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Systematic assessment of the sex ratio at birth for all countries and estimation of national imbalances and regional reference levels [1]

['Chao', 'Gerland', 'Cook', 'Alex R.', 'Alkema', 'Fengqing Chao', 'Patrick Gerland', 'Alex R. Cook', 'Leontine Alkema', 'Authors Info']

Date: 2019-04-09  

We describe a method for probabilistic and reproducible estimation of the sex ratio at birth (SRB; ratio of male to female live births) for all countries, with a focus on assessing the SRB reference levels (which we henceforth term “baseline level”) and SRB imbalance due to sex-selective abortion.

Under normal circumstances, SRB varies in a narrow range around 1.05, with only a few known variations among ethnic groups ( 1 13 ). For most of human history, SRB remained within that natural range. However, over recent decades, SRBs have risen in a number of Asian countries and in eastern Europe ( 14 30 ). The increasing imbalance in SRB is due to a combination of three main factors that lead to sex-selective abortion ( 22 24 ). Firstly, most societies with abnormal SRB inflation have persisting strong son preference, which provides the motivation. Secondly, since the 1970s, prenatal sex diagnosis and access to sex-selective abortion have become increasingly available ( 31 35 ), providing the method. Thirdly, fertility has fallen to low levels around the world that resulted in a “squeezing effect”: attaining both the desired small families and the ideal sex composition by resorting to sex selection ( 22 ). Consequently, sex-selective abortion provides a means to avoid large families while still having male offspring. Necessary conditions for the occurrence of sex-selective abortions include a large tolerance for induced abortion from both the population and the medical establishment, available techniques for early sex detection, and legal medical abortion for several weeks after onset of pregnancy ( 36 ).

Estimation of the degree of SRB imbalance is complicated by the amount of uncertainty associated with SRB observations due to data quality issues and sampling errors. While the United Nations (UN) Population Division publishes estimates for all countries in the World Population Prospects (WPP), its estimates are deterministic and depend on expert-based opinions which are not reproducible ( 37 ). Although modeling and simulation studies of the SRB have been carried out for selected countries ( 38 40 ), these studies did not estimate the SRB and its natural fluctuations; instead, SRB estimates were taken from the UN WPP. A recent assessment by the Global Burden of Disease Study 2017 ( 41 ) produced estimates for 195 countries based on 8,936 country-years of data but does not assess baseline values or imbalances. An up-to-date systematic analysis for the SRB—one of the most fundamental demographic indicators—for all countries over time using all available data with reproducible estimation method is urgently needed.

To fill the research void, we develop model-based estimates for 212 countries (referring to populations that are considered as “countries” or “areas” in the UN classification) from 1950 to 2017. Our analyses are based on a comprehensive database on national-level SRB with data from vital registration (VR) systems, censuses, and international and national surveys. In total, we have 10,835 observations, equivalent to 16,602 country-years of information, in our database from 202 countries. We implement two Bayesian hierarchical models to estimate SRBs in two types of country-years: (i) those that are not affected by sex-selective abortion and (ii) those that may be affected by sex-selective abortion that leads to SRB imbalances.

In the model for country-years not affected by sex-selective abortion, the SRB is given by the product of a baseline value and a country-year-specific multiplier that accounts for natural fluctuation around the baseline value. We allow baseline values to differ across countries within a region, and across regions, to incorporate SRB differences due to ethnic origin ( 1 13 ). Hence, for this purpose, regions refer to groupings of countries based on their dominant ethnic group ( SI Appendix, Table S17 ). For example, we group countries in Europe, North America, Australia, and New Zealand to refer to the regional grouping of countries with a majority of Caucasians. Within each country and region, we assume that the baseline value is constant over time.

The model for natural fluctuations in the SRB is fitted to the global database after excluding data from country-years that may have been affected by masculinization of the SRB. We use inclusive criteria to identify such country-years, based on a combination of qualitative and quantitative approaches. We select countries with at least one of the following manifestations of son preference: (i) a high level of desired sex ratio at birth (DSRB), (ii) a high level of sex ratio at last birth (SRLB), or (iii) strong son preference or inflated SRB suggested by a literature review. The earliest start for the sex ratio inflation is set to 1970, which is when sex-selective abortions first became available.

