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Related Experiment Videos

Maternal mortality in India: an update.

P N Mari Bhat1

  • 1Population Research Centre, Institute of Economic Growth, Delhi 110 007, India. mari@ieg.ernet.in

Studies in Family Planning
|October 19, 2002
PubMed
Summary

This study estimates maternal mortality in India using two indirect methods, finding variations between them but consistency with direct estimates for the 1990s. It highlights socioeconomic and temporal differences in maternal deaths.

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Area of Science:

  • Demography
  • Public Health
  • Epidemiology

Background:

  • Maternal mortality remains a critical public health issue in India.
  • Accurate estimation of maternal mortality is essential for effective policy interventions.
  • Indirect estimation methods offer valuable insights where direct data is limited.

Purpose of the Study:

  • To estimate maternal mortality in India using two indirect methods: the sisterhood method and a regression method based on sex differentials in adult mortality.
  • To compare these estimates with existing data from various sources.
  • To explore socioeconomic, spatial, and temporal variations in maternal mortality.

Main Methods:

  • Sisterhood method applied to 1994 rural human development survey data.
  • Regression method using India's Sample Registration System (SRS) mortality and fertility data.
  • Comparison with direct estimates from National Family Health Survey (NFHS) and SRS.

Main Results:

  • Sisterhood method yielded maternal mortality estimates approximately 15% lower for the early 1980s compared to the regression method.
  • Regression method estimates for the 1990s showed consistency with direct estimates from NFHS and SRS.
  • Analysis revealed socioeconomic differentials and spatial/temporal variations in maternal mortality.

Conclusions:

  • Indirect methods provide valuable, albeit sometimes differing, estimates of maternal mortality in India.
  • The regression method appears more consistent with direct estimates for recent periods.
  • Understanding variations is crucial for targeted maternal health strategies.

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