896 179 Sulur NTK* 30 513 27 Thondamuthur NTK* 36 434 27 Valparai TK** 38 232 14 Vettaikaranputhur NTK* 26 323 13 Total 512 5827 460 Source: Directorate of Medical and Rural Health Services (*Non-Taluk Hospital, **Taluk Hospital & ***District Head Quarters Hospital)

Table 3.3: Primary Health Centres with Sub-Centres year from 2013 to 2014 Sl.No. Name of the No. of Primary Health No. of Sub-Centres Block/Municipality Centres 1. P.N.Palayam 7 30 2. S.S.Kulam 2 13 3. Perur 4 20 4. Madukkarai 5 21 5. Thondamuthur 4 19 6. Karamadai 7 36 7. Pollachi North 3 21 8. Pollacchi South 4 18 9. Analmalai 7 32 10. Valparai 3 38 11. Kinathukadavu 3 19 12. Sultanpet 2 15 13. Sulur 4 26 14. Annur 3 20 Total 58 328 Source: Directorate of District HEALTH, Coimbatore

Table 3.4: Births and Deaths Registered in Coimbatore District year from 2013 to 2014 Live Births Registered Deaths Registered Infant Deaths 77371 29909 17 Source: Directorate of District HEALTH, Coimbatore

Table 3.5: Birth, Death and Infant Mortality Rates in Coimbatore District year from 2013 to 2014 Birth Rate Death Rate Infant Mortality Rate 15.9 4.02 6.24 Source: Directorate of District HEALTH, Coimbatore

3.2. Infant Mortality Rate

3.2.1. Infant Mortality Rate in India

Table 3.6: Infant Mortality Rate for India Year Number of Infant Deaths (Per year for every 1000 live births) 2000 68 2001 66 2002 64 2003 60 2004 58 2005 58 2006 57 2007 55 2008 53 2009 50 2010 47 2011 44 2012 42 Source: Sample Registration System (SRS) Bulletins

Figure 3.1: Trend Analysis Plot of Infant Mortality Rate for India from 2000 to 2012

Trend Analysis Plot forInfant Mortality Rate for India Linear Trend Model Yt = 70.038 - 2.07143*t

70 Variable Actual Fits 65 Accuracy Measures MAPE 1.73610 60 MA D 0.91970 MSD 1.25402 55

40 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Number of Infant Deaths (Per Deaths Infant of year forevery Number 1000 live births) Year

Trend Analysis figure 3.1 reveals that the trend of Infant mortality rate in India from 2000 to 2012. The trend plot that provides the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 70.038- 2.07143*t. The IMR/1000 Live Births for India data shows a general downward trend. The trend plot clearly stated that IMR in India reducing step by step in manner.

3.2.2. Infant Mortality Rate in Tamilnadu

Table 3.7: Infant Mortality Rate for Tamilnadu Year Number of Infant Deaths (Per year for every 1000 live births) 2000 51 2001 49 2002 44 2003 43 2004 41 2005 37 2006 37 2007 35 2008 31 2009 28 2010 24 2011 22 2012 21 Source: Sample Registration System (SRS) Bulletins

Figure 3.2: Trend Analysis Plot of Infant Mortality Rate for Tamilnadu from 2000 to 2012

Trend Analysis Plot for Infant Mortality Rate for Tamilnadu Linear Trend Model Yt = 53.385 - 2.53846*t

55 Variable Actual 50 Fits Accuracy Measures 45 MA PE 2.62174 MA D 0.85207 40 MSD 1.10059

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Number of Infant Deaths (Per Deaths Infant year of for everyNumber 1000 live births) Year

Trend Analysis figure 3.2 reveals the downward trend of Infant mortality rate in Tamilnadu from 2000 to 2012.The trend plot that provides the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 53.385-2.53846*t. The IMR/1000 Live Births for Tamilnadu data indicates a general downward trend. The trend plot clearly stated that IMR of Tamilnadu diminishing year by year.

3.2.3. Infant Mortality Rate in Coimbatore District

Table 3.8: Infant Deaths for Coimbatore District Year Infant Death 2011-2012 397 2012-2013 336 2013-2014 293 2014-2015 297 Source: Directorate of District HEALTH, Coimbatore

Figure 3.3: Trend Analysis Plot of Infant Deaths for Coimbatore District from (2011-2012) to (2014-2015)

Trend Analysis Plot of INFANT DEATHS FOR COIMBATORE DISTRICT Linear Trend Model Yt = 416.5 - 34.3000*t

400 Variable Actual Fits 380 Accuracy Measures MA PE 5.065 360 MA D 16.250 MSD 274.575 340

Infant Deat320 h

300

280

2012 2013 2014 2015 Year

Trend Analysis figure 3.3 reveals the Infant mortality rate of Coimbatore districts from 2012 to 2015. The trend plot that provides the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 416.5- 34.3000*t. The Infant mortality rate in Coimbatore District data pointed out general downward trend. Hence the data clearly reveals that the government has taken necessary steps to reduce IMR by an implementation of several schemes.

Table 3.9: Infant Mortality Rate in Coimbatore Corporation Year Infant Death 2011-2012 60 2012-2013 41 2013-2014 47 2014-2015 47 Source: Directorate of District HEALTH, Coimbatore

Figure 3.4: Trend Analysis Plot of Infant mortality rate in Coimbatore Corporation from (2011- 2012) to (2014-2015)

Trend Analysis Plot of Infant Death for COIMBATORE CORPORATION Linear Trend Model Yt = 57.0 - 3.30000*t

60 Variable Actual Fits

Accuracy Measures 55 MA PE 10.1120 MAD 4.7500 MSD 34.5750

50 Infant Deat h

40 2012 2013 2014 2015 Year

Trend analysis figure 3.4 reveals the trends in the Infant mortality rate in Coimbatore Corporation from 2012 to 2015. The trend plot that provides the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 57.0-3.30000*t. Trend Analysis figure shows that the downward trend of Infant death in Coimbatore Corporation. Even though it is the positive sign the year 2015 the infant mortality is above the trend line.

Table 3.10: Infant Mortality Rate in Coimbatore Urban Year Infant Death 2011-2012 68 2012-2013 45 2013-2014 51 2014-2015 54 Source: Directorate of District HEALTH, Coimbatore

Figure 3.5: Trend Analysis Plot of Infant mortality rate in Urban from (2011-2012) to (2014-2015)

Trend Analysis Plot of Infant Death for URBAN TOTAL Linear Trend Model Yt = 63.5 - 3.60000*t

70 Variable Actual Fits 65 Accuracy Measures MA PE 12.3576 MA D 6.5000 60 MSD 55.0500

55 Infant Deat h

2012 2013 2014 2015 Year

Trend Analysis figure 3.5 reveals the downward trend of Infant mortality rate in urban from 2012 to 2015. The trend plot that provides the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 63.5- 3.60000*t. Trend Analysis figure shows that the downward trend of Infant death in Coimbatore Urban. Even though it is the positive sign the year 2015 the infant mortality is above the trend line.

Table 3.11 Infant Mortality Rate in Coimbatore Rural Year Infant Death 2011-2012 329 2012-2013 291 2013-2014 242 2014-2015 243 Source: Directorate of District HEALTH, Coimbatore

Figure 3.6: Trend Analysis Plot of Infant Mortality Rate in Coimbatore Rural from (2011-2012) to (2014-2015)

Trend Analysis Plot of Infant Death for COIMBATORE RURAL TOTAL Linear Trend Model Yt = 353.0 - 30.7000*t

340 Variable Actual 320 Fits Accuracy Measures MA PE 3.830 300 MA D 9.750 MSD 141.575 280

Infant Deat260 h

240

220 2012 2013 2014 2015 Year

Trend Analysis figure 3.6 stated that the downward trend of Infant Mortality Rate in rural area at Coimbatore District from (2011 – 2012) to (2014 – 2015). The trend plot that provides the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 353.0-30.7000*t. Trend Analysis figure shows that the downward trend of Infant death in Coimbatore Rural. Even though it is the positive sign the year 2015 the infant mortality is above the trend line.

3.2.4. Infant Mortality Rate at Thondamuthur Block in Coimbatore District

Table 3.12: Infant Mortality Rate in Thondamuthur Block Year Infant Death 2011-2012 34 2012-2013 31 2013-2014 21 2014-2015 24 Source: Directorate of District HEALTH, Coimbatore

Figure 3.7: Trend Analysis Plot of Infant Mortality Rate in Thondamuthur Block from (2011-2012) to (2014-2015)

Trend Analysis Plot of Infant Death for THONDAMUTHUR Block Linear Trend Model Yt = 37.50 - 4.00000*t

34 Variable Actual Fits 32 Accuracy Measures MAPE 9.53863 30 MA D 2.25000 MSD 7.25000 28

26 Infant Deat h 24

20 2012 2013 2014 2015 Year

Trend Analysis figure 3.7 reveals that the downward trend of Mortality Rate in Thondamuthur Block from 2012 to 2015. The trend plot that provides the original data, and the fitted trend line, the output also displays the fitted trend equation Yt = 37.50-4.00000*t. Trend Analysis figure shows that the downward trend of Infant death in Thondamuthur Block. Even though it is the positive sign the year 2015 the infant mortality is above the trend line.

It is clearly stated that District Infant Mortality Rate is sharply a decline over the period. It ensures that the district health department is playing a decent role in improving the health status of the people in Coimbatore district.

SECTION- 4

MEDIATING CAUSE FOR HIGH LEVEL CAUSE OF INFANT MORTALITY: FINDINGS FROM FIELD SURVEY

The field survey has undertaken to analyse the role of different dimensions for high level causes of infant mortality in the sample block. The section is divided into two parts which are socio-economic dimensions of the respondents and mediating high level causes for infant mortality rate in the study area.

4.1. Part 1: Socio-Economic Dimensions

4.1.1. Age wise Classification of the Respondents

Table 4.1: Age wise classification of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Below 21 years 9 36.00 22 years to 31 years 16 64.00 32 years to 41 years 0 0 42 years & above 0 0 Total 25 100.00 Mathavarayapuram Below 21 years 12 48.00 22 years to 31 years 13 52.00 32 years to 41 years 0 0 42 years & above 0 0 Total 25 100.00 Devarayapuram Below 21 years 12 48.00 22 years to 31 years 13 52.00 32 years to 41 years 0 0 42 years & above 0 0 Total 25 100.00 Ikkarai Booluvampatti Below 21 years 10 40.00 22 years to 31 years 15 60.00 32 years to 41 years 0 0 42 years & above 0 0 Total 25 100.00 Overall Total Below 21 years 43 43.00 22 years to 31 years 57 57.00 32 years to 41 years 0 0 42 years & above 0 0 Total 100 100.00 Source: Primary Data

The table 4.1 reveals the age wise classification of pregnant women households of selected panchayats. It is inferred that 43 percent of the respondents were in the age group of below 21 years, 57 percent of the respondents were in the age group between 22 to 31 years, none of the respondents in the age group between 32 to 41 years and 42 years & above. Young mothers faced difficulties in pregnancies and deliveries because of their physical immaturity. They have limited knowledge and confidence in caring for infants and young children.

4.1.2. Educational Qualification of the Respondents

Table 4.2: Educational Qualification of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Schooling Dropout 11 44.00 Secondary Education 8 32.00 Higher Secondary Education 3 12.00 Under Graduate 2 8.00 Post Graduate 1 4.00 Total 25 100.00 Mathavarayapuram Schooling Dropout 5 20.00 Secondary Education 8 32.00 Higher Secondary Education 7 28.00 Under Graduate 4 16.00 Post Graduate 1 4.00 Total 25 100.00 Devarayapuram Schooling Dropout 14 56.00 Secondary Education 3 12.00 Higher Secondary Education 6 24.00 Under Graduate 2 8.00 Post Graduate 0 0 Total 25 100.00 Ikkarai Booluvampatti Schooling Dropout 8 32.00 Secondary Education 9 32600 Higher Secondary Education 3 12.00 Under Graduate 4 16.00 Post Graduate 1 4.00 Total 25 100.00 Overall Total Schooling Dropout 38 38.00 Secondary Education 28 28.00 Higher Secondary Education 19 19.00 Under Graduate 12 12.00 Post Graduate 3 3.00 Total 100 100.00 Source: Primary Data

The table 4.2 reveals the Educational Qualification of pregnant women households of the selected panchayats. In developing countries, mother’s educational level, as indicated here by literacy status, tends to have a strong effect on the mortality of young children (Govindasamy and Ramesh 1997; Hobcraft, McDonald, and Rutstein 1984; Mosley and Chen 1984; United Nations 1985; 1991; 1998). The above table inferred that 38 percent of the total pregnant women household were schooling dropout, 28 percent were completed their secondary education; 19 percent were completed their higher secondary education, 12

percent were completed their under graduation and only 3 percent were completed their post graduation. It is observed that the majority of the respondents are in category of school dropouts. Literate mothers usually give birth to healthier babies because they themselves tend to be healthier than mothers who are illiterate. In addition, literate mothers are more likely to provide their children with a healthy environment and nutritious food than are illiterate mothers, even when other conditions are similar.

4.1.3. Occupation of the Respondents

Table 4.3: Occupation of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Un Employed 19 76.00 Agriculture 3 12.00 Private 3 12.00 Government 0 0 Self Employee 0 0 Total 25 100.00 Mathavarayapuram Un Employed 22 88.00 Agriculture 1 4.00 Private 0 0 Government 1 4.00 Self Employee 1 4.00 Total 25 100.00 Devarayapuram Un Employed 21 84.00 Agriculture 3 12.00 Private 1 4.00 Government 0 0 Self Employee 0 0 Total 25 100.00 Ikkarai Booluvampatti Un Employed 16 64.00 Agriculture 2 8.00 Private 5 20.00 Government 1 4.00 Self Employee 1 4.00 Total 25 100.00 Overall Total Un Employed 78 78.00 Agriculture 9 9.00 Private 9 9.00 Government 2 2.00 Self Employee 2 2.00 Total 100 100.00 Source: Primary Data

The table 4.3 provides the occupation of pregnant women households of selected panchayats. It is inferred from the table that 78 percent of the respondents were unemployed, 9 percent of the respondents were belongs to agricultural and allied activities, 9 percent of the respondents were got their employment in private companies, 2 percent of the respondents were got their employment in Government and 2 percent were self employed. Most of the pregnant women are unemployed which may be stimulated for psychological problems and other family problems.

4.1.4. Religious Classification of the Respondents

Table 4.4: Religious Classification of the Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam 25 100.00 Hindu 25 100.00 Islam 0 0 Christian 0 0 Total 25 100.00 Mathavarayapuram Hindu 25 100.00 Islam 0 0 Christian 0 0 Total 25 100.00 Deverayapuram Hindu 25 100.00 Islam 0 0 Christian 0 0 Total 25 100.00 Ikkarai Booluvampatti Hindu 24 96.00 Islam 0 0 Christian 1 4.00 Total 25 100.00 Overall Total Hindu 99 99.00 Islam 0 0 Christian 1 1.00 Total 100 100.00 Source: Primary Data

The Table 4.4 reveals the classification of the religion of pregnant women households of selected panchayats. It is inferred that 99 percent of the respondents were belongs to Hindu religion, 1 percent of the respondents were belongs to Christianity. It is concluded that the majority of the respondents were belongs to Hindu Religion. Religion and membership in a scheduled caste or scheduled tribe is known to affect many aspects of life in India and is likely to affect levels of infant and child mortality as well. Some of the effect of religion and caste/tribe membership on mortality may be due to differences in life-style based on traditions and beliefs. Such differences may include customary practices related to childbirth, infant feeding, and healthcare. These practices inferences the infant and child mortality rate.

4.1.5. Income wise Classification of the Respondents

Table 4.5: Income wise Classification of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Below Rs.50000 19 76.00 Rs.50001 to Rs.150000 5 20.00 Rs.150001 to Rs.250000 1 4.00 Rs.250001 & above 0 0 Total 25 100.00 Mathavarayapuram Below Rs.50000 11 44.00 Rs.50001 to Rs.150000 12 48.00 Rs.150001 to Rs.250000 2 8.00 Rs.25001 & above 0 0 Total 25 100.00 Devarayapuram Below Rs.50000 15 60.00 Rs.50001 to Rs.150000 9 36.00 Rs.150001 to Rs.250000 1 4.00 Rs.250001 & above 0 0 Total 25 100.00 Ikkarai Boluvampatti Below Rs.50000 16 64.00 Rs.50001 to Rs.150000 8 32.00 Rs.150001 to Rs.250000 1 4.00 Rs.250001 & above 0 0 Total 25 100.00 Overall Total Below Rs.50000 61 61.00 Rs.50001 to Rs.150000 34 34.00 Rs.150001 to Rs.250000 5 5.00 Rs.250001 & above 0 0 Total 100 100.00 Source: Primary Data

Table 4.5 provides the annual income of pregnant women households of selected panchayats. It is inferred that 61 percent of the respondents were earned below 50000 per annum, 34 percent of the respondents were earned between 51000 to 150000, 5 percent of the respondents were earned between 150001 to 250000 and nobody in between 250001 and above. It is observed that majority of the respondents were earned below 50000 per annum. Poverty leads to IMR fluctuation.

4.1.6. Community wise Classification of the Respondents

Table 4.6: Community wise Classification of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Backward Class 4 16.00 Most Backward Class/Denoted Class 7 28.00 Schedule Caste 11 44.00 Schedule Tribe 3 12.00 Total 25 100.00 Mathavarayapuram Backward Class 13 52.00 Most Backward Class/Denoted Class 4 16.00 Schedule Caste 2 8.00 Schedule Tribe 6 24.00 Total 25 100.00 Deverayapuram Backward Class 8 32.00 Most Backward Class/Denoted Class 8 32.00 Schedule Caste 5 20.00 Schedule Tribe 4 16.00 Total 25 100.00 Ikkarai Booluvampatti Backward Class 12 48.00 Most Backward Class/Denoted Class 2 8.00 Schedule Caste 4 16.00 Schedule Tribe 7 28.00 Total 25 100.00 Overall Total Backward Class 37 37.00 Most Backward Class/Denoted Class 21 21.00 Schedule Caste 22 22.00 Schedule Tribe 20 20.00 Total 100 100.00 Source: Primary Data

The table 4.6 provides the community of pregnant women households of selected panchayats. It is inferred that 37 percent of the respondents were belongs to BC community, 21 percent of the respondents were belongs to MBC/DC community, 22 percent of the respondents were belongs to SC community and 20 percent of the respondents were belongs to ST community. It is observed that the majority of the respondents belong to backward class category.

4.1.7. Family types of the Respondents

Table 4.7: Types of Family of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Joint Family 17 68.00 Nuclear Family 8 32.00 Total 25 100.00 Mathavarayapuram Joint Family 15 60.00 Nuclear Family 10 40.00 Total 25 100.00 Devarayapuram Joint Family 21 84.00 Nuclear Family 4 16.00 Total 25 100.00 Ikkarai Booluvampatti Joint Family 19 76.00 Nuclear Family 6 24.00 Total 25 100.00 Overall Total Joint Family 72 72.00 Nuclear Family 28 28.00 Total 100 100.00 Source: Primary Data

The table 4.7 reveals the family types of pregnant women households of selected panchayats. Types of family have been classified in to nuclear and joint family the table clearly stated that 72 percent of the respondents were preferred joint family and 28 percent of the respondents were preferred nuclear family. It is observed majority of the respondents preferred joint family.

4.1.8. Residential Status of the Respondents

Table 4.8: Residential Status of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Own House 23 92.00 Rent House 2 8.00 Total 25 100.00 Mathavarayapuram Own House 25 100.00 Rent House 0 0 Total 25 100.00 Devarayapuram Own House 20 80.00 Rent House 10 20.00 Total 25 100.00 Ikkarai Booluvampatti Own House 21 84.00 Rent House 4 16.00 Total 25 100.00 Overall Total Own House 89 89.00 Rent House 11 11.00 Total 100 100.00 Source: Primary Data

The table 4.8 provides the residential status of pregnant women households of selected panchayats. It is inferred that 89 percent of the respondents were resided in their own house and 11 percent of the respondents were resided in rental house. It is observed that majority of the respondents resided in their own house.

4.1.9. Living conditions of the Respondents

Table 4.9: Living conditions of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Concrete 16 64.00 Tiled 5 20.00 Terrace 4 20.00 Thatched 0 0 Total 25 100.00 Mathavarayapuram Concrete 15 60.00 Tiled 8 32.00 Terrace 2 8.00 Thatched 0 0 Total 25 100.00 Devarayapuram Concrete 7 28.00 Tiled 11 44.00 Terrace 5 20.00 Thatched 2 8.00 Total 25 100.00 Ikkarai Booluvampatti Concrete 8 32.00 Tiled 9 36.00 Terrace 5 20.00 Thatched 3 12.00 Total 25 100.00 Overall Total Concrete 46 46.00 Tiled 33 33.00 Terrace 16 16.00 Thatched 5 5.00 Total 100 100.00 Source: Primary Data

The table 4.9 reveals the living conditions of pregnant women households. It is inferred that 46 percent of the respondents were lived in concrete house, 33 percent of the respondents were lived in tiled house, 16 percent of the respondents were lived in Terrace house and 5 percent of the respondents were lived in thatched house. It is observed that the majority of the respondents were lived in concrete house.

4.1.10. Size of Landholding of the Respondents

Table 4.10: Size of Landholding of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Landless 2 8.00 Marginal 20 80.00 Large 3 12.00 Total 25 100.00 Mathavarayapuram Landless 0 0 Marginal 24 96.00 Large 1 4.00 Total 25 100.00 Deverayapuram Landless 4 16.00 Marginal 20 80.00 Large 1 4.00 Total 25 100.00 Ikkarai Booluvampatti Landless 2 8.00 Marginal 21 84.00 Large 2 8.00 Total 25 100.00 Overall Total Landless 8 8.00 Marginal 85 85.00 Large 7 7.00 Total 25 100.00 Source: Primary Data

The table 4.10 provides the size of landholding of pregnant women households. It is inferred that 8 percent of the respondents were not having lands; 85 percent of the respondents were having marginal lands and 7 percent of the respondents were having large size of lands. It is observed that the majority of the respondents were having marginal size of lands.

4.1.11. Toilet Facilities of the Respondents

Table 4.11: Toilet Facilities of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Common Toilet 1 4.00 Separate Toilet 13 52.00 Open Toilet 11 44.00 Total 25 100.00 Mathavarayapuram Common Toilet 2 8.00 Separate Toilet 18 72.00 Open Toilet 5 20.00 Total 25 100.00 Deverayapuram Common Toilet 0 0 Separate Toilet 8 32.00 Open Toilet 17 68.00 Total 25 100.00 Ikkarai Booluvampatti Common Toilet 0 0 Separate Toilet 7 28.00 Open Toilet 28 72.00 Total 25 100.00 Overall Total Common Toilet 3 3.00 Separate Toilet 46 46.00 Open Toilet 51 51.00 Total 25 100.00 Source: Primary Data

The table 4.11 provides the toilet facilities of pregnant women households of selected panchayats. It is inferred 3 percent of the respondents make use of common toilets; 46 percent of the respondents make use of individual (separate) toilet and 51 percent of the respondents make use of open toilets. It is observed that the majority of the respondents make use of open toilet.

