analysis of socio-economic, demographic and...

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Chapter 6:

ANALYSIS OF SOCIO-ECONOMIC, DEMOGRAPHIC AND GEOGRAPHIC FACTORS

DETERMINING FERTILITY BY RELIGION

CONTENTS

6.1 Introduction

6.2 Determinants of Religious Fertility Differentials

6.3 Factors Influencing Fertility

6.3.1 Age at First Marriage

6.3.2 Education

6.3.3 Standard of Living

6.3.4 Rural-Urban Residence

6.3.5 Women Work Participation

6.3.6 Contraceptive Use

6.3.7 Spatial Dimensions on Fertility

6.4 Regression Analysis of Socio-economic Factors Affecting Fertility

6.5 Place of Residence and Fertility

6.6 Analysis of Interaction Effects

6.6.1 Religion X Standard of Living Interaction

6.6.2 Religion X Education Interaction

6.6.3 Religion X Region Interaction

6.7 Conclusion

References

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CHAPTER VI

ANALYSIS OF SOCIO-ECONOMIC, DEMOGRAPHIC AND GEOGRAPHIC FACTORS DETERMINING FERTILITY BY

RELIGION 6.1 Introduction

Fertility differentials among the religious groups, especially

between Hindus and Muslims in India, are well recognized in the different

demographic studies, (for details see chapter III). This is normally

explained in terms of both differentials by religion and differentials in

spatial settings of the religious groups. In Kerala, where there has been

substantial population of three concerned religions, namely, Hindu,

Muslim and Christian, the estimates of religious fertility differentials

indicated that Muslim fertility was always been higher than Hindu and

Christian fertility. SRS and NFHS data also showed that Muslim fertility

was substantially higher than Hindu fertility in Kerala. The all India picture

of fertility showed that Christian fertility is much lower than Hindu

fertility. But in Kerala, the Hindu-Christian fertility difference is small.

It has been noted in the previous chapter that, there exist a few

regional fertility differentials in Kerala. Northern districts that are

characterised by higher percentage of Muslim population and low female

literacy rate show higher fertility. On the other hand, Southern districts,

where women are more educated and better employed, show a fertility

reduction.

In the present chapter, an analysis is made in order to find out the

answers to the three following questions.

1. Does religion as a variable have any definitive role in the

determination of the number of children ever born?

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2. What is the relative significance of the socio-economic factors in

fertility decision among the religious groups?

3. Do the regional variations or the spatial settings affect the religious

fertility differentials in Kerala?

For the purpose of the analysis NFHS-II household data are used. In

the initial part of the analysis a brief explanation of the socio-economic

differentials by religion are given. Then a Regression Analysis has been

carried out taking total number of children ever born as the dependent

variable. The independent variables used in the analysis are current age of

the respondent, age at marriage, place of residence (two categories: urban

and rural), religion (three categories: Hindu, Muslim and Christian),

ethnicity (four categories: Scheduled Caste, Scheduled Tribe, Other

Backward Communities and others), level of women’s education (four

categories: illiterate, below middle school, middle school complete, and

high school complete and above), standard of living ( three categories: low,

medium and high), occupation (two categories: working and non working),

use of contraceptives use (two categories: using and not using), and region

(four categories region A, B, C and D)1. In order to understand and assess

the interaction effects, the explanatory variables have been reformulated.

New variables representing different combinations of religion and other

variables have been introduced. The effect of the new variables on the total

number of children ever born has been examined through Regression

Analysis.

6.2 Determinants of Religious Fertility Differentials

As a variable, which lies at the core of human development, fertility

may be affected by non-economic factors such as those related to culture 1 Region A: Kasaragod, Kannur, Wayanad, Kozhikode; Region B: Malappuram, Palakkad

Thrissur; Region C: Ernakulam, Kottayam, Idukki; and Region D: Alappuzha, Pthanamthitta, Kollam, Thiruvananthapuram.

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and religion. The central point in the study is religion as a core element in

the human decision on fertility. A careful examination of the available data

on socio-economic characteristics of the major religious groups in Kerala is

essential to understand the extent to which religion itself has contributed to

the emerging fertility differentials among these groups.

It is important to examine the hypotheses regarding religion and

reproduction. Religion has two main components that may influence

fertility. First it articulates a set of normative values of a community, which

is called the “pure religion effect”; and second, it is the “characteristics

effect” which is associated with other socio-economic traits that affect

reproductive behaviour. Chamie (1977) stated that there were three

hypotheses which explained why one might observe fertility differentials

by religion. The first one is ‘particularized theology hypothesis’, that

postulates that the intellectual content of the religion influences fertility

irrespective of the socio-economic and demographic contexts; the second

one is ‘characteristics hypothesis’ that postulates that fertility differentials

reflects socio-economic differences between the members of the religious

groups; and the third one is the ‘minority group status hypothesis’ that

postulates that the political and social insecurity of the minority religious

groups tend to increase their fertility compared to majority group.

6.3 Factors Influencing Fertility

The factors influencing fertility can be classified into proximate

determinants and non-proximate determinants (for details see chapter II,

2.4). The proximate determinants of fertility are those immediate variables

through which changes in fertility are effected. Non-proximate

determinants affect fertility through their impact on proximate variables.

The important proximate and non-proximate determinants of fertility are of

special importance for explaining the differentials in fertility among the

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religious groups. The variables used in the present study are: current age of

ever-married women, age at first marriage, place of residence, religion,

ethnicity, education, standard of living, contraceptive preference,

occupation and region.

6.3.1 Age at First Marriage

The proportion of married females is one of the proximate

determinants of fertility. As fertility outside marriage has been strongly

disapproved socially and is negligible in India, NFHS like the other

population surveys in India asks the questions regarding fertility within the

marriage. Since reproduction is primarily confined to married women, age

at marriage is an important determinant of duration of time spent in the

marital union and hence of fertility.

Table 6.1 Median Age at First Marriage by Religion in Kerala, NFHS II

Religion Current

Age Hindu Muslim Christian All Religion

25-29 22.2 18.2 23.3 20.9

30-34 21.4 17.6 22.6 20.4

35-39 20.8 17.5 22.5 19.8

40-44 20.4 17.4 22.3 19.9

25-49 21.2 17.7 22.6 20.3

Source: PRC, Thiruvananthapuram and IIPS, Mumbai, 1999. Note: Total medians include women belonging to other religions and scheduled-tribe women, median for whom are not shown separately.

