Evidence map›Paper›PMID 28799450›Full record

ArticleGlobal health action2017

Comparing performance of methods used to identify pregnant women, pregnancy outcomes, and child mortality in the Iganga-Mayuge Health and Demographic Surveillance Site, Uganda.

Daniel Kadobera, Peter Waiswa, Stefan Peterson, Hannah Blencowe, Joy Lawn, Kate Kerber, Nazarius Mbona Tumwesigye

Abstract read
In one paragraph

Article in Global health action, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  11. Special issue: newborn health in Uganda.Global health action · 2015
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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

7 authors.

Daniel Kadoberaa Indepth Network Maternal, Newborn and Child Health Working Group , Iganga/Mayuge Health and Demographic Surveillance System , Iganga , Uganda.
Peter Waiswaa Indepth Network Maternal, Newborn and Child Health Working Group , Iganga/Mayuge Health and Demographic Surveillance System , Iganga , Uganda.ORCID 0000-0001-9868-0515
Stefan Petersond Maternal, Newborn and Child Health Centre of Excellence, School of Public Health, College of Health Sciences , Makerere University , Kampala , Uganda.ORCID 0000-0001-7203-3096
Hannah Blencoweg Centre for Maternal, Adolescent, Reproductive and Child Health (MARCH) , London School of Hygiene and Tropical Medicine , London , UK.ORCID 0000-0003-1556-3159
Joy Lawng Centre for Maternal, Adolescent, Reproductive and Child Health (MARCH) , London School of Hygiene and Tropical Medicine , London , UK.
Kate Kerberh Saving Newborn Lives, Save the Children US , Washington , DC , USA.
Nazarius Mbona Tumwesigyei Department of Epidemiology and Biostatistics, School of Public Health, College of Health Sciences , Makerere University , Kampala , Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn most low and middle-income countries vital events registration for births and child deaths is poor, with reporting of pregnancy outcomes highly inadequate or non-existent. Health and Demographic Surveillance System (HDSS) sites and periodic population-based household-level surveys can be used to identify pregnancies and retrospectively capture pregnancy outcomes to provide data for decision making. However, little is known about the performance of different methods in identifying pregnancy and pregnancy outcomes, yet this is critical in assessing improvements in reducing maternal and newborn mortality and stillbirths.

objectiveTo explore differences between a population-based household pregnancy survey and prospective health demographic surveillance system in identifying pregnancies and their outcomes in rural eastern Uganda.

methodsThe study was done within the Iganga-Mayuge HDSS site, a member centre of the INDEPTH Network. Prospective data about pregnancies and their outcomes was collected in the routine biannual census rounds from 2006 to 2010 in the HDSS. In 2011 a cross-sectional survey using the pregnancy history survey (PHS) tool was conducted among women aged 15 to 49 years in the HDSS area. We compared differences between the HDSS biannual census updates and the PHS capture of pregnancies identified as well as neonatal and child deaths, stillbirths and abortions.

findingsA total of 10,540 women aged 15 to 49 years were interviewed during the PHS. The PHS captured 12.8% more pregnancies than the HDSS in the most recent year (2010-2011), though between 2006 and 2010 (earlier periods) the PHS captured only 137 (0.8%) more pregnancies overall. The PHS also consistently identified more stillbirths (18.2%), spontaneous abortions (94.5%) and induced abortions (185.8%) than the prospective HDSS update rounds.

conclusionsSurveillance sites are designed to prospectively track population-level outcomes. However, the PHS identified more pregnancy-related outcomes than the HDSS in this study. Asking about pregnancy and its outcomes may be a useful way to improve measurement of pregnancy outcomes. Further research is needed to identify the most effective methods of improving the capture of pregnancies and their outcomes within HDSS sites, household surveys and routine health information systems.

Indexed as

Infant MortalityPregnancy OutcomeAdolescentAdultCross-Sectional StudiesFemaleHumansInfantInfant, NewbornMedical AssistanceMiddle AgedPopulation SurveillancePregnancyProspective StudiesSurveys and QuestionnairesUgandahealth information sourcesmaternal and child health outcomesPopulation-based surveyspregnancy surveillancesurveillance systems

Identifiers

PMID28799450
PMCPMC5645672

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LicenceCC BY
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Registered trials

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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.