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Is sex ratio at birth an appropriate measure of prenatal sex selection? Findings of a theoretical model and its application to India
  1. Sylvie Dubuc1,
  2. Devinderjit Singh Sivia2
  1. 1 Department of Geography, University of Reading, Reading, UK
  2. 2 Saint John’s College, University of Oxford, Oxford, UK
  1. Correspondence to Dr Sylvie Dubuc; s.dubuc{at}reading.ac.uk

Abstract

Son preference and prenatal sex selection against females have resulted in significant sex ratio at birth (SRB) imbalances well documented in several Asian countries, including India and China. The SRB bias is generally used as indicator for the extent and trends of prenatal sex selection against females. Decreasing fertility levels are expected to increase sex selection and thus SRB bias, since desiring fewer children increases the risk for families to remain sonless (fertility squeeze effect). We developed and employ mathematical models linking family size, birth order and childbearing strategies with population SRB bias. We show that SRB bias can increase despite fewer sex selection interventions occurring, inconsistent with the expectation of the fertility squeeze effect. We show that a disproportionality effect of fertility reduction amplifies SRB bias, in addition to the fertility squeeze effect, making SRB bias an inaccurate indicator for changes in sex selection practices within a population. We propose to use sex selection propensity (proportion of couples intervening) to measure behavioural change and evaluate policies targeting sex selection practices. We apply our findings to India, showing for instance that sex selection propensity in Punjab and Delhi was lower than in Rajasthan or Uttar Pradesh, despite significantly higher SRB bias in the former. While we observe a continuous overall increase in the SRB over the 2005–2010 period in India, our results indicate that prenatal sex selection propensity started declining during that period.

  • mathematical modelling
  • maternal health
  • medical demography
  • public health
  • health policy

This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

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Footnotes

  • Handling editor Seye Abimbola

  • Contributors SD oversaw the research, conceived the conceptual model, conducted Indian data analysis and wrote the paper. DSS conceived and developed the mathematical models, and contributed to writing of the paper.

  • Funding This work was supported by grants to SD from the UK Economic and Social Research Council (ES/N01877X/1), the Nuffield Foundation (Grant CPF/37731) and the University of Oxford, Social Sciences Division, Returning Carers’ Fund 2015.

  • Competing interests None declared.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement No additional data are available.