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Cardiovascular risk factor mapping and distribution among adults in Mukono and Buikwe districts in Uganda: small area analysis
Open accessPublished version of a preprint
Abstract
Background: Sub-Saharan Africa (SSA) is experiencing an increasing burden of Cardiovascular Diseases (CVDs). Modifiable risk factors including hypertension, diabetes, obesity, central obesity, sedentary behaviours, smoking, poor diet (characterised by inadequate vegetable and fruit consumption), and psychosocial stress are attributable to the growing burden of CVDs. Small geographical area mapping and analysis of these risk factors for CVD is lacking in most of sub-Saharan Africa and yet such data has the potential to inform monitoring and exploration of patterns of morbidity, health-care use, and mortality, as well as the epidemiology of risk factors. In the current study, we map and describe the distribution of the CVD risk factors in 20 parishes in two neighbouring districts in Uganda. Methods: A baseline survey benchmarking a type-2 hybrid stepped wedge cluster randomised trial design was conducted in December 2018 and January 2019. A sample of 4372 adults aged 25–70 years was drawn from 3689 randomly selected households across 80 villages in 20 parishes in Mukono and Buikwe districts in Uganda. Descriptive statistics and generalized linear modelling controlled for clustering were conducted for this analysis in Stata 13.0, and a visual map showing risk factor distribution developed in QGIS. Results: Mapping the prevalence of selected CVD risk factors indicated substantial gender and small area geographic heterogeneity which was masked on aggregate analysis. Patterns and clustering were observed for hypertension, physical inactivity, smoking, alcohol consumption and risk factor combination. Prevalence of unhealthy diet was very high across all parishes with no significant observable differences across areas. Conclusion: Modifiable cardiovascular risk factors are common in this low-income context. Moreover, across small area geographic setting, it appears significant differences in distribution of risk factors exist. These differences suggest that underlying drivers such as sociocultural, environmental and economic determinants may be promoting or inhibiting the observed risk factor prevalences which should be further explored. In addition, the differences emphasize the value of small geographical area mapping and analysis to inform more targeted risk reduction interventions.
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Musinguzi et al. (2020) included 17 clusters (primary and community healthcare centres).
“17”
From Applications and implementation considerations for stepped-wedge designs in sub-Saharan Africa: a systematic review (2026) · cites this paper as [51]
The Methods (Design and setting of the study; page unavailable) say the baseline survey was conducted in 20 parishes, not 17 clusters. The parishes were selected because they hosted Health Centre III primary healthcare facilities; the Results also confirm participants were drawn from 20 parishes. (LLM, conf=0.88)
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Experimental — accuracy not yet measuredMusinguzi et al. (2020) chose a stepped wedge design because it enabled a randomized controlled approach alongside implementation, was ethical and logistically feasible, and ensured all facilities eventually received the intervention.
“The stepped wedge design was chosen because it enabled the use of a randomized controlled approach alongside the implementation process. It was also ethical and logistically feasible, ensuring all facilities eventually received the intervention”
From Applications and implementation considerations for stepped-wedge designs in sub-Saharan Africa: a systematic review (2026) · cites this paper as [51]
The Methods section (‘Design and setting of the study’; page not provided) says this analysis used baseline data from a stepped-wedge trial described elsewhere. It does not explain why that design was chosen or say it was ethical, logistically feasible, or ensured that all facilities received the intervention. (LLM, conf=0.83)
Experimental — accuracy not yet measuredMusinguzi et al. (2020) randomized facilities to receive the intervention at different times using random number lists, resulting in a stepped-wedge sequence.
“Facilities were randomized to receive the intervention at different times using random number lists, resulting in a stepped-wedge sequence of support implementation”
From Applications and implementation considerations for stepped-wedge designs in sub-Saharan Africa: a systematic review (2026) · cites this paper as [51]
The Methods section (“Design and setting of the study”; page unavailable) says the data came from a baseline survey for a stepped-wedge trial. It does not say that facilities were randomized to intervention times using random number lists; it says the trial was reported elsewhere. (LLM, conf=0.83)
Experimental — accuracy not yet measuredMusinguzi et al. (2020) had each facility receive two months of intensive support followed by four months of lower-intensity maintenance support.
“Each facility received two months of intensive support followed by four months of lower-intensity maintenance support”
From Applications and implementation considerations for stepped-wedge designs in sub-Saharan Africa: a systematic review (2026) · cites this paper as [51]
The Methods section (Design and setting of the study; page unavailable) says this paper analyzes a baseline survey for a stepped-wedge trial reported elsewhere. Neither that section nor the searched passages on facility support and intervention timing specify two months of intensive support followed by four months of maintenance support. (LLM, conf=0.72)
Experimental — accuracy not yet measuredMusinguzi et al. (2020) used three phases of intervention rollout: intensive support, maintenance support, and standard support.
“The intervention rollout involved three phases: intensive support, maintenance support, and standard support over several months until all facilities had received the intervention”
From Applications and implementation considerations for stepped-wedge designs in sub-Saharan Africa: a systematic review (2026) · cites this paper as [51]
The Methods (Design and setting of the study; page unavailable) say the data came from a baseline survey for a stepped-wedge trial reported elsewhere. Searches for the three named support phases and for intervention rollout found no passage describing those phases or saying that all facilities received the intervention. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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Research works printed but not linked: 16
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Cited by
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Amini, M., Zayeri, F., & Salehi, M. (2021) · BMC Public Health · doi:10.1186/s12889-021-10429-0 · Cited by 636
Musa, Z. A., Akinsolu, F. T., Salako, A. O., Abodunrin, O. R., Ola, O. M., & Ezechi, O. C. (2026) · Frontiers in Epidemiology · doi:10.3389/fepid.2026.1529289
Metadata
- Authors
- Musinguzi, G., Ndejjo, R., Ssinabulya, I., Bastiaens, H., van Marwijk, H., & Wanyenze, R. K.
- Affiliations
- University of Antwerp (BE)
- Makerere University (UG)
- Brighton and Sussex Medical School (GB)
- Corresponding author
- Musinguzi, Geofrey
- ORCID
- Venue
- BMC Cardiovascular Disorders
- Published
- 2020-06-10
- Volume
- 20
- Issue
- 1
- Pages
- 284-284
- ISSN
- 1471-2261 (ISSN-L)
- PMC
- PMC7288476
- OpenAlex
- W3033766471
- Cited by
- 28
- References
- 0
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 6 · 2023: 2 · 2022: 5 · 2021: 5 · 2020: 4
- FWCI
- 2.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Cardiovascular Disorders (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Sussex Research Online (University of Sussex) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Figshare (cc-by)
- Funders
- Horizon 2020 Framework Programme (733356)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Epidemiology › Healthcare Systems and Public Health
- Keywords
- cardiovascular risk factors, small-area mapping, hypertension, physical inactivity, smoking, alcohol consumption, unhealthy diet, obesity, abdominal obesity, diabetes mellitus, gender differences, geographic heterogeneity, Mukono district, Buikwe district, Uganda, low-income settings, risk factor clustering
- MeSH terms
- Heart Disease Risk Factors, Adult, Aged, Cardiovascular Diseases, Diabetes Mellitus, Female, Humans, Hypertension, Life Style, Male, Middle Aged, Obesity, Uganda, Prevalence, Cluster Analysis, Small-Area Analysis, Risk Assessment, Social Determinants of Health
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