From 1970 to 2010, an estimated 105 million females (births and all age groups) were missing in China (62 million) and India (43 million), the world’s two most populous countries (Bongaarts and Guilmoto, 2015). China and India account for 90% of the annual 1.2–1.5 million missing female births globally (Bongaarts and Guilmoto, 2015; Chao et al., 2019; UNFPA, 2020). Until the 1980s, the main driver of missing females was an excess of female deaths attributable to infanticide and negligence towards female children (Kumar and Sinha, 2019). Since about 1985, ultrasound-enabled prenatal sex determination followed by selective abortion of female fetuses has become the main method for families to enact strong existing cultural preferences for sons (Bongaarts and Guilmoto, 2015; Tabaie, 2017). Selective abortion of female fetuses is driven mostly by son preference but also, in the case of China, the imposition of a ‘one-child’ policy for most of China’s population which began in 1980 and officially ended only in 2016 (Ebenstein, 2010; Feng et al., 2016).

Examining sex ratio patterns among the diaspora sheds light on the differences between Indian and Chinese practices inside and outside the home countries. There are an estimated 18 million Indian and 10 million Chinese male and female diaspora as of 2020 (United Nations Population Division, 2021). Much of the migration from India and China has been to Australia, Canada, the United Kingdom (UK), and the United States (US).

Within India, selective abortion is uncommon with first births. However, a significant minority of families with a first daughter will turn to the practice so as to secure at least one son (Jha et al., 2006; Jha et al., 2011; Saikia et al., 2021). In China, a limited number of ethnic minorities and rural areas were granted exemption to the one-child policy means, which allows examination of selective abortion for the fewer second-order births. To quantify the impacts of selective abortion, we apply the conditional sex ratio (CSR) method, which examines the variation in second or third births in relation to the sex of the earlier child(ren) (Jha et al., 2011; Saikia et al., 2021). The sex of subsequent children is independent of the first and biological factors, which may affect overall sex ratio, should not vary by birth order (Jha et al., 2006). In the absence of sex selection, there is a slight deficit of girls compared to boys (i.e., a CSR of <1000) for biological reasons, leading to a ‘natural’ sex ratio of 950–975 girls per 1000 boys, a ratio observed consistently over decades in societies where selective abortion is rare (Chao et al., 2019; Guilmoto, 2007; Hesketh and Xing, 2006).

Here, we quantify the trends in CSRs among Asian diaspora populations, particularly among Indians and Chinese. We evaluated CSR trends for Indians and Chinese in home countries and among the diasporas in Australia, Canada, the UK, and the US using census data and representative samples of birth histories over two decades from 1999 to 2019.

The study included 18.4 million children aged 14 and below. Of these, 1.03 million were births in India and China. Most births in China were first (65%) and second (28%) born children with few third order births (5%) in all survey years (Table 1). In India, about 34% and 29% of all births were first and second births, respectively, and 17% were third born. About 1.1 million were births within the Indian (663,397) and Chinese (429,702) diasporas in Australia, Canada, the UK, and the US, with similar proportionate distributions for first (India 57%; China 60%), second (36%; 34%), and third order births (7%; 6%). Asian diasporas from Bangladesh, Pakistan, Hong Kong, Sri Lanka, and South Korea added 837,234 total births with 50% first, and 35% second born children. Overall, 55% of all study births were first born children and 39% were second born or third born, among whom the effects of conditional sex selection can be best observed. All CSR estimates for births in this study are shown in Supplementary file 1A-1E.

Mothers born in India

For women born in India and giving birth in India or in Canada, Australia, the UK, or the US, the sex ratio for first births remained stable within the natural range (950–975) excepting minor deviations in India in 1999 and 2016, where the CSRs favoured more boys, at 932 and 931 girls per 1000 boys, respectively (Figure 1; Panel A). CSRs for second order births with an earlier son were also close to the natural range with a slight upward trend in India from 953 (1999) to 986 (2016). For the Indian diaspora, CSRs were mostly within the natural range for second order births with an earlier son except for the US where they fluctuated (Supplementary file 1D).

