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Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study

BACKGROUND: Preterm birth (gestational age (GA) <37 weeks) is the leading cause of child mortality worldwide. However, GA is rarely assessed in population-based surveys, the major data source in low/middle-income countries. We examined the performance of new questions to measure GA in household s...

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Autores principales: Haider, M. Moinuddin, Mahmud, Kaiser, Blencowe, Hannah, Ahmed, Tahmeed, Akuze, Joseph, Cousens, Simon, Delwar, Nafisa, Fisker, Ane B., Ponce Hardy, Victoria, Hasan, S. M. Tafsir, Imam, Md. Ali, Kajungu, Dan, Khan, Md Alfazal, Martins, Justiniano S. D., Nahar, Quamrun, Nettey, Obed Ernest A., Tesega, Adane Kebede, Yargawa, Judith, Alam, Nurul, Lawn, Joy E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869446/
https://www.ncbi.nlm.nih.gov/pubmed/33557866
http://dx.doi.org/10.1186/s12963-020-00230-3
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author Haider, M. Moinuddin
Mahmud, Kaiser
Blencowe, Hannah
Ahmed, Tahmeed
Akuze, Joseph
Cousens, Simon
Delwar, Nafisa
Fisker, Ane B.
Ponce Hardy, Victoria
Hasan, S. M. Tafsir
Imam, Md. Ali
Kajungu, Dan
Khan, Md Alfazal
Martins, Justiniano S. D.
Nahar, Quamrun
Nettey, Obed Ernest A.
Tesega, Adane Kebede
Yargawa, Judith
Alam, Nurul
Lawn, Joy E.
author_facet Haider, M. Moinuddin
Mahmud, Kaiser
Blencowe, Hannah
Ahmed, Tahmeed
Akuze, Joseph
Cousens, Simon
Delwar, Nafisa
Fisker, Ane B.
Ponce Hardy, Victoria
Hasan, S. M. Tafsir
Imam, Md. Ali
Kajungu, Dan
Khan, Md Alfazal
Martins, Justiniano S. D.
Nahar, Quamrun
Nettey, Obed Ernest A.
Tesega, Adane Kebede
Yargawa, Judith
Alam, Nurul
Lawn, Joy E.
author_sort Haider, M. Moinuddin
collection PubMed
description BACKGROUND: Preterm birth (gestational age (GA) <37 weeks) is the leading cause of child mortality worldwide. However, GA is rarely assessed in population-based surveys, the major data source in low/middle-income countries. We examined the performance of new questions to measure GA in household surveys, a subset of which had linked early pregnancy ultrasound GA data. METHODS: The EN-INDEPTH population-based survey of 69,176 women was undertaken (2017-2018) in five Health and Demographic Surveillance System sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda. We included questions regarding GA in months (GAm) for all women and GA in weeks (GAw) for a subset; we also asked if the baby was ‘born before expected’ to estimate preterm birth rates. Survey data were linked to surveillance data in two sites, and to ultrasound pregnancy dating at <24 weeks in one site. We assessed completeness and quality of reported GA. We examined the validity of estimated preterm birth rates by sensitivity and specificity, over/under-reporting of GAw in survey compared to ultrasound by multinomial logistic regression, and explored perceptions about GA and barriers and enablers to its reporting using focus group discussions (n = 29). RESULTS: GAm questions were almost universally answered, but heaping on 9 months resulted in underestimation of preterm birth rates. Preference for reporting GAw in even numbers was evident, resulting in heaping at 36 weeks; hence, over-estimating preterm birth rates, except in Matlab where the peak was at 38 weeks. Questions regarding ‘born before expected’ were answered but gave implausibly low preterm birth rates in most sites. Applying ultrasound as the gold standard in Matlab site, sensitivity of survey-GAw for detecting preterm birth (GAw <37) was 60% and specificity was 93%. Focus group findings suggest that women perceive GA to be important, but usually counted in months. Antenatal care attendance, women’s education and health cards may improve reporting. CONCLUSIONS: This is the first published study assessing GA reporting in surveys, compared with the gold standard of ultrasound. Reporting GAw within 5 years’ recall is feasible with high completeness, but accuracy is affected by heaping. Compared to ultrasound-GAw, results are reasonably specific, but sensitivity needs to be improved. We propose revised questions based on the study findings for further testing and validation in settings where pregnancy ultrasound data and/or last menstrual period dates/GA recorded in pregnancy are available. Specific training of interviewers is recommended.