NFHS-II measured age at first cohabitation as a proxy for age at

consummation of marriage. Although in some States in India formal

marriage was not always immediately followed by cohabitation, in Kerala

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there was only negligible difference in the age at first marriage and age at

first cohabitation with husband for all age groups. Thus, ages at marriage,

cohabitation, and consummation of marriage almost coincide for the vast

majority of women in Kerala. Table 6.1 shows the religious wise median

age at first cohabitation with husband. The median age at first

marriage/cohabitation for a group of women was defined in the table as the

age by which half of the entire group began to cohabit, rather than the age

by which half of all the ever-cohabiting women in the group began to

cohabit2.

It is well known that, the age of marriage was relatively high in

Kerala. However, variations in the median age of marriage were found in

Kerala. Marriages took place at higher age among Christians, compared to

Hindus and Muslims. Median age at marriage for women of ages 25-49 at

survey was 22.6 years among Christians, 21.2 for Hindus and 17.7 for

Muslims. According to NFHS-I, these were 21.8, 20.4 and 16.6 for

Christian, Hindu and Muslim respectively. It is clear that the Christian-

Hindu difference was small but the median age at marriage among

Muslims was significantly low. The median age of the first marriage in

Kerala for women age 25-49 was 20 years and was two years higher in

urban areas (22 years) than in rural areas (20 years).

6.3.2 Education

The level of education attained by each of the three religious groups

has been presented in Table 6.2. The table reveals that, Muslims had lower

literacy than the other two groups. The level of literacy was higher for 2 The median age at first marriage/cohabitation with husband for a cohort of women is the age

by which 50 percent of the cohort marries/cohabits. The median age at first marriage in Kerala for women age 25-49 is 20 years and is two years higher in urban areas (22 years) than in rural areas (20 years). (The median age at first marriage could not be calculated for women age 15-19 and 20-24 because more than half of women in these age groups were not married at the time of the survey). The median age at first marriage in Kerala was constant at about 20 years till recently, rising to 21 years only for women age 25-29, (NFHS-II).

285

Christians than for Hindus. All religious groups at the educational level of

middle school complete followed almost the same pattern. For Christians

and Hindus who had the educational level of high school complete, the

difference of median age of marriage was minimal, however, at the

educational level of higher secondary and above the difference becomes

greater, especially between Muslims and other religious groups. NFHS

data showed that the level of illiteracy among ever-married women in

Kerala was relatively low (13 percent). The level of illiteracy was the

highest among Muslim women (17 percent) compared to Hindu women (12

percent), and it was the lowest among Christian women (5 percent).

Table 6.2 Educational level of Women Age 15-49 by Religion in Kerala, NFHS II

Religion

Educational Attainment Hindu Muslim Christian All Religion

Illiterate 11.5 17.3 4.5 11.1

Literate< Primary 7.3 14.5 4.3 8.7

Primary Complete 17.9 27.2 15.9 20.3

Middle Complete 16.4 18.0 18.5 17.6

High School Complete 28.7 16.3 28.6 24.5

Higher Secondary and Above 18.2 6.7 28.2 17.8

At least Literate 88.5 82.7 95.5 88.9

Source: Computed from NFHS-II, Household data files

6.3.3 Standard of Living

NFHS-II (1998-99) has arrived at an index for calculating a standard

of living index on the basis of the household assets and housing conditions.

The survey did not collect information on household income or

expenditure. NFHS computed standard of living by assigning weights to

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various items such as: type of house, separate rooms for cooking, source of

lighting, fuel for cooking, source of drinking water, toilet facility,

ownership of consumer goods, etc. The index so computed was categorised

into low, medium and high3.

Table 6.3 Standard of Living Index of Women Age 15-49 by Religion in Kerala,

NFHS II

Religion Standard of Living Hindu Muslim Christian All Religion

Low 16.2 19.3 15.9 17.1

Medium 53.8 52.4 50.3 52.2

High 27.4 26.5 33.3 29.0


Percentage distribution of standard of living showed that in the high

living standard category Christians had a higher proportion compared to

Hindus and Muslims, Table 6.3. Muslims had higher proportion in the low

standard of living category. However, the differences were not significant

between the religious groups.

3 In NFHS-II, standard of living index is calculated by adding the following sources: house

type: 0 for kachha, 2 for semi pucca and 4 for pucca; toilet facility: 0 for no facility 1for shared public pit toilet, 2 for public or shared flesh toilet or own pit toilet 4 for own flesh toilet; source of lighting: 2 for electricity, 1 for kerosene, gas or oil, 0 for other source of lighting; main fuel for cooking: 2 for electricity, liquefied natural gas or biogas, 1 for coal or kerosene, 0 for other fuel; source of drinking water: 2 for pipe, hand pump or well in residence/yard/plot 1 for public tap, hand pump or well, 0 for other water source; separate room for cooking: 1 for yes 0 for no; ownership of house: 2 for yes 0 for no; ownership of agricultural land: 4 for 5 acres or more,3 for 2.0-4.9 acres,2 for less than 2 acres or acreage not known 0 for no agricultural land; ownership of irrigated land: 2 if household owns at least some irrigated land 0 for no irrigated land; ownership of live stock: 2 if own livestock 0 if do not own livestock; ownership of durable goods: 4 for a car or tractor, 3 each for moped/ motor cycle/ telephone/ refrigerator/ or color television, 2 each for bicycle/ fan/ radio/ sewing machine/black and white television/ water pump/ bullock cart or thresher, 1 each for mattress, pressure cooker, chair, cot/ bed, table, or clock/watch. Index scores range from 0-14 for low standard of living index, 15-24 for medium standard of living index and 25- 657 for high standard of living index.

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6.3.4 Rural-Urban Residence

A notable difference between the religious groups in Kerala is in

their place of residence. The degree of urbanization namely the percentage

of ever married women age 15-49 residing in urban areas showed that the

percentage of urban women was higher for Hindus (34.8) than Christians

(31.8) and Muslims (19.4), Table 6.4. But at the national level, Muslims

had a higher percentage of their population in urban areas than the Hindus.

As mentioned in the previous chapter a notable feature of Kerala’s fertility

transition is the absence of significant rural-urban gap.

Table 6.4 Percentage of Urban Population and Work Participation of Women

Age 15-49 by Religion in Kerala, NFHS II

Religion Place of Residence -

Urban Work Participation

Rate-Working

Hindu 34.6 30.8

Muslim 19.4 9.0

Christian 31.8 25.8

Total 28.6 21.8


6.3.5 Women Work Participation

Women’s employment is much lower in Kerala (22 percent) than

the all India average (39 percent). It is also lower than that of the other

southern States like Andhra Pradesh, Tamil Nadu, and Karnataka (52-59

percent). Current employment of women at 22 percent, according to NFHS

II, is marginally lower than current employment at the time of NFHS-I, at

26 percent. Level of work participation is lower among Muslims as

compared to Hindus and Christians in Kerala. The Hindu Muslim

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difference in work participation is found to be 21.8 percentage points,

while the difference is only 5 percentage point between Hindus and

Christians.

