| 1. |
|
|
| 2. |
|
|
| 3. |
- Mendez, D. Y., et al.
(författare)
-
Characterization of data-driven clusters in diabetes-free adults and their utility for risk stratification of type 2 diabetes
- 2022
-
Ingår i: Bmc Medicine. - : Springer Science and Business Media LLC. - 1741-7015. ; 20:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. Methods Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and beta-cell function, systolic and diastolic blood pressure, and BMI. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. Results Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low beta-cell function (LRLB), low-risk high beta-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk beta-cell failure (HRBF), and high-risk insulin-resistant (HRIR). Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. Conclusions Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.
|
|
| 4. |
- Roswall, N., et al.
(författare)
-
Long-Term Exposure to Transportation Noise and Risk of Incident Stroke: A Pooled Study of Nine Scandinavian Cohorts
- 2021
-
Ingår i: Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 129:10
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Transportation noise is increasingly acknowledged as a cardiovascular risk factor, but the evidence base for an association with stroke is sparse. OBJECTIVE: We aimed to investigate the association between transportation noise and stroke incidence in a large Scandinavian population. METHODS: We harmonized and pooled data from nine Scandinavian cohorts (seven Swedish, two Danish), totaling 135,951 participants. We identified residential address history and estimated road, railway, and aircraft noise for all addresses. Information on stroke incidence was acquired through linkage to national patient and mortality registries. We analyzed data using Cox proportional hazards models, including socioeconomic and lifestyle confounders, and air pollution. RESULTS: During follow-up (median = 19.5 y), 11,056 stroke cases were identified. Road traffic noise (Lden) was associated with risk of stroke, with a hazard ratio (HR) of 1.06 [95% confidence interval (CI): 1.03, 1.08] per 10-dB higher 5-y mean time-weighted exposure in analyses adjusted for individual- and area-level socioeconomic covariates. The association was approximately linear and persisted after adjustment for air pollution [particulate matter (PM) with an aerodynamic diameter of <= 2.5 mu m (PM2.5) and NO2]. Stroke was associated with moderate levels of 5-y aircraft noise exposure (40-50 vs. <= 40 dB) (HR = 1.12; 95% CI: 0.99, 1.27), but not with higher exposure (>= 50 dB, HR = 0.94; 95% CI: 0.79, 1.11). Railway noise was not associated with stroke. DISCUSSION: In this pooled study, road traffic noise was associated with a higher risk of stroke. This finding supports road traffic noise as an important cardiovascular risk factor that should be included when estimating the burden of disease due to traffic noise.
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
|
|
| 10. |
|
|