Figure 1

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By contrast, for second and third order births with an earlier daughter or daughters, the CSRs favoured boys, being significantly below the natural range for births in all countries. For second births with an earlier daughter, the Indian diaspora in Canada had the lowest CSR (859 girls per 1000 boys) in 2001. By 2016, CSRs were largely unchanged in Australia (888), Canada (882), and India (866). For the UK and the US, CSRs were 923 (2011) and 898 in (2019), respectively.

The CSRs for third order births with two previous daughters deviated even further from the natural range in all countries and were lower in the diaspora than in India (769) itself. Canada had the lowest CSRs (540–520 girls per 1000 boys) between 2001 and 2016 for this birth order and between 2011 and 2016 in Australia, CSRs declined from 770 to 653 girls per 1000 boys. The 2019 figure from the US suggested the beginning of a possible trend towards the normal range but was based on relatively small numbers of births (Table 2).

Table 2

		Mother’s ethnicity/ancestry		Indian			Chinese
Country (Year)		Birth order and sex of previous child	Male	Female	Sex Ratio	Male	Female	Sex Ratio
	Mother’s country of birth			India			China
Australia
		Second born, one earlier daughter	1267	1129	891	2017	1889	937
2001		Third born, two earlier daughters	155	116	748	214	181	846
		Second born, one earlier daughter	1592	1399	879	2428	2341	964
2006		Third born, two earlier daughters	167	127	760	241	212	880
		Second born, one earlier daughter	3061	2680	876	2904	2731	940
2011		Third born, two earlier daughters	261	201	770	282	252	894
		Second born, one earlier daughter	7419	6590	888	5271	4664	885
2016		Third born, two earlier daughters	596	389	653	421	334	793
	Mother’s country of birth			India			China
Canada
		Second born, one earlier daughter	618	531	859	451	463	1027
2001		Third born, two earlier daughters	137	74	540	62	56	903
		Second born, one earlier daughter	12275	10825	882	8370	7855	938
2016		Third born, two earlier daughters	2085	1085	520	810	710	877
	Mother’s country of birth			India			China
UK
		Second born, one earlier daughter	6049	5515	912	465	424	912
2001		Third born, two earlier daughters	1192	1009	846	60	47	783
		Second born, one earlier daughter	8378	7730	923	1366	1263	925
2011		Third born, two earlier daughters	1280	996	778	179	173	966
	Mother’s country of birth			India			China
US
		Second born, one earlier daughter	930	815	876	710	553	779
2000		Third born, two earlier daughters	182	100	549	109	83	761
		Second born, one earlier daughter	398	362	910	292	274	938
2004		Third born, two earlier daughters	68	42	618	42	42
		Second born, one earlier daughter	1613	1521	943	1105	1094	990
2009		Third born, two earlier daughters	244	139	570	173	135	780
		Second born, one earlier daughter	1997	1947	975	1374	1250	910
2014		Third born, two earlier daughters	274	163	595	212	156	736
		Second born, one earlier daughter	2650	2381	898	1640	1524	929
2019		Third born, two earlier daughters	210	169	805	238	186	782

1. Example of CSR computation for Australia 2001 among Indian mother, parity 2: total births = 2396. Pf = 1129/2396=0.47, CSR = (0.47/(1–0.47)*1000=891). For parity 3: total = 271 pf = 116/271=0.43, CSR = (0.43/(1–0.43)*1000=748). Due to rounding of Pf value, CSR values may differ slightly.

Asian diasporas and domestic population

In Australia, Canada, the UK and the US, we contrasted the CSRs for second and third order births preceded by one or two earlier daughters among domestic-born mothers to the CSRs among diasporas of mothers born in China or India. (Figure 2). The CSRs for both birth orders were consistently within or close to the natural range of 950–975 for Australians, Canadians, the UK, and White Americans. In contrast, CSRs for the Chinese and Indian diasporas in each of these four countries deviated from the natural range for both birth orders with a more pronounced decline for third order births.

Figure 2

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The CSRs for third order births with previous daughters among the Indian diaspora in all countries were substantially lower than for the Chinese diaspora, particularly in Canada where they also varied widely between second and third births for Indian women.

