Evidence map›Paper›PMID 39385112›Full record

ArticleBMC public health2024

Socioeconomic determinants of male contraceptive use in South Africa: a secondary analysis of the 2016 SADHS data.

Yulisha Naidoo, Liezl Joubert, Karen Nhakaniso, Emmanuella Nzeribe, Folahanmi Tomiwa Akinsolu, Denis Okova, Plaxcedes Chiwire, Akim Tafadzwa Lukwa

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Yulisha Naidoo *Health Economics Unit, School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
Liezl Joubert *Health Economics Unit, School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
Karen NhakanisoBusiness School, University of the People, 595 E Colorado Blvd Suite 623, Pasadena, CA, 91101, USA.
Emmanuella NzeribeCentre for Nanomedicine and biophysics, Department of Pharmaceutical technology and raw materials development, National Institute of Pharmaceutical research and Development, NIPRD, Abuja, Nigeria.
Folahanmi Tomiwa AkinsoluCenter for Reproductive and Population Health Studies (CRePHS), Nigerian Institute of Medical Research, Lagos, Nigeria.
Denis OkovaHealth Economics Unit, School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
Plaxcedes ChiwireDepartment of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, 6200 MD, The Netherlands.
Akim Tafadzwa LukwaHealth Economics Unit, School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa. lkwaki001@myuct.ac.za.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHistorically, family planning discussions have predominantly centred on women, overlooking the crucial role men play in contraception. This is particularly concerning in regions like Sub-Saharan Africa (SSA), where reproductive health challenges are pronounced. South Africa, a key country within SSA, continues to grapple with issues such as high unintended pregnancy rates and increasing pregnancy-related mortality. Understanding the factors that deter male contraceptive use is essential for achieving universal access to sexual and reproductive health (SRH) services. This study investigates the socioeconomic disparities influencing male contraceptive use in South Africa, drawing on data from the 2016 South Africa Demographic Health Survey.

methodsThe study utilised data from the 2016 South African Demographic and Health Survey, which employed a stratified, two-stage sampling design across all provinces based on the 2011 Census. The survey focused on men aged 15-59 using the "Man's Questionnaire." Various socio-demographic and attitudinal variables were analysed using STATA 17. The analysis included multinomial logistic regression to identify determinants of male contraceptive use and the Erreygers Normalized Concentration Index to assess socioeconomic inequalities in contraceptive uptake.

resultsAmong the surveyed men, 47% reported not using any contraception, 40% used male methods, and 13% relied on their partners' contraceptive use. A majority began sexual activity between the ages of 14-17 (54%), resided in urban areas (56%), were unmarried (67%), and had attained secondary education (70%). Notably, 78% disagreed that contraception is solely a woman's responsibility, and 64% expressed positive attitudes toward contraception. Age, marital status, and education level emerged as significant factors influencing contraceptive use. The study revealed a slight pro-rich inequality in male contraception use, with socioeconomic status (SES) being the most significant contributor to this disparity (223.22%). This suggests that higher SES is associated with increased inequality in the adoption of modern male contraceptive methods.

conclusionThese findings highlight the impact of socioeconomic disparities and entrenched cultural beliefs on male contraceptive use in South Africa. To address these challenges, comprehensive strategies that prioritise education, expand family planning media campaigns and ensure equitable access to contraception are urgently needed.

Indexed as

Contraception BehaviorSocioeconomic FactorsAdolescentAdultContraceptionHealth SurveysHumansMaleMiddle AgedSouth AfricaYoung AdultDemographic Health SurveyErreygers Normalised Concentration IndexMale contraceptive useReproductive HealthSocioeconomic disparities

Identifiers

PMID39385112
PMCPMC11465895

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LicenceCC BY-NC-ND
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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.