4.1.12. Selection Preference of Hospitals by the Respondents

Table 4.12: Selection Preference of Hospitals by the Respondents Panchayats No. of Respondents Percentage (%) Theethippalayam Self Decision 8 32.00 Family Doctor Recommendation 8 32.00 Friends and Relatives Recommendation 6 24.00 Beneficiaries Recommendation 3 12.00 Total 25 100.00 Mathavarayapuram Self Decision 8 32.00 Family Doctor Recommendation 11 44.00 Friends and Relatives Recommendation 6 24.00 Beneficiaries Recommendation 0 0 Total 25 100.00 Devarayapuram Self Decision 13 52.00 Family Doctor Recommendation 9 36.00 Friends and Relatives Recommendation 1 4.00 Beneficiaries Recommendation 2 8.00 Total 25 100.00 Ikkarai Boluvampatti Self Decision 8 32.00 Family Doctor Recommendation 7 28.00 Friends and Relatives Recommendation 10 40.00 Beneficiaries Recommendation 0 0 Total 25 100.00 Overall Total Self Decision 37 37.00 Family Doctor Recommendation 35 35.00 Friends and Relatives Recommendation 23 23.00 Beneficiaries Recommendation 5 5.00 Total 100 100.00 Source: Primary Data

The table 4.12 reveals the selection of hospital of pregnant women households of selected panchayats. It is inferred that 37 percent of the respondents have taken Self Decision, 35 percent of the respondents were followed family doctor recommendation, 23 percent of the respondents were followed their friends and relatives recommendation and 5 percent of the respondents were followed the Beneficiaries Recommendations for selection of hospital. It observed that the majority of the respondents made their Self Decision.

4.1.13. Hospital Selection by the Respondents

Table 4.13: Hospital Selection by the Respondents Panchayats No. of Respondents Percentage (%) Theethippalayam Government Hospital 23 92.00 Private Hopital 2 8.00 Total 25 100.00 Mathavarayapuram Government Hospital 23 92.00 Private Hopital 2 8.00 Total 25 100.00 Devarayapuram Government Hospital 23 92.00 Private Hopital 2 8.00 Total 25 100.00 Ikkarai Booluvampatti Government Hospital 22 88.00 Private Hopital 3 12.00 Total 25 100.00 Overall Total Government Hospital 91 91.00 Private Hopital 9 9.00 Total 100 100.00 Source: Primary Data

The table 4.13 provides the types of hospital of pregnant women households of selected panchayats. It is inferred 91 percent of the respondents were chosen Government Hospital and 9 percent of the respondents were chosen Private Hospitals. It is observed that the majority of the respondents were chosen Government Hospitals.

4.1.14. Medical Insurance of the Respondents

Table 4.14: Medical Insurance of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Nil Insurance 7 28.00 Government Insurance 1 4.00 Private Insurance 0 0 Chief Ministers’ Medical Insurance Scheme 17 68.00 Total 25 100.00 Mathavarayapuram Nil Insurance 5 20.00 Government Insurance 0 0 Private Insurance 0 0 Chief Ministers’ Medical Insurance Scheme 20 80.00 Total 25 100.00 Devarayapuram Nil Insurance 1 4.00 Government Insurance 8 32.00 Private Insurance 0 0 Chief Ministers’ Medical Insurance Scheme 16 64.00 Total 25 100.00 Ikkarai Booluvampatti Nil Insurance 3 12.00 Government Insurance 0 0 Private Insurance 0 0 Chief Ministers’ Medical Insurance Scheme 22 88.00 Total 25 100.00 Overall Total Nil Insurance 16 16.00 Government Insurance 9 9.00 Private Insurance 0 0 Chief Ministers’ Medical Insurance Scheme 75 75.00 Total 100 100.00 Source: Primary Data

The table 4.14 reveals the medical insurance benefit obtained by the pregnant women households of selected panchayats. It is inferred 16 percent of the respondents were not aware of medical insurance and they were not obtained the same, 9 percent of the respondents were obtained Government Insurance, 75 percent of the respondents were obtained Chief Minister Medical Insurance Schemes and none of the respondents obtained private insurance. It is observed the most of the respondents were obtained Chief Minister Medical Insurance Schemes.

4.1.15. Infant Death of Pregnant Women Households

Table 4.15: Infant Death of Pregnant Women Households Panchayats No. of Respondents Percentage (%) Theethippalayam Yes 3 12.00 No 22 88.00 Total 25 100.00 Mathavarayapuram Yes 4 16.00 No 21 84.00 Total 25 100.00 Devarayapuram Yes 4 16.00 No 21 84.00 Total 25 100.00 Ikkarai Booluvampatti Yes 2 8.00 No 23 92.00 Total 25 100.00 Overall Total Yes 13 13.00 No 87 87.00 Total 100 100.00 Source: Primary Data

The table 4.15 provides the infant deaths in past of pregnant women households of selected panchayats. It is inferred that 13 percent of pregnant women household said previous infant death happened and 87 percent of pregnant women household said infant death has not happened in the preceding years. The majority of the respondents said the infant death has not happened in the preceding years.

4.1.16 HEALTH SERVICES AVAILABILTIY

Thondamuthur block is a revenue block in Coimbatore district, Tamilnadu. It is immediate vicinity to Narasipuram road around 15Kms from Coimbatore city. Thennamanalur, Vedapatti, Sundapalayam, Narasipuram, Poochiyur, Devarayipuram, Viraliyur, Mathampatty, Pooluvapatty and Alandurai are vicinity to Thondamuthur Block. The census of the year 2011 stated that Thondamuthur population is around 1,24,390, out of that 52 percent were male and rest of the 48 percent were females. The Literacy rate in Thondamuthur block was 68 percent of the total population, out of which male literacy consists of 79 percent and the female literacy, include 56 percent, which is more than that of National Average 59.5 Percent. In the study area 15 percent of the total population were

belongs to the age group of less than 6 years. It was found that 10668 male agriculture labours and 646 female agriculture labours were in Thondamuthur Block. There is a well organised network of Primary Health Centres is situated at Thondamuthur Block for having medical care. Hence the people need not travel beyond 15 Kms to procure medical care for their health. The population of the study initially conducted in all Primary Health Centres at Thondamuthur Block in Coimbatore District. In addition to that there are three primary health centres located at Kaliveerapalayam, Pooluvapatty and Karamadai. Each PHC operates through different sub centres at different villages in the Thondamuthur Block. The Thondamuthur block has created a distinct name in the health map of Coimbatore district by organising medical camp, creating awareness about health care, educating people in undertaking pre-natal and Post-natal care and having a well equipped hospital with adequate staff to handle emergencies. Kaliveerapalayam primary health centre include five sub centres with a total population of 46,672. Pooluvapatty primary health centre consists of seven sub centres with a total population of 43,044. Karamadai Primary health centre consists of five sub centres with a total population of 46,325. Each PHC includes two sub centres, one is immediate vicinity to Primary Health Centres and another one is far away from Primary Health Centres have been selected for the study. Poochiyur, Alandurai and Mathampatty are immediate vivinity to Primary Health Centres and Narasipuram, Sadivayal and Chettipalayam were far away form the said Primary Health Centres. The health care system in Thondamuthur block is owned by the state government of Tamilnadu. The Thondamuthur Block consists of few private hospitals and clinics for providing medical service. District Health Centres are responsible for curative activities, preventive programme, surveillance and health services. District hospitals are supposed to serve as referral institutions for all polyclinics in the districts. They are also providing training facilities for health staff working in polyclinics and Community health centres in the district. Community Health Centres (CHC) are responsible for providing health care including preventive, ambulatory, imapatient services and for referring complicatory causes to high levels for medical care.

4.1.17 ACCESSIBILTY

In Thondamuthur block, the primary health centres have been classified as Sub- Centre, Primary health centre and Community health centre; and the services of these three centres are also assisted by the presence of Rural Welfare Centres. The Sub-centres provide first level contact between the primary health centres and community health centres. Tasks assigned to these health institutions vary from state to state. In some state the Auxiliary Nursery Midwifes (ANMs) stationed in sub-centres to perform the deliveries and refer the complicated cases to Primary Health Centres. In some state emphasis inter-personal communication leads behavioural change in maternal and child health, family welfare, nutrition, immunisation, diarrhoeal control and control of communicable disease. The Primary Health Centres consists of referral units to five to six sub-centres. The activities of PHC include curative, preventive and promotive health care as well as family welfare services. Community Health Centres serve as fireferral units (Furs) for four to five PHCs and also provide facilities for obstetric care and specialist consultations. According to norms each CHC should have at least 30 beds, one operation theatre, X-ray machine, labour room, laboratory facilities, in addition to that it has to be staffed with four medical specialists like Surgeon, Physician, Gynaecologist and Paediatrician. The Primary Health Centres provide curative, preventive and promotive health and family welfare services in rural area for a population of about 30,000. PHC should have essential infrastructure, staff, equipments and supplies. PHC must also have critical infrastructure like continuous water supply, electricity, labour room, laboratory, telephone, functional vehicle, etc. PHC ought to have at least one medial officer, one laboratory technician and health assistants both males and females. PHC must hold critical equipments like deep freezer, vaccine carrier, BP instrument, autoclave, etc. Supply of contraceptives, normal delivery kit/labour room kit, essential obstetric kit, all vaccines, IFA tablets and ORS packets. Primary Health Centres have the major responsibility of providing both preventive and curative health care services in the area. Primary Health Centres have limited facilities and expertises hence they cannot provide complete obstetric care to woman. Some of the upgraded PHCs and Community Health Centres have been categorised as first referral units and these facilities have been provided with specialized equipments and kits to provide maternal health care, particularly obstetric care (EmOC). Emergency

cases can be referred form the sub-centres and primary health centres to these FRUs. PHC functioning on 24x7 basis in Thondamuthur Block.

4.1.18 VILLAGE HEALTH NURSES

In the study area, Village Health Nurses (VHNs) were moderately doing well. The respondents not only make use of VHNs for acquiring the benefit of government free service programme, but also procuring the monetary benefits during the pregnancy period. They gave importance for sending data to their higher officials. During the field survey, VHNs reported that there are two factors influence the cause of high level of Infant Mortality Rate (IMR) in Thondamuthur village which are 1) Social positioning inclusive of households, education and Occupation and 2) Mother’s Education. Village Health Nurses were performing well in the study area for trying to reduce the IMR. But the psychological factors were influencing more than that of other factors during the pregnancy period and the same leads to high level of IMR in the study area.

4.1.19 THE GROWTH CHART

In Thondamuthur block, the general aim of the growth chart is to describe the child’s birth weight, physical growth and breast feeding as well as associated factors, from birth to 24 months of age. At the individual level we found birth is rapid economic and technological development. At the individual level we found that child birth weight is associated with household economy and literacy of mother. Also child birth and growth were statistically significant and associated with economic conditions and mother’s education. In the study area, we found that Low Birth Weight (LBW) of a child has been defined by WHO, the normal weight of a child at birth is to be less than 2,500 gm (5.5 pounds).

AS per field survey, the live babies with median weight are 3000 gm and LBW is 1500 gm. The study reveals that 60 percent of the pregnancy women were affected by the psychological discomfort which led to poor intake of food during the pregnancy period. The mother’s education is very important factor for the breastfeeding for the child for the first 6 months. In addition to that 38 percent of the respondents were a school dropout which leads to Low Birth Weight of the child in the study area.

4.1.20 AFFORDABILITY

As far as health expenditure in rural area is concerned affordability is playing an important role. The results reveal that there is an inadequate spending capacity of the respondents for their health in the study area. Since 61 percent of the respondents were earned below 50000 p.a., 34 percent of the respondents were earned between 51000 to 150000 p.a., 5 percent were earned between 150001 to 250000 p.a. and none of the respondents lies in between 250001 & above.

4.1.21 HEALTH UTILITY

Utilities are cardinal values that represent the strength of an individual’s performance for specific related outcomes. The results of the study reveal that 90 percent of respondents were having treatment in Primary Health Centres and 10 percent of the respondents were having their treatment in Private hospitals. In the study area, there is no Religious and NGOs Hospital. In Tamilnadu we find 24 hours delivery services are reported to be available. As per field survey reveals that 37 percent of the respondents have taken self decision, 35 percent of the respondents were followed their family doctor recommendation, 23 percent of the respondents were followed their friends and relatives recommendations and 5 percent of the respondents were followed their Beneficiaries Recommendations for hospital decision. It is observed that the majority of the respondents made their self decision according to their economic conditions in the study area. In addition to the said result, it is informed that 91 percent o f the respondents were chosen government hospitals and 9 percent of the respondents were chosen private hospitals for obtaining their heath care services. It is observed that the majority of the respondents were chosen Primary Health Centres.

4.1.22 CARE OF THE HOSPITALS

The Primary Health Care Centres run by the government of Tamilnadu. The primary health centres are upgrading their infrastructure and other facilities for the benefit of the public health.

4.1.23 PREGNANCY PERIOD (10/10 RULES)

As per field survey, 90 percent were aware about the post pregnancy (10/10 rules), Village Health Nurses were trying to create awareness about 10/10 rules

to the respondents during the pregnancy period. The respondents were not able to follow the rules. Hence it creates many problems for the child and mother. The study reveals that 80 percent of the respondents were affected through the psychological discomfort from mother-in-laws and family members, 60 percent of the respondents were affected due to husband habits like drinking alcohol and smoking, 80 percent of the respondents were not aware of exercise practices, 95 percent of the respondents were not wearing comfortable dresses and other things, 90 percent of the respondents were not aware about the cleanliness and 80 percent of the respondents were procuring counter medicines and herbal medicines without consulting medical practitioners. Hence it is difficult to follow the 10/10 rule for the pregnant women in the rural area.

4.1.24 SOCIAL ASPECTS

The Literacy is one of the important factors in social aspects and health aspects. Hence, literate mother usually gives birth to healthier babies because they themselves tend to be more healthier than that of illiterate mother. In addition to that literate mother are more likely to provide their children with a healthy environment and nutritious food than an illiterate mother. As per field survey, 38 percent of the respondents were school dropouts among the total pregnant women households, 28 percent of the respondents were completed their secondary education, 19 percent of the respondents have completed their higher secondary education, 12 percent of the respondents have completed their under graduate and only 3 percent of the respondents have completed their post graduation. It is observed that majority of the respondents are in the category of school dropouts. Also it is inferred that 99 percent of the respondents were belongs to Hindu religion, 1 percent of the respondents were belongs to Christian religion and it is concluded that the majority of the respondents were belongs to Hindu religion. In addition to that 37 percent of the respondents were belongs to the Backward class community, 21 percent of the respondents were belongs to the Most Backward class community, 22 percent of the respondents were belongs to the Scheduled class community, 20 percent of the respondents were belongs to the Scheduled Tribe community and it is observed that majority of the respondents were belong to Backward class community.

In addition, the study stated that 72 percent of the respondents prefer joint family, 28 percent of the respondents prefer nuclear family and it is observed that majority of the respondents prefer Joint family. 89 percent of the respondents were residing in their own house, 11 percent of the respondents were residing in rental house and it is observed that majority of the respondents were residing in their own house.

The study reveals that 46 percent of the respondents were living in concrete house, 33 percent of the respondents were living in tiled house, 16 percent of the respondents were living in terrace house, 5 percent of the respondents were living in thatched house and it is observed that majority of the respondents were living in concrete house. In addition to that it is observed that 13 percent of the respondents among pregnant women household said that infant death happened earlier and 87 percent of the respondents among women household said that infant death not happened in the preceding years.

4.1.25 FINANCIAL ASPECTS

The financial crisis is an important factor for determining the health expenditure of a family. As per filed survey, the respondents were very week in financial aspects. Hence, many respondents were expecting the government free schemes for their medical expenses. The result stated that 8 percent of the respondents not having any land, 85 percent of the respondents were having marginal land and 7 percent of the respondents were having large size of lands. It is observed that the majority of the respondents were having marginal size of landholding. As far as medical insurance is concerned 16 percent of the respondents were not aware of medical insurance, 9 percent of the respondents were obtained Government insurance, 75 percent of the respondents were obtained Chief Minister Medical Insurance Schemes and none of the respondents have obtained private insurance. It is observed that majority of the respondents were obtained Chief Minister Medical Insurance Schemes.

4.2. Part - 2: Mediating Cause for High Level cause for the Infant Mortality in the Study Area

This section consists of the statistical analysis and testing the hypotheses of the present study. Primary and secondary data were properly analysed for the entire sample. Data analysis were performed with Statistical Package for Social Sciences (SPSS) using techniques that included descriptive statistics, correlation analysis and AMOS package for Structural Equation Modeling (SEM) and Bayesian estimation and testing (Senthilkumar. N and Arulraj. A, 2011), AMOS 20.0 (Arbuckle and Wothke 2006), a computer programme for formulating, fitting and testing SEM to observed/primary data, was used for SEM and the data preparation was conducted with SPSS 20.0. This section provides an empirical study on Mediating Cause for High Level of Infant Mortality Rate in the study area.

4.2.1. “MEDIATING CAUSE FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Model

The analysis presents the constructions and validation of Structural Equation Modeling (SEM) of ‘Mediating Cause for High Level Cause for the Infant Mortality Mediated model’ with the dimensions of Practitioners Services (PS), Hospital Services in Outpatients (HSO), Hospital Services in Inpatients (HSI), Social Problems (SP), Infrastructure Facilities (IF) and Economic Problems (EP). Psychological Discomfort (PD) is the Mediating factor and outcome of High Level cause for the Infant Mortality at Thondamuthur Block in Coimbatore District with the help of AMOS graphics environment.

4.2.2. Regression Mediated Structural Equation Model for “MEDIATING CAUSE FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY”

In hierarchical regression, the predictor variables are entered in sets of variables according to a pre-determined order that may infer some causal or potentially mediating relationships between the predictors and the dependent variable (Francis, 2003). Such situations are frequently of interest in the social sciences. The logic involved in hypothesizing mediating relationships is that “The Independent Variable Influences the Mediator Which, In Turn, Influences the Outcome” (Holmbeck, 1997). However, an important pre-condition for examining mediated relationships is that the independent variable is significantly associated with the dependent variable prior to testing any model for mediating variables

(Holmbeck, 1997). Of interest is the extent to which the introduction of the hypothesized mediating variable reduces the magnitude of any direct influence of the independent variable on the dependent variable. Hence the researcher empirically tested the hierarchical regression for the model conceptualized in figure 4.1 with the aid of AMOS 20.0 graphics environment.

Figure 4.1: Shows the AMOS Output with Regression Weights of “MEDIATING CAUSE FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Mediated Model

The Regression analysis reveals that the various dimensions are influencing the high level cause for the infant mortality at Thondamuthur Block in Coimbatore District. The visual representations of results suggest that the relationships between the various dimensions and Mediated factor Psychological Discomfort at Thondamuthur Block in Coimbatore District. Practitioners services is .14 followed by Hospital services in Outpatients is .57, Hospital services in Inpatients is .60, Social Problems is .21, Infrastructure Facilities is .33 and Economic problems is 1.13. The r2 value .07 confirms that the Psychological Discomfort is the mediating

factor. Practitioners’ services, Hospital services in Outpatients, Hospital services in Inpatients, Social problems and Infrastructure Facilities resulted significant impact on mediated factor, Psychological Discomfort. Economic Problem resulted insignificant impact on the mediated factor. The analysis clearly stated that Psychological Discomfort is the Mediated factor which determines the high level cause for the Infant Mortality. The results of the SEM suggested that the government should concentrate more on Psychological Discomfort than other dimensions such as Practitioners’ services, Hospital services in Outpatients, Hospital services in Inpatients, Social problems, Infrastructure Facilities and Economic Problem. Psychological Discomfort is the Mediated factor for High level Cause for the Infant Mortality and the same has been scientifically proved with the help of above SEM.

4.2.3. Bayesian Estimation and Testing for Regression Mediated Structural Equation Model of “MEDIATING CAUSE FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY”

Many management scientist are most familiar with the estimation of these models using software that analyses covariance matrix of the observed data (e.g. LISREL, AMOS, EQS), the researcher adopt a Bayesian approach for estimation and inference in AMOS 20.0 environment (Senthilkumar. N and Arulraj. A, 2011; Arbuckle and Wothke, 2006). Since, it offers numerous methodological and substantive advantages over alternative approaches (See Appendix - III).

4.2.4. Posterior Diagnostic Plots of “MEDIATING CAUSE FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY”

To check the convergence of the Bayesian MCMC method the posterior diagnostic plots are analysed. The following figures (figure 4.2 and 4.3) show the posterior frequency polygon distribution and posterior frequency histogram distribution of the parameters across the 94000 samples. The Bayesian MCMC diagnostic plots reveals that for all the figures the normality is achieved, so the structural equation model fit is accurately estimated.

Figure 4.2: Posterior frequency Polygon distribution of the Mediating Factor (IMR) and (PD) Regression Weight (W13)

Figure 4.3: Posterior frequency Histogram distribution of the Mediating Factor (IMR) and (PD) Regression Weight (W13)

The trace plot also called as time-series plot shows the sampled values of a parameter over time. This plot helps to judge how quickly the MCMC procedure converges in distribution. The following figure (figure 4.4) shows that the trace plot of the mediated factor Psychological Discomfort (PD) with other dimension across 94000 samples. If we mentally break up this plot into a few horizontal sections, the trace within any section would not look much different from the trace in any other section. This indicates that the convergence in distribution takes place rapidly and MCMC procedure very quickly forgets its starting values.

Figure 4.4: Posterior frequency Trace plot of the Mediating (IMR) and (PD) Regression Weight (W13)

To determine how long it takes for the correlations among the samples to die down, autocorrelation plot which is the estimated correlation between the sampled value at any iteration and the sampled value k iterations later for k = 1, 2, 3,…. is analysed for the “MEDIATING CAUSE FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY”. The figure 4.5 shows the correlation plot of mediated factor Psychological Discomfort (PD) with other dimension across 94000 samples. The figure exhibits that at lag 100 and beyond, the correlation is effectively 0. This indicates that by 90 iterations, the MCMC procedure has essentially forgotten its starting position. Forgetting the starting position is equivalent to convergence in distribution. Hence it is ensured that convergence in distribution was attained and that the analysed samples are indeed samples from the true posterior distribution.

Figure 4.5: Posterior frequency Autocorrelation plot of the Mediating Factor (IMR) and (PD) Regression Weight (W13)

Even though marginal posterior distributions are very important, they do not reveal relationships that may exist among the two parameters. The summary table provided in Appendix - III and the posterior frequency plots given in the figure 4.6 and figure 4.7 describe only the marginal posterior distributions of the parameters. Hence to visualize the relationships among pairs of Parameters in two-dimensional. The posterior two - dimensional surface plots and posterior two - dimensional histogram plots following figures (figure 4.6 and figure 4.7) provides bivariate marginal posterior plots of the “MEDIATING CAUSE FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” for the overall mediated factor Psychological Discomfort (PD) with other dimensions across 94000 samples. From the two figures it is revealed that the two dimensional surface plot and histogram plot also signifies the interrelationship between the mediating variable Psychological Discomfort (PD) with the other dimensions of High Level Cause for the Infant Mortality.