As a further check to see if the patterns among Indian-born mothers reflected subtle, but unmeasured biases in migration patterns, we did a further comparison of mothers born in India to those born in other South Asian countries in the UK, where migration from various South Asian countries is sufficiently common to assess such differences (Figure 3). Between the Indian diaspora and other Asian diasporas with a significant presence in the UK (Figure 3; Supplementary file 1C), the Indian diaspora had lower CSRs for both birth orders (second and third with previous daughters) compared to diasporas from Sri Lanka, Pakistan, and Bangladesh. CSRs for other Asian diasporas showed movement toward the natural range from 2001 to 2011 while CSRs for the Indian diaspora declined.

Figure 3

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We explored the patterns and trends of CSRs among home and diaspora populations of India and China. Depressed CSRs, suggesting missing girls at birth that arose almost all from selective abortion (Almond et al., 2013; Almond and Edlund, 2008; Almond and Sun, 2017; Brar et al., 2017; Edvardsson et al., 2018; Edvardsson et al., 2021; Howell et al., 2017; Jha et al., 2011; Saikia et al., 2021; Urquia et al., 2016), were observed for both Indian and Chinese populations, particularly for second and third order births following an earlier daughter or two earlier daughters. Among Indian women, CSRs were lower for third than second order births, and, surprisingly, were more pronounced in the diaspora population compared to India. Similarly, CSRs for third order births deviated more from the natural range than for second order births among women born in China. However, CSRs for second order births with either a previous son or daughter in China were more distorted compared to the Chinese diaspora. We showed evidence that selective abortion of male fetuses following a first-born boy occurs in China, along with the more commonly expected patterns of selective abortion of female fetuses following a first-born girl. We observed too few third order births in China to derive stable CSRs for comparison with the diaspora populations, among whom we documented low CSRs for third births. CSRs for second and third order births with earlier daughter(s) were lower for Indian than Chinese-born women in the diaspora.

Our findings were consistent with other studies showing similar CSR levels for India (Jha et al., 2006; Jha et al., 2011; Saikia et al., 2021). In Canada, the lowest CSRs were among Indians for third order births with two earlier daughters (Almond et al., 2013; Brar et al., 2017). This disproportion remained even without consideration of the sex composition of previous births, highlighting distorted sex ratios at third order births among Indian born mothers (Urquia et al., 2016). Sex ratios favouring boys were also observed for higher order births among Indian and Chinese born mothers in Australia (Edvardsson et al., 2018; Edvardsson et al., 2021) and the US (Almond and Edlund, 2008; Almond and Sun, 2017; Howell et al., 2017).

In the three decades from 1987 to 2016, about 13.5 million girls were missing at birth India, worsening the already distorted population sex ratio (Saikia et al., 2021), while China is estimated to have 23.1 million missing girls at birth from 1970 to 2017 (Chao et al., 2019). These deviations, indicating prenatal sex selection (Bongaarts and Guilmoto, 2015; Saikia et al., 2021), remain a major concern as entrenched cultural preferences, ineffective government policies, falling fertility rates, and the availability of modern prenatal sex determination technology facilitate the practice of sex-selective abortions.

Until 2016, China’s stringent one-child policy (1979–2015; with allowances for a second child under specific conditions) spurred sex selection even with policies prohibiting sex-selective abortions. The rise of CSRs from 1999 to 2015 for first births in China may be due to the relaxation of the one-child policy (Ouyang, 2013). However, China’s one-child policy alone did not likely cause prenatal sex selection. Related factors such as delays in getting married and starting a family, changes in economic circumstances, and the demands of urbanization have also contributed to a decrease in fertility in China (Almond et al., 2019).

Numerous interventions to halt sex-selective abortions have had varying degrees of success in India and China (Guo et al., 2016). India banned the use of prenatal technologies in its 1994 Pre-Conception and Prenatal Diagnostic Techniques Act (Tabaie, 2017), expanded cash transfer schemes for the birth of girls and raised public awareness. China’s large public gender equity campaigns (Hesketh et al., 2011; Kumar and Sinha, 2019), such as ‘Care for Girls’, monitored families suspected of practicing sex selection, especially those allowed to have a second child after an earlier daughter (Kumar and Sinha, 2019). Across Asia, regional and social variations drive the masculinized population (Guilmoto, 2007). Unlike India and China, Bangladesh and Pakistan had little evidence of selection (Bongaarts and Guilmoto, 2015) and our study showed their diaspora populations in the UK with rising CSRs towards the natural range in contrast to India. Notably, measures in the Republic of Korea effectively brought the once skewed sex ratios close to the natural range (Bongaarts and Guilmoto, 2015; Hesketh and Xing, 2006; Kumar and Sinha, 2019; UNFPA, 2020).

