Evidence map›Paper›PMID 27809824›Full record

ArticleBMC public health2016

What explains gender inequalities in HIV/AIDS prevalence in sub-Saharan Africa? Evidence from the demographic and health surveys.

Drissa Sia, Yentéma Onadja, Mohammad Hajizadeh, S Jody Heymann, Timothy F Brewer, Arijit Nandi

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 2 pooled it
45.2field-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

82 citing papers in PubMed, 2 syntheses or guidelines pooled it, 146 citations in OpenAlex.

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22 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

6 authors at 5 institutions in 3 countries.

Drissa SiaDépartement des sciences infirmières, Campus de Saint-Jérôme, Université du Québec en Outaouais, 5, rue Saint-Joseph, bureau J-3226, Saint Jérôme, Québec, J7Z 0B7, Canada. drissa.sia@uqo.ca.ORCID 0000-0003-0044-8465
Yentéma OnadjaInstitut Supérieur des Sciences de la Population (ISSP), Université Ouaga I Pr Joseph Ki-Zerbo, 03 BP 7118 Ouagadougou 03, Ouagadougou, Burkina Faso.
Mohammad HajizadehSchool of Health Administration, Dalhousie University, Halifax, Nova Scotia, Canada.
S Jody HeymannFielding School of Public Health, The University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
Timothy F BrewerDavid Geffen School of Medicine, The University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
Arijit NandiInstitute for Health and Social Policy and Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada.
University of California, Los Angeles · USDalhousie University · CAInstitut Superieur Des Sciences De La Population · BFMcGill University · CAUniversité du Québec en Outaouais · CA

Funding

CIHR ROH-115209
6 · The paper itself

Abstract

backgroundWomen are disproportionally affected by human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) in sub-Saharan Africa (SSA). The determinants of gender inequality in HIV/AIDS may vary across countries and require country-specific interventions to address them. This study aimed to identify the socio-demographic and behavioral characteristics underlying gender inequalities in HIV/AIDS in 21 SSA countries.

methodsWe applied an extension of the Blinder-Oaxaca decomposition approach to data from Demographic and Health Surveys and AIDS Indicator Surveys to quantify the differences in HIV/AIDS prevalence between women and men attributable to socio-demographic factors, sexual behaviours, and awareness of HIV/AIDS. We decomposed gender inequalities into two components: the percentage attributable to different levels of the risk factors between women and men (the "composition effect") and the percentage attributable to risk factors having differential effects on HIV/AIDS prevalence in women and men (the "response effect").

resultsDescriptive analyses showed that the difference between women and men in HIV/AIDS prevalence varied from a low of 0.68 % (P = 0.008) in Liberia to a high of 11.5 % (P < 0.001) in Swaziland. The decomposition analysis showed that 84 % (P < 0.001) and 92 % (P < 0.001) of the higher prevalence of HIV/AIDS among women in Uganda and Ghana, respectively, was explained by the different distributions of HIV/AIDS risk factors, particularly age at first sex between women and men. In the majority of countries, however, observed gender inequalities in HIV/AIDS were chiefly explained by differences in the responses to risk factors; the differential effects of age, marital status and occupation on prevalence of HIV/AIDS for women and men were among the significant contributors to this component. In Cameroon, Guinea, Malawi and Swaziland, a combination of the composition and response effects explained gender inequalities in HIV/AIDS prevalence.

conclusionsThe factors that explain gender inequality in HIV/AIDS in SSA vary by country, suggesting that country-specific interventions are needed. Unmeasured factors also contributed substantially to the difference in HIV/AIDS prevalence between women and men, highlighting the need for further study.

Indexed as

Health Status DisparitiesAdolescentAdultAfrica South of the SaharaCameroonEswatiniFemaleGhanaHealth SurveysHIV InfectionsHumansMalawiMaleMiddle AgedPrevalenceRisk FactorsBlinder-Oaxaca decompositionGender inequalityHIV/AIDSSub-Saharan Africa

Identifiers

PMID27809824
PMCPMC5095963
OpenAlexW2546868026

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.