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An exploration of the trends and patterns of sex ratio at birth in urban India and the processes behind son preference suggests a systematic worsening of SRB with increasing urban district size classes. The likelihood of giving birth to a son at the first order is highest among women with a stated son preference, which continues to effect second and third order births, given the sex of the previous child. The interrelationship between SRB and educational attainment shows an inverted U-shape. A balanced SRB among poor women corroborates their unbiased gender preference. In contrast, wealthier women and those with exposure to mass media exhibit poor SRB, although they report a neutral preference.
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January 15 , 2022 vol lViI no 3 EPW Economic & Political Weekly
Sex Ratio at Birth in Urban India
Debolina Kundu, Rakesh Mishra, Arvind Pandey, Devender Singh
An exploration of the trends and patterns of sex ratio at
birth in urban India and the processes behind son
preference suggests a systematic worsening of SRB with
increasing urban district size classes. The likelihood of
giving birth to a son at the first order is highest among
women with a stated son preference, which continues
to effect second and third order births, given the sex of
the previous child. The interrelationship between SRB
and educational attainment shows an inverted U-shape.
A balanced SRB among poor women corroborates their
unbiased gender preference. In contrast, wealthier
women and those with exposure to mass media exhibit
poor SRB, although they report a neutral preference.
The relationship between urbanisation and sex ratio at
birth (SRB) in India is a generalised perception that
lacks empirical underpinning. Studies around this
subject, which concede that declining SRB is primarily an
urban phenomenon, suffer from a lack of comprehensive
evidence-based examination of their association. While the
factors affecting SRB have been a subject of academic discus-
sion, they have never been satisfactorily resolved. The recent
decline in SRB has drawn the interest of researchers, who have
attempted to understand and differentiate its determinants
and also provide evidence of distortion. However, until now,
there has been no comprehensive study that attempts to
understand the dynamics of SRB at a granular level in urban
areas, and correlating it with determining factors. The present
study attempts to fi ll this gap.
Notably, the fertility aspirations of couples have witnessed
manifold changes in urban India with a rapid decline in infant
and child mortality, establishing demographic impacts on SRB
(Guilmoto 2009). One such demographic consequence is the
skewed SRB (urba n). The World Hea lth Orga niz at ion (2011: 12)
describes skewed SRB as “an unacceptable manifestation of
gender discrimination against girls and women and a violation
of their human rights.” An undeniable favouritism for boys at
birth has a historical cultural inheritance in India, infl uencing
discrimination against girls even in recent times such that a
signifi cant number of girls are eliminated before birth (Patel
2006). The Economic Survey, 2017–18 (GoI 2018), reports that
over the last 10–15 years, India’s performance improved on
14 out of 17 indicators related to women’s agency, attitudes,
and outcomes, especially in urban areas. However, gender
parity remains a serious challenge in different spheres of deve-
lopment. Despite advancements in economic development, the
survey shows that gender biases prevail in land possession, en-
titlements of assets, and levels of education, employment and
wages. Furthermore, it draws attention to the phenomenon of
“missing women” and “unwanted girls,” which it attributes to
the skewed SRB.
Studies suggest that skewed SRB is one of the major societal
challenges of urban India, which manifests in t he phenomenon of
“daughter defi cit (Sen 1990; Kulkarni 2007, 2012). It is well
known that biological and social variables, such as parity,
parental age, and social class, affect SRB (Rostron and James
1977). Some studies found that son-biased sex ratios are more
common in third, or higher, order of births among couples
who previously had only one daughter (Almond et al 2013).
Maternal age and birth order, the socio-economic status of
parents, etc, have also been identifi ed as factors affecting the
The authors are grateful to the anony mous reviewer P M Kulkarni and
Sanjay Kumar for their constructive comments. The authors are also
thankful to Sudeshna Maitra, Biswjit Mondal, and T C Sharma for their
research input s and Chitra Sangtani for copyediting. T his r esea rch w as
supported by the United Nations Population Fund, Delhi offi ce.
Debolina Kundu ( teaches at and Rakesh Mishra
( is a researc h associate at the National Inst itute of
Urban Affairs, New Delhi. Arvind Pandey ( is an
assistant professor at the Tata Institute of Social Sciences, Hyderabad.
Devender Singh ( is the National Prog ram Offi cer
(Population and Development), United Nations Population Fund,
New Delhi.
Economic & Political Weekly EPW Janua ry 15, 2022 vol lViI no 3 49
ratio of boys to girls among newborns (James 2010; Jacobsen
et al 1999; Almond et al 2013; Chahnazarian 1988; Markle
1974). Further, recent studies have linked large imbalances in
SRB to sex- selective abortion. It is argued that this practice
emerges when strong patriarchal norms leading to a prefer-
ence for sons over daughters are combined with extensive
access to ultrasonography that can determine the sex of the
foetus (Bongaarts 2013).
Several policy interventions have been taken against gender-
biased sex selection to protect and promote females at birth
and other discriminations faced by them at a later stage (GoI
1971, 2003). In this regard, India has enacted the Pre- Natal
Diagnostic Techniques Act, 1994, to criminalise pre- natal sex-
detection technologies. The same was amended in 2003 to
Pre-Conception and Pre-Natal Diagnostic Act, which bans pre-
conception sex selection as well (GoI 2003). The Beti Bachao,
Beti Padhao and Sukanya Samridhi Yojana are also major pro-
grammes launched by the Government of India in the recent
past. Despite these measures, the child sex ratio det eriorated
in the country (Arok iasamy and Goli 2012; Guilmoto 2007, 2009),
which is the fallout of a sharp decline in SRB. Importantly,
skewed SR B is argued to be more urban than rural in nature
(Bhat and Zavier 2007). In recent times, however, it has also
been seen to spread signifi cantly in rural and tribal areas
(Kumar and Sathyanarayana 2012).