The Indian diaspora had the most skewed CSR compared to the local population in India. This may be due to the high-quality healthcare services and easier access to abortion, particularly for immigrants with greater economic resources than in India. Canada, for instance, has a large share of foreign-born persons and has mostly unrestricted access to abortion (Almond et al., 2013). This may explain the low CSRs in Canada compared to the US, Australia, and the UK. For Chinese women, CSRs for second order births were more distorted in China than in the diaspora. This may indicate a weaker influence of cultural preference for sons for the latter while emphasizing the impact of China’s one-child policy on fertility choices.

The stark consequence of prenatal sex selection plagues Asia with an excess of males who may never find brides. In China, unmarried sons may become burdens for their aging parents while families with daughters are incentivized to increase bride prices and select rich suitors. This could explain the spike in female births after a first son in China, for those permitted to have more than one child. People leaving China may do so to have more children, including girls (Basten and Verropoulou, 2013), and this might suggest that the observed CSRs at higher-order births among Chinese diaspora were closer to normal than might otherwise be expected. By contrast, Indian migrants are unlikely to migrate because of fertility restrictions, and the observed CSRs reflect the strong preference for boys even among migrants. As third order births are a relatively small contribution to overall birth totals in all countries and given that intermarriage rates between diaspora and non-diasporas are common (Livingston and Brown, 2017; Yang and Bohm-Jordan, 2018), Western countries do not face the profound demographic deficits of women as do India and China.

Our analyses were limited by the CHNS data, which were collected for select provinces in China. Given the varying local and provincial child policies during the study period, the estimated CSRs may not represent China at the national level. In addition, the skewed CSRs may be a result of underreporting of girls. However, the use of census and nationally representative survey data strengthen the findings of the study, and underreporting should not vary greatly by birth order. As discussed extensively earlier (Jha et al., 2011; Saikia et al., 2021), the CSR has some limitations, and is by definition a crude measure of selective abortion. Nonetheless it is unaffected by the factors that may reduce overall fertility. Finally, small numbers of observed births in some strata suggest caution in interpreting overall trends. The statistical uncertainty in any point estimate is wide, but the overall patterns over time should not be materially affected by the random variation in births per calendar year. We do not show confidence intervals for the CSRs, as the absolute numbers of births in the main comparisons are sufficiently large (Table 1) such that they would generate unjustifiably narrow confidence intervals. Moreover, the main uncertainty is not their point estimate, but their variation from the expected natural range, which is independent of birth order.

Overall, prenatal selection for sons prevails because of unchanging beliefs, cultural norms, most notably among Indians, and government policies - notably within China. Our data suggest that Indian diaspora have more depressed CSRs than do Chinese, largely reflecting strong boy preference that is portable across countries. Indeed, our study should help promote a debate as to why son preference leading to selective abortion of girls is far more widespread among Indians than Chinese. There is a need to raise public awareness about this issue and advocate for daughters in India and China where persistent deficits of girls aborted before birth may result in profound long-term social consequences.

Data are publicly available except for Canada, UK and Australia, which are available through the respective census bureaus. For China and India, data can be found on https://www.cpc.unc.edu/projects/china and https://dhsprogram.com/Countries/Country-Main.cfm?ctry_id=57&c=India after a free registration on both websites. A short proposal is also required to support data request from the DHS program.

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Author details

1. Catherine Meh

   Centre for Global Health Research, Unity Health Toronto and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

   Contribution

   Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2476-8439

2. Prabhat Jha

   Centre for Global Health Research, Unity Health Toronto and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   Prabhat.jha@utoronto.ca

   Competing interests

   Reviewing editor, eLife

   "This ORCID iD identifies the author of this article:" 0000-0001-7067-8341

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