• Jillian C Ryan, Mary Barnes, and David N Cox.
• Precision Health Future Science Platform and Health & Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Gate 13 Kintore Avenue, Adelaide, South Australia 5000, Australia. Electronic address: Jillian.Ryan@csiro.au.
• Prev Med. 2021 Dec 1; 153: 106796.

AbstractLifestyle-based disease prevention and self-management strategies play an important role in the mitigation of health, social, and economic burdens associated with type 2 diabetes mellitus (T2DM) and other chronic diseases. However, there are significant implementation and translational challenges associated with the design and delivery of effective interventions. In this study, data-driven techniques for the identification of optimal target audiences and intervention targets for T2DM prevention interventions were applied. Australian adults (N = 3159) with differing T2DM status (no diabetes diagnosis, pre-diabetes, or T2DM) completed self-report assessments of diet quality, physical activity, psychological distress, future orientation, health literacy, and socio-demographic characteristics. K-medoids cluster analysis was conducted to identify homogenous groups within the research sample and proportional odds ordinal logistic regressions conducted to identify signficant predictors of T2DM status within each cluster. Results identified a two-factor optimal solution that stratified participants based on sex (male/female). Within each cluster, psychosocial variables explained approximately 25% of the variance in T2DM status, with future orientation identified as a significant modifiable predictor of T2DM. For the male cluster, health literacy was also significant (p ≤0.01). Findings indicate that men and women should be targeted separately in T2DM prevention or management programs and that future interventional research targeting future orientation is warranted.Copyright © 2021. Published by Elsevier Inc.

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