6.3.6 Contraceptive Use

Contraceptive prevalence is higher among Hindus (71.6 percent)

and Christians (71.5 percent) than among Muslims (47.2 percent) in

Kerala. Although the use of most of the methods is lower among Muslims

than among women of other religions, Muslims are particularly less likely

than Hindu or Christian women to use sterilization. Among the Hindus and

Christians half of the women are sterisiled whereas among Muslims only

33 percent are sterilized. The percentage of Christians who use the

traditional method of contraception (12 percent) is double that of the

Hindus or Muslims (6.6 percent), Table 6.5. Among the Muslims 5.5

percent are not using any method of contraception because of “religious

prohibit”, whereas only 0.6 percent among Christians do not use

contraceptives because of religious prohibit and the value is negligible in

the case of the Hindus.

Table 6.5 Percent of Women Using Contraception by Religion in Kerala, NFHS-II

Religion Any Method

Any Modern Method

Traditional Method

Female Sterilization

Not Using Any Method

Hindu 71.6 64.5 7.1 55.3 28.4

Muslim 47.2 41.1 6.1 36.2 52.8

Christian 71.5 59.2 12.3 51.6 28.5


Though the use of contraception is prevalent in all the three

concerned religions of our study, the proportion of Muslim couples using

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any means of contraception is not as large as that of the Hindu and the

Christian couples. The contraceptive prevalence has varied with the

number of living children. As the number of children increases,

contraceptive prevalence increases, but it declines marginally after the

second child among Hindus and Christians but among Muslims the decline

starts after three children, Table 6.6.

Table 6.6

Percentage Distribution of Currently Married Women Using Contraception by Religion and Number of Living Children in Kerala, NFHS-II

Religion No. of Living Children

Method Used Hindu Muslim Christian

0

No Method

Traditional

Modern

29.1

7.1

0.3

20.5

5.9

0.3

23.1

-

0.4

1

No Method

Traditional

Modern

39.3

47.5

6.4

25.5

21.6

5.2

34.0

43.6

5.3

2

No Method

Traditional

Modern

19.8

38.4

58.0

23.8

29.4

23.3

25.9

14.8

54.8

3

No Method

Traditional

Modern

8.3

2.0

27.1

14.5

19.6

34.8

13.6

12.7

32.3

4

No Method

Traditional

Modern

1.8

4.0

6.0

6.4

15.7

20.1

2.7

1.8

6.5

5+

No Method

Traditional

Modern

1.8

1.0

2.1

9.3

7.8

16.4

0.7

-

0.8


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6.3.7 Spatial Dimensions on Fertility

The conventional approach in the studies on fertility decline stressed

the importance of individual or household level variables like mother’s

education, standard of living, religion or caste affiliation and so on in

influencing fertility decision. However, the community impact of

individual decisions on the number of children seldom received any serious

attention in demographic studies (Dev et al 2002, Dharmalingam and

Morgan 2004, Montgomery and Casterline 1998, Munshi and Myaux,

2000). The spatial effect of fertility transition was also clear from many

studies, (Dev et al 2002, Gulimoto and Rajan 2001). Thus, in addition to

the characteristics like education, standard of living etc., the place in which

a woman lives also influences the decision on the number of children. The

place here stands as synonymous with the socio-cultural setting of that

particular geographic region. The socio-cultural setting of a particular

geographical area exerts a definitive influence on the couple’s decision of

the number of children in spite of the other parameters and differentials.

Researchers have shown that the progression of birth control

measures in India followed a peculiar geographical pattern starting from

coastal areas and moving towards the interland irrespective of socio-

economic differentials and religious affiliation, (Guilmito and Rajan,

2001). In another study Morgan et al (2002) found that religious fertility

differentials arose from localized conditions and therefore, varied widely

from one area to the other. Even within a State fertility rate among the

religious groups varied widely across districts due to spatial differences,

(Zachariah et al 1994, Dev et al 2002, James 1999).

In order to understand the spatial effect on fertility decision, 14

districts of the State are classified into four geographical regions The

district composition of the four geographic regions is as follows: Region A:

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Kasaragod, Kannur, Wayanad, Kozhikode; Region B: Malappuram,

Palakkad, Thrissur; Region C: Ernakulam, Kottayam, Idukki; Region D:

Alappuzha, Pathanamthitta, Kollam, Thiruvananthapuram.

6.4 Regression Analysis of Socio-economic Factors Affecting Fertility

Fertility differentials and socio-economic differentials among the

religious groups in Kerala are examined in the previous chapter (see

chapter V). It has revealed that there have been notable differences in the

socio-economic characteristics of women belonging to the three religious

groups in Kerala. Among the socio-economic factors, female education is

considered to be one of the most important factors determining fertility,

(Zachariah, 1984; Cochrane 1988; Unisa and Bhagat 2000; Dreze and

Murthi 2001). Thus, it is essential to control for the socio-economic

variables to understand whether the differentials in fertility are attributable

to socio-economic characteristics or to religion per se. For this purpose a

multivariate regression analysis has been carried out to show the influence

of socio-economic and demographic variables on fertility, Table 6.7. In the

present analysis, total number of children ever born has been taken as the

dependent variable. The independent variables included are: age of the

respondent, age at first marriage, place of residence (urban and rural),

religion (Hindu, Muslim or Christian), ethnicity (scheduled caste,

scheduled tribe, other backward communities or others), level of women’s

education (Illiterate, below middle, middle complete and high school and

above), standard of living (low, medium and high), contraceptive use

(using and not using), occupation (working, not working) and regions

(Region A: Kasaragod, Kannur, Wayanad, Kozhikode; Region B:

Malappuram, Palakkad Thrissur; Region C: Ernakulam, Kottayam, Idukki;

and Region D: Alappuzha, Pthanamthitta, Kollam, Thiruvananthapuram.)