We parametrize SRB inflation during a sex ratio transition using a trapezoid to allow for consecutive phases of increase, stagnation, and a decrease back to zero. We incorporate the fertility squeeze effect by using the total fertility rate [TFR, obtained from the UN WPP 2017 ( 37 )] into the model to inform the start year of SRB inflation. Parameters are estimated with a Bayesian hierarchical model ( 42 ) to share information across countries about the inflation start year, the maximum inflation, and the length of inflation period during the three phases.

To quantify the effect of SRB imbalance due to sex-selective abortion, we calculate the annual number of missing female births (AMFB) and the cumulative number of missing female births (CMFB) over time. AMFB is defined as the difference between the number of female live births based on SRB without inflation and the number of female live births based on SRB with inflation. CMFB for a certain period is the sum of AMFB over the period. We define countries with strong evidence of SRB inflation to be those countries with at least 1 y with at least 95% probability of a positive number of missing female births (AMFB > 0).

Results The compiled database, annual estimates for national, regional, and global SRB during 1950–2017, and national AMFB during 1970–2017 are available in Datasets S1–S4 . The SRB estimates for selected years by country are in SI Appendix, Table S20 Global and Regional SRB Estimates. The global and regional SRB median estimates and 95% uncertainty intervals in 1990 and 2017 are presented in Fig. 1 and Table 1 . Globally, the SRB in 2017 is 1.068 (95% uncertainty interval, [1.059; 1.077]). Levels and trends vary across regions. In 2017, the regional-level estimated SRBs range from 1.032 [1.026; 1.039] in sub-Saharan Africa to 1.133 [1.076; 1.187] in eastern Asia. Fig. 1. Global and regional SRB estimates in 1990 and 2017, and regional baseline values of SRB. Dots indicate median estimates, and horizontal lines refer to 95% uncertainty intervals. Regional baseline values are in dark green, where the vertical line segments refer to median estimates, and green shaded areas are 95% uncertainty intervals. Table 1. Global and regional SRB in 1990, 2000, and 2017 SRB Change of SRB World, region Baseline value 1990 2000 2017 1990–2000 2000–2017 1990–2017 World — 1.073 1.078 1.068 0.005 −0.010 −0.005 [1.064; 1.081] [1.071; 1.085] [1.059; 1.077] [−0.001; 0.013] [−0.018; −0.002] [−0.014; 0.005] southern Asia 1.052 1.084 1.097 1.086 0.014 −0.011 0.002 [1.040; 1.063] [1.066; 1.102] [1.079; 1.116] [1.066; 1.107] [0.005; 0.022] [−0.024; 0.003] [−0.011; 0.017] ENAN 1.058 1.055 1.055 1.054 0.001 −0.001 −0.001 [1.055; 1.061] [1.054; 1.056] [1.054; 1.056] [1.051; 1.057] [−0.001; 0.002] [−0.005; 0.002] [−0.004; 0.003] northern Africa 1.050 1.057 1.056 1.056 −0.002 −0.001 −0.002 [1.036; 1.064] [1.043; 1.072] [1.042; 1.070] [1.037; 1.079] [−0.009; 0.006] [−0.013; 0.020] [−0.015; 0.019] sub-Saharan Africa 1.031 1.037 1.035 1.032 −0.002 −0.002 −0.005 [1.027; 1.036] [1.031; 1.043] [1.029; 1.041] [1.026; 1.039] [−0.007; 0.002] [−0.007; 0.003] [−0.010; 0.001] Latin America and 1.041 1.045 1.045 1.044 0.000 −0.001 −0.001 the Caribbean [1.037; 1.045] [1.037; 1.053] [1.036; 1.053] [1.036; 1.053] [−0.007; 0.007] [−0.009; 0.008] [−0.009; 0.008] western Asia 1.050 1.055 1.056 1.053 0.002 −0.003 −0.001 [1.044; 1.056] [1.045; 1.064] [1.048; 1.064] [1.044; 1.063] [−0.006; 