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

Singh, NS

Singh, WS

English

Cognitive Sciences ePrint Archive

Original Article:
Identification of Factors Influencing Third Birth Transition in Manipur.
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.
Address For Correspondence:
Dr. N. Sharat Singh,
Department of Statistics,
Thoubal College under Manipur University,
Imphal, India .
E-mail: sharatbiostat@gmail.com
Citation:  Singh NS, Singh WS, Singh NS. Identification of factors influencing third birth transition in Manipur. Online J Health 
Allied Scs. 2011;10(1):8
URL: http://www.ojhas.org/issue37/2011-1-8.htm
Open Access Archives: http://cogprints.org/view/subjects/OJHAS.html and http://openmed.nic.in/view/subjects/ojhas.html
Submitted: Feb 2, 2011 Accepted: Mar 30, 2011; Published: April 15, 2011
Abstract:
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 eli-
gible 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 3 rd 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 signi-
ficance.
Key Words:  Age at  marriage;  Sex of previous child; Education of 
wife; Third child
Introduction:
To reduce the human fertility following the Cairo’s International Con-
ference on Population and Development (ICPD- 1994), India’s Na-
tional Population Policy (NPP) - 2000 had formulated the short, medi-
um and long term objectives of the policy. The medium-term object-
ive  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 eco-
nomic growth, social development, and environmental protection. Ob-
viously, the short, medium and long-term objectives are intertwined 
and failure on short or medium-run goals would have serious implica-
tion for the long-run objective of population stabilization. Further, re-
cognizing the importance of health in the process of economic and so-
cial 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, Ra-
jasthan,  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 popu-
lation growth. Lack of education and son preference may be sloe re-
sponsible 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 par-
ents 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 ad-
ditional 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 func-
tions  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.
Materials and Methods:
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 11 th July 2009. The lo-
gistic regression model is adopted to identify the determinants of third 
birth transition in the state. Here, the response variable is the trans-
ition 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,  
1
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Volume 10, Issue 1; Jan-Mar 2011
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 previ-
ous/  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 edu-
cation. The results of the analysis are interpreted on the basis of P-val -
ues of the regression coefficients (B) and odds ratios (OR) quantified  
by Exp.(B) of the variables.
Results:
Out of 1397 eligible women, 593 that is 42% ones is found to have  
their third birth in the population.  A binary logistic regression analys-
is on the transition of third birth (1 if at least 3 rd birth occurred, 0 oth-
erwise) 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 mar-
riage 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 dur-
ing infancy (P<0.05, OR=2.39) and duration of post partum amenor-
rhoea (P<0.05, OR=1.04). The significant factors are positively asso-
ciated 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 de-
terminants 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 phenomen-
on, the most important factor is sex of index child being female.
Table 1: Odds Ratios of variables on 3rd birth in Logistic Regression Model
Variable B S. E Wald P-value OR 95%CI for ORLower 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   
While controlled the effects of four other variables in the last model, the risk of having 3 rd 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 mar-
riage, 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 reem-
phasized that the high risk of 3rd birth phenomenon (P<0.001) can be quantified to be at least double times in the previous 2 nd child is 
female than that of male (OR=2.07 with 95%CI: 1.53-2.79).
Table 2: Odds Ratios of variables on 3rd birth in Stepwise Logistic Regression Model
Step Variable B S.E Wald P-value OR 95% CI for ORLower Upper
1 Age at marriage of wife -.137 .016 72.523 .000 .872 .845 .900Constant 3.628 .373 94.632 .000 37.639   
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   
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   
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   
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   
2
Discussion:
Five determinants of third birth transition are found to be educa-
tional 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 soci-
eties 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 ex-
planatory 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  ad-
vancement, 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-fa-
milial 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 ana-
lysis 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 re-
vealed 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. 
References:
1. Bardhan PK. Sex disparity in child survival in Rural 
India.  In Srinivasan TN, Bardhan PK, editors.  Rural 
poverty  in  South  India.  Oxford  University  Press; 
1988. P. 472-482.
2. Mason KO. Family change and support of elderly in 
Asia: what does we know?.  Asia Pacific Population  
Journal 1992;7(3): (East West Centre Reprint Series 
No. 286).
3. Dharmalingam A. The social  context  of  family  size 
preferences and fertility behabiour in a South Indian 
Village. Genus 1996;52:83-103.
4. Nath DC, Deka AK. The importance of son in a tradi-
tional  society:  How  elderly  parents  see  it?  Demo-
graphy India 2004;33(1):33-46.
5. Moore  M.  Indian  Plan  thwarted  by  quest  for  sons. 
Population  grows  as  farmers  insist  upon  two  male 
heirs. Washington Post 1994; Sept. A 26. 
6. Nath DC, Leonetti DL. Correlates of coital patterns in 
a  traditional  Indian  society.  In  Yadava  RC,  editors. 
Dynamics of population change (Emerging issues of 
21st Century). Delhi: Shipra Publication; 2001. P. 57-
67.
7. International Institute for Population Sciences (IIPS). 
National Family Health Survey-3, 2005-06: Key find-
ings, 2007: 5.
8. International Institute for Population Sciences (IIPS). 
National Family Health Survey-3, 2005-06: Manipur, 
2008: 46.
9. Henry  L.  Some  data  on  natural  fertility.  Eugenics  
Quarterly 1961;8:81-91.
10. Henry L.  On the measurement  of human fertility.  A 
population council book 1972, London.
11. Yadava NS, Jain SK, Kumar A. Fertility differentials 
in  Eastern  Utter  Pradesh:  a  multivariate  analysis. 
Janasamkhya 2000;18:18-29. 
12. Vignoli D. Fertility change in Egypt: From second to 
third birth.  Max-Plak Institute  for Demographic  Re-
search Working Paper 2006. 
13. Singh NS, Narendra RK, Hemochandra L. Determin-
ants  of  waiting time  to conception  in  Manipuri  wo-
men. Kuwait Medical Journal 2007;39(1):39-43.
14. Hussain R, Fikree FF, Berendes HW. The role of son 
preference in reproductive behaviour in Pakistan. Bul-
letin  of  the  World  Health  Organisation 
2000;78(3):379-388. 
15. Youssef R M. Duration and determinants of interbirth 
interval: community-based survey of women in south-
ern  Jordan.  Eastern  Mediterranean  Health  Journal  
2005;11(4):559-572. 
16. Khawaja M, Randall A. Intifada, Palestinian fertility 
and women’s education. Genus 2006;LXII(1):21-51.
3


Correlates of coital patterns in a traditional Indian society.

Deka AK. The importance of son in a traditional society: How elderly parents see it? Demography

Family change and support of elderly in Asia: what does we know?. Asia Pacific Population Journal 1992;7(3): (East West Centre Reprint Series No.

Fertility differentials in Eastern Utter Pradesh: a multivariate analysis.

for Population Sciences (IIPS). National Family Health Survey-3, 2005-06: Key findings,

Indian Plan thwarted by quest for sons. Population grows as farmers insist upon two male heirs.

On the measurement of human fertility. A population council book

Sex disparity in child survival in Rural India.

Some data on natural fertility.

The social context of family size preferences and fertility behabiour in a South Indian Village. Genus

Identification of Factors Influencing Third Birth Transition in Manipur

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Identification of Factors Influencing Third Birth Transition in Manipur

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