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Table 6.7 Regression Analysis of Factors Affecting Children Ever Born in Kerala, NFHS-II

Un standardized Coefficients

Standardized Coefficient Explanatory Variables

B Std. Error Beta t-value Significance

Level

Constant .899 .178 5.056 *** .000 Current age of respondent .085 .003 .485 31.565 *** .000 Age at Marriage -.109 .007 -.267 -16.321 *** .000 Place of Residence Urban -.125 .046 -.038 -2.690 * .007 Rural ® - - - - - Religion Hindu ® - - - - - Muslim .594 .056 .186 10.643 *** .000 Christian .208 .061 .052 3.381 ** .001 Ethnicity SC .121 .081 .023 1.499 .134 ST .229 .198 .016 1.159 .247 OBC .072 .045 .024 1.609 .108 Others ® - - - - - Level of Women’s Education Illiterate® - - - - - Below Middle -.332 .069 -.102 -4.796 *** .000 Middle Complete -.202 .060 -.052 -3.389 ** .001 H S Complete and Above -.236 .053 -.078 -4.437 *** .000 Standard of Living Low ® - - - - - Medium -.056 .055 -.019 -1.001 .317 High -.028 .061 -.009 -.463 .643 Occupation Working -.175 .050 -.050 -3.487 *** .000 Not Working ® - - - - - Contraceptive Use Using .768 .043 .255 17.906 *** .000 Not Using ® - - - - - Region Region - A .182 .058 .052 3.145 ** .002 Region - B .264 .058 .078 4.571 *** .000 Region - C .088 .058 .024 1.528 .127 Region – D ® - - - - - Adjusted R²= .485

Dependent variable: Number of children ever born. Note: *** 99 percent significant, ** 95 percent significant, * 90 percent significant; ® Reference category, Region A: Kasaragod, Kannur, Wayanad, Kozhikode; Region B: Malappuram, Palakkad Thrissur; Region C: Ernakulam, Kottayam, Idukki; Region D: Alappuzha, Pthanamthitta, Kollam, Thiruvananthapuram.

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As mentioned at the beginning of this chapter, the first part of the

analysis is aimed at understanding the role of religion in determining

fertility. From the analysis it can be seen that the selected variables

explained 48.5 percent variability (R²=.485) in the total number of children

ever born. Regression analysis using total number of children ever born as

the dependent variable indicated that the influence of religion remains

significant after controlling for the socio-economic variables. This does not

nullify the independent effect of other variables. That other variables like

age of the respondent, age at marriage, place of residence, education,

occupation (whether the respondent is working or not), contraceptive

practice, and spatial settings are also statistically significant. Effect of

education, at all levels, is significant in determining the number of children

ever born, whereas the influence of standard of living is insignificant.

The result of the analysis shows that the number of children born

has a negative relationship to age of marriage, particularly of urban

population, education (at all levels), women work participation (working)

and standard of living. It may be further observed from the analysis that,

scheduled castes, (SC) scheduled tribes (ST) and other backward

community (OBC), the socio-economically disadvantaged groups, show

significantly lower fertility, when we control for the socio-economic

variables in the regression model. But the all India picture in this regard is

quite opposite, (Bhagat, Praharaj, 2005).

Spatial impact on fertility is also clear from the analysis. Region B,

which consists of Malappuram, Palakkad and Trissur districts, has

significant influence on fertility. The reason for this may be the peculiar

socio economic and demographic characteristics of these districts, which are

favorable for increasing the number of children ever born, (See Chapter V).

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6.5 Place of Residence and Fertility In order to understand the relation between socio-economic

characteristics and fertility between rural and urban areas, a separate

analysis has been carried out, Table 6.8.

Table 6.8 Regression Analysis of Factors Affecting Children Ever Born by Place

of Residence in Kerala, NFHS-II ß Value Explanatory Variables

Urban Sig. Level Rural Sig. Level Current age of respondent .489 *** .003 *** Age at Marriage -.272 *** .009 *** Religion Hindu ® - - - - Muslim .189 *** .189 *** Christian .040 ** .040 ** Ethnicity SC .017 .017 ST .018 .018 OBC .010 * .010 Others ® - - - - Level of Women’s Education Illiterate® - - - - Below Middle -.035 * -.036 ** Middle Complete -.051 * -.051 ** H S Complete and Above -.063 ** -.063 ** Standard of Living Low ® - - - - Medium -.006 -.006 High -.009 -.009 Occupation Working -.047 ** -.047 * Not Working ® - - - - Contraceptive Use Using .255 *** .255 *** Not Using ® - - - - Region Region - A .038 * .038 * Region - B .089 .089 *** Region - C .037 .037 Region – D ® - - - - Adjusted R² .492 .474 Dependent variable: Number of children ever born Note: *** 99 percent significant, ** 95 percent significant, * 90 percent significant; ® Reference category, Region A: Kasaragod, Kannur, Wayanad, Kozhikode; Region B: Malappuram, Palakkad Thrissur; Region C: Ernakulam, Kottayam, Idukki; Region D: Alappuzha, Pthanamthitta, Kollam, Thiruvananthapuram.

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Regression analysis of the factors affecting children ever born by place

of residence shows that, effect of explanatory variables on children ever born

is almost the same both in rural and urban areas. The analysis further shows

that the influence of religion remains significant, after controlling for the

socio-economic variables, irrespective of the place of residence. Variables like

age of the respondents, age at marriage, education, contraceptive use and

religion have the same level of significance in both rural and urban areas.

Though there is absence of significant rural-urban gap in Kerala, there is a

regional effect on fertility across urban and rural areas. The significance level

is the same for all regions except that of Region B, where there is a rural urban

gap in this regard. On the other hand, ethnicity is not significant in rural areas

whereas standard of living does not affect the number of children born of rural

and urban women.

The results of the regression analysis clearly show that fertility

differentials persist even after controlling for socio-economic and

demographic variables. At the same time it should be noted that it is not

possible to neglect the role played by other independent variables. So both

characteristic hypothesis and particularized theology hypothesis are applicable

while explaining religious fertility differentials in Kerala. Thus, in order to get

a clear picture of religious fertility differentials, it is essential to examine the

effect of the interaction between religion and selected socio-economic

variables on fertility. This issue has been addressed in the subsequent part of

the analysis.

6.6 Analysis of Interaction Effects Demographic studies have suggested that, there is an interaction effect

between religion, other socio-economic variables and fertility. The interaction

hypothesis postulates that fertility differentials depend on the interaction

between socio-economic levels of the religious groups and the local

orientation of these groups toward procreation and fertility control (Chamie

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1981). The relationship between religion and fertility may not be the same

with peole at different socio-economic status. Analysis of the data from

Bangladesh Fertility Survey of 1975 by Chaudhury (1984) found Muslim

fertility to be slightly lower than Hindu fertility. But controlled for age of

marriage, Muslim fertility was higher at low ages at marriage. Contraceptive

use among Hindus was higher than among Muslims at low levels of education

but no significant difference was found at higher levels.

For the purpose of assessing interaction effects, the explanatory

variables have been reformulated. New variables representing different

combinations of religion and other variables have been introduced. The effect

of the new variables on the total number of children ever born is analysed

through regression analysis. Three Religious groups, Hindu, Muslim and

Christian and other socio-economic variables such as standard of living,

education, region, place of residence, women work participation,

contraceptive prevalence, and age at marriage are combined. For example,

the three religious groups and the three categories of standard of living yield

nine categories of the variable Religion X Standard of Living Interaction. In

the analysis of the total number of children ever born this new variable is used

along with other variables. The significance level can be compared at different

levels of the standard of living. Similar analysis has been made for the other

independent variables also, Table 6.9.