This trend is also visible across different socio-economic
groups in urban areas. Fertility desires and expectations among
the Scheduled Castes (SCs), for example, are now found to be
imitative of the general castes. Similar behavioural patterns
are observed among women of middle-income groups, emulat-
ing the behaviour of upper-income groups (Kaur et al 2017).
The SRB in urban areas is determined by multiple factors,
which vary across geographies. With increasing urbanisation,
it becomes important to investigate the causes of worsening
SRB in contemporary urban settings. The intentions that drive
couples towards son preference have remained under-
researched in urban India. It is important to study how couples
among the urban poor and vulnerable sections of society
cope with their reproductive goals, alongside the rising chal-
lenges of urbanisation. This study, thus, attempts to explore
the trends and patterns of SR B in urban India and how the
proce sses behind son preference change across urban district
size classes.
Data and Methods
The study is based on unit-level data from four rounds of the
National Family Health Survey (NFHS), esp ec ial ly NFHS-4,
2015–16 (IIPS and ICF 2017). For the estimation of SRB and its
correlates, birth history data was reconstructed for urban India
and estimations were carried out for all births in the last fi ve
years from a reference date. Son preference, which connotes a
greater desire for sons over daughters, was calculated based
on specifi c questions in the NFHS-4 questionnaire. The survey
form asked a married woman of reproductive age, the number
of sons/daughters she wants in her reproductive span. To
understand the determinants of son preference at different
birth orders, estimations were carried out on 1,31,678 married
urban women with at least one birth. A list of demographic
factors which hold proximate relations with SR B, such as birth
order, sex composition of children, and age of women, have
been analysed in addition to women’s education and occupa-
tional status, partner’s education, religion and caste of the
household, and urban wealth index.
In India, data on SRB is not available at the city level. As
a proxy, district-level information has been used. All 640
districts (Census of India 2011) were classi ed into fi ve size
classes, based on their urban population: less than 0.1 million,
0.1–0.5 million, 0.5–1 million, 1–5 million, and 5 million and
above. Later, the same districts were matched with NFHS
data and categorised into these fi ve size classes. Districts
with one million plus population, 0.1 million to one million,
and less than 0.1 million, are termed as large, medium and
small-size classes, respectively. Large and medium districts
together cover more than 55% of the total urban population of
the country.
Bivariate analysis was carried out to capture the variation in
SRB and stated preference for sons across various background
characteristics of children and mothers. Further, the approach
adopted by Arnold (1985) was used to segregate the effect of
son preference on the fertility behaviour across district size
classes. He attempted to answer what would be the change in
fertility when the sex preference is completely eliminated. In
the absence of sex preference, it is assumed that all couples
would have the same fertility behaviour at different parity of
births. Also, the number and composition of births at each
parity level would represent the fertility levels of satisfi ed
couples. Thus, taking the sex composition of children into
consideration, fertility behaviour at each parity is estimated
and denoted as actual fertility behaviour (referred as “Actual”
in Figures 3 and 4, p 51). However, for the same set of children
composition at different parities, fertility behaviour is esti-
mated assuming maximum (or minimum) values of the indi-
cator as unbiased behaviour of a couple. The highest and
lowest values are assu med depending upon the nature of
fertility indicator. For this study, the use of contraception is
considered as a positive indicator of fertility and the desired
nu mbe r of add iti ona l chi ldre n is t aken as a neg ati ve i ndi cat or.
Further, the weighted mean of actual and estimated fertility
behaviour has been estimated with weights representing the
share of fertility behaviour at each children composition. In
general, the estimates are given as ΣCiNi/ΣNi, where Ci refers
to the share (maximum or minimum) of fertility behaviour at
each parity i and Ni corresponds to the number of women at
each parity i.
In urban India, a majority of the states and union territories
already have fertility rates that are lower than the replacement
level (2.1). However, some states still have an average total
fertility rate less than or equal to three children per woman in
urban areas. Therefore, multivariate binary logistic regres-
sion has been applied in this study for capturing the probabil-
ity of having sons at fi rst three order of births to understand
the effect of various cofactors in contributing to low SRB.
January 15 , 2022 vol lViI no 3 EPW Economic & Political Weekly
The model for the logistic regression is given as (Retherford
and Choe 1993):
Log P
where x1, x2, x3…, xk are k independent covariates, and
ij is
the random error which follows a standard normal distribution.
Predicted probabilities have also been calculated.
Trends in SRB in Urban India
It is evident that there is no clear agreement in the estimates
from the two large-scale surveys (Figure 1) of the NFHS and Sam-
ple Registration System (SRS). For both 2000–04 and 2010–14,
the estimates of all-India SRB from the NFHS are higher than
that of the three-year moving average obtained from SRS. The
urban SRB from the NFHS-4 is approximately fi ve points higher
than that of SRS. The estimates of SR B from the NFHS show a
higher SRB for urban India as compared to overall India for
the periods 1987– 91 and 1993–97. However, it gradually dete-
riorated at a higher rate in urban areas than that of all-India,
lower than the average all-India SRB during 2000–04 and
2010–14. In urban India, SRB declined from 948 girls per 1,000
boys at birth in 1987–91 to 895 girls per 1,000 boys in 2010–14,
leading to a gap of 53 during the past two decades.
