An environment-wide association study for the identification of non-invasive factors for type 2 diabetes mellitus: Analysis based on the Henan Rural Cohort study
Authors' conclusion
Our findings demonstrate that non-invasive variables that can be easily measured and quickly obtained may be used to predict T2DM risk in rural populations in Henan Province.
Study context
- Population
- Rural population of Henan Province, China; Henan Rural Cohort Study
- Participants
- 30,020 participants
- Exposure
- Non-invasive variables vs Full model
- Outcome
- T2D classification by GBM model; factors associated with T2D
Methodological detailscross-sectional analysis of a cohort, random 50:50 training/testing split, logistic regression (false discovery rate < 5 %), Gradient Boosting Machine model
- Cross-sectional analysis of a cohort
- Random 50:50 training/testing split
- Logistic regression (false discovery rate < 5 %)
- Gradient Boosting Machine model
Main finding
As reported in the abstract
| Group | AUC |
|---|---|
| Non-invasive variables | 0.837 |
| Full model | 0.847 |
AUC
Non-invasive variables0.837
Full model0.847
- Non-invasive variables associated with T2D (training and testing dataset)
- 13
- Blood biochemical indexes associated with T2D
- 6
Observational data: associations, not effects.
Further findings
- Overall population prevalence of T2D
- 9.10 %
Original publication
An environment-wide association study for the identification of non-invasive factors for type 2 diabetes mellitus: Analysis based on the Henan Rural Cohort study. Diabetes Res Clin Pract. Published 23 September 2023. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →