Clustering of health behaviors and their associations with cardiometabolic risk factors among adults at high risk for type 2 diabetes in India: A latent class analysis.

BACKGROUND:We aimed to identify clusters of health behaviors and study their associations with cardiometabolic risk factors in adults at high risk for type 2 diabetes in India. METHODS:Baseline data from the Kerala Diabetes Prevention Program (n = 1000; age 30-60 years) were used for this study. Information on physical activity (PA), sedentary behavior, fruit and vegetable intake, sleep, and alcohol and tobacco use was collected using questionnaires. Blood pressure, waist circumference, 2-h plasma glucose, high-density lipoprotein and low-density lipoprotein cholesterol, and triglycerides were measured using standardized protocols. Latent class analysis was used to identify clusters of health behaviors, and multilevel mixed-effects linear regression was employed to examine their associations with cardiometabolic risk factors. RESULTS:Two classes were identified, with 87.4% of participants in class 1 and 12.6% in class 2. Participants in both classes had a high probability of not engaging in leisure-time PA (0.80 for class 1; 0.73 for class 2) and consuming <5 servings of fruit and vegetables per day (0.70 for class 1; 0.63 for class 2). However, participants in class 1 had a lower probability of sitting for >=3 h per day (0.26 vs 0.42), tobacco use (0.10 vs 0.75), and alcohol use (0.08 vs 1.00) compared to those in class 2. Class 1 had a significantly lower mean systolic blood pressure (β = -3.70 mm Hg, 95% confidence interval [CI] -7.05, -0.36), diastolic blood pressure (β = -2.45 mm Hg, 95% CI -4.74, -0.16), and triglycerides (β = -0.81 mg/dL, 95% CI -0.75, -0.89). CONCLUSION:Implementing intervention strategies, tailored to cluster-specific health behaviors, is required for the effective prevention of cardiometabolic disorders among high-risk adults for type 2 diabetes.