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OJHAS Vol. 10, Issue 1:
(Jan-Mar 2011) |
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| Identification
of Factors Influencing Third Birth Transition in Manipur |
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Sharat Singh N, Department of Statistics, Thoubal College under Manipur University, Imphal,
Shantikumar Singh W, Research Scholar
(Statistics), Jodhpur National University, Jodhpur,
Sanajaoba Singh N, Directorate of Census
Operations, Imphal. |
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Address for Correspondence |
Department of Statistics,
Thoubal College under Manipur University,
Imphal, India.
E-mail:
sharatbiostat@gmail.com |
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Singh NS, Singh WS, Singh NS. Identification
of factors influencing third birth transition in
Manipur. Online J Health Allied Scs.
2011;10(1):8 |
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Submitted: Feb 2,
2011 Accepted: Mar 30, 2011; Published: April 15, 2011 |
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| Abstract: |
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The third
birth transition has a negative impact on the national goal of fertility
replacement level (2.1) which is to be achieved by 2010. To identify
the factors influencing the demographic phenomenon, a cross sectional
as well as community based study consisting of 1397 eligible women was
conducted in the four valley districts of Manipur under cluster sampling
scheme. Analysing the empirical information through SPSS, 42% of the
study subjects transit their 3rd birth and
its major determinants could be detected to be sex preference, age at
marriage, and educational level each at 0.01 probability level of significance.
Key Words:
Age at marriage; Sex of previous child; Education of wife; Third child
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To reduce the
human fertility following the Cairo’s International Conference on
Population and Development (ICPD- 1994), India’s National Population
Policy (NPP) - 2000 had formulated the short, medium and long term objectives
of the policy. The medium-term objective is to bring the total fertility
rate to replacement level (2.1) by 2010, through vigorous implementation
of inter-sectoral operational strategies. The long-term objective is
to achieve a stable population by 2045, at a level consistent with the
requirements of sustainable economic growth, social development, and
environmental protection. Obviously, the short, medium and long-term
objectives are intertwined and failure on short or medium-run goals
would have serious implication for the long-run objective of population
stabilization. Further, recognizing the importance of health in the
process of economic and social development and improving the quality
of life of citizens, India’s National Rural Health Mission: 2005-12
also emphasises in its goals on population stabilization, gender and
demographic balance.
NFHS
reports the significant inter-state variations in the unwanted fertility
in India. Unplanned pregnancies are still relatively common. The unwanted
fertility had risen from 22% in 1992-93 to 25% in 1998-99. Nevertheless,
unwanted fertility as percent of TFR declined in the low fertility southern
states of Kerala, Tamil Nadu and Andhra Pradesh and rise up in most
of the high fertility states like Bihar, Rajasthan, Uttar Pradesh, Madhya
Pradesh, and Orissa over the same period. However, if the unwanted fertility
component is taken care of or gets eliminated then the TFR would come
down to replacement level of 2.1 or even below that in most parts of
India. The recent NFHS-3 report also stresses that if all women were
to have only the number of children they wanted, the TFR would be 1.9
instead of 2.7. Among births in the five years before the survey, 10%
were wanted later and 11% were not wanted. In the report, 71% of adults
want no more children, are already themselves sterilized, or have a
spouse who is sterilized. Among those who do want another child, about
half would like to want at least two children. Two-thirds of women and
men consider the ideal family size to be 2 children or less.
Third
birth transition is a serious demographic phenomenon for population
growth. Lack of education and son preference may be sloe responsible
factors to it. The past studies in India have identified three major
factors for son preference. They are economic, socio-cultural and religious
utilities. Sons are more likely than daughters to provide family labour
on the farm or in family business and support their parents of old age,
although there is some recognition that sons are no longer a dependable
source of old age support.(1-4) A son brings upon marriage a daughter-in-law
into his family and she provides additional help around the house as
well as an economic reward in the form of dowry payments. In the context
of India’s patriarchal family system, having one son is imperative
for continuation of the family line, and many sons provide additional
status to the family.(5) The utility of having sons also arises from
the important religious functions that only sons can provide.(6) According
to Hindu tradition, sons are needed to kindle the funeral pyre of their
deceased parents and to help in the salvation of their souls. Most of
the Indian couples have thus a strong preference for sons over daughters.