Figure 4.6: Two-dimensional Surface plot of the marginal posterior frequency distribution of the mediating factor (PD with (IMR) and (HSI) Regression Weight (W9) and (W13)

Figure 4.7: Two-dimensional Histogram plot of the marginal posterior frequency distribution of the mediating factor (PD) with (IMR) and (HSI) Regression Weight (W9) and (W13)

The following figure 4.8 shows that the two-dimensional contour plots of the mediated factor Psychological Discomfort (PD) with other dimension across 94000 samples. Ranging from dark to light, the three shades of gray represent 50%, 90% and 95% credible regions, respectively. From the figure, it is revealed that the sample citizen’s responses are normally distributed.

Figure 4.8: Two-dimensional Contour plot of the marginal posterior frequency distribution of the mediating factor (PD) with (IMR) and (HSI) Regression Weight (W9) and (W13)

The various diagnostic plots featured from figure 4.2 to figure 4.8 of the Bayesian estimation of convergence of MCMC algorithm confirms the fact that the convergence takes place and the normality is attained. Hence absolute fit of the “MEDIATING CAUSE FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” which is empirically tested with mediating factor with the dimensions Psychological Discomfort (PD) with the other dimensions of High Level cause for the Infant Mortality. Psychological Discomfort is the Mediated factor for High level Cause for the Infant Mortality and the same has been scientifically proved with the help of above SEM. Hence Psychological Discomfort should be mandatory because Psychological Discomfort is Mediating cause for High level cause for the Infant Mortality at Thondamuthur block in Coimbatore district.

4.3. MEDIATING CAUSES FOR HIGH LEVEL CAUSE FOR THE INFANT MORTALITY LATENT MODEL

Mediating Cause for High Level cause for the Infant Mortality with the help of SEM Model, the researcher could find out that, the Mediating effects on various dimensions. This analysis has been done with the help of primary data from the respondents in the study area. Let us see, the results of various dimensions influence on High Level of Infant Mortality Rate in the study area.

4.3.1. Mediating Cause for High Level Cause for the Infant Mortality at Thondamuthur Block in Coimbatore District

4.3.1.1. Structural Equation Modeling of Overall Mediated ‘HIGH LEVEL CAUSE FOR THE INFANT MORTALITY’ Latent Model

We have defined its dimension based on the setting used to explore the construct. If Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Latent Model is to be applicable in the Indian context, the dimensions and the sub dimensions on High Level cause for the Infant Mortality have to be reliable and valid in measuring High Level cause for the Infant Mortality at Thondamuthur Block in Coimbatore District. The Latent Model examines the relative importance of dimensions of High Level cause for the Infant Mortality and Psychological Discomfort (PD) is the mediating factor for the cause of High Level cause for the Infant Mortality at Thondamuthur Block in Coimbatore District.

The Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Latent Model examines the relative importance of Psychological Discomfort (PD) as a mediating cause for the High Level Cause for the Infant Mortality at Thondamuthur Block in Coimbatore District. Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Mediated Latent Model includes the measurement of sub dimensions of High Level cause for the Infant Mortality are as follows:

There are eight dimensions have been used in the present study which are

I. Practitioners Services (PS) dimension includes several sub dimensions which are Medical Records (PS1), Pharmacy Services (PS2), Medical Equipments (PS3), Doctors Services (PS4), Nursing Services (PS5) and Insurance Coverage Facilities

(PS6); II. Hospital Services in Outpatients (HSO): dimension consists of several sub dimensions which are Seating (HSO1), Waiting (HSO2), Emergency Services (HSO3), Diagnostic Services Locations (HSO4), Cleanliness of Outpatients departments (HSO5), Public Toilets (HSO6), Wheel Chair/Stretcher (HSO7) and Restaurant (HSO8); III. Hospital Services in Inpatients (HSI) dimension includes several sub dimensions which are Room Space, Amenities and Furniture (HSI1), Lighting (HSI2), Wall Colour (HSI3), Bath/Toilet Facility (HSI4), Hot Water Facilities (HSI5), Attenders (HSI6), Diet Services (HSI7) and Housekeeping (HSI8; IV. Social Problems (SP) consists of several sub dimensions which are Child Marriage (SP1), Gender (SP2), Discrimination (SP3), Less interest on Female Baby (After Scanning) (SP4), Caste (SP5), Religion (SP6), Social Structure (SP7), Cultural Norms (SP8), Value System (SP9) Inter-Caste Marriage (SP10) and Cultural Shift (SP11); V. Infrastructure Facilities (IF) dimension includes several sub dimensions which are Ambulance Services (IF1), Hospital Infrastructure (IF2), Poor Sanitation (IF3), Hygiene (IF4), Safe Drinking Water (IF5), Distance of Hospital Services (IF6), Distance of Hospital Location (IF7), Distance of Ambulance Services 15 km (IF8) and Lack of Transport Facilities (IF9); VI. Psychological Discomfort (PD) consists of several sub dimensions which are Emotion (PD1), Social Problems (PD2), Financial Problems (PD3), Husband (PD4), Mother - in – law (PD5), Relatives of Husband’s Family (PD6), Lack of Parents Support (PD7), Verbal use by others (PD8), Problems Faced At Work Place Daily (PD9), Sexual Harassment from colleagues and Higher Officials (PD10), Over Crowded Public Transport System (PD11), Lack of Time Management (PD12), Vulnerable to Working Conditions Across Diverse Occupation Informal Sectors (PD13), Varsity of Health Hazards Informal Sectors (PD14), Continually Sexual Inducement by During the Pregnancy (PD15), Continually Drank and Sexual Inducement by During the Pregnancy (PD16) and No Long Gap for Another Baby Birth (PD17); VII. Economic Problems (EP) dimension consists of several sub dimensions which are Limited access to Cash and Credit (EP1), Nutrition (EP2), Shift into agrarian Changes (EP3), Migration (EP4), Low Income (EP5) and Industrialization (EP6); VIII. High Level of Infant Mortality Rate (IMR) dimension includes several sub dimensions which are Lack of Knowledge and Skills to Care for New Born Child (IMR1), Breast Feeding Problems (IMR2), Duration of hospital stay normal birth (IMR3), Infant Care, Genital cleaning and ear cleaning (IMR4) and finally asking to the respondents

that they are agreeing for the said factor for cause for High level cause of Infant Mortality Rate (IMR5).

After identifying a potential model that best explains the data in terms of theory and model fit, a Confirmatory Factor Analysis (CFA) using Structural Equation Modeling (SEM) was used to test the invariance of the factorial model. All tests of model invariance begin with a global test of the equality of covariance structures across groups (Joreskog, 1971). The data for all groups were analysed simultaneously to obtain efficient estimates (Bentler, 1995). The constraints include, from weaker to stronger. The study has been done in step by step manner which are (1) Model Structure, (2) Model Structure and Factor Loadings, and (3) Model Structure, Factor Loadings, and Unique Variance.

4.3.1.2. Evaluation of Model Fit

According to the usual procedures, the goodness of fit is assessed by checking the statistical and substantive validity of estimates, the convergence of the estimation procedure, the empirical identification of the model, the statistical significance of the parameters, and the goodness of fit to the covariance matrix (Senthilkumar.N and Arulraj.A, 2011). The root mean squared error of approximation (RMSEA) is selected as such a measure. Values equal to 0.05 or lower are generally considered to be acceptable (Browne and Cudeck, 1993). The sampling distribution for the RMSEA can be derived, which makes it possible to compute confidence intervals. These intervals allow researchers to test for close fit and not only for exact fit, as the χ2 does. If both extremes of the confidence interval are below 0.05, then the hypothesis of close fit is rejected in favor of the hypothesis of better than close fit. If both extremes of the confidence interval are above 0.05, then the hypothesis of close fit is rejected in favor of the hypothesis of bad fit (Senthilkumar. N and Arulraj. A, 2011). Several well-known goodness-of- fit indices (GFI) were used to evaluate model fit: the chi-square2 (χ2), the comparative fit index, the unadjusted GFI, the normal fit index (NFI), the Tucker- Lewis index (TLI), the RMSEA and the standardized root mean square error residual.

Figure 4.9: Shows AMOS path diagram output for the Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model

Figure 4.9 provides AMOS’s path diagram output for the Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model, From SEM model the decision maker can understand that Practitioners Services (PS) dimension consists of 6 sub dimensions, Hospital Services in Outpatients (HSO) dimension consists of 9 sub dimensions, Hospital Services in Inpatients (HSI) dimension consists of 9 sub dimensions, Social Problems (SP) dimension consists of 10 sub dimensions, Infrastructure Facilities (IF) dimension consists of 9 sub dimensions, Psychological Discomfort (PD) dimension consists of 17 sub dimensions, Economic Problems (EP) dimension consists of 6 sub dimensions and High Level cause for the Infant Mortality dimension consists of 5 sub dimensions. The RMSEA fit statistics for the model was 0.08, which was considered as a best fit model (Brown and Cudeck, 1993; Diamantopoulos and Siguaw, 2000). The path diagram shows the Psychological Discomfort (PD) is the mediating cause for the High Level cause of Infant Mortality. The regression co- efficient 0.15 signifies the impact of mediating factor Practitioners Services (PD) on the other Dimensions towards the cause for the High Level cause for the Infant Mortality at Thondamuthur Block in Coimbatore District, Tamilnadu.

4.3.1.3. Evaluation of “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Mediated Latent Model

The following table 4.16 provides the summary of the various goodness-of-fit statistics and other values corresponding to the Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model. Also the last column in the table provides the acceptable level for the various goodness-of- fit statistics and other values. The below table it is revealed that all the criterions of goodness-of-fit statistics and other measures of statistics are acceptable for the Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model.

Table 4.16: Summary of the Various Goodness of Fit Statistics and Other Values Corresponding to the “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model “HIGH LEVEL CAUSE FOR Acceptable THE INFANT MORTALITY” S.No. Measures of fit level for Structural Equation good fit Latent Model 1. Chi-square2 (χ2) at p 0.01 4467.671 Significant 2. Degree of freedom (d.f) 2392 Accepted 3. Comparative Fit Index (CFI) 0.425 >0.90 4. Bentler – Bonett Indes or Normed Fit 0.312 >0.90 Index (NFI) 5. Root Mean Squared error of <0.08 0.078 Approximation (RMSEA) Accepted 6. Non Centrality Parameter (NCP) 3247.265 Accepted 7. Non Centrality Parameter, Lower 3031.610 Accepted Boundary (NCPLO 90) 8. Non Centrality Parameter, Upper 3470.158 Accepted Boundary (NCPHI 90) 9. Parsimony adjusted NFI (PNFI) 0.292 Accepted 10. Parsimony adjusted CFI (PCFI) 0.397 Accepted 11. Minimum value of Discrepancy (FMIN) 56.962 Accepted 12. Lower Limit of FMIN (LO90) 30.622 Accepted 13. Upper Limit of FMIN (HI90) 35.052 Accepted 14. Browne-Cudeck Criterion (BCC) 7362.598 Accepted 15. ECVI 61.710 Accepted 16. LO90 of ECVI 59.531 Accepted 17. HI90 of ECVI 63.961 Accepted 18. MECVI of ECVI 74.370 Accepted 19. HOELTER .05 45 <= 20. HOELTER .01 45 Atleast 200 21. Regression Co-Efficient 0.15 <1.92 Source: Amos 20.0 output

4.3.1.4. Bayesian Estimation and Testing of “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model

In this section has been adopted for the procedure of assessing convergence of MCMC algorithm of maximum likelihood. To estimate the MCMC convergence the researcher has adopted two methods namely, convergence in distribution, convergence of posterior summaries. The values of posterior mean accurately estimate the “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model. From the above table the highest value of Convergence Statistics (C.S) is 1.001 which is less than the 1.002 conservative measures (Gelman et. al. 2004) (See Appendix - IV).

4.3.1.5. Posterior Diagnostic Plots of “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model

To check the convergence of the Bayesian MCMC method the posterior diagnostic plots are analysed. The following figures (figure 4.10 and figure 4.11) show the posterior frequency polygon distribution and posterior frequency histogram distribution of the parameters across the 98000 samples. The Bayesian MCMC diagnostic plots reveals that for all the figures the normality is achieved, so the structural equation latent model fit is accurately estimated. The trace plot also called as time-series plot shows the sampled values of a parameter over time.

Figure 4.10: Posterior frequency Polygon distribution of the Mediating Factor (PD) and (IMR) Regression Weight (W70)

Figure 4.11: Posterior frequency Histogram distribution of the Mediating Factor (PD) and (IMR) Regression Weight (W70)

This plot helps to judge how quickly the MCMC procedure converges in distribution. The following figure (figure 4.12) shows the trace plot of the “HIGH

LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model for the mediated factor Psychological Discomfort (PD) to High Level cause for the Infant Mortality dimension across 98000 samples. If we mentally break up this plot into a few horizontal sections, the trace within any section would not look much different from the trace in any other section. This indicates that the convergence in distribution takes place rapidly. Hence the Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model MCMC procedure very quickly forgets its starting values.

Figure 4.12: Posterior frequency Trace plot of the Mediating Factor (PD) and (IMR) Regression Weight (W70)

Figure 4.13: Posterior frequency Autocorrelation plot of the Mediating Factor (PD) and (IMR) Regression Weight (W70)

The figure 4.13 provides the correlation plot of the Overall Mediated Inclusive Growth for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model for the mediated factor Psychological Discomfort (PD) to High Level cause for the Infant Mortality dimension across 98000 samples. The figure exhibits that at lag 100 and beyond, the correlation is effectively 0. This indicates that by 90 iterations, the MCMC procedure has essentially forgotten its starting position. Forgetting the starting position is equivalent to convergence in distribution. Hence it is ensured that convergence in distribution was attained and that the analysed samples are indeed samples from the true posterior distribution. Even though marginal posterior distributions are very important, they do not reveal relationships that may exist among the two parameters. The summary table provided in Appendix - IV and the posterior frequency plots given in the figure 4.14 and figure 4.15 describe only the marginal posterior distributions of the parameters. Hence to visualize the relationships among pairs of Parameters in two-dimensional. The posterior frequency surface plot and posterior frequency histogram plot following figures (figure 4.14 and figure 4.15) provides bivariate marginal posterior plots of the Overall Mediated for “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model for the mediated factor Psychological Discomfort (PD) with other dimensions across 98000 samples.

Figure 4.14: Two-dimensional Surface plot of the marginal posterior frequency distribution of the mediating factor (PD) and (IMR) and (HSI) Regression Weight (W68) and (W70)

Figure 4.15: Two-dimensional Histogram plot of the marginal posterior frequency distribution of the mediating factor (PD) and (IMR) and (HSI) Regression Weight (W68) and (W70)

From the two figures it is revealed that the two dimensional surface plot and histogram plot also signifies the interrelationship between the mediating variable Psychological Discomfort (PD) with the other dimensions of High Level cause for the Infant Mortality and Hospital Services in Inpatient. The following figure 4.16 displays the two-dimensional plot of the bivariate posterior frequency distribution density across 98000 samples. Ranging from dark to light, the three shades of gray represent 50%, 90% and 95% credible regions, respectively. From the figure, it is revealed that the sample citizen’s responses are normally distributed. The various diagnostic plots featured from figure 4.10 to figure 4.16 of the Bayesian estimation of convergence of MCMC algorithm confirms the fact that the convergence takes place and the normality is attained. Hence absolute fit of “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model.

Figure 4.16: Two-dimensional Contour plot of the marginal posterior frequency distribution of the mediating factor (PD) and (IMR) and (HSI) Regression Weight (W68) and (W70)

From the “HIGH LEVEL CAUSE FOR THE INFANT MORTALITY” Structural Equation Latent Model which is empirically tested with mediating factor with the dimensions Practitioners Services (PD) Hospital Services in Outpatients (HSO), Hospital Services in Inpatients (HSI), Social Problems (SP), Infrastructure Facilities (IF), Economic Problems (EP) and High Level cause of Infant Mortality Rate (IMR) it is evident that the High Level cause for the Infant Mortality should concentrate on the Psychological Discomfort (PD) is the most important aspect of High Level cause for the Infant Mortality at Thondamuthur Block in Coimbatore District, Tamil Nadu.

It is probable that a significant proportion of the remaining obstetric morbidity is related to the social and psychological background and lifestyle of pregnant women. These factors include socio-demographic characteristics of the woman (Dott & Fort 1975; Brennan & Lancashire 1978; Eisner et al. 1979; Hendershot 1979; Osbourne et al. 1981; Robinson et al. 1982; Naeye & Peters 1982; Carn- Hill et al. 1983; Murphy et al. 1984; Ericson et al. 1984), her attitude to the pregnancy (Heinstein 1967; Pohlman 1969; Laukaran & van den Berg 1980), her mental health state (Gunter 1963; Nuckolls et al. 1972; Jones 1978; Standley et al. 1979; Newton et al. 1979), and such behavioural factors as cigarette smoking (Meyer et al. 1976; Rantakallio 1979; Harlap & Shiono 1980), alcohol consumption (Jones et al. 1974; Hanson et al. 1976; Ouellette et al. 1977; Olegsard et al. 1979; Harlap & Shiono 1980; Kline et al. 1980; English & Bower 1983), analgesic use (Turner & Collins 1975) or the decision to work during pregnancy (Waldron et al. 1982; Chamberlain & Garcia 1983; Mamelle et al. 1984).

The generic "stress" or "anxiety" construct was formulated from several instruments or variables: a measure of pregnancy symptoms; a stress measure which is a modification of the Life Events Inventory (Holmes and Rahe 1967), which includes items from the Hassles Scale Anxiety Scale Questionnaire (Calteli 1957); four separate subscales (Maternal Attitude to Pregnancy Instrument) (Blau et al. 1964). Self esteem was assessed by the Rosenberg instrument (Rosenberg 1965); loci of control, by the sex role attitudes were evaluated by the Cole instrument (Cole 1979).

In recent years a handful of key epidemiological studies have generated discussion on the application of econometric methods to overcome its associated problems (Briscoe, Akin et al. 1990).

4.4. Results of SEM Model

The SEM models provide a degree of covariance and invariance’s of sub- dimensions in determining the infant mortality in the study area. The social and behavioural studies are playing a vital role in determining infant mortality rate in India. The State Planning Commission encourages for investigating the mediating cause for high level cause for the infant mortality at Thondamuthur Block in Coimbatore District. However, the project findings base on econometric models. The SEM models provide a degree of covariance and invariance’s of sub- dimensions in determining the cause of high level cause for the infant mortality in the study area. Public health services (Practitioners services, hospital Services in Outpatients and Hospital Services in Inpatients) resulted insignificant impact on determining Infant mortality and health of the children in Thondamuthur Block. Hence it is not a factor for the high level cause for the Infant Mortality. However, it is notable that psychological discomfort dimension is a significant determinant dimensions for the cause of high level cause for the infant mortality in Thondamuthur Block. Social Problems, Infrastructure facilities and economic problems dimensions resulted marginal impact on infant mortality. Since the state government provides various schemes for pregnant women during maternity period and also for improving child health. But the Social Problems, Infrastructure facilities and economic problems dimensions created psychological problems during maternity period. Within the last decade, considerable interest has developed in the possible roles of stress and other psychosocial factors as mediators of pregnancy outcomes. Interest in this area also has been stimulated by evidence that psychological factors influence immune function (Ader 1981, Cohen 1991, Jemmott and Locke 1984) and by the recognition that psychosocial factors may play a role, yet undefined, in premature birth (Centers for Disease Control 1991). Recent reports indicate that neuroendocrine, bio chemical, and psychosocial factors interact to influence the immune system (Geiser 1989) and many stressful life events have been reported in association with decreases in measures of human immune status. Social support has been reported by Geiser

(1989) to mediate the impact of stress on the immune response. Others suggest a relationship between stress and low birth weight (Newton and Hunt 1984). The role of the catecholamine, adrenaline and nor adrenaline, and cortical as indicators of stress induced by human external and internal environmental demands, and their increased excretion during pregnancy, has been firmly established. SEM empirically proved that psychological discomfort dimension is the mediated factor for the cause of high level cause for the infant mortality at Thondamuthur block in Coimbatore district.

SECTION - 5

FINDINGS, CONCLUSION AND POLICY RECOMMENDATIONS

The study is meant to evaluate the dimensions associated with infant mortality at Thondamuthur block in Coimbatore District. We summarise the findings based on the analysis which are as under.

5.1. Findings from Socio-Economic Dimensions of the Respondents

Age: We observed that majority of the respondents were in the age groups between 22 years to 31 years. Very young mothers faced difficulties in their pregnancies and deliveries, because of their physical immaturity. They have limited knowledge and confidence in caring for their infants and young children. Women are in the category over 30 years suffered age-related problems during their pregnancy and delivery.

Educational Qualification: We observed that the majority of the respondents were School Drops out. Literate mothers create healthier environment and provide nutritious food to their infants than compared with illiterate mother.

Occupation: We observed that most of the pregnant women were unemployed which stimulate psychological and family problems.

Religion: We observed that the majority of the respondents were belongs to Hindu religion. Religion and membership in a scheduled caste or scheduled tribe is known to affect many aspects of life in India and is likely to affect levels of infant and child mortality as well. Some of the effect of religion and caste/tribe membership on mortality may be due to differences in life-style based on traditions and beliefs. Such differences may include customary practices related to childbirth, infant feeding, and healthcare. These practices inferences the infant and child mortality rate.

Income: We observed that the majority of the respondents’ family annual income is below Rs.50000/ lived in joint families with own concrete houses. The majority respondents belong to marginalised group (Dalits & Tribes). The majority of respondents were made use of PHCs and Chief Minister insurance Schemes.

