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


Journal

Population health metrics
ISSN: 1478-7954
Titre abrégé: Popul Health Metr
Pays: England
ID NLM: 101178411

Informations de publication

Date de publication:
08 02 2021
Historique:
entrez: 9 2 2021
pubmed: 10 2 2021
medline: 29 10 2021
Statut: epublish

Résumé

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. 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). 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 33557866
doi: 10.1186/s12963-020-00230-3
pii: 10.1186/s12963-020-00230-3
pmc: PMC7869446
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

16

Investigateurs

Peter Byass (P)
Joy E Lawn (JE)
Peter Waiswa (P)
Hannah Blencowe (H)
Judith Yargawa (J)
Joseph Akuze (J)
Ane B Fisker (AB)
Justiniano S D Martins (JSD)
Amabelia Rodrigues (A)
Sanne M Thysen (SM)
Gashaw Andargie Biks (GA)
Solomon Mokonnen Abebe (SM)
Tadesse Awoke Ayele (TA)
Telake Azale Bisetegn (TA)
Tadess Guadu Delele (TG)
Kassahun Alemu Gelaye (KA)
Bisrat Misganaw Geremew (BM)
Lemma Derseh Gezie (LD)
Tesfahun Melese (T)
Mezgebu Yitayal Mengistu (MY)
Adane Kebede Tesega (AK)
Temesgen Azmeraw Yitayew (TA)
Simon Kasasa (S)
Edward Galigawango (E)
Collins Gyezaho (C)
Judith Kaija (J)
Dan Kajungu (D)
Tryphena Nareeba (T)
Davis Natukwatsa (D)
Valerie Tusubira (V)
Yeetey A K Enuameh (YAK)
Kwaku P Asante (KP)
Francis Dzabeng (F)
Seeba Amenga Etego (SA)
Alexander A Manu (AA)
Grace Manu (G)
Obed Ernest Nettey (OE)
Sam K Newton (SK)
Seth Owusu-Agyei (S)
Charlotte Tawiah (C)
Charles Zandoh (C)
Nurul Alam (N)
Nafisa Delwar (N)
M Moinuddin Haider (MM)
Md Ali Imam (MA)
Kaiser Mahmud (K)
Angela Baschieri (A)
Simon Cousens (S)
Vladimir S Gordeev (VS)
Victoria Ponce Hardy (VP)
Doris Kwesiga (D)
Kazuyo Machiyama (K)

Références

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Auteurs

M Moinuddin Haider (MM)

Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh. moin@icddrb.org.

Kaiser Mahmud (K)

Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.

Hannah Blencowe (H)

Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.

Tahmeed Ahmed (T)

Nutrition and Clinical Services Division, icddr,b, Dhaka, Bangladesh.

Joseph Akuze (J)

Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.
Centre of Excellence for Maternal Newborn and Child Health Research, Makerere University, Kampala, Uganda.
Department of Health Policy, Planning and Management, Makerere University School of Public Health, Kampala, Uganda.

Simon Cousens (S)

Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.
Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK.

Nafisa Delwar (N)

Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.

Ane B Fisker (AB)

Bandim Health Project, Bissau, Guinea-Bissau.
Research Centre for Vitamins and Vaccines, Statens Serum Institut, Copenhagen, Denmark.
Open Patient Data Explorative Network (OPEN), University of Southern Denmark, Odense, Denmark.

Victoria Ponce Hardy (V)

Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.

S M Tafsir Hasan (SMT)

Nutrition and Clinical Services Division, icddr,b, Dhaka, Bangladesh.

Md Ali Imam (MA)

Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.

Dan Kajungu (D)

IgangaMayuge Health and Demographic Surveillance System, Makerere University Centre for Health and Population Research, Makerere, Uganda.

Md Alfazal Khan (MA)

Matlab Health Research Centre, icddr,b, Dhaka, Bangladesh.

Justiniano S D Martins (JSD)

Bandim Health Project, Bissau, Guinea-Bissau.

Quamrun Nahar (Q)

Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.

Obed Ernest A Nettey (OEA)

Kintampo Health Research Centre, Kintampo, Ghana.

Adane Kebede Tesega (AK)

Dabat Research Centre Health and Demographic Surveillance System, Dabat, Ethiopia.
Department of Health Systems and Policy, University of Gondar Institute of Public Health, Gondar, Ethiopia.

Judith Yargawa (J)

Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.

Nurul Alam (N)

Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.

Joy E Lawn (JE)

Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.

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