Excess under-5 female mortality across India: a spatial analysis using 2011 census data

Guilmoto, C.Z., Saikia, N. ORCID: https://orcid.org/0000-0001-6735-6157, Tamrakar, V., & Bora, J.K. (2018). Excess under-5 female mortality across India: a spatial analysis using 2011 census data. Lancet Global Health 6 650-658. 10.1016/S2214-109X(18)30184-0.

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Abstract

Background Excess female mortality causes half of the missing women (estimated deficit of women in countries with suspiciously low proportion of females in their population) today. Globally, most of these avoidable deaths of women occur during childhood in China and India. We aimed to estimate excess female under-5 mortality rate (U5MR) for India’s 35 states and union territories and 640 districts.

Methods Using the summary birth history method (or Brass method), we derived district-level estimates of U5MR by sex from 2011 census data. We used data from 46 countries with no evidence of gender bias for mortality to estimate the effects and intensity of excess female mortality at district level. We used a detailed spatial and statistical analysis to highlight the correlates of excess mortality at district level.

Findings Excess female U5MR was 18·5 per 1000 livebirths (95% CI 13·1–22·6) in India 2000–2005, which corresponds to an estimated 239 000 excess deaths (169 000–293 000) per year. More than 90% of districts had excess female mortality, but the four largest states in northern India (Uttar Pradesh, Bihar, Rajasthan, and Madhya Pradesh) accounted for two-thirds of India’s total number. Low economic development, gender inequity, and high fertility were the main predictors of excess female mortality. Spatial analysis confirmed the strong spatial clustering of postnatal discrimination against girls in India.

Interpretation The considerable effect of gender bias on mortality in India highlights the need for more proactive engagement with the issue of postnatal sex discrimination and a focus on the northern districts. Notably, these regions are not the same as those most affected by skewed sex ratio at birth.

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