5.2. Findings for Mediating Cause for High Level Cause for the Infant Mortality in the Study Area

The social and behavioural studies are playing a vital role in determining infant mortality rate in India. The State Planning Commission encourages for investigating the mediating cause for high level cause of infant mortality at Thondamuthur Block in Coimbatore District. However, the project findings base on econometric models. The SEM models provide a degree of covariance and invariance’s of sub-dimensions in determining the cause of high level cause of infant mortality in the study area. Public health services (Practitioners services, hospital Services in Outpatients and Hospital Services in Inpatients) resulted insignificant impact on determining Infant mortality and health of the children in Thondamuthur Block. Hence it is not a factor for the high level cause for the Infant Mortality. However, it is notable that psychological discomfort dimension is a mediating dimensions for the high level cause for the infant mortality at Thondamuthur Block in Coimbatore district. Social Problems, Infrastructure facilities and economic problems dimensions resulted marginal impact on infant mortality. Since the state government provides various schemes for pregnant women during maternity period and also for improving child health. But the Social Problems, Infrastructure facilities and economic problems dimensions created psychological problems during maternity period. Within the last decade, considerable interest has developed in the possible roles of stress and other psychosocial factors as mediators of pregnancy outcomes. Interest in this area also has been stimulated by evidence that psychological factors influence immune function (Ader 1981, Cohen 1991, Jemmott and Locke 1984) and by the recognition that psychosocial factors may play a role, yet undefined, in premature birth. Recent reports indicate that neuroendocrine, bio chemical and psychosocial factors interact to influence the immune system (Geiser 1989) and many stressful life events have been reported in association with decreases in measures of human immune status. Social support has been reported by Geiser (1989) to mediate the impact of stress on the immune response. Others suggest a relationship between stress and low birth weight (Newton and Hunt 1984). The role of the catecholamine, adrenaline and nor adrenaline and cortical as indicators of stress induced by human external and internal environmental demands and their increased excretion during pregnancy, has been firmly

established. SEM empirically proved that psychological discomfort dimension is the mediated cause for the high level cause for the infant mortality at Thondamuthur Block in Coimbatore District.

5.3. Empirically Proved from Conceptual Model

Figure 5.1: Empirically Proved Conceptual Model for High Level cause for the Infant Mortality

Practitioners Services

Hospital Services in Outpatients Demographic Variable

Hospital Services in Inpatients High Level cause of Infant Mortality Rate

Social Problems

Infrastructure Facilities Psychological Discomfort

Economic Problems

The conceptual research model empirically proved (figure 5.1). Thus, the present study has focused on High Level cause for the Infant Mortality. This report identifies that the Psychological Discomfort is the mediating cause for the High Level cause for the Infant Mortality at Thondamuthur Block in Coimbatore District.

5.4. Conclusion and Policy Recommendations

The present study has been made to eradicate the infant mortality completely. There are many studies discussed about the Infant Mortality Rate exclusively. This is the only study has been made to find out the mediating cause for the high level cause of infant mortality. It is found from the previous studies that the Infant Mortality Rate has increasing due to various factors such as child sex, mothers’ literacy, caste, birth order and mothers’ age etc...

In this study, we have scientifically proved that psychological discomfort is the mediating cause for the high level cause for infant mortality. Hence social scientist, policy makers and government should concentrate on psychological discomfort to eradicate Infant Mortality permanently.

Medical practitioners’ services such as doctor services, nursing services, pharmacy services and medical equipment services development will not make any changes in Infant Mortality.

Improvement in hospital services, promoting emergency services, diagnostic services, cleanness services, lab services and housekeeping services have not helped to reduce Infant Mortality.

Social factors such as child marriage, gender discrimination, caste, religion, inter- caste marriage and cultural shift are important factors but the same have not been directly influenced on the high level cause for the Infant Mortality.

Infrastructure facilities include ambulance services, sanitation services and transportation services will not support to reduce Infant Mortality.

Finance is the backbone of everything. Without finance nothing can be done. Economic factor includes financial crises of the poor, lack of procurement of nutrition, migration due to low income and industrialization. The results from our study stated that economic problem is not a mediating cause for the high level cause for the Infant mortality. Hence the policy maker need not give much importance to the economic problem factor.

The present study scientifically proves that psychological discomfort factor is a medicating cause for the high level cause for the infant mortality at Thondamuthur Block in Coimbatore district. It means if there is any change in psychological discomfort factor then it will reflects immediately in Infant Mortality.

Psychological Discomfort management alone the one and only solution for eradicating the infant mortality completely and the same has been scientifically proved with the help of structural equation model.

Psychological Discomfort factor includes emotions of pregnant mothers, behaviour of husband, mother-in-law, friends and other relatives, lack of parents and friends support, sexual harassment in working place, varsity health hazards in informal sector, continuous sex inducement during the pregnancy time due to continuous drinking habit of the spouse and not proper interval between two babies.

Psychological Discomfort is the mediating cause for the high level cause for the Infant mortality is not only applicable at Thondamuthur Block in Coimbatore district but also applicable in Tamilnadu, India. Hence, it is clear that there is a tiny change the above said factor which will cause immediate impact in Infant Mortality.

The policy makers, social science scientist, consultants and the Government should carefully make use of the said factor to eradicate the infant mortality at Thondamuthur Block in Coimbatore District. We should take necessary steps to concentrate on Psychological Discomfort factor instead of concentrating on other factor such as medical practitioner’s services, transportation services, economic issues of the poor and hospital services.

Hence we conclude form the study that Psychological Discomfort is a mediating cause for the high level cause for the Infant mortality is not only applicable at Thondamuthur Block in Coimbatore district, but also applicable in Tamilnadu and India.

There is a need to create a committee to make ‘Effective Management of Psychological Discomfort’ factor to eradicate infant mortality completely.

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Appendix - I (a)

MEDIATING CAUSES FOR HIGH LEVEL OF INFANT MORTALITY RATE AT THONDAMUTHUR BLOCK OF COIMBATORE DISTRICT

Questionnaire

Please indicate your responses with the appropriate level of Agree for the factors mentioned below.

1. Highly disagree 2.Disagree 3.Some what ok 4.Undesired 5.Some what disagree 6. Agree 7. Highly agree

S. Questions Highly disagree - Highly No agree Practitioners Services 1. Medical Records 1 2 3 4 5 6 7 2. Pharmacy Services 1 2 3 4 5 6 7 3. Medical Equipments 1 2 3 4 5 6 7 4. Doctors Services 1 2 3 4 5 6 7 5. Nursing Services 1 2 3 4 5 6 7 6. Insurance Coverage Facilities 1 2 3 4 5 6 7 Hospital Services in Outpatients 7. Seating 1 2 3 4 5 6 7 8. Waiting 1 2 3 4 5 6 7 9. Emergency Services 1 2 3 4 5 6 7 10. Diagnostic Services Locations 1 2 3 4 5 6 7 11. Cleanliness of Outpatients departments 1 2 3 4 5 6 7 12. Public Toilets 1 2 3 4 5 6 7 13. Wheel Chair/Stretcher 1 2 3 4 5 6 7 14. Restaurant 1 2 3 4 5 6 7 15. Lab Facilities 1 2 3 4 5 6 7 Hospital Services in Inpatients 16. Room Space, Amenities and Furniture 1 2 3 4 5 6 7 17. Lighting 1 2 3 4 5 6 7 18. Wall Colour 1 2 3 4 5 6 7 19. Bath/Toilet Facility 1 2 3 4 5 6 7 20. Hot Water Facilities 1 2 3 4 5 6 7 21. Attenders 1 2 3 4 5 6 7 22. Diet Services 1 2 3 4 5 6 7 23. Housekeeping 1 2 3 4 5 6 7 24. Lab Facilities 1 2 3 4 5 6 7 Social Problems 25. Child Marriage 1 2 3 4 5 6 7 26. Gender Discrimination 1 2 3 4 5 6 7 27. Less interest on Female Baby (After Scanning) 1 2 3 4 5 6 7 28. Caste 1 2 3 4 5 6 7 29. Religion 1 2 3 4 5 6 7 30. Social Structure 1 2 3 4 5 6 7 31. Cultural Norms 1 2 3 4 5 6 7 32. Value System 1 2 3 4 5 6 7 33. Inter-Caste Marriage 1 2 3 4 5 6 7 34. Cultural Shift 1 2 3 4 5 6 7 Infrastructure Facilities 35. Ambulance Services 1 2 3 4 5 6 7 36. Hospital Infrastructure 1 2 3 4 5 6 7 37. Poor Sanitation 1 2 3 4 5 6 7 38. Hygiene 1 2 3 4 5 6 7 39. Safe Drinking Water 1 2 3 4 5 6 7 40. Distance of Hospital Services 1 2 3 4 5 6 7 41. Distance of Hospital Location 1 2 3 4 5 6 7 42. Distance of Ambulance Services 15 km 1 2 3 4 5 6 7 43. Lack of Transport Facilities 1 2 3 4 5 6 7 Psychological Discomfort 44. Emotion 1 2 3 4 5 6 7 45. Social Problems 1 2 3 4 5 6 7 46. Financial Problems 1 2 3 4 5 6 7 47. Husband 1 2 3 4 5 6 7 48. Mother - in - law 1 2 3 4 5 6 7 49. Relatives of Husband’s Family 1 2 3 4 5 6 7 50. Lack of Parents Support 1 2 3 4 5 6 7 51. Verbal use by others 1 2 3 4 5 6 7 52. Problems Faced At Work Place Daily 1 2 3 4 5 6 7 53. Sexual Harassment from colleagues and 1 2 3 4 5 6 7 Higher Officials 54. Over Crowded Public Transport System 1 2 3 4 5 6 7 55. Lack of Time Management 1 2 3 4 5 6 7 56. Vulnerable to Working Conditions Across 1 2 3 4 5 6 7 Diverse Occupation Informal Sectors 57. Varsity of Health Hazards Informal Sectors 1 2 3 4 5 6 7 58. Continually Sexual Inducement by During the 1 2 3 4 5 6 7 Pregnancy 59. Continually Drank and Sexual Inducement by 1 2 3 4 5 6 7 During the Pregnancy 60. No Long Gap for Another Baby Birth 1 2 3 4 5 6 7 Economic Problems 61. Limited access to Cash and Credit 1 2 3 4 5 6 7 62. Nutrition 1 2 3 4 5 6 7 63. Shift into agrarian Changes 1 2 3 4 5 6 7 64. Migration 1 2 3 4 5 6 7 65. Low Income 1 2 3 4 5 6 7 66. Industrialization 1 2 3 4 5 6 7 High Level of Infant Mortality Rate 67. Lack of Knowledge and Skills to Care for New 1 2 3 4 5 6 7 Born Child 68. Breast Feeding Problems 1 2 3 4 5 6 7 69. Duration of hospital stay normal birth 1 2 3 4 5 6 7 70. Infant Care, Genital cleaning and ear cleaning 1 2 3 4 5 6 7 71. Do you Agree that above are face cause for 1 2 3 4 5 6 7 High level of Infant Mortality Rate Personal Information 1. Name : 2. Age : 1) Below 21 years 2) 22 years to 31 years 2) 32 years to 41 years 2) 42 years & above 3. Educational : 1) Schooling 2) Secondary 3) Higher Qualification Dropout Education Secondary Education 4) Under 5) Post Graduate Graduate 4. Occupation : 1) Un Employed 2) Agriculture 3) Private 4) Government 5) Self Employee 5. Religion : 1) Hindu 2) Islam 3) Christian 6. Annual Income : 1) Below Rs.50000 2) Rs.50001 to Rs.150000 3) Rs.150001 to 4) Rs.250001 & Above Rs.250000 7. Community : 1) Backward Class 2) Most Backward Class/Denoted Class 3) Schedule Cast 4) Schedule Tribe 8. Types of Family : 1) Joint Family 2) Nuclear Family 9. Residential House : 1) Own House 2) Rent House 10. Types of House : 1) Concrete 2) Tiled 3) Terrace 4) Thatched 11. Size of : 1) Landless 2) Marginal 3) Large Landholding 12. Toilet Facilities : 1) Common Toilet 2) Separate 3) Open Toilet Toilet 13. Recommendation : 1) Self Decision 2) Family Doctor of Hospital Recommendation 3) Friends and Relatives 4) Beneficiaries Recommendation Recommendation 14. Types of Hospital : 1) Government Hospital 2) Private Hospital 15. Medical Insurance : 1) Nil Insurance 2) Government Insurance 3) Private Insurance 4) Chief Minister Insurance Scheme 16. Any Infant Death : 1) Yes 2) No

Appendix - I (b)

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Please indicate your responses with the appropriate level of Agree for the factors mentioned below.

1. Highly disagree 2.Disagree 3.Some what ok 4.Undesired 5.Some what disagree 6. Agree 7. Highly agree

Å.±ñ ¯ûÇ¨ÁôÒ¸û «¾¢¸ ´òÐì¦¸¡ûÇ¡¨Á -«¾¢¸ ´òÐì¦¸¡ûÙ¾ø ÁÕòÐÅ §º¨Å¸û; 1. ÁÕòÐÅ À¾¢§ÅÎ¸û (1) (2) (3) (4) (5) (6) (7) 2. ÁÕó¾¸ §º¨Å¸û (1) (2) (3) (4) (5) (6) (7) 3. ÁÕòÐÅ ¯À¸Ã½í¸û (1) (2) (3) (4) (5) (6) (7) 4. ÁÕòÐÅ÷ §º¨Å¸û (1) (2) (3) (4) (5) (6) (7) 5. ¦ºÅ¢Ä¢Â÷ §º¨Å¸û (1) (2) (3) (4) (5) (6) (7) 6. ¬Ôû ¸¡ôÀ¢ðÎ ¾¢ð¼ Åº¾¢ (1) (2) (3) (4) (5) (6) (7) ÒÈ§¿¡Â¡Ç¢¸ÙìÌ ÁÕòÐÅÁ¨É §º¨Å¸û ; 7. þÕì¨¸ Åº¾¢ (1) (2) (3) (4) (5) (6) (7) 8. ¸¡ò¾¢ÕìÌõ §¿Ãõ (1) (2) (3) (4) (5) (6) (7) 9. «ÅºÃ¸¡Ä ¯¾Å¢¸û (1) (2) (3) (4) (5) (6) (7) 10. À¡¢§º¡¾¨Éô À½¢¸Ç¢ý «¨ÁÅ¢¼õ (1) (2) (3) (4) (5) (6) (7) 11. ¦ÅÇ¢ôÒÈ §¿¡Â¡Ç¢¸û Ð¨ÈÂ¢ý (1) (2) (3) (4) (5) (6) (7) àö¨Á 12. ¦À¡Ð ¸Æ¢ôÀ¨È Åº¾¢ (1) (2) (3) (4) (5) (6) (7) 13. ºì¸Ã ¿¡ü¸¡Ä¢ / ¨¸ÀÎì¨¸ Åº¾¢ (1) (2) (3) (4) (5) (6) (7) 14. ¯½Å¸ Åº¾¢¸û (1) (2) (3) (4) (5) (6) (7) 15. ¬öÅ¸ Åº¾¢¸û (1) (2) (3) (4) (5) (6) (7) ¯ û §¿¡Â¡Ç¢¸Ùì¸¡É ÁÕòÐÅÁ¨É §º¨Å¸û 16. «¨ÈÂ¢ý «Ç× ÁüÚõ ÁÕòÐÅ (1) (2) (3) (4) (5) (6) (7) Åº¾¢¸û 17. ¦ÅÇ¢îºõ (1) (2) (3) (4) (5) (6) (7) 18. ÍÅ¡¢ý Åñ½õ (1) (2) (3) (4) (5) (6) (7) 19. ¸Æ¢ôÀ¨È Åº¾¢ ÁüÚõ ÌÇ¢ÂÄ¨È Åº¾¢ (1) (2) (3) (4) (5) (6) (7) 20. ¦Åó¿£÷ Åº¾¢ (1) (2) (3) (4) (5) (6) (7) 21. ¯¾Å¢Â¡Ç÷¸û (1) (2) (3) (4) (5) (6) (7) 22. ¯½× ì¸ðÎôÀ¡ðÎ ¯¾Å¢ (1) (2) (3) (4) (5) (6) (7) 23. «¨ÈÂ¢ý ÀÃ¡Á¡¢ôÒ (1) (2) (3) (4) (5) (6) (7) 24. ¬öÅ¸ Åº¾¢ (1) (2) (3) (4) (5) (6) (7) ºã¸ô À¢Ãîº¨É¸û 25. ÌÆó¨¾ò ¾¢ÕÁ½õ (1) (2) (3) (4) (5) (6) (7) 26. À¡Ä¢É À¡ÌÀ¡Î (1) (2) (3) (4) (5) (6) (7) 27. ¦Àñ ÌÆó¨¾¸û Á£¾¡É Ì¨ÈÅ¡É (1) (2) (3) (4) (5) (6) (7) Å¢ÕôÀõ 28. º¡¾¢ (1) (2) (3) (4) (5) (6) (7) 29. Á¾õ (1) (2) (3) (4) (5) (6) (7) 30. ºã¸ ¸ð¼¨ÁôÒ (1) (2) (3) (4) (5) (6) (7) 31. ¸Ä¡îº¡Ã ÅÆ¢Ó¨È (1) (2) (3) (4) (5) (6) (7) 32. Á¾¢ôÒ Ó¨È¸û (1) (2) (3) (4) (5) (6) (7) 33. ¸ÄôÒ ¾¢ÕÁ½õ (1) (2) (3) (4) (5) (6) (7) 34. ÀñÀ¡ðÎ Á¡üÈõ (1) (2) (3) (4) (5) (6) (7) ¯û ¸ð¼¨ÁôÒ Åº¾¢¸û 35. ¬õÒÄýŠ §º¨Å (1) (2) (3) (4) (5) (6) (7) 36. ÁÕòÐÅÁ¨É ¯û ¸ð¼¨ÁôÒ Åº¾¢ (1) (2) (3) (4) (5) (6) (7) 37. Ì¨ÈÅ¡É ¯¼ø¿Äõ ¸¡ìÌõ ²üÀ¡Î (1) (2) (3) (4) (5) (6) (7) 38. Í¸¡¾¡Ãõ (1) (2) (3) (4) (5) (6) (7) 39. À¡Ð¸¡ì¸ôÀð¼ ÌÊ¿£÷ (1) (2) (3) (4) (5) (6) (7) 40. ÁÕòÐÅÁ¨É ¦¾¡¨Ä× (1) (2) (3) (4) (5) (6) (7) 41. ÁÕòÐÅÁ¨É «¨ÁóÐûÇ (1) (2) (3) (4) (5) (6) (7) þÕôÀ¢¼ò¾¢ü¸¡É àÃõ 42. 15 ¸¢. Á¢ ¦¾¡¨ÄÅ¢ø ¬õÒÄýŠ (1) (2) (3) (4) (5) (6) (7) §º¨Å 43. §À¡ìÌÅÃòÐ Åº¾¢Â¢ý¨Á (1) (2) (3) (4) (5) (6) (7) ¯ÇÅ¢Âø ¡£¾¢Â¡É ÁÉ ¯¨Çîºø 44. ¯½÷îº¢ÅºôÀÎ¾ø (1) (2) (3) (4) (5) (6) (7) 45. ºã¸ô À¢Ãîº¨É¸û (1) (2) (3) (4) (5) (6) (7) 46. À½ô À¢Ãîº¨É¸û (1) (2) (3) (4) (5) (6) (7) 47. ¸½Å÷ (1) (2) (3) (4) (5) (6) (7) 48. Á¡Á¢Â¡÷ (1) (2) (3) (4) (5) (6) (7) 49. ¸½Å¡¢ý ÌÎõÀ ¯ÈÅ¢É÷¸û (1) (2) (3) (4) (5) (6) (7) 50. ¦Àü§È¡¡¢ý ¬¾ÃÅ¢ý¨Á (1) (2) (3) (4) (5) (6) (7) 51. À¢ÈÃ¡ø ÀÂýÀÎò¾ôÀÎõ ¦º¡ü¸û (1) (2) (3) (4) (5) (6) (7) 52. À½¢Ò¡¢Ôõ ¿¢ÚÅÉò¾¢ø ¾¢Éó§¾¡Úõ (1) (2) (3) (4) (5) (6) (7) ²üÀÎõ À¢Ãîº¨É¸û 53. ¯¼ý À½¢Ò¡¢§Å¡÷ ÁüÚõ ¯Â÷ (1) (2) (3) (4) (5) (6) (7) «¾¢¸¡¡¢¸Ç¡ø ²üÀÎõ À¡Ä¢Éò ¦¾¡ó¾Ã×¸û 54. §À¡ìÌÅÃòÐ ¦¿È¢ºø (1) (2) (3) (4) (5) (6) (7) 55. ¸¡Ä §ÁÄ¡ñ¨Á þý¨Á (1) (2) (3) (4) (5) (6) (7) 56. Å¨ÃÂÚì¸ôÀ¼¡¾ Ð¨ÈÂ¢ø Á¡ÚÀð¼ (1) (2) (3) (4) (5) (6) (7) À½¢Â¢ø À¡¾¢ôÒ ¾ÃìÜÊÂ Å¨¸Â¢ø À½¢Ò¡¢Ôõ ¿¢¨Ä 57. Å¨ÃÂÚì¸ôÀ¼¡¾ Ð¨ÈÂ¢ø ²üÀÎõ (1) (2) (3) (4) (5) (6) (7) ¯¼ø ¿Äì §¸Î 58. ¸÷ôÀ¸¡Äò¾¢ø ¦¾¡¼÷ À¡Ä¢Âø (1) (2) (3) (4) (5) (6) (7) àñÎ¾ø 59. ¸÷ôÀ¸¡Äò¾¢ø ¦¾¡¼÷ ÌÊôÀÆì¸õ (1) (2) (3) (4) (5) (6) (7) ÁüÚõ À¡Ä¢Âø àñÎ¾ø 60. «Îò¾ ÌÆó¨¾ À¢ÈôÀ¢ü¸¡É (1) (2) (3) (4) (5) (6) (7) þ¨¼¦ÅÇ¢Â¢ý¨Á ¦À¡ÕÇ¡¾¡Ã À¢Ãîº¨É¸û 61. À½õ ÁüÚõ ¸¼ý ¦ÀÚÅ¾¢ø º¢ì¸ø (1) (2) (3) (4) (5) (6) (7) 62. ºòÐ½× (1) (2) (3) (4) (5) (6) (7) 63. Å¢Åº¡Â Á¡üÈò¾¢üÌ ¿¸÷¾ø (1) (2) (3) (4) (5) (6) (7) 64. þ¼ô¦ÀÂ÷× (1) (2) (3) (4) (5) (6) (7) 65. Ì¨ÈÅ¡É ÅÕÅ¡ö (1) (2) (3) (4) (5) (6) (7) 66. ¦¾¡Æ¢øÁÂÁ¡¾ø (1) (2) (3) (4) (5) (6) (7) º¢Í þÈôÒ Å£¾õ «¾¢¸¡¢ò¾ø ; 67. «È¢Å¢ý¨Á ÁüÚõ º¢Í ÀÃ¡Á¡¢ò¾Ä¢ø (1) (2) (3) (4) (5) (6) (7) ¾¢È¨ÁÂ¢ý¨Á 68. ¾¡öôÀ¡ø °ðÎÅ¾¢ø º¢ì¸ø (1) (2) (3) (4) (5) (6) (7) 69. Í¸ôÀ¢ÃÅºò¾¢ý §À¡Ð (1) (2) (3) (4) (5) (6) (7) ÁÕòÐÅÁ¨ÉÂ¢ø ¾íÌõ ¸¡Ä «Ç× 70. º¢Í ÀÃ¡Á¡¢ôÒ, À¡ÖÚôÒ ÁüÚõ ¸¡Ð (1) (2) (3) (4) (5) (6) (7) Íò¾õ ¦ºö¾ø 71. §ÁüÜÈ¢Â¨Å¸û º¢Í þÈôÒ Å£¾õ (1) (2) (3) (4) (5) (6) (7) «¾¢¸¡¢ì¸ì ¸¡Ã½õ ±ýÀ¨¾ ²üÚì ¦¸¡ûÅ£Ã¡.

