Trends in missing females at birth in India from 1981 to 2016: analyses of 2·1 million birth histories in nationally representative surveys
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Bibliographic record
Abstract
BACKGROUND: Half of the world's missing female births occur in India, due to sex-selective abortion. It is unknown whether selective abortion of female fetuses has changed in recent years across different birth orders. We sought to document the trends in missing female births, particularly among second and third children, at national and state levels. METHODS: We examined birth histories from five nationally representative household surveys (National Family Health Surveys 1-4 and District Level Household Survey 2) to compute the conditional sex ratio (defined as the number of girls born per 1000 boys depending on previous birth sex) in India during 1981-2016. We estimated decadal variation in conditional sex ratio for 1987-96, 1997-2006, and 2007-16, and quantified trends in the numbers of missing female births for the states constituting >95% of India's population, as well as in 5-year intervals for each survey round. We used multivariate logistic regression to calculate the odds ratio of a second (or third) girl depending on the sex of the earlier child (or children), adjusting for education, wealth, religion, caste, and place of residence. FINDINGS: We assessed 2·1 million birth histories across the five surveys. Applying the conditional sex ratios from the surveys to national births, we found that 13·5 million female births were missing during the three decades of observation (1987-2016), on the basis of a natural sex ratio of 950 girls per 1000 boys. Missing female births increased from 3·5 million in 1987-96 to 5·5 million in 2007-16. Contrasting the conditional sex ratio from the first decade of observation (1987-96) to the last (2007-16) showed worsening for the whole of India and almost all states, among both birth orders. Punjab, Haryana, Gujarat, and Rajasthan had the most skewed sex ratios, comprising nearly a third of the national totals of missing second-born and third-born females at birth. From about 1986, the conditional sex ratio for second-order or third-order births after an earlier daughter or daughters diverged notably from that after an earlier son or sons. From 1981 to 2016, the sex ratio for second-born children after an earlier daughter decreased from 930 (99% CI 869-990) to 885 (859-912), and that for third-born children after two earlier daughters decreased from 968 (866-1069) to 788 (746-830). The probability of missing girls was mostly determined by earlier daughters, even after considering wealth quintile and education levels. The conditional sex ratio among the richest and most educated mothers was most distorted compared with lower wealth and education groups, and generally decreased with time, until a modest improvement in 2007-16. INTERPRETATION: In contrast to the substantial improvements in female child mortality in India, missing female births, driven by selective abortion of female fetuses, continues to increase across the states. Inclusion of a question on sex composition of births in the forthcoming census would provide local information on sex-selective abortion in each village and urban area of the country. FUNDING: None. TRANSLATION: For the Hindi translation of the abstract see Supplementary Materials section.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it