0.009] [−0.011; 0.006] [−0.011; 0.008] Caucasus and central Asia 1.062 1.065 1.077 1.075 0.012 −0.003 0.010 [1.050; 1.075] [1.056; 1.074] [1.070; 1.085] [1.065; 1.084] [0.005; 0.020] [−0.011; 0.006] [0.001; 0.019] southeastern Asia 1.063 1.067 1.068 1.073 0.001 0.005 0.006 [1.055; 1.072] [1.059; 1.076] [1.060; 1.077] [1.061; 1.086] [−0.008; 0.010] [−0.007; 0.017] [−0.007; 0.018] eastern Asia 1.063 1.115 1.157 1.133 0.042 −0.024 0.018 [1.054; 1.072] [1.080; 1.147] [1.128; 1.189] [1.076; 1.187] [0.009; 0.083] [−0.081; 0.029] [−0.043; 0.079] Oceania 1.067 1.068 1.068 1.067 0.000 0.000 −0.001 [1.058; 1.077] [1.048; 1.088] [1.046; 1.089] [1.045; 1.089] [−0.014; 0.014] [−0.017; 0.016] [−0.019; 0.017] Median estimates are numbers before the brackets. Numbers in the brackets are 95% uncertainty intervals. —, the model does not estimate a global baseline value. Between 1990 and 2017, the change in the global SRB is not statistically significant. For the same period, none of the regional estimated SRBs have significant reductions, while Caucasus and central Asia have an increase at 0.010 [0.001; 0.019]. Between 1990 and 2000, the increase in global SRB is at 0.005 [−0.001; 0.013]. During 1990–2000, the increases on regional SRB are significantly above zero in eastern Asia at 0.042 [0.009; 0.083], southern Asia at 0.014 [0.005; 0.022], and Caucasus and central Asia at 0.012 [0.005; 0.020]. Between 2000 and 2017, the changes of SRB are not significant for any regions. However, on a global level, the decrease of SRB during 2000–2017 is significantly below zero at −0.010 [−0.018; −0.002]. The regional SRB baseline values range from 1.031 [1.027; 1.036] in sub-Saharan Africa to 1.063 [1.055; 1.072] in southeastern Asia, 1.063 [1.054; 1.072] in eastern Asia, and 1.067 [1.058; 1.077] in Oceania ( Table 1 and Fig. 1 ). When comparing to the conventional value of 1.05 for SRB baseline adopted by the UN WPP ( 37 ), the regional baseline values differ significantly from 1.05 for 6 out of 10 regions: significantly above 1.05 for “ENAN” (the combination of countries in Europe, North America, Australia, and New Zealand), southeastern Asia, eastern Asia, and Oceania and significantly below 1.05 for sub-Saharan Africa and Latin America and the Caribbean. In 2017, the aggregated SRB in three regions (southern Asia, Caucasus and central Asia, and eastern Asia) are significantly above their corresponding regional baseline median estimates. In 1990, the aggregated regional-level SRB in southern Asia and eastern Asia are significantly above their regional baseline median estimates. National SRB Estimates Case Studies. We illustrate SRB estimates for 12 countries which are identified to have strong statistical evidence of SRB inflation. The SRB median estimates and 95% uncertainty intervals for the 12 countries are shown in Table 2 and Fig. 2 . TFR estimates are overlaid onto SRB estimates in Fig. 2 , to illustrate the relationship between the start year of SRB inflation period and fertility decline, as incorporated into the model to estimate the start year of inflation period. Table 2. SRB results for countries with strong statistical evidence of SRB inflation SRB Year Country Region Start year Max 2017 Start inflation Max India southern Asia 1.061 1.113 1.098 1975 1995 [1.035; 1.087] [1.090; 1.137] [1.071; 1.124] [1970; 1981] Albania ENAN 1.079 1.127 1.083 1988 2006 [1.058; 1.101] [1.104; 1.150] [1.054; 1.113] [1973; 