Data‐driven cluster analysis of adults with prediabetes: Findings from the Japan diabetes prevention study

Puntos clave

• The aim is to identify biologically distinct subtypes of prediabetes and their association with diabetes risk and intervention responses.
• Performed unsupervised clustering analysis on data from the Japan diabetes prevention study.
• Categorized adults with prediabetes into different subtypes based on biological characteristics.
• Evaluated differences in diabetes risk and intervention response among identified subtypes.
• Identified three distinct prediabetic subtypes with varying diabetes risk levels.
• Each subtype demonstrated different responses to intervention strategies.
• Findings support the need for precision prevention tailored to specific subtypes.