SRB, at the national and subnational levels, varied signi cantly
between the NFHS-1 and NFHS-4. Table 1 presents the statewise
total SRB and urban SRB calculated from each round of the NFHS.
The urban SRB was poorer than the total SRB in 1993–97, except
for the southern states and Nagaland, Tripura, and Odisha. A
similar pattern was observed in the NFHS-2 (1998–99); however,
this was not explicit in the NFHS-3. According to the NFHS-4,
urban Andhra Pradesh, Kerala, Tamil Nadu, Odisha, Nagaland,
and Tripura had a better SRB than the national average, which
could be attributed to the less patriarchal nature of these
states as compared to North-Western India (Dyson and Moore
1983; Basu 1992; Bhat and Zavier 2007).
Moreover, the government accelerated the implementation of
the amended Pre-Conception and Pre-Natal Diagnostic Tech-
niques (PCPNDT) Act, 1994, and launched other programmes to
encourage female births, ever since the 2001 Census revealed
a poor child sex ratio. This resulted in a slight improvement of
SRB in urban areas, above the state averages during 2005–06.
However, the NFHS-4 shows a further decline in SR B in both
state averages and urban areas.
District size-class (urban): This section analyses the impact of
the level of urbanisation and SR B at the district level. Figure 2
Sex ratio a t birth (SRB)
Figure 1: Trends in SRB
SRS Total SRS Urban NFHS Total NFHS Urban
SRS Total SRS urban NFHS urban
NFHS Total
SRB i n NFH S is c alcu late d for all b irt hs in the f ive comp lete cale nda r year s (1987– 91,
1993–97, 2000–0 4 and 2010–14) taken from bir th history d ata of all-rou nds. SRS fi gures
correspo nd to the mid-p oint for the pe riods 1998–200 0 to 2013–15.
Source: SRS a nd NFHS, variou s years.
Figure 2: Percentage of Urban Population and SRB
Sex ratio a t birth (SRB)
Urban Population (%)
Urban district size class
8.1 15.5
SRB Urban population (%)
Less than 0.1-0.5 million 0.5-1 million 1-5 million 5 million and
0.1 million above
The SRB estimates are based on the five-year calendar period 2010–14, and NFHS-4, 2015–16.
Source: NFHS -4, 2015–16.
Table 1: Statewise SRB
Tota l Urban
States 1992–93 1998 –99 2005– 06 2015–16 1992–93 1998–99 2 005–06 2015–16
Andhra Prad esh 1,005 950 872 899 1,020 930 934 972
Arunachal Pr adesh 971 820 1,001 910 1,137 672 1,052 861
Assam 962 909 982 901 931 808 1,148 813
Bihar 955 944 921 931 1,125 1,115 1,000 925
Chhattisgarh – – 890 958 – – 1,147 945
Delhi 884 847 859 820 876 860 910 814
Goa 965 878 945 949 888 826 852 883
Gujarat 980 901 897 873 842 973 991 801
Haryana 904 877 726 846 860 797 851 788
Himachal Prad esh 852 9 03 901 930 799 950 914 829
Jammu and Kashm ir 880 911 908 910 838 883 1,190 877
Jharkhand – – 1,062 930 – – 948 879
Karnataka 929 964 970 909 899 1,006 845 882
Kerala 961 892 934 1,028 959 822 1,239 1,041
Madhya Prade sh 930 915 1,014 913 943 9 62 879 895
Maharashtra 961 926 865 911 996 959 709 918
Manipur 1,057 1,068 1,010 964 1,130 1,014 1,072 956
Meghalaya 1,021 849 929 992 1,184 1,028 805 855
Mizoram 980 936 1,032 986 869 975 1,077 956
Nagaland 943 884 902 955 1,093 1,162 1,016
Odisha 948 992 886 941 992 973 816 996
Punjab 828 874 742 845 860 787 639 817
Rajasthan 893 89 6 897 869 813 920 874 824
Sikkim – 896 986 802 1,000 872 627
Tamil Nadu 1,018 1,00 0 991 950 1,059 976 773 9 81
Telangana – – – 875 – – 905
Tripura 908 981 978 936 759 1,311 875 1,072
Uttar Pra desh 909 972 915 896 8 81 919 852 886
Uttarakhand – – 873 878 – – 1,299 823
West Bengal 963 927 947 947 985 951 887 890
India 941 938 919 911 948 942 897 895
SRB has been e stimated f rom birth -history f iles of all fo ur rounds of the N FHS for all bir ths
in the five c ompleted ca lendar years (1987–91, 1993–97, 2000–0 4, and 2010–14).
Source: NFHS v arious roun ds.
Economic & Political Weekly EPW Janua ry 15, 2022 vol lViI no 3 51
plots SRB at the district level arranged into different size classes
based on urban population. The results indicate that with
increasing size classes, the share of urban population inc reases
and SRB declines, refl ecting a top-heavy urbanisation pattern
along with the incidence of worst SRB in highly urbanised
districts. Those districts with over a million urban population,
namely 1–5 million and 5 million plus size classes, have the
worst SRB of 897 and 820 females per 1,000 male at birth
respectively. Medium and small urban districts have better
SRB as compared to the larger distr ic ts.