1997] Montenegro ENAN 1.056 1.099 1.072 1980 1997 [1.031; 1.084] [1.067; 1.130] [1.045; 1.100] [1971; 1991] Tunisia northern Africa 1.057 1.085 1.054 1982 2000 [1.034; 1.080] [1.061; 1.108] [1.028; 1.081] [1976; 1989] Armenia Caucasus and central Asia 1.059 1.176 1.117 1992 2000 [1.034; 1.084] [1.150; 1.203] [1.087; 1.149] [1990; 1993] Azerbaijan Caucasus and central Asia 1.068 1.171 1.134 1991 2003 [1.041; 1.095] [1.145; 1.197] [1.097; 1.168] [1988; 1994] Georgia Caucasus and central Asia 1.063 1.115 1.065 1992 2003 [1.034; 1.098] [1.090; 1.141] [1.039; 1.092] [1977; 1994] Vietnam southeastern Asia 1.076 1.126 1.122 2001 2012 [1.052; 1.099] [1.089; 1.171] [1.070; 1.186] [1991; 2005] China eastern Asia 1.073 1.179 1.143 1981 2005 [1.047; 1.103] [1.141; 1.221] [1.079; 1.205] [1972; 1989] Hong Kong, SAR of China eastern Asia 1.082 1.157 1.078 2004 2011 [1.066; 1.098] [1.140; 1.174] [1.059; 1.098] [2002; 2005] Republic of Korea eastern Asia 1.072 1.151 1.056 1982 1990 [1.052; 1.092] [1.131; 1.171] [1.034; 1.078] [1978; 1984] Taiwan, Province of China eastern Asia 1.069 1.100 1.076 1982 2004 [1.060; 1.079] [1.090; 1.110] [1.065; 1.087] [1972; 1987] Countries are presented by region. Median estimates are numbers before brackets. Numbers in brackets are 95% uncertainty intervals. SRB “Max” refers to the maximum SRB after inflation starts. Year “Max” refers to the year in which the maximum SRB is after inflation starts. Fig. 2. SRB estimates during 1950–2017 for countries with strong statistical evidence of SRB inflation. The scale on the left y axis refers to SRB, and the scale on the right y axis refers to TFR. Red lines and shaded areas are country-specific SRB median estimates and their 95% uncertainty intervals. Dark green horizontal lines are median estimates for regional SRB baselines. Light green horizontal lines are median estimates for national SRB baselines. Observations from different data series are differentiated by colors, where VR data are black solid dots. The blue square dots are the UN WPP 2017 TFR estimates. Blue vertical lines indicate median estimates for start and end years (if before 2017) of SRB inflation period. TFR values in the start years of SRB inflation periods are shown. Among the 12 countries, 9 are from Asian regions (Caucasus and central Asia, eastern Asia, southeastern Asia, and southern Asia). TFR values at the start of sex ratio transitions vary across countries. As shown in Fig. 2 , India is a country with a high TFR value of 5.2 at the start of its inflation period in 1975, while SRB inflation is estimated to start in Vietnam in 2001 when its TFR declined to 2.0 and in Hong Kong, SAR of China in 2004 with a TFR at 1.0. Since the start of the inflation, SRBs reached their maximum before 2017 for all 12 countries. During the sex ratio transitions, SRB reached its maximum after 2000 in 9 countries. The earliest maximum occurred in Republic of Korea in 1990, and the latest occurred in Vietnam in 2012. The highest median estimates of in-country maximum SRB since the start of inflation are in China (1.179 [1.141; 1.221] in 2005), Armenia (1.176 [1.150; 1.203] in 2000), Azerbaijan (1.171 [1.145; 1.197] in 2003), Hong Kong, SAR of China (1.157 [1.140; 1.174] in 2011), and Republic of Korea (1.151 [1.131; 1.171] in 1990). The SRBs have converged back to the range of natural fluctuations in 2007 for Republic of Korea, in 2013 for Hong Kong (SAR of China), and in 2016 for Georgia. By 