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Biases in Survey Estimates of Neonatal Mortality: Results From a Validation Study in Urban Areas of Guinea-Bissau

Author

Listed:
  • Stéphane Helleringer

    (New York University - Abu Dhabi)

  • Li Liu

    (Johns Hopkins University)

  • Yue Chu

    (The Ohio State University)

  • Amabelia Rodrigues

    (Bandim Health Project)

  • Ane Barent Fisker

    (Bandim Health Project
    University of Southern Denmark)

Abstract

Neonatal deaths (occurring within 28 days of birth) account for close to one-half of all deaths among children under age 5 worldwide. In most low- and middle-income countries, data on neonatal deaths come primarily from household surveys. We conducted a validation study of survey data on neonatal mortality in Guinea-Bissau (West Africa). We used records from an urban health and demographic surveillance system (HDSS) that monitors child survival prospectively as our reference data set. We selected a stratified sample of 599 women aged 15–49 among residents of the HDSS and collected the birth histories of 422 participants. We cross-tabulated survey and HDSS data. We used a mathematical model to investigate biases in survey estimates of neonatal mortality. Reporting errors in survey data might lead to estimates of the neonatal mortality rate that are too high, which may limit our ability to track progress toward global health objectives.

Suggested Citation

  • Stéphane Helleringer & Li Liu & Yue Chu & Amabelia Rodrigues & Ane Barent Fisker, 2020. "Biases in Survey Estimates of Neonatal Mortality: Results From a Validation Study in Urban Areas of Guinea-Bissau," Demography, Springer;Population Association of America (PAA), vol. 57(5), pages 1705-1726, October.
  • Handle: RePEc:spr:demogr:v:57:y:2020:i:5:d:10.1007_s13524-020-00911-6
    DOI: 10.1007/s13524-020-00911-6
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    References listed on IDEAS

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    1. Kenneth Hill & Yoonjoung Choi, 2006. "Neonatal mortality in the developing world," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 14(18), pages 429-452.
    2. Haws, Rachel A. & Mashasi, Irene & Mrisho, Mwifadhi & Schellenberg, Joanna Armstrong & Darmstadt, Gary L. & Winch, Peter J., 2010. ""These are not good things for other people to know": How rural Tanzanian women's experiences of pregnancy loss and early neonatal death may impact survey data quality," Social Science & Medicine, Elsevier, vol. 71(10), pages 1764-1772, November.
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    4. Stéphane Helleringer & Gilles Pison & Almamy Kanté & Géraldine Duthé & Armelle Andro, 2014. "Reporting Errors in Siblings’ Survival Histories and Their Impact on Adult Mortality Estimates: Results From a Record Linkage Study in Senegal," Demography, Springer;Population Association of America (PAA), vol. 51(2), pages 387-411, April.
    5. Stephane Helleringer & Daniel Arhinful & Benjamin Abuaku & Michael Humes & Emily Wilson & Andrew Marsh & Adrienne Clermont & Robert E Black & Jennifer Bryce & Agbessi Amouzou, 2018. "Using community-based reporting of vital events to monitor child mortality: Lessons from rural Ghana," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-18, January.
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    Cited by:

    1. Hallie Eilerts & Julio Romero Prieto & Jeffrey W. Eaton & Georges Reniers, 2021. "Age patterns of under-5 mortality in sub-Saharan Africa during 1990‒2018: A comparison of estimates from demographic surveillance with full birth histories and the historic record," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(18), pages 415-442.
    2. Hathi, Payal, 2022. "Population science implications of the inclusion of stillbirths in demographic estimates of child mortality," SocArXiv sz8n9, Center for Open Science.

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