It is found that the mean number of children born has varied

substantially across religion. The mean number of children ever born is higher

for Muslims (4.26) compared to Hindus (2.78) and Christians (2. 64).

Regression analysis has been carried out to examine the nature of interaction

between religion and socio-economic variables. Based on religion and socio-

economic variables seven sets of analysis are performed. Since inclusion of two

interaction variables in a single analysis would bring in multicollinearity, only

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one interaction is carried out at a time examining the interaction effect between

religion and socio-economic variables on total number of children ever born.

Table 6.9 Variables Used to Assess the Interaction Effect

Interaction Variable Description of Reformulated Variables

Religion X Standard of Living Hindu X Standard of Living ®

Muslim X Low Standard of Living Muslim X Medium Standard of Living Muslim X High Standard of Living Christian X Low Standard of Living Christian X Medium Standard of Living Christian X High Standard of Living

Religion X Education Hindu X Education ®

Muslim X Below Middle School Muslim X Middle School Complete Muslim X H.S Complete and above Christian X Below Middle School Christian X Middle School Complete Christian X H.S Complete and above

Religion X Region Hindu X Region ®

Muslim X Region A Muslim X Region B Muslim X Region C Muslim X Region D Christian X Region A Christian X Region B Christian X Region C Christian X Region D

Religion X Place of Residence Hindu X Place of Residence ®

Muslim X Urban Muslim X Rural Christian X Urban Christian X Rural

Religion X Women Work Participation Hindu X Women Work Participation®

Muslim X Working Muslim X Not Working Christian X Working Christian X Not Working

Religion X Contraceptive Prevalence Hindu X Contraceptive Prevalence®

Muslim X Using Muslim X Not Using Christian X Using Christian X Not Using

Religion X Age at Marriage Hindu X Age at Marriage ®

Muslim X Age at Marriage Christian X Age at Marriage

® Reference category

298

6.6.1 Religion X Standard of Living Interaction The result of regression analysis showed that the interaction effect

of religion and standard of living on the total number of children ever

born was insignificant. This means that the interaction between religion

and standard of living is not a crucial factor influencing fertility decisions

among the religious groups. Though the religion X standard of living

interaction is moderate by religion, the correlation is different. The

relation is negative between different levels of standard of living and

fertility among Christian, it is positive among Muslims at higher standard

of living and negative at medium standard of living. Other variables such

as age at marriage, contraceptive prevalence, education, Muslim religion

and region have significant influence on fertility decision making. 20.2

percent of variation in fertility can be explained by Muslim religion.

Region B, which consists of Malappuram, Palakkad and Trissur districts

and with substantial Muslim Population, has significant positive

correlation with children ever born. While age at marriage and higher

level of education show strong negative correlation with children ever

born, Muslim population and use of contraceptive measures show positive

correlation with children ever born, Table 6.10.

299

Table 6.10 Religion X Standard of Living Interaction




Level

Constant .875 .182 4.809 *** .000 Current age of respondent .085 .003 .484 31.446 *** .000 Age at Marriage -.109 .007 -.268 -16.336 *** .000 Place of Residence Urban -.121 .046 -.037 -2.608 * .009 Rural ® - - - - - Religion Hindu ® - - - - - Muslim .644 .110 .202 5.876 *** .000 Christian .305 .144 .076 2.122 .034 Ethnicity SC .122 .081 .023 1.511 .131 ST .222 .198 .016 1.123 .261 OBC .073 .045 .024 1.631 .103 Others ® - - - - - Level of Women’s Education Illiterate® - - - - - Below Middle - - - - - Middle Complete -.204 .060 -.052 -3.414 ** .001 H S Complete and Above -.235 .053 -.078 -4.421 *** .000 Standard of Living Low ® - - - - - Medium .002 .078 .001 .031 .975 High -.029 .086 -.009 -.341 .733 Occupation Working -.173 .050 -.049 -3.440 ** .001 Not Working ® - - - - - Contraceptive Use Using .767 .043 .254 17.896 *** .000 Not Using ® - - - - - Region Region - A .181 .058 .052 3.124 ** .002 Region - B .263 .058 .078 4.552 *** .000 Region - C .090 .058 .025 1.552 .121 Region – D ® - - - - - Religion X Standard of Living Interaction Muslim X Low Std. of living ® - - - - - Muslim X Medium Std. of living -.115 .122 -.029 -.940 .347 Muslim X High Std. of living .047 .136 .009 .343 .731 Christian X Low Std. of living ® - - - - - Christian X Medium Std. of living -.137 .162 -.025 -.844 .399 Christian X High Std. of living -.077 .173 -.012 -.442 .658 Adjusted R² = .481

Dependent variable: Total Number of Children Ever Born. The variable Education below middle is constant or having missing correlation. Note: *** 99 percent significant, ** 95 percent significant, * 90 percent significant; ® Reference Variable.

300

Table 6.11 Religion X Education Interaction




Level

Constant .887 .178 4.992 *** .000 Current age of respondent .084 .003 .478 31.146 *** .000 Age at Marriage -.111 .007 -.272 -16.723 *** .000 Place of Residence Urban -.119 .046 -.036 -2.586 .010 Rural ® - - - - - Religion Hindu ® - - - - - Muslim .845 .072 .265 11.730 *** .000 Christian .123 .111 .031 1.102 .271 Ethnicity SC .151 .080 .029 1.887 .059 ST .276 .197 .019 1.403 .161 OBC .066 .044 .022 1.491 .136 Others ® - - - - - Level of Women’s Education Illiterate® - - - - - Below Middle - - - - - Middle Complete -.126 .083 -.032 -1.517 .129 H S Complete and Above -.046 .067 -.015 -.693 .489 Standard of Living Low ® - - - - - Medium -.051 .055 -.017 -.921 .357 High -.031 .061 -.010 -.515 .607 Occupation Working -.147 .050 -.042 -2.924 ** .003 Not Working ® - - - - - Contraceptive Use Using .759 .043 .252 17.808 *** .000 Not Using ® - - - - - Region Region - A .154 .058 .044 2.670 * .008 Region - B .248 .057 .074 4.326 *** .000 Region - C .072 .058 .020 1.252 .211 Region – D ® - - - - - Religion X Education Interaction Muslim X Illiterate ® - - - - - Muslim X Below Middle School - - - - - Muslim X Middle School Complete -.251 .126 -.039 -1.990 * .009 Muslim X H.S Complete and above -.691 .107 -.121 -6.447 * .007 Christian X Illiterate ® - - - - - Christian X Below Middle School - - - - - Christian X Middle School Complete .221 .172 .025 1.284 .199 Christian X H.S Complete and above .047 .134 .009 .350 .726 Adjusted R² = .489

Dependent variable: Total Number of Children Ever Born. The variables Education below middle, Muslim X Below Middle Education and Christian X Below Middle Education are constant or having missing correlation. Note: ® Reference Variable; *** 99 percent significant, ** 95 percent significant, * 90 percent significant.