Sex preference and fertility behaviour: The previous section
established that the SRB declines with district size classes. In the
face of long-standing biases towards sons, corresponding at-
titudinal changes are also seen in the fertility behaviour of
urban dwellers. Several studies have argued that the prefer-
ence for sons affects the composition of children and, as a
result, the completed family size (Arnold 1985; Rajaretnam
and Deshpande 1994; Kulkarni 1999). This section adopts
Arnold’s (1985) approach to capture the impact of sex prefer-
ence on fertility regulation in currently married women
across district size classes.
Figure 3 demonstrates the effect of son preference on
ferti lity behaviour through contraceptive use. In urban India,
nearly 57.2% women use modern methods in the effect of
son preference as compared to 67.8% otherwise with the
highest gap (13.7%) noted in fi ve million and above size
class, signifying that the average contraceptive use is higher
among females with no gender preference as compared to
women with a son preference in urban India. In the fi rst
two size classes, the gap between the use of contraception
in the presence and absence of gender preferences is nearly
the same. The results show that with the increasing size class
of districts, the use of modern contraceptive increased
from 50.1% to 61.3% for those who reported a gender prefer-
ence. This could be because of greater awareness among
women living in million-plus districts. Further, the decision
to adopt modern contraception not only depends on gender
preferences but also on the intention of childbe aring and
completion behaviour.
Figure 4 depicts intense fertility regulations in the effect
of son preference with increasing district size classes. Impor-
tantly, only 33.6% of currently married women do not want
to continue further childbearing, which, in the absence of
son preferences, increases to 39.5%. An almost 5.9% gap is
observed in the further continuation of childbearing, in effect
of son prefe rence in small districts. In fi ve million plus size
class, 29.7% women do not prefer to continue childbearing,
while in the effect of son preference, the percentage increases
to 39.7%. The results show that in the effect of son preference,
women continue to bear a higher number of children in all
district size classes. Thus, gender preference brings a huge
change in fertility regulations in urban India. This clearly
indicates that across diffe rent district size classes, sex prefer-
ence continues to have a dampening effect on the intentions
of ending childbearing.
Correlates o f SRB and Son Prefere nce
Table 2 (p 52) demonstrates the mean SRB and proportion of
women with son preference by socio-economic and demo-
graphic characteristics. The interlinkages between the wealth
of urban households and mean SRB (Table 2) show that the
poor have the most reasonable mean SRB at 943 female births
per 1,000 male births. As one goes up the ladder of the wealth
quintiles, the mean SR B deteriorates with the worst mean SRB
among the richest wealth quintile, who have better access and
obvious affordability to sex determination technologies and
sex-selective abortions (Javed and Mughal 2018). Ironically,
wealthy households have a lower proportion of women with
stated son preference. This is because women from wealthy
households respond with more socially desirable answers to
the survey questions. In contrast, poor households express
their true preference, yet rarely avail sex-selective abortions.
An analysis by caste group reveals that the Other Backward
Class (OBC) and the general category have a relatively better
mean SRB than SCs and Scheduled Tribes (STs), though
the estimates corresponding to these two categories are also
below the ideal level. Surprisingly, SCs, who have the lowest
mean SR B in urban areas, reported the least proportion of
women with a stated son preference. Sudha and Rajan (2003)
highlighted that although SCs were often characterised
Figure 3: Ef fect of Sex Pre ference on Cont raceptive Use am ong Currently
Married Wo men in Urban Di strict Siz e Classes
Use of contraception (%)
50.1 51.4
59.3 60.5
66.7 68.2
Less than 0.1
0.1–0.5 million 0.5–1 million 1–5 million 5 million and
Urban district size class
Actual Estimated
Source: Comp uted from th e NFHS-4, 2015–16
Fig ure 4 : Per cen tage of Wo men D esir ing No Mo re Ch ild ren b y Urb an Di str ict
Size Class
37.7 36.8
32.6 33.5
39.1 38.9 39.7 39.5
Less than 0.1
0.1–0.5 million 0.5–1 million 1–5 million 5 million and
Tot al
Not desiring any more children (%)
Urban distirct size class
Actual Estimated
Source: Comp uted from th e NFHS-4, 2015–16.
January 15 , 2022 vol lViI no 3 EPW Economic & Political Weekly
by greater gender egalitarianism, in recent years, they do not
exhibit any less gender bias in child outcomes. The fi ndings of
the present study are aligned with this argument, indicating
that with increasing awareness among marginalised sections
living in urban areas, there is a convergence of trends of SRB
across social groups.
The mean SRB across religions shows that the Hindus have a
poorer mean SRB than the Muslims, although the proportion of
women with stated son preference is higher among Muslims. A
signifi cant gap in the preference for sons among Hindus and
Muslims in the presence of worsened SRB indicates t wo diverse
pathways of discrimination opted by them. Discrimination
against females at birth among Muslims is characterised by
higher son preference, higher fertility, and lesser adoption of
family planning (Dharmalingam and Morgan 2004). Con-
versely, bias against girls at birth among Hindus is closely as-
sociated with the practice of modern technologies in the elimi-
nation of unborn girls. In light of this, Bhagat and Praharaj
(2005) have expressed concern over widening in the SR B dif-
ferentials among Hindus and Muslims. Christians, on the oth-
er hand, se em to have a ba la nc ed mean SRB.
The education levels of women also affect SRB. Women with
no education have a relatively better SRB than women who
have completed primary and secondary education. An imp-
rovement in SRB is, however, seen among women with higher
education. Thus, education and SRB shows a U-shaped relation
in urban India (Echávarri and Ezcurra 2010). Interestingly, the
percentage of women with stated son preference declines with
the increasing educational attainment of women.