2017, the lowest SRBs among the 12 countries are 1.054 [1.028; 1.081] in Tunisia and 1.056 [1.034; 1.078] in Republic of Korea, while the highest are 1.134 [1.097; 1.168] in Azerbaijan and 1.143 [1.079; 1.205] in China. Missing Female Births Estimates. From 1970 to 2017, the total CMFB for the 12 countries with strong statistical evidence of SRB inflation is 23.1 [19.0; 28.3] million ( Table 3 and Fig. 3 ). The majority of CMFB between 1970 and 2017 are concentrated in China, with 11.9 [8.5; 15.8] million, and in India, with 10.6 [8.0; 13.6] million. The CMFB between 1970 and 2017 in China and India made up 51.40% [41.28%; 61.28%] and 45.94% [36.09%; 55.83%], respectively, of the total CMFB. Table 3. CMFB for periods 1970–1990, 1991–2000, 2001–2017, and 1970–2017, for countries with strong statistical evidence of SRB inflation CMFB (thousands) Proportion of the total CMFB, % Country (region) 1970–1990 1991–2000 2001–2017 1970–2017 1970–1990 1991–2000 2001–2017 1970–2017 India 2,190 3,379 5,062 10,632 56.58 47.22 41.79 45.94 (S.A.) [1,058; 3,736] [2,426; 4,362] [3,488; 6,667] [7,972; 13,597] [28.97; 94.09] [36.51; 58.53] [31.46; 53.06] [36.09; 55.83] Albania 0 4 7 11 0.00 0.05 0.06 0.05 (ENAN) [0; 7] [1; 7] [5; 9] [6; 21] [0.00; 0.20] [0.01; 0.11] [0.04; 0.08] [0.03; 0.09] Montenegro 0 1 1 2 0.01 0.01 0.01 0.01 (ENAN) [0; 1] [0; 1] [1; 2] [1; 4] [0.00; 0.05] [0.00; 0.02] [0.00; 0.01] [0.01; 0.02] Tunisia 5 13 19 37 0.13 0.19 0.15 0.16 (N.A.) [0; 13] [6; 20] [9; 29] [20; 56] [0.01; 0.43] [0.08; 0.30] [0.07; 0.26] [0.08; 0.25] Armenia 0 6 14 19 0.00 0.08 0.11 0.08 (C.C.A.) [0; 0] [5; 7] [11; 16] [16; 23] [0.00; 0.00] [0.06; 0.11] [0.08; 0.15] [0.07; 0.11] Azerbaijan 0 15 56 72 0.00 0.21 0.47 0.31 (C.C.A.) [0; 1] [10; 22] [47; 66] [59; 85] [0.00; 0.03] [0.13; 0.33] [0.36; 0.63] [0.24; 0.40] Georgia 0 6 6 12 0.00 0.08 0.05 0.05 (C.C.A.) [0; 5] [4; 8] [4; 10] [8; 19] [0.00; 0.13] [0.05; 0.12] [0.03; 0.09] [0.03; 0.09] Vietnam 0 0 254 254 0.00 0.00 2.10 1.10 (S.E.A.) [0; 0] [0; 47] [140; 400] [143; 409] [0.00; 0.00] [0.00; 0.64] [1.13; 3.50] [0.60; 1.82] China 1,617 3,622 6,656 11,895 41.76 50.60 54.95 51.40 (E.A.) [81; 3,899] [2,426; 4,800] [4,423; 8,953] [8,504; 15,780] [3.13; 69.42] [38.99; 61.27] [43.25; 65.33] [41.28; 61.28] Hong Kong, SAR of China 0 0 7 7 0.00 0.00 0.06 0.03 (E.A.) [0; 0] [0; 0] [5; 9] [5; 9] [0.00; 0.00] [0.00; 0.00] [0.04; 0.08] [0.02; 0.04] Republic of Korea 50 91 14 155 1.30 1.27 0.12 0.67 (E.A.) [36; 82] [73; 111] [5; 31] [122; 206] [0.68; 3.06] [0.94; 1.73] [0.04; 0.27] [0.49; 0.95] Taiwan, Province of China 9 21 17 47 0.22 0.29 0.14 0.20 (E.A.) [2; 25] [10; 30] [7; 29] [23; 73] [0.04; 0.73] [0.13; 0.45] [0.06; 0.25] [0.10; 0.33] Countries are presented by region. Median estimates are the numbers before the brackets. Numbers inside the brackets are the 95% uncertainty intervals. Proportions may not sum up to 100%, due to rounding. S.A., southern Asia; N.A., northern Africa; C.C.A., Caucasus and central Asia; S.E.A., southeastern Asia; E.A., eastern Asia. Fig. 3. SRB in 2017 and the CMFB during 1970–2017, by country. Countries are colored by the levels of their SRB median estimates. Radii of circles are proportional to CMFB for countries. For high-resolution plot of Fig. 3, see SI Appendix, section 11.

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[1] Url: https://www.pnas.org/content/early/2019/04/09/1812593116

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