Sex differences in mortality among children, adolescents, and young people aged 0-24 years: a systematic assessment of national, regional, and global trends from 1990 to 2021.

BACKGROUND: Differences in mortality exist between sexes because of biological, genetic, and social factors. Sex differentials are well documented in children younger than 5 years but have not been systematically examined for ages 5-24 years. We aimed to estimate the sex ratio of mortality from birth to age 24 years and reconstruct trends in sex-specific mortality between 1990 and 2021 for 200 countries, major regions, and the world. METHODS: We compiled comprehensive databases on the mortality sex ratio (ratio of male to female mortality rates) for individuals aged 0-4 years, 5-14 years, and 15-24 years. The databases contain mortality rates from death registration systems, full birth and sibling histories from surveys, and reports on household deaths in censuses. We modelled the sex ratio of age-specific mortality as a function of the mortality in both sexes using Bayesian hierarchical time-series models. We report the levels and trends of sex ratios and estimate the expected female mortality and excess female mortality rates (the difference between the estimated female mortality and the expected female mortality) to identify countries with outlying sex ratios. FINDINGS: Globally, the mortality sex ratio was 1·13 (ie, boys were more likely to die than girls of the same age) for ages 0-4 years (90% uncertainty interval 1·11 to 1·15) in 2021. This ratio increased with age to 1·16 (1·12 to 1·20) for 5-14 years, reaching 1·65 for 15-24 years (1·52 to 1·75). In all age groups, the global sex ratio of mortality increased between 1990 and 2021, driven by faster declines in female mortality. In 2021, the probability of a newborn male reaching age 25 years was 94·1% (93·7 to 94·4), compared with 95·1% for a newborn female (94·7 to 95·3). We found a disadvantage of females versus males (compared with countries with similar total mortality) in 2021 in five countries for ages 0-4 years (Algeria, Bangladesh, Egypt, India, and Iran), one country (Suriname) for ages 5-14 years, and 13 countries for ages 15-24 years (including Bangladesh and India). We found the reverse pattern (disadvantage of males vs females compared with countries of similar total mortality) in one country in ages 0-4 years (Vietnam) and eight countries in ages 15-24 years (including Brazil and Mexico). Globally, the number of excess female deaths from birth to age 24 years was 86 563 (-6059 to 164 000) in 2021, down from 544 636 (453 982 to 633 265) in 1990. INTERPRETATION: The global sex ratio of mortality for all age groups in the first 25 years of life increased between 1990 and 2021. Targeted interventions should focus on countries with outlying sex ratios of mortality to reduce disparities due to discrimination in health care, nutrition, and violence. FUNDING: The Bill & Melinda Gates Foundation, US Agency for International Development, and King Abdullah University of Science and Technology.

Estimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach.

BACKGROUND: The sex ratio at birth (SRB; ratio of male to female births) in Nepal has been reported around the normal level on the national level. However, the national SRB could mask the disparity within the country. Given the demographic and cultural heterogeneities in Nepal, it is crucial to model Nepal SRB on the subnational level. Prior studies on subnational SRB in Nepal are mostly based on reporting observed values from surveys and census, and no study has provided probabilistic projections. We aim to estimate and project SRB for the seven provinces of Nepal from 1980 to 2050 using a Bayesian modeling approach. METHODS: We compiled an extensive database on provincial SRB of Nepal, consisting 2001, 2006, 2011, and 2016 Nepal Demographic and Health Surveys and 2011 Census. We adopted a Bayesian hierarchical time series model to estimate and project the provincial SRB, with a focus on modelling the potential SRB imbalance. RESULTS: In 2016, the highest SRB is estimated in Province 5 (Lumbini Pradesh) at 1.102, corresponding to 110.2 male births per 100 female births, with a 95% credible interval (1.044, 1.127) and the lowest SRB is in Province 2 at 1.053 (1.035, 1.109). The SRB imbalance probabilities in all provinces are generally low and vary from 16% in Province 2 to 81% in Province 5 (Lumbini Pradesh). SRB imbalances are estimated to have begun at the earliest in 2001 in Province 5 (Lumbini Pradesh) with a 95% credible interval (1992, 2022) and the latest in 2017 (1998, 2040) in Province 2. We project SRB in all provinces to begin converging back to the national baseline in the mid-2030s. By 2050, the SRBs in all provinces are projected to be around the SRB baseline level. CONCLUSIONS: Our findings imply that the majority of provinces in Nepal have low risks of SRB imbalance for the period 1980-2016. However, we identify a few provinces with higher probabilities of having SRB inflation. The projected SRB is an important illustration of potential future prenatal sex discrimination and shows the need to monitor SRB in provinces with higher possibilities of SRB imbalance.