Women working in the agricultural sector have the highest
mean SRB, followed by those who are not working. These two
groups are followed by women in the service sector and manual
jobs. The worst mean SRB is among white collared jobs who
also reported the least son preference.
The mean SRB exhibited deterioration with women’s expo-
sure to mass media. Women with no ex posure to media repor-
ted the highest son preference, while the least was reported by
women with full media exposure (Bhat and Zavier 2003).
Also, women who are fully exposed to mass media have a
highly skewed SRB, contrary to their low stated son preference.
Mean SRB for women by birth order of the child is an impor-
tant factor as it determines the fertility behaviour of couples.
Urban India, with an average fertility rate of 1.8, has a poorer
SRB at higher bir th order (> 3) a s compared to c hildren of fi rst
or second birth orders. Couples who have achieved their
desired number of sons in the rst two birth orders tend to
stop the childbearing process, whereas women who have one
or two daughters and preferably want a son, tend to undergo
sex-selective abortions for higher parities. This is one of the
main reasons for the worsening of SRB at higher birth orders,
which has been corroborated by earlier studies (Das Gupta
and Bhat 1997; Bhat and Zavier 2007).
For migrant and native women, the fi ndings are quite intri-
guing. The newly arrived migrant women report better SRB.
The stated son preference among women shows that the rec-
ently migrated women have low stated son preference. As the
period of stay in cities increases, the percentage of women
with son preference also increases. The socialisation hypothe-
sis seems to be most relevant in the relationship between mig-
ration, fertility, and SRB. The urban fertility behaviour of a
Table 2: SRB and Per centage of State d Son Prefere nce by Socio- economic
and Demog raphic Char acteristi cs in Urban Ind ia
SRB 9 5% Confiden ce Son 95% C onfiden ce
Interval Preference Interval
Lower Upper Lower Upper
Limit Limit Limit Limit
Women age
15–24 959.5 958.9 960.1 9.9 9.7 10.1
25–34 870.9 869.8 872.0 13.4 13.2 13.6
35–49 892.6 890.2 895.0 18.4 18.1 18.6
Women educati on
Illiterate 909.8 908.3 911.4 25.0 24.6 25.5
Primary 864.9 862.1 867.6 18.4 17.9 18.9
Secondary 889.3 888.2 890.3 12.1 12.0 12.3
Higher 913.8 912.4 915.1 9.2 8.9 9.4
Partner ed ucation
Illiterate 945.8 943.0 948.6 23.1 21.8 24.4
Primary 888.2 882.9 893.5 19.5 18.2 20.7
Secondary 863.4 860.4 86 6.3 14.8 14.3 15.4
Higher 974.5 973.6 975.5 10.8 10.1 11.5
Don't know/missing 894.2 893.4 895.0 13.9 13.7 14.0
Women oc cupatio n
Not working 90 6.0 904.2 907.7 13.3 13.0 13.7
White collar 798.5 785.0 812.3 11.7 10.7 12.8
Agricultural worker 978.1 975.7 980.5 20.9 18.7 23.2
Service/manual work 885. 8 879.7 892.1 14.7 13.8 15.7
Don’t know/missing 893.9 893.1 894.7 14.2 14.0 14.3
Birth ord er
First-order 912.8 911.8 913.7
Second-order 936.0 935.3 936.8
Thre e or more 8 01.5 798.7 804. 3
Urban wealth i ndex
Poorest 943.2 942.4 944.0 19.4 19.1 19.8
Poorer 867.4 865.4 869.3 15.1 14.8 15.4
Middle 924.4 923. 2 925.6 13.8 13.5 14.1
Richer 857.8 855.6 860.1 12.6 12.3 12.9
Richest 864.9 862.5 867.3 10.0 9.7 10.2
SC 881.0 879.5 882.6 11.8 11.6 12.0
ST 890.1 888.3 891.9 14.7 14.4 15.0
OBC 910.9 907.9 913.8 14.2 13.5 14.9
General 900.3 899.2 901.3 15.2 15.0 15.4
Don't know/
not reported 927.5 925.2 929.7 16.0 15.4 16.7
Hindu 893.5 892.6 894.4 13.4 13.2 13.5
Muslim 902.2 900.8 903.6 18.1 17.7 18.4
Christian 996.8 996.7 997.0 13.2 12.4 14.1
Others 803.3 795.9 810.7 9.0 8.4 9.6
Media exposure
No 932.8 931.2 934. 5 25.2 24.5 26.0
Partial 895.7 894.9 896.5 13.9 13.8 14.1
Full 861.6 858.8 864.4 10.8 10.5 11.2
Dur atio n of s tay (i n yea rs)
0–5 942.5 941.8 943.2 12.3 12.0 12.6
5–9 873.1 871.6 874.5 13.9 13.5 14.2
10+ 836.6 834.1 839.0 16.5 16.3 16.8
Native 920.6 917.6 923.5 10.7 10.4 11.0
The SRB est imates are bas ed on the fiv e-year cale ndar period 2010 –14.
Source: The N FHS-4, 2015–16.
Economic & Political Weekly EPW Janua ry 15, 2022 vol lViI no 3 53
newly arrived migrant is largely an effect of his/her previous
socialisation process and fades out with suffi cient exposure to
urban areas (Goldb erg 1959).
Determinants of Male Births
In this section, three multivariate logistic regressions have
been run to capture the socio-economic and demographic
det erminants of male birth at the fi rst three birth orders. As
per NFHS-4, the urban total fertility rate was around 1.8 births
per woman, with majority of the states having achieved
below rep lacement level fertility, with the exceptions of Uttar
Pradesh, Bihar, and Madhya Pradesh (IIPS and ICF 2017).