301

Table 6.12 Religion X Region Interaction




Level

Constant .914 .179 5.095 *** .000 Current age of respondent .086 .003 .486 31.632 *** .000 Age at Marriage -.108 .007 -.265 -16.187 *** .000 Place of Residence Urban -.131 .046 -.040 -2.811 * .005 Rural ® - - - - - Religion Hindu ® - - - - - Muslim .335 .108 .105 3.092 ** .002 Christian .211 .088 .052 2.405 .016 Ethnicity SC .122 .081 .023 1.505 .133 ST .241 .198 .017 1.218 .224 OBC .044 .046 .015 .962 .336 Others ® - - - - - Level of Women’s Education Illiterate® - - - - - Below Middle - - - - - Middle Complete -.200 .060 -.051 -3.346 ** .001 H S Complete and Above -.227 .053 -.075 -4.259 *** .000 Standard of Living Low ® Medium -.058 .055 -.019 -1.038 .299 High -.030 .062 -.009 -.493 .622 Occupation Working -.164 .050 -.047 -3.263 ** .001 Not Working ® - - - - - Contraceptive Use Using .779 .043 .258 18.131 *** .000 Not Using ® - - - - - Region Region - A .166 .073 .048 2.258 .012 Region - B .171 .078 .051 2.202 * .008 Region - C .034 .079 .009 .436 .663 Region – D ® - - - - - Religion X Region Interaction Muslim X Region A .234 .135 .046 1.727 ** .004 Muslim X Region B .419 .135 .092 3.093 ** .001 Muslim X Region C .295 .151 .044 1.954 .051 Muslim X Region D ® - - - - - Christian X Region A -.184 .241 -.011 -.764 .445 Christian X Region B -.137 .168 -.014 -.816 .414 Christian X Region C .033 .138 .005 .238 .812 Christian X Region D ® - - - - - Adjusted R² = .483

Dependent variable: Total Number of Children Ever Born. The variable Education below middle is constant or has missing correlation. Note: е: Excluded Variable; ® Reference Variable; *** 99 percent significant, ** 95 percent significant, * 90 percent significant.

302

Table 6.13 Religion X Residence Interaction




Level

Constant .886 .178 4.979 *** .000 Current age of respondent .085 .003 .486 31.563 *** .000 Age at Marriage -.109 .007 -.267 -16.269 *** .000 Place of Residence Urban -.108 .060 -.033 -1.813 .070 Rural ® - - - - - Religion Hindu ® - - - - - Muslim .622 .061 .195 10.161 *** .000 Christian .182 .073 .045 2.499 .013 Ethnicity SC .125 .081 .024 1.551 .121 ST .230 .198 .016 1.162 .245 OBC .069 .045 .023 1.544 .123 Others ® - - - - - Level of Women’s Education Illiterate® - - - - - Below Middle - - - - - Middle Complete -.199 .060 -.051 -3.336 ** .001 H S Complete and Above -.233 .053 -.077 -4.382 *** .000 Standard of Living Low ® - - - - - Medium -.056 .055 -.019 -1.010 .313 High -.031 .062 -.009 -.501 .617 Occupation Working -.174 .050 -.050 -3.465 ** .001 Not Working ® - - - - - Contraceptive Use Using .769 .043 .255 17.933 *** .000 Not Using ® - - - - - Region Region - A .184 .058 .053 3.184 ** .001 Region - B .266 .058 .079 4.602 *** .000 Region - C .084 .058 .023 1.449 .148 Region – D ® - - - - - Religion X Residence Interaction Muslim X Urban -.129 .110 -.020 -1.181 .238 Muslim X Rural ® - - - - - Christian X Urban .084 .122 .012 .685 .494 Christian X Rural ® - - - - - Adjusted R² = .482

Dependent variable: Total Number of Children Ever Born. The variable Education below middle is constant or has missing correlation. Note: ® Reference Variable; *** 99 percent significant, ** 95 percent significant, * 90 percent significant.

303

Table 6.14

Religion X Work Participation Interaction

Un standardized

Coefficients

Standardized

Coefficient

Explanatory Variables B Std. Error Beta

t-value

Significance Level

Constant .883 .178 4.951 *** .000 Current age of respondent .085 .003 .486 31.587 *** .000 Age at Marriage -.109 .007 -.267 -16.280 *** .000 Place of Residence Urban -.124 .046 -.038 -2.679 * .007 Rural ® - - - - - Religion Hindu ® - - - - - Muslim .621 .059 .194 10.516 *** .000 Christian .215 .071 .053 3.050 ** .002 Ethnicity SC .117 .081 .022 1.451 .147 ST .224 .198 .016 1.133 .257 OBC .072 .045 .024 1.601 .110 Others ® - - - - - Level of Women’s Education Illiterate® - - - - - Below Middle - - - - - Middle Complete -.203 .060 -.052 -3.397 ** .001 H S Complete and Above -.233 .053 -.077 -4.393 *** .000 Standard of Living Low ® - - - - - Medium -.057 .056 -.019 -1.025 .305 High -.031 .062 -.009 -.503 .615 Occupation Working -.139 .061 -.040 -2.271 .023 Not Working ® - - - - - Contraceptive Use Using .766 .043 .254 17.871 *** .000 Not Using ® - - - - - Region Region - A .183 .058 .053 3.172 ** .002 Region - B .260 .058 .077 4.502 *** .000 Region - C .086 .058 .024 1.485 .138 Region – D ® - - - - - Religion X Work Participation Interaction Muslim X Working -.204 .140 -.023 -1.460 .144 Muslim X Not Working ® - - - - - Christian X Working -.026 .128 -.003 -.199 .842 Christian X Not Working ® - - - - - Adjusted R² = .481

Dependent variable: Total Number of Children Ever Born. The variable Education below middle is constant or has missing correlation. Note: ® Reference Variable; *** 99 percent significant, ** 95 percent significant, * 90 percent significant.

