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Related Experiment Videos

Measuring sterility from incomplete birth histories.

U Larsen1, J Menken

  • 1Department of Statistics, University of Lund, Sweden.

Demography
|May 1, 1989
PubMed
Summary

This study introduces new methods for measuring sterility using incomplete birth histories. Fertility estimates after a certain age proved more reliable than traditional measures, offering better insights into reproductive health patterns.

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Area of Science:

  • Demography
  • Reproductive Health
  • Statistical Modeling

Background:

  • Assessing sterility is crucial for understanding population dynamics and reproductive health.
  • Incomplete birth histories from demographic surveys present challenges for accurate sterility measurement.
  • Existing methods, like the open birth interval, have limitations.

Purpose of the Study:

  • To develop and evaluate methods for measuring sterility and its age pattern from incomplete reproductive histories.
  • To compare the robustness of new estimation techniques against traditional measures.

Main Methods:

  • Simulation study to assess method characteristics under varying conditions.
  • Analysis of World Fertility Survey data from sub-Saharan Africa.
  • Estimation of sterility levels and age patterns using fertility data subsequent to a given age.

Main Results:

  • Estimates based on fertility subsequent to a given age are more robust to variations in reproductive determinants, sample size, and sampling variation.
  • Sterility levels varied significantly across sub-Saharan African countries: high in Cameroon, intermediate in Lesotho and Sudan, and low in Ghana and Kenya.
  • Comparison with an English historical population provided a reference for relative sterility levels.

Conclusions:

  • The proposed methods offer a more reliable approach to measuring sterility from incomplete birth histories.
  • Significant regional variations in sterility exist within sub-Saharan Africa, highlighting the need for context-specific reproductive health strategies.
  • These findings contribute to a better understanding of reproductive health indicators in demographic research.

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