Long-term predictors of insulin resistance: role of lifestyle and metabolic factors in middle-aged men.
OBJECTIVE
Predictors of insulin resistance have hitherto only been examined in cross-sectional studies without information on lifestyle factors. Few researchers have measured insulin sensitivity directly and compared different metabolic and lifestyle predictors in a large population.


METHODS
Our aim was to investigate independent long-term predictors of insulin sensitivity in a large population-based sample (the Uppsala Longitudinal Study of Adult Men cohort) of 50-year-old men who underwent a euglycemic clamp 20 years later (n = 770). Subjects with diabetes and treatment of cardiovascular disease at baseline were excluded. In linear regression models, metabolic (BMI, triglycerides, HDL cholesterol, glucose, and blood pressure) and lifestyle factors (physical activity, smoking, saturated fat biomarkers, and socioeconomic status) were independent variables at baseline (age 50 years) and insulin sensitivity-dependent variables at follow-up (age 70 years). A subsample of only normal-weight men from the initial population was also examined (n = 440).


RESULTS
BMI was the strongest predictor of insulin sensitivity even after addition of metabolic factors. One SD (+/-2.8) increase in BMI corresponded to a mean 19% decrease in insulin sensitivity. After addition of lifestyle factors, all factors except triglycerides and smoking were significant predictors. BMI remained the strongest predictor (beta = -0.67 [95% CI -0.83 to -0.51], P < 0.0001) followed by physical activity, HDL cholesterol, saturated fat, and socioeconomic status (all P < 0.05). BMI remained the strongest predictor in normal-weight subjects also (P < 0.001). In addition, after adjustment for baseline insulin concentrations, BMI remained the strongest predictor (P < 0.001).


CONCLUSIONS
Multiple factors, including novel factors such as saturated fat and socioeconomic status, independently predict insulin sensitivity after 20 years. BMI is, however, the single strongest predictor, even in normal-weight subjects.
Risérus
Ulf
U
Clinical Nutrition and Metabolism, Department of Public Health and Caring Sciences, Uppsala Science Park, 751 85 Uppsala, Sweden. ulf.riserus@pubcare.uu.se
Arnlöv
Johan
J
Berglund
Lars
L
D000368:Aged; D001794:Blood Pressure; D015992:Body Mass Index; D015331:Cohort Studies; D015309:Glucose Clamp Technique; D006306:Health Surveys; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance / Q000502:physiology*; D008019:Life Style; D008055:Lipids / Q000097:blood; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D013548:Sweden
D007328:Insulin; D008055:Lipids