Over time, do anthropometric measures still predict diabetes incidence in chinese han nationality population from chengdu community?

Abstract

Objective. To examine whether anthropometric measures could predict diabetes incidence in a Chinese population during a 15-year follow-up. Design and Methods. The data were collected in 1992 and then again in 2007 from the same group of 687 individuals. Waist circumference, body mass index, waist to hip ratio, and waist to height ratio were collected based on a standard protocol. To assess the effects of baseline anthropometric measures on the new onset of diabetes, Cox's proportional hazards regression models were used to estimate the hazard ratios of them, and the discriminatory power of anthropometric measures for diabetes was assessed by the area under the receiver operating curve (AROC). Results. Seventy-four individuals were diagnosed with diabetes during a 15-year follow-up period (incidence: 10.8%). These anthropometric measures also predicted future diabetes during a long follow-up (P < 0.001). At 7-8 years, the AROC of central obesity measures (WC, WHpR, WHtR) were higher than that of general obesity measures (BMI) (P < 0.05). But, there were no significant differences among the four anthropometric measurements at 15 years. Conclusions. These anthropometric measures could still predict diabetes with a long time follow-up. However, the validity of anthropometric measures to predict incident diabetes may change with time.

Figure 1

The flow chart of the study.

Figure 2

Cumulative incidence of DM in different anthropometric variables groups in multivariate COX-regression in Model 2. Model 2 adjusted for age, sex, smoking, alcohol intake, regular physical exercise, family history of diabetes, SBP, HDL, TG, and FPG. SBP = systolic blood pressure, HDL-C = high density lipoprotein cholesterol, TG = triglyceride, and FPG = fasting plasma glucose.