Evidence map›Paper›PMID 34215304›Full record

ArticleConflict and health2021

Comparative analysis of the health status of the population in six health zones in South Kivu: a cross-sectional population study using the WHODAS.

Samuel Lwamushi Makali, Espoir Bwenge Malembaka, Anne-Sophie Lambert, Hermès Bimana Karemere, Christian Molima Eboma, Albert Tambwe Mwembo, Steven Barnes Ssali, Ghislain Bisimwa Balaluka, Phillippe Donnen, Jean Macq

Abstract read
In one paragraph

Article in Conflict and health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

10 authors.

Samuel Lwamushi MakaliEcole Régionale de Santé Publique, Faculté de Médecine, Université Catholique de Bukavu, Bukavu, Democratic Republic of Congo. samuelmakali11@gmail.com.ORCID http://orcid.org/0000-0003-3538-1715
Espoir Bwenge MalembakaEcole Régionale de Santé Publique, Faculté de Médecine, Université Catholique de Bukavu, Bukavu, Democratic Republic of Congo.
Anne-Sophie LambertInstitut de Recherche Santé et Société, Université Catholique de Louvain, Brussels, Belgium.
Hermès Bimana KaremereEcole Régionale de Santé Publique, Faculté de Médecine, Université Catholique de Bukavu, Bukavu, Democratic Republic of Congo.
Christian Molima EbomaEcole Régionale de Santé Publique, Faculté de Médecine, Université Catholique de Bukavu, Bukavu, Democratic Republic of Congo.
Albert Tambwe MwemboEcole de Santé Publique, Université de Lubumbashi, Lubumbashi, Democratic Republic of Congo.
Steven Barnes SsaliMakerere University, Kampala, Uganda.
Ghislain Bisimwa BalalukaEcole Régionale de Santé Publique, Faculté de Médecine, Université Catholique de Bukavu, Bukavu, Democratic Republic of Congo.
Phillippe DonnenEcole de Santé Publique, Université Libre de Bruxelles, Brussels, Belgium.
Jean MacqInstitut de Recherche Santé et Société, Université Catholique de Louvain, Brussels, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe eastern Democratic Republic of Congo (DRC) has experienced decades-long armed conflicts which have had a negative impact on population's health. Most research in public health explores measures that focus on a specific health problem rather than overall population health status. The aim of this study was to assess the health status of the population and its predictors in conflict settings of South Kivu province, using the World Health Organization Disability Assessment Schedule (WHODAS).

methodsBetween May and June 2019, we conducted a community-based cross-sectional survey among 1440 adults in six health zones (HZ), classified according to their level of armed conflict intensity and chronicity in four types (accessible and stable, remote and stable, intermediate and unstable). The data were collected by a questionnaire including socio-demographic data and the WHODAS 2.0 tool with 12 items. The main variable of the study was the WHODAS summary score measuring individual's health status and synthesize in six domains of disability (household, cognitive, mobility, self-care, social and society). Univariate analysis, correlation and comparison tests as well as hierarchical multiple linear regression were performed.

resultsThe median WHODAS score in the accessible and stable (AS), remote and stable (RS), intermediate (I) and unstable (U) HZ was 6.3 (0-28.6); 25 (6.3-41.7); 22.9 (12.5-33.3) and 39.6 (22.9-54.2), respectively. Four of the six WHODAS domain scores (household, cognitive, mobility and society) were the most altered in the UHZs. The RSHZ and IHZ had statistically comparable global WHODAS scores. The stable HZs (accessible and remote) had statistically lower scores than the UHZ on all items. In regression analysis, the factors significantly associated with an overall poor health status (or higher WHODAS score) were advanced age, being woman, being membership of an association; being divorced, separated or widower and living in an unstable HZ.

conclusionsArmed conflicts have a significantly negative impact on people's perceived health, particularly in crisis health zones. In this area, we must accentuate actions aiming to strengthen people's psychosocial well-being.

Indexed as

ConflictDRCHealth statusPopulationSouth KivuWHODAS

Identifiers

PMID34215304
PMCPMC8254209

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.