Projecting sex imbalances at birth at global, regional and national levels from 2021 to 2100: scenario-based Bayesian probabilistic projections of the sex ratio at birth and missing female births based on 3.26 billion birth records.

INTRODUCTION: Skewed levels of the sex ratio at birth (SRB) due to sex-selective abortions have been observed in several countries since the 1970s. They will lead to long-term sex imbalances in more than one-third of the world's population with yet unknown social and economic impacts on affected countries. Understanding the potential evolution of sex imbalances at birth is therefore essential for anticipating and planning for changing sex structures across the world. METHODS: We produced probabilistic SRB projections from 2021 to 2100 based on different scenarios of sex ratio transition and assessed their implications in terms of missing female births at global, regional and national levels. Based on a comprehensive SRB database with 3.26 billion birth records, we project the skewed SRB and missing female births with a Bayesian hierarchical time series mixture model. The SRB projections under reference scenario S1 assumed SRB transitions only for countries with strong statistical evidence of SRB inflation, and the more extreme scenario S2 assumed a sex ratio transition for countries at risk of SRB inflation but with no or limited evidence of ongoing inflation. RESULTS: Under scenario S1, we projected 5.7 (95% uncertainty interval (1.2; 15.3)) million additional missing female births to occur by 2100. Countries affected will be those already affected in the past by imbalanced SRB, such as China and India. If all countries at risk of SRB inflation experience a sex ratio transition as in scenario S2, the projected missing female births increase to 22.1 (12.2; 39.8) million with a sizeable contribution of sub-Saharan Africa. CONCLUSION: The scenario-based projections provide important illustrations of the potential burden of future prenatal sex discrimination and the need to monitor SRBs in countries with son preference. Policy planning will be needed in the years to come to minimise future prenatal sex discrimination and its impact on social structures.

Sex ratio at birth in Vietnam among six subnational regions during 1980-2050, estimation and probabilistic projection using a Bayesian hierarchical time series model with 2.9 million birth records.

The sex ratio at birth (SRB, i.e., the ratio of male to female births) in Vietnam has been imbalanced since the 2000s. Previous studies have revealed a rapid increase in the SRB over the past 15 years and the presence of important variations across regions. More recent studies suggested that the nation's SRB may have plateaued during the 2010s. Given the lack of exhaustive birth registration data in Vietnam, it is necessary to estimate and project levels and trends in the regional SRBs in Vietnam based on a reproducible statistical approach. We compiled an extensive database on regional Vietnam SRBs based on all publicly available surveys and censuses and used a Bayesian hierarchical time series mixture model to estimate and project SRB in Vietnam by region from 1980 to 2050. The Bayesian model incorporates the uncertainties from the observations and year-by-year natural fluctuation. It includes a binary parameter to detect the existence of sex ratio transitions among Vietnamese regions. Furthermore, we model the SRB imbalance using a trapezoid function to capture the increase, stagnation, and decrease of the sex ratio transition by Vietnamese regions. The model results show that four out of six Vietnamese regions, namely, Northern Midlands and Mountain Areas, Northern Central and Central Coastal Areas, Red River Delta, and South East, have existing sex imbalances at birth. The rise in SRB in the Red River Delta was the fastest, as it took only 12 years and was more pronounced, with the SRB reaching the local maximum of 1.146 with a 95% credible interval (1.129, 1.163) in 2013. The model projections suggest that the current decade will record a sustained decline in sex imbalances at birth, and the SRB should be back to the national SRB baseline level of 1.06 in all regions by the mid-2030s.

Probabilistic projection of the sex ratio at birth and missing female births by State and Union Territory in India.