304

Table 6.15 Religion X Contraception Interaction




Level

Constant .953 .180 5.302 *** .000 Current age of respondent .085 .003 .484 31.521 *** .000 Age at Marriage -.110 .007 -.270 -16.460 *** .000 Place of Residence Urban -.126 .046 -.038 -2.714 * .007 Rural ® - - - - - Religion Hindu ® - - - - - Muslim .480 .074 .151 6.458 *** .000 Christian .298 .103 .074 2.896 ** .004 Ethnicity SC .122 .081 .023 1.508 .132 ST .221 .198 .015 1.120 .263 OBC .071 .045 .024 1.598 .110 Others ® - - - - - Level of Women’s Education Illiterate® - - - - - Below Middle - - - - - Middle Complete -.197 .060 -.050 -3.305 ** .001 H S Complete and Above -.231 .053 -.077 -4.351 *** .000 Standard of Living Low ® - - - - - Medium -.055 .055 -.018 -.988 .323 High -.029 .061 -.009 -.472 .637 Occupation Working -.170 .050 -.048 -3.385 ** .001 Not Working ® - - - - - Contraceptive Use Using .712 .059 .236 12.052 *** .000 Not Using ® - - - - - Region Region - A .187 .058 .054 3.235 ** .001 Region - B .273 .058 .081 4.737 *** .000 Region - C .088 .058 .024 1.527 .127 Region – D ® - - - - - Religion X Contraception Interaction Muslim X Using .225 .093 .052 2.427 .015 Muslim X Not Using ® - - - - - Christian X Using -.126 .121 -.027 -1.039 .299 Christian X Not Using ® - - - - - Adjusted R² = .483


305

Table 6.16 Religion X Age at Marriage Interaction

Un standardized Coefficients Standardized Coefficient Explanatory Variables

B Std. Error Beta t-value Significance Level

Constant .692 .199 3.468 ** .001 Current age of respondent .477 .003 .482 31.393 *** .000 Age at Marriage -.732 .008 -.239 -12.139 *** .000 Place of Residence Urban -.120 .046 -.037 -2.597 * .009 Rural ® - - - - - Religion Hindu ® - - - - - Muslim .827 .294 .572 6.218 *** .000 Christian -.153 .395 -.038 -.388 .698 Ethnicity SC .140 .081 .026 1.738 .082 ST .248 .197 .017 1.258 .208 OBC .921 .045 .023 1.554 .120 Others ® - - - - - Level of Women’s Education Illiterate® - - - - - Below Middle - - - - - Middle Complete -.200 .059 -.051 -3.362 ** .001 H S Complete and Above -.240 .053 -.080 -4.525 *** .000 Standard of Living Low ® - - - - Medium -.160 .055 -.021 -1.114 .265 High -.553 .061 -.011 -.580 .562 Occupation Working -.166 .050 -.047 -3.317 ** .001 Not Working ® - - - - - Contraceptive Use Using .775 .043 .257 18.117 *** .000 Not Using ® - - - - - Region Region - A .163 .058 .047 2.821 * .005 Region - B .239 .058 .071 4.144 *** .000 Region - C .536 .058 .021 1.304 .192 Region – D ® - - - - - Religion X Age at Marriage Hindu X Age at Marriage ® - - - - - Muslim X Age at Marriage -.828 .016 -.378 -4.325 .012 Christian X Age at Marriage .578 .018 .087 .875 .381 Adjusted R² = .485


306

6.6.2 Religion X Education Interaction

The result of the regression analysis showing the effect of religion x

education interaction upon the number of children ever born reveals that

among the eight selected interaction variables Muslim X Below Middle

school and Christian X Below Middle school education are constant or

having missing correlation with children ever born, Table 6.11. The other

two variables Muslim X Middle school Complete and Muslim X high

school Complete and above have negative relationship with the total

number of children ever born. This negative relationship is highly

significant in the case of the variable Muslim X high school complete and

above. The interaction variables showing the Christian and different levels

of education are not significant at all. The higher the levels of women

education the lesser will be the chance of additional children among

Muslims. This result is consistent with the findings from the district level

analysis of fertility differentials, (for details see chapter V). Thus, low level

of education can be considered as one of the reasons for higher fertility

among Muslims in Kerala. In other words, the interaction analysis shows

religion X education effect among Muslims.

6.6.3 Religion X Region Interaction

It is clear that there exist regional variations in religious fertility in

Kerala, (for details see chapter V). So it is not the socio-economic

characteristics of the religious groups but rather the region, to which

women of the different religious groups belong to, that matters more in

the decision on the number of children. The place should be viewed as

synonymous with the cultural settings of that particular geographical

region. In other words, let the couples be poor, illiterate, belonging to a

lower caste or Muslim community, their living in a certain spatial settings

307

can be the reason for their having fewer number of children. (James,

Sajini, 2005).

Regression analysis explaining religion X region interaction is

shown in Table 6.12. The result of interaction analysis using the

reformulated variable reveals that among the eight variables used in

Religion X Region interaction analysis two variables, Muslim X Region A,

and Muslim X Region B have significant positive correlation with the total

number of children ever born. All the other regions show the same positive

relation between Muslim population and fertility, though the influence is

not significant.

The interaction between religion and all the other variables is also

discussed. The analysis of variables like Religion X Place of Residence,

(Table 6:13), Religion X Women Work Participation, (Table 6:14),

Religion X Contraceptive Prevalence, (Table 6:15) and Religion X Age at

Marriage (Table 6:16) shows no or insignificant effect on fertility.

6.7 Conclusion

In this chapter, an attempt has been made to understand the effect of

selected socio economic variables on the number of children ever born.

The analysis revealed that among the independent variables age at

marriage, level education and women work participation showed strong

negative relation with the number of children born. On the other hand, the

relation is positive in the case of respondent’s age, contraceptive use and

religious affiliation. Also the analysis shows the strong regional impact on

fertility. The variables such as respondent’s place of residence, ethnicity

and standard of living have not shown any significant effect on fertility.

The analysis reveals that, the influence of religion remains

significant after controlling for the other socio-economic variables. This is

true for other variables such as age at marriage, level of education,

308

contraceptive use, women work participation and regional variations also.

Further, the result of the analysis shows that the effect of the independent

variables on the number of children ever born is almost the same

irrespective of the place of residence.

The analysis of interaction effect of religion and selected socio-

economic variables has revealed that, there is an interaction between

religion and education. The Religion X Education interaction is significant

for Muslims. The Muslim X Middle School Complete and Muslim X High

School Complete and above seem to have a significant negative effect on

the number of children ever born. The analysis shows that the Muslim X

Middle School Complete and Christian X Middle School6 Complete are

constant or having a missing correlation.

The hypothesis of the present study claims that, religious fertility

differentials are caused by the spatial settings and the differences in the

geographical concentration of religious groups. This has been tested in the

analysis. The result of the Religion X Region interaction analysis is

consistent with this proposition. Muslim X Region A and Muslim X

Region B interactions show significant positive effect on fertility. The

overall Muslim population in these regions is high and the spatial

dimensions are not conducive to a reduction in the fertility in these regions.

