ANALYSIS OF SOCIO-ECONOMIC, DEMOGRAPHIC AND...
Transcript of 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).
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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
Source: Computed from NFHS-II, Household data files
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
Source: Computed from NFHS-II, Household data files
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
Source: Computed from NFHS-II, Household data files
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
Source: Computed from NFHS-II, Household data files
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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
Un standardized Coefficients
Standardized Coefficient Explanatory Variables
B Std. Error Beta t-value Significance
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
Un standardized Coefficients
Standardized Coefficient Explanatory Variables
B Std. Error Beta t-value Significance
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
Un standardized Coefficients
Standardized Coefficient Explanatory Variables
B Std. Error Beta t-value Significance
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
Un standardized Coefficients
Standardized Coefficient Explanatory Variables
B Std. Error Beta t-value Significance
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
Un standardized Coefficients
Standardized Coefficient Explanatory Variables
B Std. Error Beta t-value Significance
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
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.
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
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.
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
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Differentials”, Economic and Political Weekly, Vol 40, No 5, pp
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Chaudhury, R.H (1984): “Hindu Muslim Differential Fertility How Much
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Cochrane, S.H, (1998): “Effects of Education Health and Social Security on
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James, K.S and Sajini, B. Nair, (2005): “Accelerated Decline in Fertility in
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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