Evidence map›Paper›PMID 34582455›Full record

ArticlePLoS medicine2021

Implications of armed conflict for maternal and child health: A regression analysis of data from 181 countries for 2000-2019.

Mohammed Jawad, Thomas Hone, Eszter P Vamos, Valeria Cetorelli, Christopher Millett

Open access · goldAbstract read
In one paragraph

Article in PLoS medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 3 pooled it
15.7field-weighted citation impact, top 1% 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

65 citing papers in PubMed, 3 syntheses or guidelines pooled it, 110 citations in OpenAlex.

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5 more citing papers are in PubMed but not listed here.

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

5 authors at 3 institutions in 3 countries.

Mohammed JawadPublic Health Policy Evaluation Unit, Imperial College London, London, United Kingdom.ORCID 0000-0002-1051-2136
Thomas HonePublic Health Policy Evaluation Unit, Imperial College London, London, United Kingdom.ORCID 0000-0003-0703-6973
Eszter P VamosPublic Health Policy Evaluation Unit, Imperial College London, London, United Kingdom.
Valeria CetorelliUnited Nations Relief and Works Agency for Palestine Refugees in the Near East, Amman, Jordan.ORCID 0000-0002-7310-6557
Christopher MillettPublic Health Policy Evaluation Unit, Imperial College London, London, United Kingdom.ORCID 0000-0002-0793-9884
Imperial College London · GBUnited Nations Relief and Works Agency for Palestine Refugees in the Near East · JOUniversity of Lisbon · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArmed conflicts have major indirect health impacts in addition to the direct harms from violence. They create enduring political instability, destabilise health systems, and foster negative socioeconomic and environmental conditions-all of which constrain efforts to reduce maternal and child mortality. The detrimental impacts of conflict on global maternal and child health are not robustly quantified. This study assesses the association between conflict and maternal and child health globally. METHODS AND

findingsData for 181 countries (2000-2019) from the Uppsala Conflict Data Program and World Bank were analysed using panel regression models. Primary outcomes were maternal, under-5, infant, and neonatal mortality rates. Secondary outcomes were delivery by a skilled birth attendant and diphtheria, pertussis, and tetanus (DPT) and measles vaccination coverage. Models were adjusted for 10 confounders, country and year fixed effects, and conflict lagged by 1 year. Further lagged associations up to 10 years post-conflict were tested. The number of excess deaths due to conflict was estimated. Out of 3,718 country-year observations, 522 (14.0%) had minor conflicts and 148 (4.0%) had wars. In adjusted models, conflicts classified as wars were associated with an increase in maternal mortality of 36.9 maternal deaths per 100,000 live births (95% CI 1.9-72.0; 0.3 million excess deaths [95% CI 0.2 million-0.4 million] over the study period), an increase in infant mortality of 2.8 per 1,000 live births (95% CI 0.1-5.5; 2.0 million excess deaths [95% CI 1.6 million-2.5 million]), a decrease in DPT vaccination coverage of 4.9% (95% CI 1.5%-8.3%), and a decrease in measles vaccination coverage of 7.3% (95% CI 2.7%-11.8%). The long-term impacts of war were demonstrated by associated increases in maternal mortality observed for up to 7 years, in under-5 mortality for 3-5 years, in infant mortality for up to 8 years, in DPT vaccination coverage for up to 3 years, and in measles vaccination coverage for up to 2 years. No evidence of association between armed conflict and neonatal mortality or delivery by a skilled birth attendant was found. Study limitations include the ecological study design, which may mask sub-national variation in conflict intensity, and the quality of the underlying data.

conclusionsOur analysis indicates that armed conflict is associated with substantial and persistent excess maternal and child deaths globally, and with reductions in key measures that indicate reduced availability of organised healthcare. These findings highlight the importance of protecting women and children from the indirect harms of conflict, including those relating to health system deterioration and worsening socioeconomic conditions.

Indexed as

Armed ConflictsChild HealthChild MortalityExposure to ViolenceMaternal MortalityAdolescentAdultAgedChild, PreschoolFemaleHealth Services AccessibilityHumansInfantInfant, NewbornMaleMiddle Aged

Identifiers

PMID34582455
PMCPMC8478221
OpenAlexW3204541044

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.