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spelling pubmed-78694462021-02-08 Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study Haider, M. Moinuddin Mahmud, Kaiser Blencowe, Hannah Ahmed, Tahmeed Akuze, Joseph Cousens, Simon Delwar, Nafisa Fisker, Ane B. Ponce Hardy, Victoria Hasan, S. M. Tafsir Imam, Md. Ali Kajungu, Dan Khan, Md Alfazal Martins, Justiniano S. D. Nahar, Quamrun Nettey, Obed Ernest A. Tesega, Adane Kebede Yargawa, Judith Alam, Nurul Lawn, Joy E. Popul Health Metr Research BACKGROUND: Preterm birth (gestational age (GA) <37 weeks) is the leading cause of child mortality worldwide. However, GA is rarely assessed in population-based surveys, the major data source in low/middle-income countries. We examined the performance of new questions to measure GA in household surveys, a subset of which had linked early pregnancy ultrasound GA data. METHODS: The EN-INDEPTH population-based survey of 69,176 women was undertaken (2017-2018) in five Health and Demographic Surveillance System sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda. We included questions regarding GA in months (GAm) for all women and GA in weeks (GAw) for a subset; we also asked if the baby was ‘born before expected’ to estimate preterm birth rates. Survey data were linked to surveillance data in two sites, and to ultrasound pregnancy dating at <24 weeks in one site. We assessed completeness and quality of reported GA. We examined the validity of estimated preterm birth rates by sensitivity and specificity, over/under-reporting of GAw in survey compared to ultrasound by multinomial logistic regression, and explored perceptions about GA and barriers and enablers to its reporting using focus group discussions (n = 29). RESULTS: GAm questions were almost universally answered, but heaping on 9 months resulted in underestimation of preterm birth rates. Preference for reporting GAw in even numbers was evident, resulting in heaping at 36 weeks; hence, over-estimating preterm birth rates, except in Matlab where the peak was at 38 weeks. Questions regarding ‘born before expected’ were answered but gave implausibly low preterm birth rates in most sites. Applying ultrasound as the gold standard in Matlab site, sensitivity of survey-GAw for detecting preterm birth (GAw <37) was 60% and specificity was 93%. Focus group findings suggest that women perceive GA to be important, but usually counted in months. Antenatal care attendance, women’s education and health cards may improve reporting. CONCLUSIONS: This is the first published study assessing GA reporting in surveys, compared with the gold standard of ultrasound. Reporting GAw within 5 years’ recall is feasible with high completeness, but accuracy is affected by heaping. Compared to ultrasound-GAw, results are reasonably specific, but sensitivity needs to be improved. We propose revised questions based on the study findings for further testing and validation in settings where pregnancy ultrasound data and/or last menstrual period dates/GA recorded in pregnancy are available. Specific training of interviewers is recommended. BioMed Central 2021-02-08 /pmc/articles/PMC7869446/ /pubmed/33557866 http://dx.doi.org/10.1186/s12963-020-00230-3 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Haider, M. Moinuddin
Mahmud, Kaiser
Blencowe, Hannah
Ahmed, Tahmeed
Akuze, Joseph
Cousens, Simon
Delwar, Nafisa
Fisker, Ane B.
Ponce Hardy, Victoria
Hasan, S. M. Tafsir
Imam, Md. Ali
Kajungu, Dan
Khan, Md Alfazal
Martins, Justiniano S. D.
Nahar, Quamrun
Nettey, Obed Ernest A.
Tesega, Adane Kebede
Yargawa, Judith
Alam, Nurul
Lawn, Joy E.
Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study
title Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study
title_full Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study
title_fullStr Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study
title_full_unstemmed Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study
title_short Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study
title_sort gestational age data completeness, quality and validity in population-based surveys: en-indepth study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869446/
https://www.ncbi.nlm.nih.gov/pubmed/33557866
http://dx.doi.org/10.1186/s12963-020-00230-3
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