The sex ratio at birth (SRB) in India has been reported to be imbalanced since the 1970s. Previous studies have shown there is a great variation in the SRB between geographic locations across India till 2016. Considering the enormous population and regional heterogeneity of India, producing probabilistic SRB projections at the state level is crucial for policy planning and population projection. In this paper, we implement a Bayesian hierarchical time series model to project the SRB across India by state. We generate SRB probabilistic projections from 2017 to 2030 for 29 States and Union Territories (UTs) in India, and present results for 21 States/UTs with data available from the Sample Registration System. Our analysis takes into account two state-specific factors that contribute to sex-selective abortion in India, resulting in sex imbalances at birth: the intensity of son preference and fertility squeeze. We project that the highest deficits in female births will occur in Uttar Pradesh, with a cumulative number of missing female births of 2.0 (95% credible interval [1.9; 2.2]) million from 2017 to 2030. The total female birth deficits during 2017-2030 for the whole of India is projected to be 6.8 [6.6; 7.0] million.

On the estimation of female births missing due to prenatal sex selection.

This research note is prompted by a paper by Kashyap (Is prenatal sex selection associated with lower female child mortality? Population Studies 73(1): 57-78). Kashyap's paper, which provides 40 original estimates of missing female births, relies on an alternative definition of missing female births, leading to estimates of about half the magnitude of other estimates. There appears, therefore, a real need to take stock of the concept of missing female births widely used by statisticians around the world for assessing the demographic consequences of prenatal sex selection. This research note starts with a brief review of the history of the concept and the difference between Amartya Sen's original method and the alternative method found elsewhere to compute missing female births. We then put forward three different arguments (deterministic and probabilistic approaches, and consistency analysis) in support of the original computation procedure based on the number of observed male births and the expected sex ratio at birth.

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

The sex ratio at birth (SRB; ratio of male to female live births) imbalance in parts of the world over the past few decades is a direct consequence of sex-selective abortion, driven by the coexistence of son preference, readily available technology of prenatal sex determination, and fertility decline. Estimation of the degree of SRB imbalance is complicated because of unknown SRB reference levels and because of the uncertainty associated with SRB observations. There are needs for reproducible methods to construct SRB estimates with uncertainty, and to assess SRB inflation due to sex-selective abortion. We compile an extensive database from vital registration systems, censuses and surveys with 10,835 observations, and 16,602 country-years of information from 202 countries. We develop Bayesian methods for SRB estimation for all countries from 1950 to 2017. We model the SRB regional and national reference levels, the fluctuation around national reference levels, and the inflation. The estimated regional reference levels range from 1.031 (95% uncertainty interval [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. We identify 12 countries with strong statistical evidence of SRB imbalance during 1970-2017, resulting in 23.1 [19.0; 28.3] million missing female births globally. The majority of those missing female births are in China, with 11.9 [8.5; 15.8] million, and in India, with 10.6 [8.0; 13.6] million.

National and regional under-5 mortality rate by economic status for low-income and middle-income countries: a systematic assessment.