In an effort to have sons, many couples continue to have children after
achieving their desire family size. In case of intention, about 20%
of Indian couples want more sons than daughters, but only 2 to 3% of
them want more daughters than sons.(7) In Manipur, 31.2% of ever married
women who want more sons than daughters according to NFHS-3:2005-06
which is declining from that of 36.5% in NFHS-2:1998-99 and 43.4% in
NFHS-1:1992-93.(8) Despite, no community based study has so far been
conducted in the state particularly in hill and rural areas where ‘natural
fertility’(9,10) seems to be existed. Thus, it is to investigate the
socio-demographic determinants of third birth transition.
A cross sectional
as well as community based study of 1397 currently married women of
reproductive age group having at least two live births was conducted
through a cluster sampling scheme in four valley districts of Manipur
– Bishnupur, Imphal East, Imphal West and Thoubal. The survey was
performed during the six months of July 2009-January 2010 with the reference
date of 11th July 2009. The logistic regression model is
adopted to identify the determinants of third birth transition in the
state. Here, the response variable is the transition of third birth
which is quantified by the issue of third live birth. It is defined
to be 1, if the mother has at least third live birth and 0, otherwise
(having at most two live births). The explanatory variables considered
are religion (1for subject religion & 0 for other religion), residence
(urban=1& rural=0), type of family (nuclear=1& joint=0), educational
level, employment status (employed=1 & others=0), age at marriage,
couple’s desire number of son, death of previous child during infancy
say infant mortality (death=1, alive=0), sex of previous/ index child
(female=1, male=0) and the use of contraceptives (used=1, others=0)
during transition of third birth. For categorical variables, binary
dummy variable (0, 1) is utilized. The educational level is measured
by the number of completed academic years in education. The results
of the analysis are interpreted on the basis of P-values of the regression
coefficients (B) and odds ratios (OR) quantified by Exp.(B) of the variables.
Out of 1397
eligible women, 593 that is 42% ones is found to have their third birth
in the population. A binary logistic regression analysis on the
transition of third birth (1 if at least 3rd birth occurred,
0 otherwise) is carried out to identify the determinants thereof. Here,
seven significant variables out of fourteen classified ones can be detected
with their adjusted Ors shown in table-1. The significant factors found
in the model are education of wife (P<0.01, OR=0.90), age at marriage
of wife (P<0.01, OR=0.89), employment of husband (P<0.01, OR=2.16),
couple’s desire number of son (P<0.01, OR=1.73), sex of previous/index
child (P<0.01, OR=2.08), death of previous child during infancy (P<0.05,
OR=2.39) and duration of post partum amenorrhoea (P<0.05, OR=1.04).
The significant factors are positively associated with third birth except
level of education and age at marriage which have negative impacts thereon.
Here, the level of significance of each variable is observed after adjusted
the effects of other factors under study. It is to say that the effects
of the significant variables are found keeping that of others to be
constant or so termed adjusted.
In
the stepwise (Forward Wald) logistic regression, the best set of determinants of
third birth is found to be five factors. They are type of family, education of
wife, age at marriage, couple’s desire number of son, and sex of previous child
depicted in table-2. In the last fifth step, the logistic regression is fitted
with the five variables. After adjusted the joint effects of four other
variables in the last model, achievement of educational level and age at
marriage of wife are observed to be negatively associated with the phenomenon of
third birth transition. Among the three variables having positive impacts on the
phenomenon, the most important factor is sex of index child being female.
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Table
1: Odds Ratios of variables on 3rd birth in
Logistic Regression Model
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Variable |
B |
S.
