Maternal and Child Nutrition (Apr 2022)

Critical assessment of the current indicator for antenatal iron‐containing supplementation coverage: Insights from a mixed‐methods study

  • Aatekah Owais,
  • Sara Wuehler,
  • Rebecca Heidkamp,
  • Vrinda Mehra,
  • Lynnette M. Neufeld,
  • Lisa M. Rogers,
  • Kuntal Kumar Saha

DOI
https://doi.org/10.1111/mcn.13314
Journal volume & issue
Vol. 18, no. 2
pp. n/a – n/a

Abstract

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Abstract Daily consumption of iron‐containing supplements is recommended for all pregnant women but there is no approved global standard indicator for assessing supplementation coverage. Furthermore, the validity of commonly used coverage indicators for iron‐containing supplement consumption is questionable. The WHO–UNICEF Technical Expert Advisory Group on Nutrition Monitoring, and partners, have systematically worked to identify a feasible and valid indicator of iron‐containing supplement coverage for reporting by countries. In 2019, we conducted key informant interviews with respondents in eight countries, fielded an online survey (in three languages using SurveyMonkey) to which 142 nutrition professionals from 52 countries responded, and used Demographic and Health Surveys (DHS) data from four countries to assess determinants of the quality of iron‐containing supplement coverage data. Less than half (45%) of online survey respondents were satisfied with the current methods for collecting iron‐containing supplement coverage data in their context. Recommended changes by study respondents include recall period <5 years, adding questions about counselling, including other beneficiary groups, and assessing supply chain functionality. The DHS analysis suggested an association between time since pregnancy and data quality. Data heaping on multiples of 30 was observed in 40%–75% of data. There is a clear demand for a revised indicator and measurement guidance for coverage of iron‐containing supplementation during pregnancy. Future research should continue the development and validation of a global indicator, to more precisely validate the quality of recall data, including the distinction between distribution and consumption using various question formulations.

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