BACKGROUND: The progress to achieve the fourth Millennium Development Goal in reducing mortality rate in children younger than 5 years since 1990 has been remarkable. However, work remains to be done in the Sustainable Development Goal era. Estimates of under-5 mortality rates at the national level can hide disparities within countries. We assessed disparities in under-5 mortality rates by household economic status in low-income and middle-income countries (LMICs). METHOD: We estimated country-year-specific under-5 mortality rates by wealth quintile on the basis of household wealth indices for 137 LMICs from 1990 to 2016, using a Bayesian statistical model. We estimated the association between quintile-specific and national-level under-5 mortality rates. We assessed the levels and trends of absolute and relative disparity in under-5 mortality rate between the poorest and richest quintiles, and among all quintiles. FINDINGS: In 2016, for all LMICs (excluding China), the aggregated under-5 mortality rate was 64·6 (90% uncertainty interval [UI] 61·1-70·1) deaths per 1000 livebirths in the poorest households (first quintile), 31·3 (29·5-34·2) deaths per 1000 livebirths in the richest households (fifth quintile), and in between those outcomes for the middle quintiles. Between 1990 and 2016, the largest absolute decline in under-5 mortality rate occurred in the two poorest quintiles: 77·6 (90% UI 71·2-82·6) deaths per 1000 livebirths in the poorest quintile and 77·9 (72·0-82·2) deaths per 1000 livebirths in the second poorest quintile. The difference in under-5 mortality rate between the poorest and richest quintiles decreased significantly by 38·8 (90% UI 32·9-43·8) deaths per 1000 livebirths between 1990 and 2016. The poorest to richest under-5 mortality rate ratio, however, remained similar (2·03 [90% UI 1·94-2·11] in 1990, 1·99 [1·91-2·08] in 2000, and 2·06 [1·92-2·20] in 2016). During 1990-2016, around half of the total under-5 deaths occurred in the poorest two quintiles (48·5% in 1990 and 2000, 49·5% in 2016) and less than a third were in the richest two quintiles (30·4% in 1990, 30·5% in 2000, 29·9% in 2016). For all regions, differences in the under-5 mortality rate between the first and fifth quintiles decreased significantly, ranging from 20·6 (90% UI 15·9-25·1) deaths per 1000 livebirths in eastern Europe and central Asia to 59·5 (48·5-70·4) deaths per 1000 livebirths in south Asia. In 2016, the ratios of under-5 mortality rate in the first quintile to under-5 mortality rate in the fifth quintile were significantly above 2·00 in two regions, with 2·49 (90% UI 2·15-2·87) in east Asia and Pacific (excluding China) and 2·41 (2·05-2·80) in south Asia. Eastern and southern Africa had the smallest ratio in 2016 at 1·62 (90% UI 1·48-1·76). Our model suggested that the expected ratio of under-5 mortality rate in the first quintile to under-5 mortality rate in the fifth quintile increases as national-level under-5 mortality rate decreases. INTERPRETATION: For all LMICs (excluding China) combined, the absolute disparities in under-5 mortality rate between the poorest and richest households have narrowed significantly since 1990, whereas the relative differences have remained stable. To further narrow the rich-and-poor gap in under-5 mortality rate on the relative scale, targeted interventions that focus on the poorest populations are needed. FUNDING: National University of Singapore, UN Children's Fund, United States Agency for International Development, and the Bill & Melinda Gates Foundation.

National, regional, and global sex ratios of infant, child, and under-5 mortality and identification of countries with outlying ratios: a systematic assessment.

BACKGROUND: Under natural circumstances, the sex ratio of male to female mortality up to the age of 5 years is greater than one but sex discrimination can change sex ratios. The estimation of mortality by sex and identification of countries with outlying levels is challenging because of issues with data availability and quality, and because sex ratios might vary naturally based on differences in mortality levels and associated cause of death distributions. METHODS: For this systematic analysis, we estimated country-specific mortality sex ratios for infants, children aged 1-4 years, and children under the age of 5 years (under 5s) for all countries from 1990 (or the earliest year of data collection) to 2012 using a Bayesian hierarchical time series model, accounting for various data quality issues and assessing the uncertainty in sex ratios. We simultaneously estimated the global relation between sex ratios and mortality levels and constructed estimates of expected and excess female mortality rates to identify countries with outlying sex ratios. FINDINGS: Global sex ratios in 2012 were 1·13 (90% uncertainty interval 1·12-1·15) for infants, 0·95 (0·93-0·97) for children aged 1-5 years, and 1·08 (1·07-1·09) for under 5s, an increase since 1990 of 0·01 (-0·01 to 0·02) for infants, 0·04 (0·02 to 0·06) for children aged 1-4 years, and 0·02 (0·01 to 0·04) for under 5s. Levels and trends varied across regions and countries. Sex ratios were lowest in southern Asia for 1990 and 2012 for all age groups. Highest sex ratios were seen in developed regions and the Caucasus and central Asia region. Decreasing mortality was associated with increasing sex ratios, except at very low infant mortality, where sex ratios decreased with total mortality. For 2012, we identified 15 countries with outlying under-5 sex ratios, of which ten countries had female mortality higher than expected (Afghanistan, Bahrain, Bangladesh, China, Egypt, India, Iran, Jordan, Nepal, and Pakistan). Although excess female mortality has decreased since 1990 for the vast majority of countries with outlying sex ratios, the ratios of estimated to expected female mortality did not change substantially for most countries, and worsened for India. INTERPRETATION: Important differences exist between boys and girls with respect to survival up to the age of 5 years. Survival chances tend to improve more rapidly for girls compared with boys as total mortality decreases, with a reversal of this trend at very low infant mortality. For many countries, sex ratios follow this pattern but important exceptions exist. An explanation needs to be sought for selected countries with outlying sex ratios and action should be undertaken if sex discrimination is present. FUNDING: The National University of Singapore and the United Nations Children's Fund (UNICEF).