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1. ¦ÀÂ÷ : 2. ÅÂÐ : 1) 21 ìÌ ¸£ú 2) 22 ÅÂÐ Ó¾ø 31 ÅÂÐ Å¨Ã 3) 32 ÅÂÐ Ó¾ø 41 4) 41 ìÌ §Áø ÅÂÐ Å¨Ã 3. ¸øÅ¢ò ¾Ì¾¢ : 1) ¨¸Å¢ð¼ 2) ¯Â÷¿¢¨Ä ¸øÅ¢ 3) §Áø¿¢¨Ä ¸øÅ¢ ÀûÇ¢ô ÀÊôÒ 4) þÇ¿¢¨Ä 5) ÓÐ¿¢¨Ä ¸øÅ¢ ¸øÅ¢ 4. ¦¾¡Æ¢ø : 1) §Å¨ÄÂ¢ø 2) §ÅÇ¡ñ 3) ¾É¢Â¡÷ °Æ¢Â÷ þø¨Ä ¦¾¡Æ¢ø 4) «ÃÍ 5) ÍÂ ¦¾¡Æ¢ø °Æ¢Â÷ 5. Á¾õ : 1) þóÐ 2) þŠÄ¡Á¢Âõ 3) ¸¢ÕŠÐÅõ 6. ¬ñÎ : 1) å.50000 ìÌ ¸£ú 2) å.50001 Ó¾ø å.150000 ÅÕÁ¡Éõ Å¨Ã 3) å.1250001 Ó¾ø 4) å.250001 ìÌ §Áø å.250000 Å¨Ã 7. þÉõ : 1) À¢ÈÀð¼ ÅÌôÀ¢É÷ 2) Á¢¸×õ À¢ÈÀð¼ ÅÌôÀ¢É÷ 3) ¾¡úò¾ôÀð¼ ÅÌôÀ¢É÷ 4) ÀÆíÌÊÂ¢É÷ 8. ÌÎõÀò¾¢ý : 1) ÜðÎì ÌÎõÀõ 2) ¾É¢ìÌÎõÀõ Å¨¸ 9. ÌÊÂ¢ÕôÒ : 1) ¦º¡ó¾ Å£Î 2) Å¡¼¨¸ Å£Î 10. ÌÊÂ¢ÕôÒ Å¨¸ : 1) ¸¡í¸¢¡¢ð ¸¡Ä½¢ Å£Î 2) µðÎ Å£Î 3) Á¡Ê Å£Î 4) Ü¨Ã Å£Î 11. ¿¢Ä «Ç× : 1) ¿¢Äõ þø¨Ä 2) ÌÈ¢ôÀ¢ð¼ «Ç× ¿¢Äõ 3) «¾¢¸ ¿¢Äõ 12. ¸Æ¢ôÀ¢¼ Åº¾¢ : 1) ¦À¡Ð ¸Æ¢ôÀ¢¼õ 2) ¾É¢ ¸Æ¢ôÀ¢¼õ 3) ¾¢Èó¾¦ÅÇ¢ ¸Æ¢ôÀ¢¼õ 13. ÁÕòÐÅÁ¨É : 1) ¦º¡ó¾ ÓÊ× 2) ÌÎõÀ ÁÕòÐÅ¡¢ý À¡¢óÐ¨Ã ¬§Ä¡º¨É 3) ¿ñÀ÷ ÁüÚõ ¯ÈÅ¢É÷ 4) ÀÂ½Ç¢¸Ç¢ý ¬§Ä¡º¨É ¬§Ä¡º¨É 14. ÁÕòÐÅÁ¨É : 1) «ÃÍ ÁÕòÐÅÁ¨É 2) ¾É¢Â¡÷ ÁÕòÐÅÁ¨É Åº¾¢ 15. ÁÕòÐÅ : 1) ¸¡ôÀ£Î þø¨Ä 2) «ÃÍ ¸¡ôÀ£Î ¸¡ôÀ£Î 3) ¾É¢Â¡÷ ¸¡ôÀ£Î 4) Ó¾Ä¨Áîº¡¢ý ÁÕòÐÅ ¸¡ôÀ£Î 16. ²¾Ûõ º¢Í : 1) ¬õ 2) þø¨Ä þÈôÒ

APPENDIX – II

VILLAGE/URBAN/BLOCK LEVEL DATA OF COIMBATORE DISTRICT

Village Wise Data of Thondamuthur Block

Table 1: Population of Thondamuthur Block Villages No. Total Male Female Household Thennammanallur 1443 (7.84%) 5098 (7.68%) 2491 (7.52%) 2607 (7.84%) Devarayapuram 1802 (9.78%) 6417 (9.68%) 3144 (9.49%) 3273 (9.87%) Jagirnaickenpalyam 334 (1.82%) 1486 (2.24%) 813 (2.45%) 673 (2.04%) Vellaimalaipattinam 916 (4.97%) 4066 (6.13%) 2032 (6.13%) 2034 (6.13%) Narasipuram 831 (4.51%) 3078 (4.64%) 1574 (4.75%) 1504 (4.53%) Madavarayapuram 1797 (9.75%) 6365 (9.59%) 3226 (9.74%) 3139 (9.46%) Ikkaraibooluvampatti 1834 (9.95%) 6361 (9.59%) 3183 (9.61%) 3178 (9.58%) Madampatti 1999 (10.85%) 6771 (10.22%) 3359 (10.14%) 3412 (10.28%) Theethipalayam 2386 (12.95%) 8629 (13.02%) 4296 (12.97%) 4333 (13.06%) Boluvampatti(R.F) 78 (0.42%) 224 (0.35%) 119 (0.36%) 105 (0.33%) Perur Chettipalayam (CT) 5004 (27.16%) 17809 (26.86%) 8891 (26.84%) 8918 (26.88%) Total 18424 (100%) 66304 (100%) 33128 (100%) 33176 (100%) Source: District Planning Commission, Coimbatore.

Table 2: 0-6 age group population of Thondamuthur Block Villages Total Percentage Male Percentage Female Percentage Thennammanallur 450 7.52 225 7.28 225 7.76 Devarayapuram 538 8.98 278 9.00 260 8.97 Jagirnaickenpalyam 91 1.52 54 1.75 37 1.28 Vellaimalaipattinam 275 4.59 149 4.82 126 4.35 Narasipuram 245 4.09 125 4.05 120 4.14 Madavarayapuram 619 10.34 342 11.07 277 9.56 Ikkaraibooluvampatti 536 8.95 270 8.74 266 9.18 Madampatti 595 9.94 312 10.09 283 9.77 Theethipalayam 847 14.14 425 13.75 422 14.56 Boluvampatti(R.F) 22 0.37 18 0.58 4 0.14 Perur Chettipalayam (CT) 1770 29.56 892 28.87 878 30.29 Total 5988 100.00 3090 100.00 2898 100.00 Source: District Planning Commission, Coimbatore.

Table 3: SC Population of Thondamuthur Block Villages Total Percentage Male Percentage Female Percentage Thennammanallur 1838 14.47 901 14.25 937 14.69 Devarayapuram 1577 12.42 768 12.15 809 12.69 Jagirnaickenpalyam 403 3.17 207 3.27 196 3.07 Vellaimalaipattinam 790 6.22 400 6.34 390 6.12 Narasipuram 466 3.67 234 3.70 232 3.64 Madavarayapuram 510 4.02 274 4.34 236 3.70 Ikkaraibooluvampatti 1367 10.77 679 10.74 688 10.78 Madampatti 1384 10.91 700 11.07 684 10.73 Theethipalayam 1395 10.97 686 10.85 709 11.12 Boluvampatti(R.F) 0 0 0 0 0 0 Perur Chettipalayam (CT) 2968 23.38 1472 23.29 1496 23.46 Total 12698 100.00 6321 100.00 6377 100.00 Source: District Planning Commission, Coimbatore.

Table 4: ST Population of Thondamuthur Block Villages Total Percentage Male Percentage Female Percentage Thennammanallur 1 0.11 1 0.22 0 0 Devarayapuram 0 0 0 0 0 0 Jagirnaickenpalyam 0 0 0 0 0 0 Vellaimalaipattinam 15 1.63 6 1.30 9 1.97 Narasipuram 145 15.80 70 15.22 75 16.38 Madavarayapuram 53 5.77 32 6.96 21 4.59 Ikkaraibooluvampatti 495 53.92 240 52.17 255 55.68 Madampatti 9 0.98 4 0.87 5 1.09 Theethipalayam 25 2.72 16 3.48 9 1.97 Boluvampatti(R.F) 171 18.63 90 19.57 81 17.69 Perur Chettipalayam (CT) 4 0.44 1 0.22 3 0.66 Total 918 100.00 460 100.00 458 100.00 Source: District Planning Commission, Coimbatore.

Table 5: Literate of Thondamuthur Block Villages Total Percentage Male Percentage Female Percentage Thennammanallur 3316 7.16 1830 7.29 1486 7.00 Devarayapuram 4078 8.80 2175 8.66 1903 8.97 Jagirnaickenpalyam 1115 2.41 672 2.68 443 2.09 Vellaimalaipattinam 2737 5.91 1447 5.76 1290 6.08 Narasipuram 2034 4.39 1145 4.56 889 4.19 Madavarayapuram 4587 9.90 2468 9.83 2119 9.99 Ikkaraibooluvampatti 4043 8.73 2273 9.05 1770 8.34 Madampatti 4748 10.25 2584 10.29 2164 10.20 Theethipalayam 6329 13.66 3424 13.64 2905 13.69 Boluvampatti(R.F) 112 0.24 64 0.25 48 0.23 Perur Chettipalayam (CT) 13228 28.55 7026 27.98 6202 29.23 Total 46327 100.00 25108 100.00 21219 100.00 Source: District Planning Commission, Coimbatore

Table 6: Illiterate of Thondamuthur Block Villages Total Male Female Thennammanallur 1782 (8.92%) 661 (8.24%) 1121 (9.38%) Devarayapuram 2339 (11.71%) 969 (12.08%) 1370 (11.46%) Jagirnaickenpalyam 371 (1.86%) 141 (1.76%) 230 (1.92%) Vellaimalaipattinam 1329 (6.65%) 585 (7.29%) 744 (6.22%) Narasipuram 1044 (5.23%) 429 (5.35%) 615 (5.14%) Madavarayapuram 1778 (8.90%) 758 (9.45%) 1020 (8.53%) Ikkaraibooluvampatti 2318 (11.60%) 910 (11.35%) 1408 (11.78%) Madampatti 2023 (10.13%) 775 (9.66%) 1248 (10.44%) Theethipalayam 2300 (11.51%) 872 (10.87%) 1428 (11.94%) Boluvampatti(R.F) 112 (0.56%) 55 (0.69%) 57 (0.48%) Perur Chettipalayam (CT) 4581 (22.93%) 1865 (23.26%) 2716 (22.71%) Total 19977 (100%) 8020 (100%) 11957 (100%) Source: District Planning Commission, Coimbatore

Table 7: Total Workers of Thondamuthur Block Villages Total Male Female Thennammanallur 2591 (7.91%) 1626 (7.76%) 965 (8.17%) Devarayapuram 3453 (10.54%) 2082 (9.93%) 1371 (11.61%) Jagirnaickenpalyam 735 (2.24%) 461 (2.20%) 274 (2.32%) Vellaimalaipattinam 1891 (5.77%) 1051 (5.01%) 840 (7.11%) Narasipuram 1874 (5.72%) 1117 (5.33%) 757 (6.41%) Madavarayapuram 3097 (9.45%) 2003 (9.55%) 1094 (9.27%) Ikkaraibooluvampatti 3385 (10.33%) 2081 (9.93%) 1304 (11.04%) Madampatti 3594 (10.97%) 2159 (10.30%) 1435 (12.15%) Theethipalayam 3901 (11.90%) 2690 (12.83%) 1211 (10.26%) Boluvampatti(R.F) 145 (0.44%) 72 (0.34%) 73 (0.62%) Perur Chettipalayam (CT) 8106 (24.73%) 5623 (26.82%) 2483 (21.03%) Total 32772 (100%) 20965 (100%) 11807 (100%) Source: District Planning Commission, Coimbatore

Table 8: Main Workers of Thondamuthur Block Villages Total Male Female Thennammanallur 2014 (7.35%) 1266 (6.95%) 748 (8.13%) Devarayapuram 3213 (11.72%) 1965 (10.80%) 1248 (13.56%) Jagirnaickenpalyam 454 (1.66%) 336 (1.84%) 118 (1.28%) Vellaimalaipattinam 1772 (6.46%) 1008 (5.53%) 764 (8.29%) Narasipuram 1387 (5.06%) 912 (5.01%) 475 (5.16%) Madavarayapuram 2192 (8.00%) 1452 (7.97%) 740 (8.04%) Ikkaraibooluvampatti 2764 (10.08%) 1773 (9.74%) 991 (10.76%) Madampatti 3269 (11.92%) 2041 (11.21%) 1228 (13.34%) Theethipalayam 3284 (11.98%) 2362 (12.97%) 922 (10.02%) Boluvampatti(R.F) 2 (0.01%) 1 (0.01%) 1 (0.01%) Perur Chettipalayam (CT) 7063 (25.76%) 5092 (27.97%) 1971 (21.41%) Total 27414 (100%) 18208 (100%) 9206 (100%) Source: District Planning Commission, Coimbatore

Table 9: Cultivator of Thondamuthur Block Villages Total Male Female Thennammanallur 303 (11.49%) 214 (11.68) 89 (11.08) Devarayapuram 521 (19.78%) 331 (18.07) 190 (23.67) Jagirnaickenpalyam 84 (3.19%) 76 (4.15) 8 (0.99) Vellaimalaipattinam 287 (10.89%) 196 (10.69) 91 (11.33) Narasipuram 103 (3.91%) 76 (4.15) 27 (3.36) Madavarayapuram 326 (12.38%) 213 (11.63) 113 (14.07) Ikkaraibooluvampatti 269 (10.21%) 162 (8.84) 107 (13.33) Madampatti 437 (16.58%) 297 (16.21) 140 (17.43) Theethipalayam 253 (9.60%) 222 (12.12) 31 (3.86) Boluvampatti(R.F) 0 (0%) 0 (0) 0 (0) Perur Chettipalayam (CT) 52 (1.97%) 45 (2.46) 7 (0.88) Total 2635 (100%) 1832 (100) 803 (100) Source: District Planning Commission, Coimbatore

Table 10: Agri Labour of Thondamuthur Block Villages Total Male Female Thennammanallur 894 (9.00%) 496 (9.58%) 398 (8.37%) Devarayapuram 1651 (16.63%) 875 (16.92%) 776 (16.34%) Jagirnaickenpalyam 181 (1.83%) 104 (2.01%) 77 (1.61%) Vellaimalaipattinam 1108 (11.16%) 545 (10.54%) 563 (11.84%) Narasipuram 347 (3.49%) 215 (4.15%) 132 (2.77%) Madavarayapuram 724 (7.29%) 422 (8.15%) 302 (6.35%) Ikkaraibooluvampatti 1396 (14.06%) 747 (14.43%) 649 (13.65%) Madampatti 1471 (14.83%) 720 (13.94%) 751 (15.79%) Theethipalayam 772 (7.77%) 362 (6.99%) 410 (8.64%) Boluvampatti(R.F) 0 (0%) 0 (0%) 0 (0%) Perur Chettipalayam (CT) 1384 (13.94%) 688 (13.29%) 696 (14.64%) Total 9928 (100%) 5174 (100%) 4754 (100%) Source: District Planning Commission, Coimbatore

Table 11: Household of Thondamuthur Block Villages Total Male Female Thennammanallur 12 (2.34%) 5 (1.68%) 7 (3.24%) Devarayapuram 53 (10.34%) 32 (10.84%) 21 (9.63%) Jagirnaickenpalyam 2 (0.38%) 2 (0.67%) 0 (0%) Vellaimalaipattinam 43 (8.36%) 22 (7.43%) 21 (9.63%) Narasipuram 22 (4.28%) 13 (4.39%) 9 (4.12%) Madavarayapuram 54 (10.50%) 32 (10.83%) 22 (10.09%) Ikkaraibooluvampatti 68 (13.24%) 42 (14.18%) 26 (11.92%) Madampatti 56 (10.89%) 26 (8.78%) 30 (13.76%) Theethipalayam 57 (11.08%) 34 (11.48%) 23 (10.55%) Boluvampatti(R.F) 0 (0%) 0 (0%) 0 (0%) Perur Chettipalayam (CT) 147 (28.59%) 88 (29.72%) 59 (27.06%) Total 514 (100%) 296 (100%) 218 (100%) Source: District Planning Commission, Coimbatore

Table 12: Other Workers of Thondamuthur Block Villages Total Male Female Thennammanallur 805 (5.61%) 551 (5.05%) 254 (7.42%) Devarayapuram 988 (6.89%) 727 (6.66%) 261 (7.62%) Jagirnaickenpalyam 187 (1.33%) 154 (1.44%) 33 (0.96%) Vellaimalaipattinam 334 (2.34%) 245 (2.24%) 89 (2.59%) Narasipuram 915 (6.38%) 608 (5.57%) 307 (8.94%) Madavarayapuram 1088 (7.58%) 785 (7.19%) 303 (8.81%) Ikkaraibooluvampatti 1031 (7.19%) 822 (7.54%) 209 (6.09%) Madampatti 1305 (9.10%) 998 (9.15%) 307 (8.94%) Theethipalayam 2202 (15.35%) 1744 (15.99%) 458 (13.34%) Boluvampatti(R.F) 2 (0.01%) 1 (0.01%) 1 (0.02%) Perur Chettipalayam (CT) 5480 (38.22%) 4271 (39.16%) 1209 (35.24%) Total 14337 (100%) 10906 (100%) 3431 (100%) Source: District Planning Commission, Coimbatore

Table 13: Marginal Workers Population of Thondamuthur Block Villages Total Male Female Thennammanallur 577 (10.76%) 360 (13.05%) 217 (8.34%) Devarayapuram 240 (4.42%) 117 (4.24%) 123 (4.74%) Jagirnaickenpalyam 281 (5.24%) 125 (4.54%) 156 (5.99%) Vellaimalaipattinam 119 (2.24%) 43 (1.55%) 76 (2.94%) Narasipuram 487 (9.08%) 205 (7.44%) 282 (10.84%) Madavarayapuram 905 (16.89%) 551 (19.98%) 354 (13.61%) Ikkaraibooluvampatti 621 (11.59%) 308 (11.19%) 313 (12.04%) Madampatti 325 (6.06%) 118 (4.28%) 207 (7.95%) Theethipalayam 617 (11.54%) 328 (11.89%) 289 (11.11%) Boluvampatti(R.F) 143 (2.66%) 71 (2.57%) 72 (2.76%) Perur Chettipalayam (CT) 1043 (19.46%) 531 (19.27%) 512 (19.68%) Total 5358 (100%) 2757 (100%) 2601 (100%) Source: District Planning Commission, Coimbatore.

Table 14: Cultivator for Marginal Workers Population of Thondamuthur Block Villages Total Male Female Thennammanallur 18 (12.67%) 11 (15.94%) 7 (9.58%) Devarayapuram 16 (11.26%) 8 (11.59%) 8 (10.95%) Jagirnaickenpalyam 15 (10.56%) 12 (17.39%) 3 (4.10%) Vellaimalaipattinam 9 (6.33%) 0 (0%) 9 (12.32%) Narasipuram 3 (2.11%) 1 (1.44%) 2 (2.73%) Madavarayapuram 34 (23.94%) 13 (18.84%) 21 (28.76%) Ikkaraibooluvampatti 11 (7.74%) 5 (7.24%) 6 (8.21%) Madampatti 14 (9.85%) 6 (8.69%) 8 (10.95%) Theethipalayam 9 (6.33%) 5 (7.24%) 4 (5.47%) Boluvampatti(R.F) 0 (0%) 0 (0%) 0 (0%) Perur Chettipalayam (CT) 13 (9.15%) 8 (11.59%) 5 (6.84%) Total 42 (100%) 69 (100%) 73 (100%) Source: District Planning Commission, Coimbatore.

Table 15: Agri Labour for Marginal Workers Population of Thondamuthur Block Villages Total Male Female Thennammanallur 233 (7.10%) 145(8.92%) 88(5.31%) Devarayapuram 63(1.92%) 24(1.47%) 39(2.35%) Jagirnaickenpalyam 242(7.38%) 101(6.21%) 141(8.51%) Vellaimalaipattinam 52(1.58%) 18(1.10%) 34(2.05%) Narasipuram 416(12.68%) 159(9.79%) 257(15.52%) Madavarayapuram 591(18.02%) 393(24.19%) 198(11.96%) Ikkaraibooluvampatti 485(14.79%) 228(14.03%) 257(15.52%) Madampatti 209(6.37%) 64(3.94%) 145(8.76%) Theethipalayam 434(13.23%) 236(14.53%) 198(11.96%) Boluvampatti(R.F) 139(4.23%) 69(4.24%) 70(4.22%) Perur Chettipalayam (CT) 415(12.65%) 187(11.51%) 228(13.77%) Total 3279(100%) 1624(100%) 1655(100%) Source: District Planning Commission, Coimbatore.

Table 16: Household for Marginal Workers Population of Thondamuthur Block Villages Total Male Female Thennammanallur 16 (11.67%) 13 (19.69%) 3 (4.22%) Devarayapuram 8 (5.83%) 5 (7.57%) 3 (4.22%) Jagirnaickenpalyam 4 (2.91%) 3 (4.54%) 1 (1.40%) Vellaimalaipattinam 13 (9.48%) 2 (3.03%) 11 (15.49%) Narasipuram 6 (4.37%) 1 (1.51%) 5 (7.04%) Madavarayapuram 37 (27.00%) 23 (34.84%) 14 (19.71%) Ikkaraibooluvampatti 11 (8.02%) 4 (6.06%) 7 (9.85%) Madampatti 14 (10.21%) 3 (4.54%) 11 (15.49%) Theethipalayam 4 (2.91%) 2 (3.03%) 2 (2.81%) Boluvampatti(R.F) 0 (0%) 0 (0%) 0 (0%) Perur Chettipalayam (CT) 24 (17.51%) 10 (15.15%) 14 (19.71%) Total 137 (100%) 66 (100%) 71 (100%) Source: District Planning Commission, Coimbatore.