Women who reported a son preference have a higher likeli-
hood of conceiving a son at each birth order. The chances of
having a son at the fi rst two birth orders are relatively higher
among women who posited preference for son. Consequently,
the chances of having sons at the second and third birth
orders declined among the women who reported female pref-
erence. It is also evident that the chance of having a son at the
second and third birth order is dependent on the sex composi-
tion of the earlier children.
The study shows that women having at least one male child
in the fi rst two birth orders have a lesser likelihood of having a
son at the third birth, as compared to women who have no
male children. Women’s age is also a signifi cant determining
factor. Their chances of having a son at all three birth orders
are high in the age group of 35–49 years.
The chances of having a son declines with increasing levels of
education among women and their partners at each birth order
(Table 3). Poor women, too, have a higher likelihood of having a
son at a higher birth order. The chances of having a son at the fi rst
birth is highest among the women from large districts. However,
the chances of bearing a son at second order birth is higher
among women belonging to smaller districts. The increasing
number of male births at lower birth orders among women with
exposure to mass media indicates strong son preference. This
result corroborates the earlier fi ndings which show that women
with exposure to mass media have skewed mean SRB, despite
® Reference c ategory ; p-value: * ** < 0.01, ** < 0.05, and * < 0.1. Analysis ha s been contro lled for regi ons in India.
Table 3: Predicted Probabilities (%) of Male Birth at First Three Birth Orders in Urban India
Birth 95% CI Bir th 95% CI Birth 95% CI Birth 95% CI Birth 95% CI Birth 95% CI
Order 1 LL UL Order 2 LL UL Order 3 LL UL Order 1 LL UL Ord er 2 LL UL Ord er 3 LL UL
Sex preference
No pref eren ce ® 51. 6 51.6 51.6 4 0.2 4 0.1 40. 3 2 3.3 2 3.2 23.4
Son p re fer ence 61.9*** 61.8 61.9 47.5* 47.3 47.6 41.4 * 41.2 41. 6
pr ef er en ce 29.1* ** 29.0 29.1 2 2. 3* 22 .1 22. 5 24.5* 24.1 24.9
Sibling composi tion
One child
No male® 43.1 43.0 43.2 - - -
One male 38.7* 38.6 38.8 - - -
Tw o chi ldr en
No Male® - - - 37.6 37.4 37.8
One Male - - - 24.5* 24.4 24.6
Two male - - - 22.6* 22.5 22.8
Women age
15–24® 50.9 50.8 50.9 19.6 19.5 19.8 10.1 9.9 10.2
25–34 52.1* 52.1 52.2 38.2* 38.1 38.3 21.7* 21.5 21.8
35–49 53.7* 53.6 53.7 46.6* 46.6 46.7 31.3* 31.2 31.5
Women education
Illiterat 53.6 53.6 53.7 47.0 4 6.8 47.1 39.3 39.2 39.5
Primar y 52.4 52.3 52.5 45.2* 45.1 45.4 32.5* 32.3 32.7
Secondary 52.0** 52.0 52.1 39.8 39.7 39.9 22.7* 22.6 22.8
Higher 51.7* * 51.7 51.8 32.0 31.8 32.1 11.5* 11.4 11.6
Partner ed ucation
Illiterate® 54.0 53.8 54.3 43.5 43.0 43.9 37.2 36.6 37.8
Primary 50.8 50.6 51.1 44.5 44.0 45.0 32.3 31.7 32.9
Secondary 52.4** 52.3 52.6 40.0 39.7 40.2 25.2 25.0 25.5
Higher 52.7* 52.5 52.8 33.9 33.6 34.2 17.8 17.5 18.2
Don't know/
missing 52.2* 52.2 52.3 41.0 40.9 41.1 26.9 26.8 27.1
Women occu pation
Not wo rking® 51.7 51.7 51. 8 39.2 39. 0 39.4 26.2 25.9 26. 5
White collar 54.0** 53.7 54.2 35.6 35.1 36.1 20.0 19.3 20.7
Agricultural worker 52.8 52.4 53.2 43.9 43.1 44.6 33.8 32.8 34.7
manual work 49.5** 49.3 49.7 42.8 42.4 43.3 29.2 28.6 29.8
Don’t know/
missing 52.4 52.4 52.4 41.0 4 0.9 41.1 26.9 26.8 27.0
Use of family plannin g
Not usin g ® 50.7 50.7 50.8 33.0 32.9 33.0 25.6 25.4 25.7
Modern met hod 52.1** 52.0 52.1 36.7* 36.5 36.8 21.9 21.7 22.1
Sterilisation 56.8** 56.7 56.8 52.9* 52.8 53.0 29.9* 29.7 30.0
Traditional method 51.2** 51.1 51.3 38.2* 38. 0 38.4 26.1 25.7 26.4
Wealth Index
Poores 51. 2 51.1 51. 3 42.1 42 .0 42.3 33.9 33.7 3 4.1
Poorer 51.5 51.4 51.6 41.1 41.0 41.3 28.6* 28.4 28.8
Middle 52.7 52.6 52.7 39.9* 39.8 40.1 25.9* 25.7 26.1
Richer 52.4 52.3 52.4 40.7 4 0.5 40.8 24.0* 23.8 24.2
Richest 53.7** 53.7 53. 8 39.8 39.6 39.9 19.7* 19.5 19.9
SC® 52.2 52.1 52.3 41.9 41.7 42.1 29.7 29.5 29.9
ST 51. 2* 51.1 51. 3 4 0.0 39.8 40. 2 30.0 29. 8 30.3
OBC 52.3* 52.2 52.3 41.4 41.3 41.5 27.1* 26.9 27.2
Others 52.7** 52.7 52.8 39.8 39.7 39.9 23.9* 23.8 24.1
Don't know/
not reported 52.6* 52.5 52.8 37.6* 37.3 38.0 24.5* 24.0 24.9
Hindu® 52.4 52.4 52.5 40.7 40.6 40.7 25.1 2 5.0 25.2
Muslim 52.2 52.1 52.3 41.8* 41.6 42.0 34.3* 34.0 34.5
Christian 50.3** 50.2 50.5 40.0* 39.8 40.3 28.8* 28.5 29.1
Others 53.4 53.2 53.5 39.3* 38.9 39.6 21.3* 21.0 21.7
Media exposure
No ® 51.6 51.5 51.8 4 4.1 43.8 44.4 37.0 36 .7 37.4
Partial 52.4 52.4 52.4 40.9* 40.8 41.0 26.9 26.8 27.0
Full 51.9 51. 8 51.9 37.6 37.4 37.8 18.9* 18.7 19.2
Dur atio n of s tay (i n yea rs)
