ArticleBMC public health2022
Cardiovascular (Framingham) and type II diabetes (Finnish Diabetes) risk scores: a qualitative study of local knowledge of diet, physical activity and body measurements in rural Rakai, Uganda.
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Comparison of FINDRISC and the Framingham Model for Predicting CHD Risk: Results from the Kharameh Cohort Study.Vascular health and risk management · 2026Article
- Evolving Strategies for Use of Phytochemicals in Prevention and Long-Term Management of Cardiovascular Diseases (CVD).International journal of molecular sciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundNon-communicable diseases such as cardiovascular conditions and diabetes are rising in sub-Saharan Africa. Prevention strategies to mitigate non-communicable diseases include improving diet, physical activity, early diagnosis, and long-term management. Early identification of individuals at risk based on risk-score models - such as the Framingham Risk Score (FRS) for 10-year risk of cardiovascular disease and the Finnish type 2 Diabetes risk score (FINDRISC) for type 2 diabetes which are used in high-income settings - have not been well assessed in sub-Saharan Africa. The purpose of this study was to qualitatively assess local knowledge of components of these risk scores in a rural Ugandan setting.
methodsSemi-structured qualitative in-depth interviews were conducted with a purposively selected sample of 15 participants who had responded to the FRS and FINDRISC questionnaires and procedures embedded in the Rakai Community Cohort Study. Data were summarized and categorized using content analysis, with support of Atlas.ti.
resultsParticipants described local terms for hypertension ("pulessa") and type 2 diabetes ("sukaali"). Most participants understood physical activity as leisure physical activity, but when probed would also include physical activity linked to routine farm work. Vegetables were typically described as "plants", "leafy greens", and "side dish". Vegetable and fruit consumption was described as varying seasonally, with peak availability in December after the rainy season. Participants perceived themselves to have good knowledge about their family members' history of type 2 diabetes and hypertension.
conclusionsWhile most items of the FRS and FINDRISC were generally well understood, physical activity needs further clarification. It is important to consider the seasonality of fruits and vegetables, especially in rural resource-poor settings. Current risk scores will need to be locally adapted to estimate the 10-year risk of cardiovascular diseases and type 2 diabetes in this setting.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.