Table 17: Other Workers for Marginal Workers Population of Thondamuthur Block Villages Total Male Female Thennammanallur 310 (17.22%) 191 (19.13%) 119 (14.84%) Devarayapuram 153 (8.5%) 80 (8.01%) 73 (9.10%) Jagirnaickenpalyam 20 (1.11%) 9 (0.90%) 11 (1.37%) Vellaimalaipattinam 45 (2.5%) 23 (2.30%) 22 (2.74%) Narasipuram 62 (3.44%) 44 (4.40%) 18 (2.24%) Madavarayapuram 243 (13.5%) 122 (12.22%) 121 (15.08%) Ikkaraibooluvampatti 114 (6.33%) 71 (7.11%) 43 (5.36%) Madampatti 88 (4.88%) 45 (4.50%) 43 (5.36%) Theethipalayam 170 (9.44%) 85 (8.51%) 85 (10.59%) Boluvampatti(R.F) 4 (0.22%) 2 (0.20%) 2 (0.24%) Perur Chettipalayam (CT) 591 (32.83%) 326 (32.66%) 265 (33.04%) Total 1800 (100%) 998 (100%) 802 (100%) Source: District Planning Commission, Coimbatore.

Table 18: Non Workers for Marginal Workers Population of Thondamuthur Block Villages Total Male Female Thennammanallur 2507 (7.47%) 865 (7.11%) 1642 (7.68%) Devarayapuram 2964 (8.83%) 1062 (8.73%) 1902 (8.90%) Jagirnaickenpalyam 751 (2.23%) 352 (2.89%) 399 (1.86%) Vellaimalaipattinam 2175 (6.48%) 981 (8.06%) 1194 (5.58%) Narasipuram 1204 (3.59%) 457 (3.75%) 747 (3.49%) Madavarayapuram 3268 (9.74%) 1223 (10.05%) 2045 (9.56%) Ikkaraibooluvampatti 2976 (8.87%) 1102 (9.06%) 1874 (8.76%) Madampatti 3177 (9.47%) 1200 (9.86%) 1977 (9.25%) Theethipalayam 4728 (14.09%) 1606 (13.20%) 3122 (14.60%) Boluvampatti(R.F) 79 (0.23%) 47 (0.38%) 32 (0.14%) Perur Chettipalayam (CT) 9703 (28.93%) 3268 (26.86%) 6435 (30.11%) Total 33532 (100%) 12163 (100%) 21369 (100%) Source: District Planning Commission, Coimbatore.

Urban wise data of Thondanmuthur Block

Table 19: Population of Thondamuthur Block Urban No. Household Total Male Female Thondamuthur (TP) 3320 (16.92%) 11492 (16.39%) 5572 (16.06%) 5920 (16.73%) Dhaliyur (TP) 3208 (16.35%) 11500 (16.41%) 5758 (16.60%) 5742 (16.23%) Vedapatti (TP) 3209 (16.36%) 11658 (16.64%) 5758 (16.60%) 5900 (16.68%) Perur (TP) 2211 (11.27%) 8004 (11.42%) 4010 (11.56%) 3994 (11.29%) Thenkarai (TP) 2093 (10.67%) 7349 (10.49%) 3657 (10.54%) 3692 (10.43%) Booluvapatti (TP) 3575 (18.22%) 12853 (18.34%) 6386 (18.42%) 6467 (18.27%) Alanthurai (TP) 2004 (10.21%) 7221 (10.31%) 3547 (10.22%) 3674 (10.37%) Total 19620 (100%) 70077 (100%) 34688 (100%) 35389 (100%) Source: District Planning Commission, Coimbatore.

Table 20: 0-6 age group population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 1051 16.96 525 16.67 526 17.26 Dhaliyur (TP) 1014 16.36 517 16.41 497 16.31 Vedapatti (TP) 1133 18.28 569 18.07 564 18.50 Perur (TP) 690 11.13 345 10.96 345 11.32 Thenkarai (TP) 567 9.16 299 9.50 268 8.79 Booluvapatti (TP) 1153 18.61 591 18.77 562 18.44 Alanthurai (TP) 589 9.50 303 9.62 286 9.38 Total 6197 100.00 3149 100.00 3048 100.00 Source: District Planning Commission, Coimbatore.

Table 21: SC Population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 2274 15.88 1093 15.47 1181 16.28 Dhaliyur (TP) 1424 9.94 700 9.91 724 9.98 Vedapatti (TP) 4398 30.71 2177 30.81 2221 30.61 Perur (TP) 1211 8.46 602 8.52 609 8.40 Thenkarai (TP) 1016 7.10 513 7.26 503 6.93 Booluvapatti (TP) 2901 20.26 1448 20.50 1453 20.03 Alanthurai (TP) 1096 7.65 532 7.53 564 7.77 Total 14320 100.00 7065 100.00 7255 100.00 Source: District Planning Commission, Coimbatore.

Table 22: ST Population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 193 23.59 97 23.60 96 23.59 Dhaliyur (TP) 1 0.12 0 0 1 0.25 Vedapatti (TP) 0 0 0 0 0 0 Perur (TP) 0 0 0 0 0 0 Thenkarai (TP) 77 9.42 42 10.22 35 8.60 Booluvapatti (TP) 22 2.69 11 2.68 11 2.70 Alanthurai (TP) 525 64.18 261 63.50 264 64.86 Total 818 100.00 411 100.00 407 100.00 Source: District Planning Commission, Coimbatore.

Table 23: Literate of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 8167 16.95 4292 16.55 3875 17.41 Dhaliyur (TP) 8279 17.18 4501 17.35 3778 16.99 Vedapatti (TP) 8562 17.76 4519 17.42 4043 18.17 Perur (TP) 6144 12.75 3252 12.54 2892 13.00 Thenkarai (TP) 4393 9.12 2482 9.56 1911 8.58 Booluvapatti (TP) 8120 16.85 4474 17.25 3646 16.40 Alanthurai (TP) 4527 9.39 2421 9.33 2106 9.45 Total 48192 100.00 25941 100.00 22251 100.00 Source: District Planning Commission, Coimbatore.

Table 24: Illiterate of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 3325 15.19 1280 14.64 2045 15.57 Dhaliyur (TP) 3221 14.72 1257 14.37 1964 14.95 Vedapatti (TP) 3096 14.15 1239 14.16 1857 14.13 Perur (TP) 1860 8.50 758 8.67 1102 8.39 Thenkarai (TP) 2956 13.51 1175 13.43 1781 13.56 Booluvapatti (TP) 4733 21.63 1912 21.86 2821 21.47 Alanthurai (TP) 2694 12.30 1126 12.87 1568 11.93 Total 21885 100.00 8747 100.00 13138 100.00 Source: District Planning Commission, Coimbatore.

Table 25: Total Workers of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 5680 16.31 3579 15.93 2101 16.98 Dhaliyur (TP) 5841 16.77 3764 16.76 2077 16.79 Vedapatti (TP) 4991 14.33 3487 15.52 1504 12.16 Perur (TP) 3696 10.61 2596 11.56 1100 8.89 Thenkarai (TP) 4083 11.72 2462 10.97 1621 13.11 Booluvapatti (TP) 6574 18.87 4190 18.65 2384 19.27 Alanthurai (TP) 3967 11.39 2384 10.61 1583 12.80 Total 34832 100.00 22462 100.00 12370 100.00 Source: District Planning Commission, Coimbatore.

Table 26: Main Workers of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 5168 16.23 3278 15.59 1890 17.48 Dhaliyur (TP) 5267 16.55 3477 16.54 1790 16.56 Vedapatti (TP) 4447 13.97 3321 15.80 1126 10.42 Perur (TP) 3531 11.09 2527 12.02 1004 9.29 Thenkarai (TP) 3912 12.29 2390 11.37 1522 14.07 Booluvapatti (TP) 5862 18.41 3815 18.14 2047 18.93 Alanthurai (TP) 3647 11.46 2215 10.54 1432 13.25 Total 31834 100.00 21023 100.00 10811 100.00 Source: District Planning Commission, Coimbatore.

Table 27: Cultivator of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 274 10.17 205 11.71 69 7.32 Dhaliyur (TP) 243 9.02 161 9.19 82 8.70 Vedapatti (TP) 58 2.15 45 2.57 13 1.38 Perur (TP) 25 0.93 23 1.32 2 0.21 Thenkarai (TP) 729 27.06 432 24.67 297 31.49 Booluvapatti (TP) 751 27.88 521 29.75 230 24.39 Alanthurai (TP) 614 22.79 364 20.79 250 26.51 Total 2694 100.00 1751 100.00 943 100.00 Source: District Planning Commission, Coimbatore.

Table 28: Agri Labour of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 1347 14.14 718 14.70 629 13.54 Dhaliyur (TP) 1409 14.79 713 14.60 696 14.98 Vedapatti (TP) 657 6.89 350 7.17 307 6.62 Perur (TP) 252 2.65 127 2.60 125 2.69 Thenkarai (TP) 1787 18.75 943 19.31 844 18.16 Booluvapatti (TP) 2274 23.86 1137 23.27 1137 24.48 Alanthurai (TP) 1803 18.92 896 18.35 907 19.53 Total 9529 100.00 4884 100.00 4645 100.00 Source: District Planning Commission, Coimbatore.

Table 29: Household of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 149 23.54 72 23.84 77 23.26 Dhaliyur (TP) 104 16.43 45 14.90 59 17.82 Vedapatti (TP) 72 11.37 39 12.91 33 9.97 Perur (TP) 96 15.17 54 17.89 42 12.69 Thenkarai (TP) 101 15.96 35 11.59 66 19.94 Booluvapatti (TP) 54 8.53 26 8.61 28 8.46 Alanthurai (TP) 57 9.00 31 10.26 26 7.86 Total 633 100.00 302 100.00 331 100.00 Source: District Planning Commission, Coimbatore.

Table 30: Other Workers of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 3398 17.90 2283 16.21 1115 22.79 Dhaliyur (TP) 3511 18.50 2558 18.16 953 19.48 Vedapatti (TP) 3660 19.29 2887 20.50 773 15.80 Perur (TP) 3158 16.64 2323 16.49 835 17.07 Thenkarai (TP) 1295 6.83 980 6.95 315 6.44 Booluvapatti (TP) 2783 14.66 2131 15.13 652 13.33 Alanthurai (TP) 1173 6.18 924 6.56 249 5.09 Total 18978 100.00 14086 100.00 4892 100.00 Source: District Planning Commission, Coimbatore.

Table 31: Marginal Workers Population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 512 17.08 301 20.92 211 13.53 Dhaliyur (TP) 574 19.15 287 19.94 287 18.41 Vedapatti (TP) 544 18.15 166 11.54 378 24.25 Perur (TP) 165 5.50 69 4.79 96 6.16 Thenkarai (TP) 171 5.70 72 5.01 99 6.35 Booluvapatti (TP) 712 23.75 375 26.06 337 21.62 Alanthurai (TP) 320 10.67 169 11.74 151 9.68 Total 2998 100.00 1439 100.00 1559 100.00 Source: District Planning Commission, Coimbatore.

Table 32: Cultivator for Marginal Workers Population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 13 11.71 10 16.95 3 5.77 Dhaliyur (TP) 7 6.31 5 8.47 2 3.85 Vedapatti (TP) 14 12.61 10 16.95 4 7.69 Perur (TP) 10 9.01 3 5.08 7 13.46 Thenkarai (TP) 2 1.80 1 1.70 1 1.92 Booluvapatti (TP) 3 2.70 1 1.69 2 3.85 Alanthurai (TP) 62 55.86 29 49.15 33 63.46 Total 111 100.00 59 100.00 52 100.00 Source: District Planning Commission, Coimbatore.

Table 33: Agri Labour for Marginal Workers Population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 172 16.09 91 22.58 81 12.16 Dhaliyur (TP) 175 16.37 91 22.58 84 12.61 Vedapatti (TP) 269 25.16 32 7.94 237 35.59 Perur (TP) 9 0.84 2 0.50 7 1.05 Thenkarai (TP) 62 5.80 19 4.71 43 6.46 Booluvapatti (TP) 317 29.65 142 35.24 175 26.28 Alanthurai (TP) 65 6.08 26 6.45 39 5.86 Total 1069 100.00 403 100.00 666 100.00 Source: District Planning Commission, Coimbatore.

Table 34: Household for Marginal Workers Population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 24 11.21 4 5 20 14.93 Dhaliyur (TP) 14 6.54 2 2.5 12 8.96 Vedapatti (TP) 18 8.41 8 10 10 7.47 Perur (TP) 2 0.93 0 0 2 1.48 Thenkarai (TP) 13 6.08 2 2.5 11 8.21 Booluvapatti (TP) 120 56.08 60 75 60 44.77 Alanthurai (TP) 23 10.75 4 5 19 14.18 Total 214 100.00 80 100.00 134 100.00 Source: District Planning Commission, Coimbatore.

Table 35: Other Workers for Marginal Workers Population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 303 18.89 196 21.85 107 15.13 Dhaliyur (TP) 378 23.57 189 21.07 189 26.73 Vedapatti (TP) 243 15.15 116 12.93 127 17.96 Perur (TP) 144 8.98 64 7.13 80 11.32 Thenkarai (TP) 94 5.86 50 5.57 44 6.23 Booluvapatti (TP) 272 16.96 172 19.18 100 14.14 Alanthurai (TP) 170 10.59 110 12.27 60 8.49 Total 1604 100.00 897 100.00 707 100.00 Source: District Planning Commission, Coimbatore.

Table 36: Non Workers for Marginal Workers Population of Thondamuthur Block Urban Total Percentage Male Percentage Female Percentage Thondamuthur (TP) 5812 16.49 1993 16.30 3819 16.59 Dhaliyur (TP) 5659 16.06 1994 16.31 3665 15.92 Vedapatti (TP) 6667 18.92 2271 18.58 4396 19.10 Perur (TP) 4308 12.22 1414 11.57 2894 12.57 Thenkarai (TP) 3266 9.27 1195 9.77 2071 9.00 Booluvapatti (TP) 6279 17.81 2196 17.96 4083 17.74 Alanthurai (TP) 3254 9.23 1163 9.51 2091 9.08 Total 35245 100.00 12226 100.00 23019 100.00 Source: District Planning Commission, Coimbatore.

Block Wise data of Coimbatore District

Table 37: Population of Coimbatore District Urban No. Household Total Male Female (%) % % % Perianaickanpalam 57553 (6%) 205389 (5.93%) 103722 (5.99%) 101667 (5.88%) Sarcarsamakulam 13974 (1.45%) 48793 (1.44%) 24370 (1.4%) 24423 (1.41%) Madukarai 40287 (4.2%) 146080 (4.24%) 73348 (4.24%) 72732 (4.20%) Thondamuthur 38044 (3.96%) 136381 (3.94%) 67816 (3.92%) 68565 (3.96%) Annur 30457 (3.16%) 108673 (3.14%) 54323 (3.14%) 54350 (3.14%) Karamadai 73189 (7.63%) 260172 (7.53%) 129447 (7.48%) 130725 (7.56%) Sulur 70178 (7.32%) 243687 (7.04%) 122530 (7.08%) 121157 (7.03%) Sulthanpet 22922 (2.36%) 77364 (2.23%) 38639 (2.23%) 38725 (2.24%) Pollachi North 55504 (5.76%) 196521 (5.68%) 97641 (5.64%) 98880 (5.74%) Pollachi South 36026 (3.76%) 124755 (3.6%) 61979 (3.58%) 62776 (3.63%) Kinathukadavu 31606 (3.28%) 108269 (3.13%) 53896 (3.12%) 54373 (3.14%) Anaimalai 61813 (6.61%) 217242 (6.28%) 107523 (6.24%) 109719 (6.34%) Corporation 426482 (44.51%) 1584719 (45.82%) 794063 (45.94%) 790656 (45.73%) District Total 958035 (100%) 3458045 (100%) 1729297 (100%) 1728748 (100%) Source: District Planning Commission, Coimbatore.

Table 38: 0-6 age group population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 18509 5.79 9485 5.82 9024 5.78 Sarcarsamakulam 4397 1.37 2222 1.36 2175 1.39 Madukarai 13233 4.14 6792 4.16 6441 4.12 Thondamuthur 12185 3.84 6239 3.82 5946 3.82 Annur 9645 3.03 4975 3.04 4670 2.99 Karamadai 23023 7.20 11703 7.16 11320 7.25 Sulur 24168 7.56 12339 7.55 11829 7.57 Sulthanpet 5957 1.86 3022 1.85 2935 1.88 Pollachi North 16158 5.05 8204 5.04 7954 5.09 Pollachi South 10337 3.23 5287 3.23 5050 3.23 Kinathukadavu 8529 2.67 4375 2.68 4154 2.66 Anaimalai 16972 5.34 8674 5.34 8298 5.34 Corporation 156219 48.92 79913 48.95 76306 48.88 District Total 319332 100 163230 100 156102 100 Source: District Planning Commission, Coimbator

Table 39: SC Population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 25868 4.83 12990 4.86 12878 4.78 Sarcarsamakulam 9447 1.76 4719 1.76 4728 1.75 Madukarai 30097 5.64 14942 5.59 15155 5.63 Thondamuthur 27018 5.04 13386 5.04 13632 5.07 Annur 28616 5.33 14368 5.38 14248 5.29 Karamadai 44149 8.23 21985 8.23 22164 8.24 Sulur 37940 7.07 18969 7.13 18971 7.05 Sulthanpet 17903 3.34 8885 3.32 9018 3.35 Pollachi North 33702 6.28 16603 6.23 17099 6.35 Pollachi South 25551 4.76 12695 4.75 12856 4.78 Kinathukadavu 22060 4.14 10876 4.07 11184 4.15 Anaimalai 71816 13.40 35504 13.29 36312 13.53 Corporation 161744 30.18 81038 30.35 80706 30.03 District Total 535911 100 266960 100 268951 100 Source: District Planning Commission, Coimbatore.

Table 40: ST Population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 3929 13.86 1985 13.93 1944 13.79 Sarcarsamakulam 25 0.08 11 0.07 14 0.09 Madukarai 1109 3.94 572 4.04 537 3.84 Thondamuthur 1736 6.14 871 6.14 865 6.13 Annur 45 0.15 23 0.16 22 0.15 Karamadai 8712 30.73 4317 30.30 4395 31.17 Sulur 169 0.59 94 0.65 75 0.53 Sulthanpet 13 0.04 9 0.06 4 0.03 Pollachi North 949 3.34 477 3.34 472 3.34 Pollachi South 236 0.84 118 0.83 118 0.83 Kinathukadavu 1756 6.19 862 6.05 894 6.34 Anaimalai 7955 28.06 4032 28.30 3923 27.82 Corporation 1708 6.04 874 6.13 834 5.94 District Total 28342 100 14245 100 14097 100 Source: District Planning Commission, Coimbatore.

Table 41: Literate of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalm 156097 5.92 83762 6.00 72335 5.84 Sarcarsamakulam 33640 1.27 18210 1.30 15430 1.24 Madukarai 106359 4.03 57336 4.14 49023 3.94 Thondamuthur 94519 3.58 51049 3.65 43470 3.50 Annur 71832 2.74 39598 2.83 32234 2.59 Karamadai 185053 7.02 99211 7.14 85842 6.94 Sulur 182064 6.90 97884 7.02 84180 6.78 Sulthanpet 51363 1.94 28491 2.04 22872 1.84 Pollachi North 146811 5.56 77948 5.58 68863 5.54 Pollachi South 88463 3.35 47641 3.41 40822 3.28 Kinathukadavu 71941 2.73 39755 2.85 32186 2.59 Anaimalai 150862 5.72 81716 5.85 69146 5.59 Corporation 1296903 49.24 672189 48.19 624714 50.33 District Total 2635907 100 1394790 100 1241117 100 Source: District Planning Commission, Coimbatore

Table 42: Illiterate of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 49292 5.99 19960 5.96 29332 6.04 Sarcarsamakulam 15153 1.84 6160 1.84 8993 1.84 Madukarai 39721 4.84 16012 4.78 23709 4.86 Thondamuthur 41862 5.09 16767 5.04 25095 5.14 Annur 36841 4.48 14725 4.40 22116 4.53 Karamadai 75119 9.13 30236 9.03 44883 9.20 Sulur 61623 7.49 24646 7.36 36977 7.58 Sulthanpet 26001 3.16 10148 3.03 15853 3.25 Pollachi North 49710 6.04 19693 5.88 30017 6.15 Pollachi South 36292 4.43 14338 4.28 21954 4.50 Kinathukadavu 36328 4.44 14141 4.24 22187 4.54 Anaimalai 66380 8.07 25807 7.73 40573 8.34 Corporation 287816 35.00 121874 36.43 165942 34.03 District Total 822138 100 334507 100 487631 100 Source: District Planning Commission, Coimbatore.

Table 43: Total Workers of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 95450 6.08 64866 5.98 30584 6.30 Sarcarsamakulam 23535 1.50 15556 1.44 7979 1.64 Madukarai 67996 4.33 46302 4.27 21694 4.47 Thondamuthur 67604 4.31 43427 4.00 24177 4.98 Annur 56628 3.61 35896 3.34 20732 4.27 Karamadai 120923 7.73 82146 7.58 38777 7.99 Sulur 113915 7.26 77845 7.18 36070 7.43 Sulthanpet 44842 2.85 26361 2.44 18481 3.84 Pollachi North 95186 6.07 63404 5.85 31782 6.57 Pollachi South 62430 3.98 40159 3.70 22271 4.59 Kinathukadavu 59357 3.78 36480 3.39 22877 4.74 Anaimalai 115476 7.36 67785 6.25 47691 9.83 Corporation 644608 41.14 482898 44.58 161710 33.35 District Total 1567950 100 1083125 100 484825 100 Source: District Planning Commission, Coimbatore.

Table 44: Main Workers of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 86789 6.04 60455 5.94 26334 6.25 Sarcarsamakulam 19912 1.37 13712 1.34 6200 1.47 Madukarai 60532 4.19 42382 4.14 18150 4.34 Thondamuthur 59248 4.10 39231 3.83 20017 4.75 Annur 52155 3.64 33984 3.34 18171 4.34 Karamadai 109408 7.58 76450 7.47 32958 7.83 Sulur 103023 7.13 72481 7.08 30542 7.25 Sulthanpet 41057 2.84 24806 2.43 16251 3.86 Pollachi North 87816 6.08 60145 5.88 27671 6.57 Pollachi South 58948 4.08 38656 3.78 20292 4.82 Kinathukadavu 55022 3.81 34698 3.39 20324 4.82 Anaimalai 105129 7.28 63217 6.18 41912 9.95 Corporation 604213 41.86 462111 45.20 142102 33.75 District Total 1443252 100 1022328 100 420924 100 Source: District Planning Commission, Coimbatore.

Table 45: Cultivator of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 3847 5.10 2431 4.94 1416 5.44 Sarcarsamakulam 1783 2.36 1222 2.48 561 2.15 Madukarai 5845 7.75 3847 7.78 1998 7.68 Thondamuthur 5329 7.07 3583 7.25 1746 6.74 Annur 7882 10.45 5035 10.18 2847 10.95 Karamadai 11694 15.50 7465 15.10 4229 16.26 Sulur 4120 5.46 2818 5.70 1302 5.00 Sulthanpet 9593 12.74 5820 11.79 3773 14.54 Pollachi North 4493 5.95 3136 6.34 1357 5.21 Pollachi South 4223 5.59 2853 5.79 1370 5.26 Kinathukadavu 9042 11.99 5736 11.60 3306 12.73 Anaimalai 4226 5.60 3018 6.10 1208 4.64 Corporation 3334 4.44 2448 4.95 886 3.40 District Total 75411 100 49412 100 25999 100 Source: District Planning Commission, Coimbatore.