0–5 ® 51.8 51.7 51.8 2 9.1 28 .9 29.2 20.4 20.2 20 .6
5–9 52.9* 52.8 53.0 38.9* 38.8 39.1 19.3 19.1 19.5
10+ 52.8* 52.7 52.8 47.0* 47.0 47.1 31.1* 31.0 31.3
Native 51.3* 51.2 51.3 39.4* 39.1 39.6 27.8* 27.4 28. 2
District size class
Less than
0.1 m illi on® 51.5 51.4 51.6 39.6 39.4 39.8 27.5 27.2 27.7
0.1–0.5 million 52.3 52.3 52.4 41.0*** 40.9 41.1 27.9 27.7 28.1
0.5–1 million 52.6 52.6 52.7 41.4 41.2 41.5 26.8 26.6 27.0
1–5 million 52.2** 52.2 52.3 40.8* 40.6 4 0.9 25.7 25.5 25.9
5 million a nd
above 54.0** 53.7 54.2 36.2* 35.7 36. 8 23.4 22.7 24.1
January 15 , 2022 vol lViI no 3 EPW Economic & Political Weekly
their low stated son preference (Javed and Mughal 2018). It also
shows that women might offer socially acceptable answers in
terms of birth preferences, although they actually bear sons.
Native women have the least likelihood of having a son at the
rst birth, which dramatically increases in second and higher
order births. For women who are sterilised, the likelihood of
having a son at all three birth orders is higher compared to
women using other family planning methods. Hindus have
relatively higher chances of having a son at fi rst birth, whereas
Muslims have a higher probability of having a son at second
and third order births. This fi nding supports the stated son
preferences among Muslim women (Table 2), which indicates
that Muslim women show higher son preference and higher
chances of having a son at later birth orders. Further, women from
OBC and other s c ategories have higher cha nces of havi ng a s on
at fi rst and second birth orders. However, STs and SCs have
higher chances of having a son at the third birth order. Across
geographical regions, the likelihood of a son at fi rst birth order
is higher among women in the northern region, followed by the
western region. The chances of having a son in the second and
third order births are higher in the northern and central region.
The macro-level analysis points to a gradual worsening of SR B
in urban areas, highlighting the legacy of patriarchal norms.
At disaggregated levels, SRB has deteriorated monotonically,
except the southern and north–eastern states which reported
an urban SRB higher than the national average.
The analysis reveals that the urban SR B has worsened, not
only among women who have certain stated preference for
sons, but also among women who posited neutral views. Expo-
sure to mass media has sensitised urban dwellers against vari-
ous forms of discrimination and restrictive laws. This has had
a huge impact on the reporting pattern of gender bias but has,
unfortunately, not matched with actual behaviour.
It is often surmised that the reported ideal number of chil-
dren might be infl uenced by the actual number of living sons
and daughters (Pande and Astone 2007). The likelihood of
giving birth to a son at the second and third birth orders is
affected by the previous sex composition of children. Surpris-
ingly, with the progression towards bigger districts, the gap in
the use of contraception widens between women who show
son preference and those who do not. Also, the poorest class
have the most favourable mean SRB, which declines system-
atically with the richest wealth quintile as the rich can afford
to access sex determination technologies and sex-selective
abortions. Ironically, wealthier households have lower pro-
portion of women with stated son preference and respond to
questions on son preference with more socially desirable
answers. Conversely, poor households tend to state their true
preferences, yet exceptionally avail sex-selective abortions.
In the present study, severely distorted SRBs in the presence
of high meta-preference for sons, makes it evident that daugh-
ters are still not welcome in urban societies. The widespread
campaign around PCPNDT Act, 1994, has created awareness
about the criminal offences related to the sex determination
test and the elimination of female foetuses through abortion.
However, in practice, it has not been widely practised, espe-
cially in peri-urban areas where urban regulations are relaxed,
calling for the strengthening of governance mechanisms in
city peripheries. The rapid advancement in medical techno-
logy has also made it easier and more affordable to seek sex
determination and the termination of pregnancies. The regis-
tration and monitoring of pregnancies can be an ameliorative
step in this regard. Similarly, imparting appropriate gender-
sensitive education and promoting attitudinal changes to treat
daughters at par with sons by providing proper nutrition, edu-
cation, skill training, and working opportunities as well as
access to resources, wou ld also lead to a more balanced SRB in
the cities.