The analysis of interaction shows that the effect of various socio-

economic factors is not a precondition for religious fertility differentials in

Kerala. Couples of the same religion residing at different regions take

different fertility decisions even after controlling for the socio-economic

characteristics. In other words, couples with same socio-economic

characteristics from different religious groups residing at different region

may take different fertility decisions. So it is not the socio-economic

characteristics of the religious groups but the region where they live or the

309

spatial settings that determine the number of children born. Though

Muslims have higher fertility compared to Hindus and Christians, their

number of children at the southern districts is low or comparable to other

religious groups. Alternatively, the number of children of other religious

groups residing in northern districts is high compared to their brothers or

sisters living in the southern part of the State.

Thus, fertility differentials among religious groups are a

phenomenon which may disappear when the differentials in the spatial

settings and the concentration of religions in a certain region are minimized

to zero. However, the relationship between fertility and the spatial

dimensions is very complex so the ways through which these relationships

influence religious fertility differentials are yet to be analysed clearly. This

calls for further research.

310

References

Baghat, R. B. and Praharaj Purujit, (2005): “Hindu Muslim Fertility

Differentials”, Economic and Political Weekly, Vol 40, No 5, pp

411-418.

Chamie, Joseph. (1981): “Religion and Fertility Arab Christian-Muslim

Differentials”, Cambridge University, Sidney.

Chaudhury, R.H (1984): “Hindu Muslim Differential Fertility How Much

Religious and How Much Socio?”, Social Action, Vol. 34, No. 3, pp

251-273.

Cochrane, S.H, (1998): “Effects of Education Health and Social Security on

Fertility in Developing Countries”, World Bank, Washington D C.

Dev, Mahendra S, James K.S and Binayak Sen (2002): “Causes of Fertility

decline in India and Bangladesh: Role of Community”, Economic

and Political Weekly, Vol 37, No 43, pp 4447-4454.

Dharmalingam, A. and Philip Morgan, (2004): “Pervasive Hindu-Muslim

Fertility Differences in India”, Demography, Vol.41, No. (3), pp

529-545.

Dreze,Jean and Murthi, (2001): “Fertility Education and Development:

Evidence from India:, Population and Development Review, Vol.

22, No 1, pp 33-63.

Guilmoto, Christopher, Z and Rajan S. I, (2001): “Half a Century of

Fertility Transition in Indian Districts, 1951-2001”, Population and

Development Review, Vol.27 No. 4, pp 713-738.

James K.S (1999): “Fertility Decline in Andhra Pradesh: A search for

Alternative Hypothesis”, Economic and Political Weekly, Vol. 34,

No. 8, pp 491-499.

311

James, K.S and Sajini, B. Nair, (2005): “Accelerated Decline in Fertility in

India Since the 1980s: Trends Among Hindu and Muslims”,

Economic and Political Weekly, Vol. 40, No. 5, pp 375-383.

Montgomery, Mark R and John B Castrerline, (1998): “Social Net works

and Diffusion of Fertility Control”, Working Paper No 119,

Population Council, New York.

Morgan, S P, S Stash, H Smith and K O Mason (2002): “Muslim and Non

Muslim Differences in Female Autonomy and Fertility, Evidence

from Four Asian Countries”, Population and Development Review,

Vol 28, No. 3, pp 515-538.

Munshi, Kaivan and Jaques Myaux, (2000): “Social Change and Individual

Decision: Within an Application to the Demographic Transition”,

University of Pennsylvania (unpublished).

Unisa, S. and R. D. Bhagat (2000): “Social Dimension of Fertility in India

-Insights from a Regional Study”, International Journal of

Anthropology, Vol. 15, Nos 1 and 2, pp 81-90.

Zachariah, K.C (1984): “Determinants of Fertility Decline in India”, World

Bank, Washington D C.

Zachariah, K.C, Rajan, S, I, Sarma, P. S, Navaneethan, K, Nair P.G.S and

Mishra U. S. (1994): “Demographic Transition in Kerala in the

1980s” Centre for Development Studies, Trivandrum.

312

INDEX

Age at Marriage: 280,286, 287,

296, 297-311

Baghat,R.B: 309

Bhagat R.D: 309

Binayak Sen: 309

Chamie, Joseph: 285, 297,

310

Chaudhury, R.H: 314

Christian: 283, 286, 287-292, 295,

298-311

Cochrane, S.H: 295, 310

Contraceptive Use: 282, 291, 295,

296, 298, 299, 300, 298-307

Dev, Mahendra S: 284, 294,

308, 309

Dharmalingam, A: 310

Dreze,Jean: 310

Education: 282, 284, 286, 287, 288,

297, 296-312

Ethnicity: 284, 286, 295, 296, 298,

299, 300, 308

Fertility: 288, 290, 295-300, 308-

311

Guilmoto, Christopher: 310

Hindu: 284, 287, 288, 289, 292,

295, 300-311

Interaction Analysis: 298

James K.S: 311, 314, 311

Jaques Myaux: 311

John B Castrerline: 311

Mason, K O: 310

Median Age at Marriage: 286, 287

Mishra, U.S: 310

Montgomery, Mark R: 294,

315

Morgan, S P: 310

Multicollinearity: 298

Multivariate Regression Analysis:

295

Munshi Kaiva: 311

Murthi: 294, 311

Muslim: 284, 286, 287, 292, 311

Nair, P.G.S: 311

Navaneethan: K 311

NFHS: 283, 284, 286, 288, 290,

291, 298

Other Backward Community: 298,

303, 300-305

Philip Morgan: 310

313

Place of Residence: 281, 282, 284,

285, 290, 295, 296, 300,

301, 303-310

Praharaj Purujit: 297 314

Rajan: S.I 299, 314, 311

Religion: 282-313

Religion X Age at Marriage

Interaction: 301, 309, 310

Religion X Contraceptive

Prevalence Interaction: 301,

308, 310

Religion X Educational Attainment

Interaction: 282, 301, 304,

310, 310

Religion X Place of Residence

Interaction: 301, 308, 310

Religion X Region Interaction:

282, 301, 305, 310, 309

Religion X Standard Of Living

Interaction: 282, 300, 301,

302, 302

Religion X Women Work

Participation Interaction:

282, 284, 299, 300, 301-312

Sajini, B.Nair: 311, 3151

Sarma: P. S 311

Scheduled Caste: 284, 288, 295,

296, 297, 298, 301, 304,

305, 306, 307, 308

Scheduled Tribe: 284, 286, 297

Smith, H 311

Socio-Economic Factors: 282, 284,

295

Spatial Dimension on Fertility:

282, 294, 312, 311

SRS: 283

Standard of Living: 311

Stash: S 311

Unisa: S 298, 311

Women Work Participation: 282,

290, 291, 297, 300, 307,

311, 312

Zachariah, K.C: 311

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