Table 46: Agri Labour of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 6617 3.28 3546 3.35 3071 3.20 Sarcarsamakulam 3749 1.86 2062 1.95 1687 1.76 Madukarai 9937 4.93 4988 4.74 4949 5.17 Thondamuthur 19457 9.66 10058 9.52 9399 9.84 Annur 14438 7.17 7731 7.34 6707 7.00 Karamadai 21908 10.88 12414 11.75 9494 9.94 Sulur 7286 3.64 3900 3.69 3386 3.53 Sulthanpet 14705 7.30 7530 7.12 7175 7.49 Pollachi North 19801 9.83 9835 9.30 9966 10.42 Pollachi South 16061 7.97 8181 7.74 7880 8.23 Kinathukadavu 19423 9.64 9665 9.14 9758 10.19 Anaimalai 41308 20.54 21791 20.64 19517 20.39 Corporation 6661 3.30 3939 3.72 2722 2.84 District Total 201351 100 105640 100 95711 100 Source: District Planning Commission, Coimbatore.

Table 47: Household of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 1975 4.43 1029 3.98 946 5.05 Sarcarsamakulam 378 0.84 193 0.74 185 0.98 Madukarai 1320 2.96 658 2.54 662 3.53 Thondamuthur 1147 2.57 598 2.34 549 2.93 Annur 2100 4.74 1162 4.49 938 5.00 Karamadai 6104 13.69 3334 12.89 2770 14.79 Sulur 3314 7.43 2147 8.30 1167 6.23 Sulthanpet 3164 7.09 1722 6.66 1442 7.69 Pollachi North 3320 7.44 1780 6.88 1540 8.22 Pollachi South 2268 5.08 1198 4.63 1070 5.74 Kinathukadavu 1527 3.44 813 3.14 714 3.84 Anaimalai 1545 3.46 875 3.38 670 3.57 Corporation 16420 36.83 10345 40.03 6075 32.43 District Total 44582 100 25854 100 18728 100 Source: District Planning Commission, Coimbatore.

Table 48: Other Workers of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 74350 6.64 53449 6.35 20901 7.45 Sarcarsamakulam 14002 1.24 10235 1.24 3767 1.34 Madukarai 43430 3.87 32889 3.90 10541 3.75 Thondamuthur 33315 2.96 24992 2.97 8323 2.96 Annur 27735 2.47 20056 2.38 7679 2.73 Karamadai 69702 6.24 53237 6.34 16465 5.87 Sulur 88303 7.87 63616 7.56 24687 8.80 Sulthanpet 13595 1.21 9734 1.156 3861 1.37 Pollachi North 60202 5.36 45394 5.39 14808 5.27 Pollachi South 36396 3.24 26424 3.14 9972 3.55 Kinathukadavu 25030 2.23 18484 2.19 6546 2.33 Anaimalai 58050 5.17 37533 4.46 20517 7.34 Corporation 577798 51.50 445379 52.93 132419 47.24 District Total 1121908 100 841422 100 280486 100 Source: District Planning Commission, Coimbatore.

Table 49: Marginal Workers Population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 8661 6.94 4411 7.25 4250 6.65 Sarcarsamakulam 3623 2.90 1844 3.03 1779 2.79 Madukarai 7464 5.98 3920 6.44 3544 5.54 Thondamuthur 8356 6.70 4196 6.90 4160 6.54 Annur 4473 3.58 1912 3.14 2561 4.00 Karamadai 11515 9.23 5696 9.36 5819 9.10 Sulur 10892 8.73 5364 8.82 5528 8.65 Sulthanpet 3785 3.04 1555 2.55 2230 3.49 Pollachi North 7370 5.94 3259 5.39 4111 6.44 Pollachi South 3482 2.79 1503 2.49 1979 3.09 Kinathukadavu 4335 3.49 1782 2.93 2553 3.99 Anaimalai 10347 8.29 4568 7.51 5779 9.04 Corporation 40395 32.39 20787 34.19 19608 30.69 District Total 124698 100 60797 100 63901 100 Source: District Planning Commission, Coimbatore.

Table 50: Cultivator for Marginal Workers Population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 303 6.30 159 7.04 144 5.67 Sarcarsamakulam 150 3.14 80 3.54 70 2.75 Madukarai 482 10.04 249 10.99 233 9.17 Thondamuthur 253 5.26 128 5.64 125 4.92 Annur 319 6.63 126 5.55 193 7.64 Karamadai 740 15.39 342 15.08 398 15.67 Sulur 388 8.09 173 7.64 215 8.46 Sulthanpet 348 7.24 158 6.96 190 7.48 Pollachi North 182 3.78 88 3.88 94 3.70 Pollachi South 134 2.78 58 2.55 76 2.99 Kinathukadavu 408 8.48 169 7.45 239 9.42 Anaimalai 216 4.49 78 3.44 138 5.44 Corporation 883 18.38 459 20.24 424 16.69 District Total 4806 100 2267 100 2539 100 Source: District Planning Commission, Coimbatore.

Table 51: Agri Labour for Marginal Workers Population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 1038 3.64 455 3.85 583 3.45 Sarcarsamakulam 1847 6.44 927 7.85 920 5.45 Madukarai 1581 5.53 686 5.84 895 5.30 Thondamuthur 4348 15.16 2027 17.16 2321 13.75 Annur 1676 5.84 666 5.64 1010 5.98 Karamadai 3806 13.27 1704 14.43 2102 12.46 Sulur 1529 5.33 648 5.48 881 5.24 Sulthanpet 1382 4.81 501 4.24 881 5.24 Pollachi North 2693 9.39 911 7.73 1782 10.56 Pollachi South 1330 4.63 481 4.07 849 5.03 Kinathukadavu 2148 7.49 796 6.74 1352 8.03 Anaimalai 4072 14.20 1448 12.26 2624 15.55 Corporation 1225 4.27 557 4.71 668 3.96 District Total 28675 100 11807 100 16868 100 Source: District Planning Commission, Coimbatore.

Table 52: Household for Marginal Workers Population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 400 7.26 135 7.54 265 7.14 Sarcarsamakulam 147 2.67 55 3.06 92 2.48 Madukarai 163 2.99 55 3.06 108 2.94 Thondamuthur 351 6.37 146 8.13 205 5.52 Annur 244 4.43 89 4.96 155 4.17 Karamadai 765 13.90 267 14.88 498 13.42 Sulur 470 8.54 142 7.94 328 8.84 Sulthanpet 301 5.46 104 5.79 197 5.34 Pollachi North 315 5.72 106 5.90 209 5.63 Pollachi South 155 2.84 40 2.22 115 3.10 Kinathukadavu 182 3.30 37 2.06 145 3.90 Anaimalai 272 4.94 92 5.12 180 4.85 Corporation 1738 31.58 526 29.34 1212 32.67 District Total 5503 100 1794 100 3709 100 Source: District Planning Commission, Coimbatore.

Table 53: Other Workers for Marginal Workers Population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 6920 8.07 3662 8.15 3258 7.99 Sarcarsamakulam 1479 1.72 782 1.74 697 1.70 Madukarai 5238 6.14 2930 6.52 2308 5.65 Thondamuthur 3404 3.97 1895 4.24 1509 3.69 Annur 2234 2.60 1031 2.29 1203 2.94 Karamadai 6204 7.23 3383 7.52 2821 6.94 Sulur 8505 9.92 4401 9.79 4104 10.09 Sulthanpet 1754 2.04 792 1.76 962 2.35 Pollachi North 4180 4.87 2154 4.79 2026 4.96 Pollachi South 1863 2.19 924 2.05 939 2.30 Kinathukadavu 1597 1.86 780 1.73 817 2.00 Anaimalai 5787 6.75 2950 6.59 2837 6.95 Corporation 36549 42.64 19245 42.83 17304 42.44 District Total 85714 100 44929 100 40785 100 Source: District Planning Commission, Coimbatore.

Table 54: Non Workers for Marginal Workers Population of Coimbatore District Urban Total Percentage Male Percentage Female Percentage Perianaickanpalam 109939 5.84 38856 6.04 71083 5.74 Sarcarsamakulam 25258 1.33 8814 1.36 16444 1.34 Madukarai 78084 4.13 27046 4.18 51038 4.10 Thondamuthur 68777 3.63 24389 3.79 44388 3.56 Annur 52045 2.75 18427 2.85 33618 2.70 Karamadai 139249 7.39 47301 7.33 91948 7.39 Sulur 129772 6.86 44685 6.91 85087 6.84 Sulthanpet 32522 1.74 12278 1.90 20244 1.62 Pollachi North 101335 5.36 34237 5.29 67098 5.39 Pollachi South 62325 3.29 21820 3.37 40505 3.25 Kinathukadavu 48912 2.58 17416 2.69 31496 2.53 Anaimalai 101766 5.38 39738 6.14 62028 4.98 Corporation 940111 49.73 311165 48.15 628946 50.56 District Total 1890095 100 646172 100 1243923 100 Source: District Planning Commission, Coimbatore.

APPENDIX - III

BAYESIAN CONVERGENCE DISTRIBUTION FOR “MEDIATING CAUSES FOR HIGH LEVEL OF INFANT MORTALITY RATE” REGRESSION MODEL

Table 1: Bayesian Convergence Distribution for “MEDIATING CAUSES FOR HIGH LEVEL OF INFANT MORTALITY RATE” Regression Model Regression weights Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PD<--EP 1.1286 0.0017 0.1553 1.0001 0.0063 0.0527 0.3935 1.8507 W1 PD<--IF 0.3290 0.0027 0.1672 1.0001 -0.0394 0.1060 -0.3561 1.0000 W2 PD<--SP 0.2169 0.0016 0.1140 1.0001 0.0005 0.0893 -0.2671 0.7312 W3 PD<--HSI 0.6057 0.0035 0.2626 1.0001 0.0002 0.0404 -0.5001 1.7120 W4 PD<--HSO -0.5748 0.0030 0.2191 1.0001 -0.0108 0.0242 -1.5297 0.3549 W5 PD<--PS 0.1460 0.0042 0.3045 1.0001 -0.0076 0.0526 -1.2556 1.3504 W6 IMR<--PS 0.0535 0.0010 0.0989 1.0001 -0.0272 0.0718 -0.4067 0.4615 W7 IMR<--HSO -0.0194 0.0011 0.0733 1.0001 -0.0237 0.0533 -0.3672 0.3530 W8 IMR<--HSI 0.0853 0.0011 0.0872 1.0001 0.0198 0.0854 -0.3041 0.4763 W9 IMR<--SP 0.1237 0.0007 0.0366 1.0002 -0.0215 0.0689 -0.0222 0.2778 W10 IMR<--IF 0.0053 0.0008 0.0557 1.0001 0.0081 0.0661 -0.2241 0.2421 W11 IMR<--EP 0.1903 0.0010 0.0628 1.0001 0.0126 0.1071 -0.0982 0.5036 W12 IMR<--PD 0.0677 0.0005 0.0337 1.0001 -0.0146 0.1704 -0.0917 0.2307 W13 Means Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PS 35.5823 0.0072 0.4328 1.0001 -0.0031 0.1223 33.4949 37.5018 M1 HSO 51.9128 0.0066 0.5486 1.0001 -0.0101 0.1336 49.4240 54.2708 M2 HSI 50.6571 0.0052 0.5025 1.0001 0.0178 0.0868 48.5695 52.7641 M3 SP 55.3209 0.0156 0.9347 1.0001 0.0333 0.1189 51.4667 60.6837 M4 IF 48.9765 0.0095 0.6679 1.0001 0.0047 0.0939 46.1269 52.2934 M5 EP 29.5971 0.0074 0.7201 1.0001 0.0203 0.0924 26.5260 33.5105 M6 Intercepts Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PD 18.8278 0.1366 10.3126 1.0001 0.0399 0.1117 -21.0773 63.5741 I1 IMR 3.7258 0.0384 3.3533 1.0001 -0.0132 0.1078 -10.4059 18.5002 I2 Covariances Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PS<->EP -1.7668 0.0543 3.4083 1.0001 -0.1196 0.1862 -17.7341 13.2941 C1 EP<->HSO 0.3576 0.0732 4.2635 1.0001 0.0250 0.2987 -19.6018 20.0613 C2 EP<->HSI -0.5606 0.0738 3.9539 1.0002 0.0196 0.3139 -18.7071 18.1469 C3 EP<->SP 30.9854 0.1634 8.0722 1.0002 0.5068 0.6856 4.8509 81.2720 C4 EP<->IF 23.7583 0.0862 5.8175 1.0001 0.4762 0.4815 2.3742 54.7915 C5 SP<->IF 22.4207 0.1652 7.1748 1.0003 0.4447 0.6002 -1.4480 68.7301 C6 HSI<->IF 7.8366 0.0628 3.7065 1.0001 0.2747 0.3780 -6.9318 30.2861 C7 HSO<->IF 9.0231 0.0495 4.0606 1.0001 0.2538 0.2837 -6.7203 31.8193 C8 PS<->IF 10.4412 0.0299 3.3104 1.0000 0.4141 0.4299 -3.2595 27.3530 C9 HSI<->SP 14.3197 0.0837 5.2757 1.0001 0.3217 0.3491 -6.1240 42.8339 C10 HSO<->SP 9.5049 0.0921 5.6307 1.0001 0.2652 0.3522 -11.1768 40.6987 C11 PS<->SP 4.5034 0.0536 4.3591 1.0001 0.1589 0.2740 -12.2499 27.2250 C12 HSO<->HSI 18.3062 0.0678 3.6993 1.0002 0.6194 0.6667 6.8002 37.1131 C13 PS<->HSI 14.4610 0.0568 2.9040 1.0002 0.6693 1.0548 5.0721 33.5268 C14 PS<->HSO 14.5448 0.0620 3.0737 1.0002 0.6723 0.9978 4.5370 32.7168 C15 Variances Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PS 18.6017 0.0526 2.9041 1.0002 0.6937 1.0256 9.2647 35.7015 V1 EP 52.0141 0.1710 8.0414 1.0002 0.5951 0.5601 28.6473 96.7870 V2 HSO 29.8439 0.0909 4.6465 1.0002 0.6017 0.5933 16.1839 53.9898 V3 HSI 25.5717 0.0705 4.0066 1.0002 0.6677 0.8558 14.0393 49.4220 V4 SP 86.5290 0.2625 13.4160 1.0002 0.6164 0.8270 46.0772 174.5425 V5 IF 44.0898 0.1077 6.7579 1.0001 0.5995 0.7005 23.8240 85.1532 V6 e2 62.6980 0.1957 9.4879 1.0002 0.6120 0.5926 35.3138 114.0337 V7 e1 6.4161 0.0160 0.9781 1.0001 0.6684 1.0642 3.5906 14.1203 V8 Source: Amos 20.0 Output