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This paper examines trends and estimated sex ratio at birth (SRB) for India and child mortality (q5) risk, 1981 and 1991, and discusses how the 2001 Census results are foreshadowed. Earlier state-level (rural vs urban) analyses are extended to present these data at the district level in the form of maps. Multivariate statistical analyses exploring social and economic covariates that affect the likelihood of gender bias in death (female disadvantage in child mortality risk) have been conducted. The female disadvantage is evident in birth and death spread over India in the decade 1981-1991. Though infant and child mortality levels fell for girls and boys, gender differences persisted, and penetrated the hitherto egalitarian south. Masculine SRB that were seen only in urban areas of the north-west in 1981 have spread to urban areas of many northern states in 1991. Multivariate analyses suggest that between 1981-1991, women's status variables become less associated with reduced gender bias. Modernisation variables suggest less association with gender bias, or that a substitution of pre-natal for post-natal elimination of unwanted daughters may be occurring. These findings are situated in the literature on gender, education, paid work participation, and marriage system changes in India.
This study analyses the effects of observed preference for boys on Pakistani women’s participation in household decision-making. We find a significant association between female participation in various household decisions and their preference for boys. Bearing at least one son is associated with 5 per cent, 7 per cent, and 5 per cent higher say in decisions involving healthcare, social, and consumption matters, respectively. Women’s role in financial affairs, however, does not change significantly. Female participation in decision-making grows with the number of sons but only up to third parity. The improvement in female participation remains limited and decision- or context-specific.
Many women in rural South India either postpone or avoid adopting family planning because of their preferences for the birth of a child of a particular sex, according to analyses of data from four cross-sectional surveys that were conducted between 1985 and 1990 and from eight evaluation surveys of sterilization and IUD acceptors that were conducted between 1982 and 1989. Overall, couples prefer families composed of at least one son and one daughter, but in areas where contraceptive prevalence rates are high, most couples have two sons, with or without a daughter, before they initiate contraceptive use; in low-prevalence areas, couples most often have two sons and one daughter before beginning to practice family planning. In the absence of sex preference, contraceptive prevalence rates could be expected to increase by about 12% in high-prevalence areas and by around 25% in low-prevalence areas; in both areas, levels of marital fertility could be expected to decline by about 20% from current levels.
In this paper it is argued that in studies of urban fertility, the relationship between socio-economic variables and fertility has been obscured by the presence of rural migrants in the populations under investigation. Accordingly, data obtained from families of completed fertility in six probability samples of metropolitan Detroit are divided into two groups, farm migrants and two-generation urbanites.In general, the socio-economic differences in fertility observed among the “pure” urban types in Detroit are found to be small and inconsistent, most of them being statistically insignificant. The inverse fertility pattern found in the total Detroit population is attributed to : (a) the overrepresentation of farm migrants (who have high fertility) in the lowest social and economic positions in the city, and (b) the pronounced inverse pattern of fertility among the farm migrants.It is suggested that the absence of an inverse fertility pattern among twogeneration urbanites and its presence among the farm migrants can be attributed to differences in family organization.
With an emphasis on decentralised planning in India, the district has become the primary unit of planning and monitoring development programmes. The Census of India is the only source providing useful demographic information at the district and administrative levels below it. The findings of this study indicate that India is undergoing a fertility transition, yet around one-third of districts have a birth rate of 25 or more. High fertility districts have shown a faster pace of decline. Furthermore, around a quarter of the districts are characterised by a very low implied sex ratio at birth, of less than 900. Spatial analysis reveals a contiguous pattern of low ratios in the north-western part of the country and emerging pockets in Maharashtra and Gujarat followed by Orissa.
Data from the 2001 Census reveal that the sex ratio at birth may have increased by 6 percentage points in India since 1985, and in some parts by 20 percentage points. Data from the National Family Health Survey of 1998-99 show that while the use of prenatal diagnostic techniques has become fairly common only a minority misuses them for aborting female foetuses. The effect of PNDT use on the sex ratio at birth is found to be contingent on whether women are in the male-selection situation (i e, with at least one previous birth but have had no sons) or not. While income and education are found to increase the use of PNDT, their misuse is governed more by cultural factors and the sex composition of children already born.
Preference for sons over daughters, evident in China's and South Asia's male sex ratios, is commonly rationalized by poverty and the need for old-age support. In this article we study South and East Asian immigrants to Canada, a group for whom the economic imperative to select sons is largely absent. Analyzing the 2001 and 2006 censuses, 20 percent samples, we find clear evidence of extensive sex selection in favor of boys at higher parities among South and East Asian immigrants unless they are Christian or Muslim. The latter finding accords with the explicit prohibition against (female) infanticide—traditionally the main sex-selection method—in these religions. Our findings point to a strong cultural component to both the preference for sons and the willingness to resort to induced abortion based on sex.
The main states of India are broadly grouped into two demographic regimes. In contrast to states in the north, southern states are characterized by lower marital fertility, later age at marriage, lower infant and child mortality and comparatively low ratios of female to male infant and child mortality. The division between the two regimes broadly coincides with the division between areas of northern kinship/low female autonomy and southern kinship/high female autonomy. The analysis suggests that female social status is probably the most important element in comprehending India's demographic situation. Women in the south tend to be more active in the labor force, are more likely to take innovative action in adopting fertility control, and are more apt to utilise health services for themselves and their children.-Authors