Research & Evidence

Evidence brief: Prevalence and associated factors of non-communicable diseases among men: A cross-sectional analysis of Kenya Demographic and Health Survey 2022 data

A sourced PLOS One study, published 2026-07-20. Read the researchers’ findings, methods and context, with links to connected African health evidence.

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Illustrative stock photograph from Unsplash. It does not depict the reported event, study participants or a confirmed Kenyan facility. Source: https://images.unsplash.com/photo-1579684385127-1ef15d508118

Published in PLOS One on 2026-07-20, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.

Original authors: John Baptist Asiimwe, Lilian Nuwabaine, Angella Namulema, Quraish Sserwanja, Joseph Kawuki, Grace Nambozi, Grace Afrifa-Anane

Source: PLOS One • DOI 10.1371/journal.pone.0327266

Read the complete primary study ↗ · Creative Commons Attribution licence

From the researchers

Abstract

Non-communicable diseases (NCDs) are the leading cause of morbidity and mortality worldwide, with low- and middle-income countries (LMICs) increasingly being disproportionately affected. Although anecdotal evidence or reports indicate an increasing number of Kenyan men having NCDs, the prevalence and associated factors are not well understood. Therefore, this study aimed to determine the prevalence and associated factors of non-communicable diseases among men in Kenya.

Secondary data comprising 14,439 men aged 15–54 years from the 2022 cross-sectional Demographic and Health Survey (KDHS) in Kenya were analyzed using univariable and multivariable logistic regression analyses in SPSS, version 29.

Overall, the percentage of men with at least one NCD was 9.4% (95% confidence interval [CI]: 8.7–10.2%). Whereas the proportion of participants with multiple NCDs was 1.9 (95% CI: 1.6–2.3). Across NCDs, the highest prevalent NCD was hypertension (3.5% 95%CI:3.1–3.9) followed by depression (2.2% (95%CI:1.9–2.5), anxiety (1.6% (95%CI:1.3–1.9), arthritis (1.4% (95%CI:1.1–1.6), heart disease (1.2% (95%CI:0.9–1.5), diabetes (1% (95%CI:0.8–1.3), lung disease (1% (95%CI:0.7–1.3), and cancer (0.1% (95%CI:0–0.1). In terms of multiple chronic conditions (multimorbidity), the majority of the participants had diabetes and hypertension (0.5% (95%CI:0.3–0.7) followed by hypertension and depression (0.3% (95%CI:0.2–0.4), hypertension and anxiety (0.3% (95%CI:0.2–0.4), and arthritis and depression (0.2% (95%CI:0.1–0.2). Several factors, such as age, region, residence, ethnicity, education level, health status, wealth index, religion, media access, and living a sedentary lifestyle, were found to be significantly associated with the prevalence of NCDs.

The overall prevalence of NCDs among men is relatively low based on available national data. We found that sociodemographic and lifestyle factors were significantly associated with the prevalence of NCDs. Although causal relationships cannot be inferred from this study, the findings suggest that initiatives such as tailored health education, regular medical checkups, and the promotion of physical activity may be relevant components of broader efforts to support men’s health in relation to non‑communicable diseases (NCDs). Region‑specific policies and culturally sensitive approaches may help address variations in risk factors and observed ethnic disparities. Encouraging healthier lifestyle practices among men of all backgrounds and improving access to integrated healthcare in rural areas may also be important considerations. Further research is needed to explore how media exposure, media content, health messaging, and religious contexts may influence men’s exposure to NCDs in Kenya and other sub-Saharan countries.

Reading this evidence

Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.

This briefing makes the source accessible within the wider research & evidence desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.

© 2026 John Baptist Asiimwe, Lilian Nuwabaine, Angella Namulema, Quraish Sserwanja, Joseph Kawuki, Grace Nambozi, Grace Afrifa-Anane. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.

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Health Signal’s publication desk curates source-based health analysis and attributed research briefings. Study authors and originating institutions are credited within each article. Preparation used AI assistance; source and licence checks do not constitute independent replication or clinical endorsement.

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