APPENDIX - IV

BAYESIAN ESTIMATION AND TESTING OF “HIGH LEVEL OF INFANT MORTALITY RATE” STRUCTURAL EQUATION LATENT MODEL

Table 1: Bayesian Convergence Distribution for “HIGH LEVEL OF INFANT MORTALITY RATE” Structural Equation Latent Model Regression weights Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PS2<--PS 1.2878 0.0251 0.1897 1.0001 0.5148 -0.0277 0.7956 2.0760 W1 PS3<--PS 1.2560 0.0242 0.1877 1.0000 0.3150 0.3821 0.6534 2.3481 W2 PS4<--PS 1.4360 0.0332 0.2261 1.0001 0.8037 0.4106 0.8771 2.3306 W3 PS5<--PS 0.6895 0.0252 0.1912 1.0000 0.1950 -0.1116 0.1160 1.3638 W4 PS6<--PS 1.2342 0.0584 0.3838 1.0001 0.3761 0.1437 -0.2752 2.6529 W5 HSO2<--HSO 0.8261 0.0766 0.4822 1.0001 1.6717 2.9830 -0.4061 3.0002 W6 HSO3<--HSO 0.7954 0.0613 0.3438 1.0000 1.3391 1.9350 0.1223 2.2170 W7 HSO4<--HSO 0.7601 0.0538 0.2941 1.0000 1.6603 2.6942 0.2336 2.0043 W8 HSO5<--HSO 1.6748 0.0979 0.5316 1.0000 1.5942 2.3396 0.7291 3.8872 W9 HSO6<--HSO 2.0060 0.1244 0.6500 1.0001 1.5703 2.3595 0.9353 4.7372 W10 HSO7<--HSO 0.8865 0.0537 0.3570 1.0001 1.4461 2.6952 -0.0004 2.6038 W11 HSO8<--HSO 1.5238 0.0897 0.4878 1.0001 1.6364 2.8668 0.7224 3.6032 W12 HSO9<--HSO 1.7285 0.0977 0.5290 1.0001 1.6155 2.2016 0.9430 3.9476 W13 HSI8<--HSI 0.4926 0.0295 0.1834 1.0001 0.2942 0.2399 -0.1578 1.0047 W14 HSI7<--HSI 1.1592 0.0751 0.3619 1.0001 0.8210 -0.4672 0.3599 2.0617 W15 HSI6<--HSI 0.6594 0.0342 0.2080 1.0001 0.4738 -0.4188 0.1056 1.4060 W16 HSI5<--HSI 1.1781 0.0631 0.3707 1.0002 0.5643 0.1100 0.1967 2.5858 W17 HSI4<--HSI 1.6031 0.0731 0.4248 1.0001 0.6085 0.7950 0.5678 3.2763 W18 HSI3<--HSI 0.8068 0.0435 0.2399 1.0001 0.5353 -0.0495 -0.0018 1.4980 W19 HSI2<--HSI 0.9141 0.0440 0.2285 1.0001 0.5774 -0.2778 0.3287 1.6286 W20 HSI1<--HSI 0.9032 0.0428 0.2151 1.0001 0.5792 -0.3165 0.3294 1.5876 W21 PD2<--PD 3.4897 0.2429 1.0864 1.0001 -0.3689 -1.1937 0.7382 5.2632 W22 PD3<--PD 2.7799 0.1529 0.7260 1.0001 -0.2413 -0.2446 0.5171 4.4113 W23 PD4<--PD 0.5263 0.0604 0.3401 1.0001 0.7000 0.3951 -0.3780 2.0647 W24 PD5<--PD 0.4991 0.0567 0.3384 1.0001 -0.3660 -0.1984 -0.9390 1.4316 W25 PD6<--PD 0.6122 0.0939 0.4606 1.0001 -0.0015 -1.0742 -0.3596 1.8121 W26 PD7<--PD -0.4238 0.0829 0.4160 1.0001 0.0306 -0.7306 -1.4692 0.7199 W27 PD8<--PD 1.1491 0.0673 0.3674 1.0001 0.2364 -0.7293 -0.0082 1.9927 W28 PD9<--PD 2.1822 0.1118 0.5605 1.0002 -0.1442 -0.5638 0.5334 3.7029 W29 PD10<--PD 3.4719 0.2526 1.1295 1.0001 -0.1540 -1.2372 0.7503 5.3186 W30 PD11<--PD 2.0583 0.1152 0.5803 1.0001 -0.0706 -0.1061 0.1987 3.4351 W31 PD12<--PD 2.5246 0.1990 0.9143 1.0001 0.0592 -1.2335 0.3442 4.1599 W32 PD13<--PD 3.0613 0.2204 0.9929 1.0001 -0.1670 -1.2088 0.6064 4.6756 W33 PD14<--PD 3.4887 0.2418 1.0846 1.0001 -0.1107 -1.2186 0.8352 5.2443 W34 PD15<--PD 3.8998 0.2655 1.1913 1.0001 -0.2189 -1.2966 0.8190 5.7606 W35 PD16<--PD 4.4809 0.3472 1.5413 1.0001 0.1199 -1.1892 0.9907 7.1780 W36 PD17<--PD 3.3367 0.2000 0.9207 1.0001 -0.5156 -0.8371 0.7366 4.7684 W37 SP2<--SP 2.8388 0.1597 0.7846 1.0002 -0.1116 0.0369 0.3811 4.5061 W38 SP3<--SP 2.8621 0.1225 0.6275 1.0001 -1.1160 1.2213 0.3820 4.4577 W39 SP4<--SP 6.0679 0.2506 1.1826 1.0001 -1.2786 2.2006 1.2665 7.9191 W40 SP5<--SP 6.2932 0.2435 1.1603 1.0001 -1.6703 3.1019 1.3048 8.2409 W41 SP6<--SP 4.9696 0.2160 1.0194 1.0001 -1.0457 1.5318 1.0863 6.7834 W42 SP7<--SP 3.5111 0.1483 0.7143 1.0001 -1.4191 1.8805 0.6605 4.6371 W43 SP8<--SP 3.4822 0.1422 0.6918 1.0002 -1.1455 1.2918 0.6430 4.7337 W44 SP9<--SP 4.0415 0.1985 0.9816 1.0001 -0.4986 -0.0342 0.6205 5.9500 W45 SP10<--SP 4.0498 0.1875 0.8886 1.0001 -0.9697 1.3150 0.7124 5.5563 W46 IF2<--IF 1.3954 0.0899 0.5040 1.0001 0.6401 -0.0841 0.1649 3.2273 W47 IF3<--IF 1.4537 0.1035 0.5945 1.0000 1.4993 3.0295 0.2859 4.2327 W48 IF4<--IF 1.4710 0.1009 0.5354 1.0001 0.1817 -0.8792 0.0965 3.0401 W49 IF5<--IF 1.4037 0.0576 0.4197 1.0001 0.4682 1.2880 0.1306 3.6974 W50 IF6<--IF 3.6282 0.2450 1.2218 1.0001 0.5005 -0.6241 0.7253 7.0554 W51 IF7<--IF 4.4379 0.2863 1.4492 1.0001 0.5097 -0.4892 1.3764 8.5224 W52 IF8<--IF 3.0370 0.1609 0.8764 1.0001 0.6584 -0.2026 0.7570 5.9211 W53 IF9<--IF 3.5308 0.2298 1.1846 1.0000 0.5958 0.0168 0.5742 7.3850 W54 EP2<--EP 0.7804 0.0160 0.1323 1.0001 0.3327 -0.0426 0.3417 1.3239 W55 EP3<--EP 1.4336 0.0281 0.1764 1.0001 0.6338 0.0091 0.8001 2.0611 W56 EP4<--EP 1.4393 0.0293 0.1799 1.0001 0.6667 0.1663 0.9467 2.1556 W57 EP5<--EP 1.2050 0.0244 0.1667 1.0001 0.5938 0.4325 0.6732 1.8568 W58 EP6<--EP 1.1618 0.0290 0.1737 1.0001 0.3473 -0.4960 0.6052 1.7485 W59 IMR4<--IMR 6.9962 0.4992 2.4662 1.0000 -0.3486 -0.8738 0.1610 11.6340 W60 IMR3<--IMR 9.8357 0.7101 3.4406 1.0001 -0.4644 -0.8371 1.5500 17.5790 W61 IMR2<--IMR 13.1786 0.9640 4.5935 1.0001 -0.3431 -0.8043 2.5199 22.1870 W62 IMR1<--IMR 14.8975 1.0313 4.9755 1.0001 -0.6599 -0.7632 3.0430 24.5328 W63 PD<--SP 0.1863 0.0318 0.2258 1.0001 0.3965 0.9866 -0.6374 1.1274 W64 PD<--PS -0.3319 0.0564 0.3581 1.0001 -1.8335 4.8451 -3.2922 0.4253 W65 PD<--IF 0.2036 0.0468 0.4261 1.0001 3.9935 22.4266 -0.8037 3.9549 W66 PD<--HSO -0.9994 0.1216 0.6795 1.0000 -1.5072 2.6507 -5.4351 -0.0428 W67 PD<--HSI 1.1319 0.1417 0.8103 1.0002 1.6112 2.4843 -0.0978 5.9010 W68 PD<--EP 0.2058 0.0244 0.1322 1.0001 -0.2013 1.4544 -0.3219 1.0320 W69 IMR<--PD 0.2047 0.0139 0.0793 1.0001 1.5320 2.9629 0.0544 0.5631 W70 Intercepts Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PS1 5.9433 0.0062 0.0730 1.0001 0.2876 -0.0741 5.6947 6.2339 I1 PS2 5.8648 0.0127 0.0899 1.0001 0.0779 -0.6596 5.5817 6.1769 I2 PS3 6.0056 0.0126 0.0984 1.0001 -0.3148 0.1526 5.6846 6.3264 I3 PS4 5.9972 0.0098 0.0929 1.0001 0.0032 -0.3573 5.6625 6.3204 I4 PS5 6.0285 0.0102 0.0872 1.0001 -0.1951 0.0433 5.7287 6.3049 I5 PS6 5.6939 0.0128 0.1475 1.0001 0.0788 -0.0407 5.1499 6.2136 I6 HSO1 5.7644 0.0116 0.0971 1.0002 0.1199 -0.2231 5.4324 6.0993 I7 HSO2 5.5568 0.0109 0.1145 1.0001 0.0253 -0.0652 5.1382 6.0465 I8 HSO3 5.9338 0.0082 0.0851 1.0000 -0.1791 0.1111 5.6112 6.3266 I9 HSO4 5.8645 0.0058 0.0584 1.0001 -0.2195 0.2320 5.6424 6.0883 I10 HSO5 5.7518 0.0138 0.1004 1.0001 0.3299 -0.1995 5.4144 6.1288 I11 HSO6 5.5544 0.0116 0.1148 1.0000 0.1532 -0.1287 5.1891 6.0217 I12 HSO7 5.6394 0.0107 0.0954 1.0001 -0.3311 0.2984 5.2182 5.9948 I13 HSO8 5.8575 0.0081 0.0813 1.0001 0.0488 0.3963 5.4826 6.1741 I14 HSO9 5.9138 0.0117 0.0876 1.0001 -0.0563 0.1744 5.6285 6.2464 I15 HSI9 5.7587 0.0080 0.0745 1.0001 0.1327 -0.2836 5.5009 6.0141 I16 HSI8 5.7330 0.0080 0.0657 1.0000 0.0594 -0.2619 5.4990 6.0116 I17 HSI7 5.7161 0.0095 0.0887 1.0001 0.0209 0.0088 5.4180 6.0411 I18 HSI6 5.5950 0.0068 0.0715 1.0001 -0.0486 0.2848 5.2355 5.8644 I19 HSI5 5.2014 0.0157 0.1194 1.0001 -0.1583 -0.2720 4.7714 5.6501 I20 HSI4 5.2382 0.0155 0.1495 1.0001 0.3143 0.0716 4.6701 5.8332 I21 HSI3 5.7633 0.0103 0.0829 1.0001 0.2061 0.5996 5.4392 6.0757 I22 HSI2 5.8152 0.0089 0.0708 1.0001 0.1740 -0.4379 5.5923 6.0562 I23 HSI1 5.8255 0.0071 0.0625 1.0001 -0.0300 -0.0155 5.5916 6.0658 I24 PD1 4.5893 0.0164 0.1427 1.0000 0.0162 -0.2723 4.1289 5.1072 I25 PD2 4.8913 0.0111 0.1290 1.0001 0.0374 0.0832 4.4325 5.4300 I26 PD3 4.8345 0.0201 0.1499 1.0001 0.2159 -0.3918 4.3347 5.4892 I27 PD4 5.3689 0.0141 0.1137 1.0001 0.0992 -0.2620 5.0178 5.8128 I28 PD5 5.4490 0.0112 0.1132 1.0002 0.1814 -0.1099 5.1043 6.0014 I29 PD6 5.5037 0.0094 0.0987 1.0001 -0.1746 -0.0168 5.1093 5.9284 I30 PD7 5.8190 0.0133 0.1164 1.0001 -0.4449 0.7782 5.3621 6.2012 I31 PD8 5.4006 0.0118 0.1020 1.0001 0.1019 0.4437 4.9882 5.8092 I32 PD9 5.4129 0.0107 0.1156 1.0001 -0.0845 0.3276 4.8260 5.9269 I33 PD10 5.3647 0.0139 0.1225 1.0000 -0.2649 0.3272 4.8554 5.7824 I34 PD11 4.4648 0.0150 0.1358 1.0001 0.2392 0.0191 3.9675 5.1264 I35 PD12 4.7040 0.0160 0.1435 1.0001 0.1283 -0.0329 4.1001 5.2024 I36 PD13 4.9902 0.0146 0.1284 1.0001 0.0859 -0.0751 4.4689 5.5989 I37 PD14 4.8988 0.0140 0.1252 1.0001 0.2194 -0.0629 4.3989 5.3967 I38 PD15 4.7929 0.0123 0.1393 1.0001 0.2443 0.3632 4.2802 5.4398 I39 PD16 4.7395 0.0130 0.1411 1.0001 -0.0773 0.3527 4.0605 5.3255 I40 PD17 5.1277 0.0142 0.1479 1.0001 -0.0162 -0.0668 4.4993 5.7598 I41 SP1 4.8678 0.0170 0.1545 1.0001 0.0826 -0.0616 4.2374 5.4214 I42 SP2 5.1904 0.0129 0.1216 1.0002 0.3107 0.2328 4.7177 5.6681 I43 SP3 5.6778 0.0107 0.1091 1.0001 0.0664 -0.2589 5.1455 6.0812 I44 SP4 5.4813 0.0151 0.1346 1.0001 -0.2056 -0.0996 4.9619 6.0439 I45 SP5 5.5806 0.0170 0.1506 1.0001 -0.0097 -0.1465 5.0284 6.2818 I46 SP6 5.6969 0.0172 0.1310 1.0001 -0.1024 0.1008 5.2144 6.1572 I47 SP7 5.6863 0.0075 0.0928 1.0000 -0.1078 0.0742 5.2482 6.0621 I48 SP8 5.7880 0.0128 0.1124 1.0001 0.2151 -0.2064 5.3857 6.2089 I49 SP9 5.5059 0.0253 0.1802 1.0001 0.2228 -0.0712 5.0017 6.0792 I50 SP10 5.7646 0.0196 0.1323 1.0001 -0.2228 -0.0465 5.3811 6.2861 I51 IF1 5.8855 0.0135 0.1006 1.0001 0.2015 -0.0662 5.5862 6.2356 I52 IF2 5.8538 0.0076 0.0753 1.0001 0.1003 0.0592 5.5219 6.1720 I53 IF3 5.7125 0.0106 0.0913 1.0001 0.0377 -0.2394 5.3175 6.1472 I54 IF4 5.6663 0.0073 0.0861 1.0002 0.1379 0.1091 5.3336 6.0135 I55 IF5 5.6628 0.0097 0.0971 1.0001 0.0203 0.3398 5.2537 6.0649 I56 IF6 5.2563 0.0124 0.1251 1.0000 -0.0286 -0.0375 4.7956 5.6717 I57 IF7 5.1238 0.0138 0.1409 1.0001 0.2171 0.1709 4.5717 5.6377 I58 IF8 5.0504 0.0173 0.1316 1.0001 0.0875 -0.4653 4.5348 5.5768 I59 IF9 4.7996 0.0106 0.1392 1.0000 -0.2116 -0.1274 4.2174 5.2464 I60 EP1 4.6951 0.0138 0.1237 1.0000 0.0622 -0.1171 4.2498 5.2535 I61 EP2 5.1488 0.0146 0.1242 1.0001 0.0225 -0.4966 4.6590 5.6220 I62 EP3 4.8772 0.0154 0.1428 1.0001 0.1119 -0.1226 4.2778 5.4017 I63 EP4 5.0138 0.0183 0.1505 1.0002 0.3271 -0.0804 4.4769 5.6462 I64 EP5 4.8949 0.0155 0.1420 1.0001 0.0023 -0.1956 4.3190 5.4104 I65 EP6 5.0287 0.0147 0.1284 1.0001 -0.0712 0.0090 4.5271 5.5477 I66 IMR5 5.8305 0.0085 0.0861 1.0001 0.1841 -0.1682 5.5580 6.1456 I67 IMR4 5.4258 0.0131 0.1143 1.0001 -0.1055 0.0901 4.9292 5.8757 I68 IMR3 5.5443 0.0110 0.0958 1.0001 0.0923 0.1808 5.0959 5.8809 I69 IMR2 5.5281 0.0139 0.1119 1.0001 -0.1640 0.1905 5.0619 5.9177 I70 IMR1 5.3086 0.0119 0.1136 1.0000 -0.2338 0.3196 4.8219 5.8491 I71 Covariances Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PS<->SP 0.0098 0.0014 0.0162 1.0001 0.9676 6.0889 -0.0948 0.1799 C1 EP<->SP 0.1000 0.0078 0.0482 1.0002 2.5838 9.7469 0.0063 0.4934 C2 PS<->HSO 0.1572 0.0076 0.0476 1.0001 0.1024 -0.5411 0.0350 0.3447 C3 HSO<->IF 0.0259 0.0025 0.0175 1.0001 1.0623 3.2751 -0.0504 0.1190 C4 HSI<->IF 0.0347 0.0028 0.0217 1.0001 1.2736 3.2649 -0.0255 0.1825 C5 EP<->IF 0.1684 0.0093 0.0641 1.0002 1.0744 1.6951 0.0394 0.5013 C6 EP<->PS -0.0321 0.0085 0.0667 1.0001 -0.1093 -0.2372 -0.3176 0.2049 C7 PS<->HSI 0.2198 0.0106 0.0651 1.0000 0.1081 -0.0869 0.0663 0.5860 C8 EP<->HSI -0.0064 0.0072 0.0639 1.0001 0.3350 0.8247 -0.2272 0.3294 C9 HSO<->HSI 0.2003 0.0118 0.0693 1.0002 0.5420 0.1681 0.0491 0.5513 C10 EP<->HSO -0.0271 0.0084 0.0543 1.0001 0.1000 -0.0672 -0.1876 0.1891 C11 PS<->IF 0.0439 0.0029 0.0232 1.0001 1.3558 3.2567 -0.0194 0.2109 C12 HSO<->SP 0.0218 0.0018 0.0156 1.0001 1.7741 7.4951 -0.0278 0.1631 C13 SP<->IF 0.0271 0.0026 0.0164 1.0001 2.9941 13.6794 -0.0111 0.1828 C14 HSI<->SP 0.0260 0.0022 0.0182 1.0000 1.8922 7.6643 -0.0422 0.1820 C15 Variances Mean S.E. S.D. C.S. Skewness Kurtosis Min Max Name PS 0.3027 0.0115 0.0824 1.0001 0.4540 0.3497 0.1111 0.8383 V1 HSO 0.2130 0.0158 0.0867 1.0002 -0.0978 -0.6471 0.0269 0.4836 V2 HSI 0.2602 0.0197 0.1056 1.0001 0.7468 1.0880 0.0662 0.8318 V3 SP 0.0559 0.0102 0.0577 1.0000 5.1880 33.8367 0.0158 0.8355 V4 IF 0.0919 0.0097 0.0560 1.0001 1.4641 3.1690 0.0154 0.4637 V5 EP 0.9599 0.0292 0.2390 1.0001 0.7749 1.3144 0.3909 2.1596 V6 e72 0.0002 0.0023 0.0187 1.0001 -1.0677 8.0380 -0.1855 0.1272 V7 e73 0.0032 0.0007 0.0039 1.0000 2.6486 7.4806 0.0002 0.0272 V8 e1 0.2851 0.0061 0.0474 1.0001 0.3881 -0.2130 0.1455 0.4581 V9 e2 0.2592 0.0057 0.0508 1.0001 0.4328 0.2765 0.0953 0.4785 V10 e3 0.3734 0.0055 0.0554 1.0000 0.4418 0.2421 0.2071 0.6472 V11 e4 0.2648 0.0075 0.0584 1.0001 0.3387 -0.4207 0.1088 0.4797 V12 e5 0.6212 0.0107 0.0975 1.0001 0.6632 0.0464 0.3579 0.9687 V13 e6 2.0024 0.0240 0.2627 1.0001 0.6364 0.6686 1.2169 3.3710 V14 e7 0.7039 0.0113 0.1036 1.0000 0.6106 0.5609 0.4378 1.2304 V15 e8 1.2746 0.0182 0.1737 1.0001 0.5480 0.6396 0.8071 2.5036 V16 e9 0.5752 0.0088 0.0788 1.0001 0.0982 -0.1321 0.2981 0.9102 V17 e10 0.2631 0.0042 0.0384 1.0002 0.2923 0.1449 0.1597 0.4406 V18 e11 0.4220 0.0084 0.0687 1.0001 0.5152 0.1439 0.2062 0.6881 V19 e12 0.6393 0.0073 0.1017 1.0001 0.6223 1.0859 0.3379 1.2667 V20 e13 0.7388 0.0119 0.1003 1.0001 0.6298 0.2308 0.4583 1.2024 V21 e14 0.3557 0.0066 0.0576 1.0000 0.7409 0.6885 0.2051 0.6367 V22 e15 0.2076 0.0040 0.0368 1.0000 0.2911 -0.0362 0.0851 0.3738 V23 e16 0.2942 0.0045 0.0443 1.0001 0.2490 -0.0004 0.1563 0.4693 V24 e17 0.4135 0.0086 0.0658 1.0001 0.4558 -0.4355 0.2367 0.6443 V25 e18 0.4199 0.0067 0.0645 1.0001 0.4478 1.1417 0.2199 0.8667 V26 e19 0.5049 0.0102 0.0817 1.0001 0.7842 0.6279 0.2802 0.8995 V27 e20 1.1727 0.0264 0.1798 1.0002 0.3582 -0.0630 0.6815 1.9091 V28 e21 1.7349 0.0255 0.2547 1.0001 0.6376 0.6624 0.9977 2.8913 V29 e22 0.5715 0.0080 0.0826 1.0001 0.4297 0.2002 0.3350 0.9694 V30 e23 0.3051 0.0055 0.0453 1.0000 0.3253 -0.1949 0.1747 0.4885 V31 e24 0.2575 0.0044 0.0409 1.0001 0.5923 0.2459 0.1445 0.4241 V32 e25 2.0688 0.0533 0.3356 1.0001 0.1040 -0.6533 1.0080 3.2097 V33 e26 1.1646 0.0202 0.1742 1.0001 0.5702 0.4086 0.6677 1.9208 V34 e27 1.5020 0.0216 0.2198 1.0001 0.6592 0.7612 0.8717 2.3580 V35 e28 1.4381 0.0372 0.2432 1.0001 0.6914 0.4049 0.8160 2.4739 V36 e29 1.2233 0.0197 0.1828 1.0001 0.4537 0.1309 0.7365 2.0057 V37 e30 1.0973 0.0246 0.1850 1.0001 0.5729 0.1330 0.5613 1.7225 V38 e31 1.4394 0.0342 0.2352 1.0001 0.6925 0.1708 0.8874 2.3291 V39 e32 1.0378 0.0148 0.1447 1.0001 0.3446 0.0650 0.5803 1.9230 V40 e33 1.1600 0.0425 0.2361 1.0001 0.9469 0.6168 0.6109 1.9091 V41 e34 0.7971 0.0127 0.1276 1.0001 0.3246 0.0377 0.4166 1.2741 V42 e35 1.7268 0.0255 0.2396 1.0001 0.2398 -0.2757 1.0005 2.7836 V43 e36 1.3687 0.0207 0.1919 1.0001 0.4971 0.4515 0.7515 2.1876 V44 e37 0.8888 0.0155 0.1350 1.0001 0.5584 0.3729 0.5281 1.5247 V45 e38 0.8297 0.0164 0.1327 1.0002 0.7803 1.3046 0.4949 1.5140 V46 e39 1.0005 0.0235 0.1811 1.0001 0.8705 1.0706 0.5543 1.9010 V47 e40 0.9926 0.0317 0.2039 1.0001 1.0988 2.1278 0.5230 1.8392 V48 e41 1.5213 0.0296 0.2326 1.0001 0.6619 0.9157 0.8521 2.5776 V49 e42 2.1541 0.0364 0.3026 1.0001 0.3738 0.1434 1.2825 3.4048 V50 e43 1.1520 0.0164 0.1637 1.0001 0.1908 0.1200 0.6554 2.0008 V51 e44 0.8972 0.0109 0.1184 1.0001 0.2291 -0.0356 0.5179 1.4497 V52 e45 0.3434 0.0073 0.0679 1.0001 0.7299 1.4993 0.1246 0.7029 V53 e46 0.4219 0.0085 0.0808 1.0001 0.1160 -0.4487 0.1766 0.7281 V54 e47 0.4469 0.0084 0.0817 1.0001 0.6211 0.9193 0.2386 0.8094 V55 e48 0.4936 0.0095 0.0846 1.0001 0.4144 0.0938 0.2273 0.9173 V56 e49 0.6508 0.0100 0.0986 1.0001 0.7335 1.7347 0.3590 1.2591 V57 e50 1.6466 0.0320 0.2571 1.0001 0.4746 0.1309 0.9370 2.8540 V58 e51 0.7151 0.0107 0.1114 1.0001 0.3793 -0.3323 0.4161 1.1973 V59 e52 0.7550 0.0165 0.1294 1.0002 0.9413 1.0061 0.3989 1.3110 V60 e53 0.4754 0.0047 0.0633 1.0001 0.3212 0.2406 0.2525 0.9025 V61 e54 0.6999 0.0168 0.1115 1.0001 0.5003 -0.2938 0.3863 1.1290 V62 e55 0.6887 0.0110 0.0974 1.0001 0.3295 0.0437 0.3697 1.1765 V63 e56 0.7616 0.0121 0.1187 1.0001 0.7114 0.8767 0.4316 1.3079 V64 e57 0.8750 0.0151 0.1487 1.0001 0.5288 0.8918 0.4518 1.8312 V65 e58 0.6163 0.0211 0.1653 1.0001 0.3725 0.2053 0.1638 1.3994 V66 e59 1.0233 0.0163 0.1581 1.0001 0.3467 0.3781 0.5364 1.7952 V67 e60 1.2586 0.0288 0.2145 1.0001 0.5627 0.2901 0.5789 2.0453 V68 e61 0.7850 0.0131 0.1176 1.0001 0.4655 0.1738 0.4137 1.4019 V69 e62 1.0729 0.0152 0.1480 1.0001 0.4302 0.5384 0.5542 1.8871 V70 e63 0.4885 0.0077 0.0871 1.0001 0.6878 1.1166 0.2247 0.9568 V71 e64 0.4698 0.0082 0.0890 1.0001 0.7577 0.8989 0.1518 0.9410 V72 e65 0.9198 0.0165 0.1460 1.0001 0.5277 0.6039 0.5155 1.5433 V73 e66 0.8184 0.0128 0.1269 1.0001 0.6728 0.8215 0.4175 1.5730 V74 e67 0.8875 0.0280 0.1673 1.0001 0.6417 -0.3004 0.5213 1.3911 V75 e68 1.0273 0.0177 0.1512 1.0001 0.6551 0.5825 0.6068 1.7175 V76 e69 0.5605 0.0133 0.1019 1.0001 0.7265 1.3900 0.2727 1.0620 V77 e70 0.4762 0.0087 0.0898 1.0001 0.3942 0.5036 0.2082 0.9670 V78 e71 0.4750 0.0146 0.1117 1.0002 0.3378 0.5048 0.1484 0.8860 V79 Source: SPSS 20.0 Output

APPENDIX V

Case Studies

Case study one

The case study reveals the bitter experience of a girl named Pushpa. Her husband Dinesh is a sixteen years old coolie, a 8th drop out belonging to sc community. Pushpa confessed her love affair with Dinesh and became pregnant at the age of 15. Further, she told her parents were agri labours. Due to lack of transport facility, Pushpa was not often able to visit hospital and her poor feeding womb had lost nutritious food to help the growth of the child. The inadequacy of transportation led to more infant deaths in the block.

Case study two

Another case study in the village unfolds the story of Amaravathi who conveyed her experience from Devarayipuram village. She conceived at the age of 17 and her baby’s health was good. Her second pregnancy was diagnosed with in three month from the date of the birth the first baby. But the second happened to die within a week from the date of birth and the same happened again for her next child. She informed that her husband was alcoholic that resulted in poor nutrition and her bad health. It was found that she had no time to visit hospital owing to her profession of daily wage worker. There was no preferred interval between two babies. Therefore awareness about government schemes had to be created. Because of anxiety and practical difficulty in their life, they had lost their children. Many psychological problems effected in more infant deaths in the block.

Case study three

%A girl named Bakiyalakshmi told her difficulty that she faced in the village, Devarayipuram. Kathirvel, her husband was a coolie and she was also working on a daily basis earning her wages from rupees 150 to 200 per day. The entire amount earned was used for their day to day activities alone and saved nothing. She further said her first baby had been dead and her second one was also in serious condition. Though she was making use of 108 ambulance services for her emergency purpose it had never reached her destination in time. Due to this lack of transportation infant death rates was higher in the block.

Case study four

Kamatchi from Vellurukampalayam narrated her bitter experience. She said her husband was a coolie and they were getting the meagre wages Rupees 200 to 300. Her husband was an alcoholic had the habit of spending most of his wages in consuming alcohol. The rest of the amount was used for their family maintenance. During the period Dr.Muthulakshmi Reddy Maternity Scheme was not easy to avail. They spend much money and savings in private hospital instead. Money problem was the prime cause the psychological discomfort during the pregnancy period. it had also resulted in weight loss of the baby and sometimes led to the infant death. Case study five

A 17 year old Priya from Vellimalai got married to a tailor. She had a year old baby and was pregnant undergoing treatment at PHC in Pooluvampatty. She informed that she had received good treatment. She also added let her husband had taken good care of her health. In spite of all these comforts they suffered financial crises. She said they were depressed with their debt of their family and the same created more psychological problems during her pregnancy time. Hence she had last her first child