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• Studies using strict definitions to investigate the association between metabolic phenotypes (MP) and diabetes are scarce. • Participants with obesity/healthy MP were not at increased diabetes risk compared to the ones with normal weight/healthy MP. • Reduced grip strength was associated with a higher risk of diabetes incidence in the long-term. • High grip strength attenuated the risk associated with metabolically unhealthy phenotypes. The association of diabetes risk in the long-term, metabolic phenotypes (MP) and muscle strength is unclear. We aimed to investigate the association between strictly defined MP, grip strength (GS) and diabetes. MP were defined according to BMI and presence of any individual metabolic abnormality for ≥18 years, in participants of the North West Adelaide Health Study (Australia) free of diabetes at baseline. The association of MP and dominant hand GS with incident diabetes over 15-years follow-up and the moderation effect of GS on the association between diabetes and MP were investigated by logistic regression models. Of 3039 participants followed over 13.3 years (SD 2.6), 236 (7.8%) developed diabetes. Compared to the metabolically healthy (MH) normal weight phenotype, the metabolically unhealthy (MU) overweight (OR 6.15, 95%CI 2.43–15.59) and obese (OR 12.32, 95%CI 4.97–30.52) phenotypes were associated with a high risk of diabetes, but not the MU normal weight (OR 1.73, 95%CI 0.57–5.25), MH overweight (OR 1.15, 95%CI 0.31–4.31) or MH obese phenotypes (OR 0.77, 0.07–8.89). GS was inversely associated with diabetes (OR 0.97, 95% CI 0.95–0.99) and attenuated the risk associated with MU overweight (beta = −0.296, p = 0.039) and MU normal weight (beta = −0.773; p for interaction = 0.009). Strictly defined MP (rather than based on metabolic syndrome criteria) and GS, a proxy of muscle strength, might be useful for stratifying the risk of diabetes in the long-term. Improving muscle strength might be an important strategy to reduce diabetes risk. [ABSTRACT FROM AUTHOR]

Purpose: The relative advantages of dietary analysis methods, particularly in identifying dietary patterns associated with bone mass, have not been investigated. We evaluated principal component analysis (PCA), partial least-squares (PLS) and reduced-rank regressions (RRR) in determining dietary patterns associated with bone mass.Methods: Data from 1182 study participants (45.9% males; aged 50 years and above) from the North West Adelaide Health Study (NWAHS) were used. Dietary data were collected using a food frequency questionnaire (FFQ). Dietary patterns were constructed using PCA, PLS and RRR and compared based on the performance to identify plausible patterns associated with bone mineral density (BMD) and content (BMC).Results: PCA, PLS and RRR identified two, four and four dietary patterns, respectively. All methods identified similar patterns for the first two factors (factor 1, “prudent” and factor 2, “western” patterns). Three, one and none of the patterns derived by RRR, PLS and PCA were significantly associated with bone mass, respectively. The “prudent” and dairy (factor 3) patterns determined by RRR were positively and significantly associated with BMD and BMC. Vegetables and fruit pattern (factor 4) of PLS and RRR was negatively and significantly associated with BMD and BMC, respectively.Conclusions: RRR was found to be more appropriate in identifying more (plausible) dietary patterns that are associated with bone mass than PCA and PLS. Nevertheless, the advantage of RRR over the other two methods (PCA and PLS) should be confirmed in future studies. [ABSTRACT FROM AUTHOR]