E |
Wald |
P-value |
OR |
95%CI for OR |
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Lower |
Upper |
| Residence |
-0.306 |
0.189 |
2.608 |
.106 |
0.736 |
0.508 |
1.068 |
| Type of family |
0.312 |
0.161 |
3.765 |
.052 |
1.366 |
0.997 |
1.871 |
| Religion
(Hindu) |
0.094 |
0.240 |
0.152 |
.697 |
1.098 |
0.686 |
1.758 |
| Religion
(Muslim) |
0.154 |
0.731 |
0.045 |
.833 |
1.167 |
0.278 |
4.893 |
| Education
of husband |
0.018 |
0.025 |
0.507 |
.476 |
1.018 |
0.970 |
1.068 |
| Education
of wife |
-0.102 |
0.018 |
31.529 |
.000 |
0.903 |
0.871 |
0.936 |
| Employment
status of husband |
0.770 |
0.173 |
19.894 |
.000 |
2.160 |
1.540 |
3.029 |
| Employment
status of wife |
0.656 |
0.387 |
2.877 |
.090 |
1.928 |
0.903 |
4.115 |
| Age at marriage
of wife |
-0.111 |
0.018 |
37.760 |
.000 |
0.895 |
0.863 |
0.927 |
| Couples desire
number of son |
0.547 |
0.107 |
25.921 |
.000 |
1.728 |
1.400 |
2.133 |
| Sex of previous
child |
0.734 |
0.157 |
21.955 |
.000 |
2.084 |
1.533 |
2.833 |
| Use of contraceptives |
0.124 |
0.318 |
0.152 |
.697 |
1.132 |
0.606 |
2.113 |
| Death of
previous child |
0.870 |
0.154 |
18.112 |
.045 |
2.387 |
1.028 |
6.174 |
| Post partum
amenorrhoea |
0.036 |
0.016 |
5.124 |
.024 |
1.037 |
1.005 |
1.069 |
| Constant |
1.615 |
0.639 |
6.387 |
.011 |
5.027 |
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While
controlled the effects of four other variables in the last model, the
risk of having 3rd birth can significantly be reduced (P<0.01)
by 7% corresponding to one year advancement in education as its OR-value
0.93 with 95%CI: 0.901-0.95. As one year delay in marriage, the women
can be free of 11% from the risk of 3rd birth in the sense
that at an average a woman has 11% more significant risk of being 3rd
birth with respect to one year earlier of her marriage (P<0.01, OR=0.89
with 95%CI: 0.87-0.93). But, highly significant risk of 74% is observed
to each increment in the couple’s desire number of son as supported
by its test values (P<0.01, OR=1.74 95%CI: 1.42-2.143) as the joint
effect of other four factors in the last model is typically controlled.
This sex preference effect is again reemphasized that the high risk
of 3rd birth phenomenon (P<0.001) can be quantified to
be at least double times in the previous 2nd child is female than
that of male (OR=2.07 with 95%CI: 1.53-2.79).
