Anthropometric metabolic subtypes and health outcomes: A data‐driven cluster analysis
Authors' conclusion
Anthropometric metabolic subtypes identified with easily accessible parameters reflecting multifaceted pathology of overweight and obesity were associated with distinct risks of long-term adverse health outcomes.
Study context
- Population
- UK Biobank participants; clusters based on waist-to-height ratio, BMI, handgrip strength, TG/HDL-C ratio and neutrophil-to-lymphocyte ratio; replication in NHANESUK Biobank
- Participants
- 397,424 participants
- Exposure
- Anthropometric metabolic clusters 2–6 vs cluster 1
- Outcome
- Incident adverse health outcomes by cluster
Methodological detailsK-means cluster analysis, replication in NHANES, Cox proportional hazards regression
- K-means cluster analysis
- Replication in NHANES
- Cox proportional hazards regression
Main finding
As reported in the abstract
- Six replicable clusters were identified
- Cluster 2 vs 1: no increased all-cause mortality despite higher BMI; small but significant increased risks of CV mortality, incident major adverse cardiovascular events (MACE), chronic renal failure; decreased risks of respiratory-disease mortality and incident dementia
- Clusters 3, 4, 5 and 6 vs 1: substantially increased risks of all-cause, CV and cancer mortality, incident MACE and chronic renal failure
Observational data: associations, not effects.
Further findings
Replication of mortality associations
- Associations of clusters with mortality risk were replicated in the NHANES cohort
Original publication
Anthropometric metabolic subtypes and health outcomes: A data‐driven cluster analysis. Diabetes Obes Metab. Published 28 February 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →