ArticleHealth science reports2024
Association of BMI and incidence of type 2 diabetes in Saudi population.
Article in Health science reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 2 citations in OpenAlex.
- Rising obesity and shifting disease patterns in Saudi Arabia: a nine-year population-based analysis of chronic disease burden and multimorbidity profiles.BMC public health · 2026Article
- Risk factors for type 2 diabetes mellitus among university students in Saudi Arabia: a multi-regional cross-sectional study.Frontiers in endocrinology · 2026Observational
- Study of the Association ofInternational journal of general medicine · 2025Article
- Association of BMI and incidence of type 2 diabetes in Saudi population.Health science reports · 2024Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The study aims to identify the optimal body mass index (BMI) cut-off for obesity based on the risk of developing type 2 diabetes among the general population visiting primary health care in Saudi Arabia. Methods: A cross-sectional study was conducted in Al-Ahsa City, Saudi Arabia, from January to June 2022. The study included Saudi citizens aged 35 and older who had not previously or currently been diagnosed with type 2 diabetes. Data were collected through electronic health records from 48 primary healthcare centers. The variables derived from medical records were age, gender, HbA1c, weight, and height. Results: The BMI mean among nondiabetic, prediabetic, and diabetic groups were 29.6 ± 6.2, 31.2 ± 6.6, and 31.7 ± 6.9 kg/m Conclusion: The current study correlated the result of HbA1c levels with BMI cut-off values as a modifiable risk factor for developing type 2 diabetes among the Al-Ahsa population in Saudi Arabia. The BMI mean among nondiabetic, prediabetic, and diabetic groups were 29.6 ± 6.2, 31.2 ± 6.6, and 31.7 ± 6.9 kg/m2, respectively. This study provided a list of BMI values as cut-off points with their sensitivity and specificity measures so the policymaker could utilize them. The best cut-off point could be decided based on cost-effective analysis. Further studies in the future might help evaluate the efficacy of screening programs and the association between BMI and other types of diabetes.
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