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Table
2: Odds Ratios of variables on 3rd birth in
Stepwise Logistic Regression Model
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Step |
Variable |
B |
S.E |
Wald |
P-value |
OR |
95% CI for OR |
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Lower |
Upper |
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1 |
Age at marriage of wife |
-.137 |
.016 |
72.523 |
.000 |
.872 |
.845 |
.900 |
| Constant |
3.628 |
.373 |
94.632 |
.000 |
37.639 |
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2 |
Education of wife |
-.080 |
.015 |
28.086 |
.000 |
.923 |
.897 |
.951 |
| Age at marriage
of wife |
-.112 |
.017 |
44.815 |
.000 |
.894 |
.866 |
.924 |
| Constant |
3.773 |
.381 |
97.846 |
.000 |
43.531 |
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3 |
Education of wife |
-.076 |
.015 |
24.810 |
.000 |
.927 |
.899 |
.955 |
| Age at marriage
of wife |
-.104 |
.017 |
37.180 |
.000 |
.902 |
.872 |
.932 |
| Couples desire
no. of son |
.443 |
.100 |
19.441 |
.000 |
1.557 |
1.279 |
1.895 |
| Constant |
2.621 |
.455 |
33.196 |
.000 |
13.746 |
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4 |
Education of wife |
-.080 |
.015 |
26.407 |
.000 |
.924 |
.896 |
.952 |
| Age at marriage
of wife |
-.105 |
.017 |
37.244 |
.000 |
.900 |
.870 |
.931 |
| Couples desire
no. of son |
.541 |
.105 |
26.632 |
.000 |
1.717 |
1.398 |
2.108 |
| Sex of previous
child |
.739 |
.153 |
23.470 |
.000 |
2.094 |
1.553 |
2.823 |
| Constant |
2.137 |
.470 |
20.641 |
.000 |
8.470 |
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5 |
Type of family |
.316 |
.155 |
4.158 |
.041 |
1.371 |
1.012 |
1.857 |
| Education
of wife |
-.078 |
.016 |
24.915 |
.000 |
.925 |
.898 |
.954 |
| Age at marriage
of wife |
-.106 |
.017 |
37.896 |
.000 |
.899 |
.869 |
.930 |
| Couples desire
no. of son |
.555 |
.105 |
27.748 |
.000 |
1.743 |
1.417 |
2.143 |
| Sex of previous
child |
.726 |
.153 |
22.534 |
.000 |
2.068 |
1.532 |
2.791 |
| Constant |
1.916 |
.482 |
15.782 |
.000 |
6.792 |
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Five determinants
of third birth transition are found to be educational level of wife,
age at marriage, couple’s desire number of son, sex of previous child
and the type of family. As such, the five significant factors fit the
last regression model. In many societies as the couples are educated,
eagerness to restrict the family size increases. The present findings
observe the similar view. But, comparing the effects of education of
husband (P>0.05) with the wife counterpart, it is evident that the
education of wife (P<0.01, OR=0.90) plays more significant role in
reducing third birth transition. It is observed in logistic regression
with fourteen explanatory variables after controlling the effects of
other variables. The effects may include delaying age at marriage, reduction
in the desired family size, increase opportunities for personal advancement,
awareness of social mobility and freedom from close familiarities of
women outside the home and greater exposure to knowledge and favourable
attitude towards family limitations. Thus, enhancement of education
is supposed to result in non-familial aspiration and a greater understanding
of the process and ways of controlling high fertility. This view is
supported by the findings of Yadava et al.(11) Again from the
event-history analysis of 2000 Egyptian Demographic and Health Survey,
Vignoli (12) stresses that the difficult change in the fertility of
women with high educational status seems to be responsible for the stalling
fertility decline during recent years. The study also revealed that
the preference for at least one son in the family on the progression
to the third child is weakening among women who have completed secondary
education.
However,
the sex of the previous/ index child is demographic factor which can
not be managed by human hand. The value of the OR say 2.07 means that
the risk of third birth transition is increased more than double times
when the previous child is female than that of male counterpart. While
adjusted the joint effects of other four variables in the last model,
couple’s desire number of son is also observed to be high influential
factor (P<0.01) leading to third birth. It is advocated by OR value
of 1.74 which indicates that the risk of third birth is increased by
74% corresponding to desire of one more son. It is thought to be caused
by the fact that influence of son preference is high in the study population.
This view is supported by Singh et al.(13) They found that the duration
of waiting time to conception is significantly short as the desire number
of son increases. The finding is in agreement with some other past findings
too. In many developing countries, reproductive intentions and behaviours
are strongly influenced by sex of surviving children.(7,14-16) This
ill behave may have retarded India’s fertility decline and therefore
the present fertility level is far behind the national socio-demographic
goals which is to be achieved by 2010 according to the prime target
of National Population Policy 2000.
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