Evidence map›Paper›PMID 33557866›Full record

ArticlePopulation health metrics2021

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

M Moinuddin Haider, Kaiser Mahmud, Hannah Blencowe, Tahmeed Ahmed, Joseph Akuze, Simon Cousens, Nafisa Delwar, Ane B Fisker, Victoria Ponce Hardy, S M Tafsir Hasan and 11 more

Open access · goldAbstract read
In one paragraph

Article in Population health metrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.0field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors at 5 institutions in 7 countries.

M Moinuddin HaiderHealth Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh. moin@icddrb.org.
Kaiser MahmudHealth Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Hannah BlencoweMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.
Tahmeed AhmedNutrition and Clinical Services Division, icddr,b, Dhaka, Bangladesh.
Joseph AkuzeMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.
Simon CousensMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.
Nafisa DelwarHealth Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Ane B FiskerBandim Health Project, Bissau, Guinea-Bissau.
Victoria Ponce HardyMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.
S M Tafsir HasanNutrition and Clinical Services Division, icddr,b, Dhaka, Bangladesh.
Md Ali ImamHealth Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Dan KajunguIgangaMayuge Health and Demographic Surveillance System, Makerere University Centre for Health and Population Research, Makerere, Uganda.
Md Alfazal KhanMatlab Health Research Centre, icddr,b, Dhaka, Bangladesh.
Justiniano S D MartinsBandim Health Project, Bissau, Guinea-Bissau.
Quamrun NaharHealth Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Obed Ernest A NetteyKintampo Health Research Centre, Kintampo, Ghana.
Adane Kebede TesegaDabat Research Centre Health and Demographic Surveillance System, Dabat, Ethiopia.
Judith YargawaMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.
Nurul Alam *Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh.
Joy E Lawn *Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK.
Every Newborn-INDEPTH Study Collaborative Group
International Centre for Diarrhoeal Disease Research · BDBandim Health Project · GWLondon School of Hygiene & Tropical Medicine · GBKintampo Health Research Centre · GHStatens Serum Institut · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreterm 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.

methodsThe 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).

resultsGAm 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.

conclusionsThis 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.

Indexed as

Premature BirthChildFemaleGestational AgeHumansInfantInfant, NewbornPovertyPregnancyPrenatal CareSurveys and QuestionnairesDemographyGestational ageHousehold surveyLast menstrual periodPreterm birthSurveillanceUltrasound

Identifiers

PMID33557866
PMCPMC7869446
OpenAlexW3127527423

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.