Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study

Abstract

Aims/hypothesis: We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later.

Methods: Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC.

Results: The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age(2) and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity.

Conclusions/interpretation: These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes.

Keywords: Environment; Genes; Obesity; Predictors; Type 2 diabetes.

Fig. 1

AUCs for incidence of (a) obesity, (b) type 2 diabetes, (c) IFG and (d) IGT. Solid line, genetic model; dashed line, lifestyle model; dotted line, combined model

Fig. 2

ORs (95% CI) for incidence of (a) obesity, (b) type 2 diabetes, (c) IFG and (d) IGT. Smoking status: non-smokers vs current smokers; education: school vs university education; physical activity: inactive vs active; alcohol intake, GRSs and diet scores: 1st vs 4th quartiles