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

Abstract

Abstract 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 =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.

Keywords

• cardiometabolic risk
• clustering
• diabetes
• health behaviors
• latent class