Lifestyle patterns and incident type 2 diabetes in the Dutch lifelines cohort study

Ming-Jie Duan; Louise H Dekker; Juan-Jesus Carrero; Gerjan Navis

doi:10.1016/j.pmedr.2022.102012

Lifestyle patterns and incident type 2 diabetes in the Dutch lifelines cohort study

Prev Med Rep. 2022 Oct 3:30:102012. doi: 10.1016/j.pmedr.2022.102012. eCollection 2022 Dec.

Authors

Ming-Jie Duan¹, Louise H Dekker^{1

2}, Juan-Jesus Carrero³, Gerjan Navis¹

Affiliations

¹ Department of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands.
² National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
³ Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Abstract

We aimed to identify the underlying subgroups of the population characterized by distinct lifestyle patterns, and to investigate the associations between lifestyle patterns and risk of incident type 2 diabetes. Using data from the Dutch Lifelines cohort study, latent class analysis was performed to derive lifestyle patterns on five lifestyle factors, i.e., smoking, diet quality, TV watching time, physical activity level, and risk drinking. Associations between lifestyle patterns and incident type 2 diabetes were estimated. Among 61,869 participants analyzed, we identified 900 cases of type 2 diabetes during follow-up (205,696 person-years; incidence rate 4.38 per 1000 person-years). Five lifestyle pattern groups were identified. Using the "healthy lifestyle group" as reference, the "unhealthy lifestyle group" had the highest risk for type 2 diabetes (HR 1.51 [95%CI 1.24, 1.85]), followed by the "poor diet and low physical activity group" (HR 1.26 [95%CI 1.03, 1.55]). The "risk drinker group" and the "couch potato group" (characterized by excessive TV watching) showed no significantly elevated risk. These models were adjusted for age, sex, total energy intake, education, BMI, family history of diabetes, and blood glucose level at baseline. Our study shows that lifestyle factors tended to cluster in unique behavioral patterns within the heterogeneous population. These lifestyle patterns were differentially associated with incident type 2 diabetes. Our findings support the relevance of considering lifestyle patterns in type 2 diabetes prevention. Tailored prevention strategies that target multiple lifestyle risk factors for different lifestyle pattern groups may optimize the effectiveness of diabetes prevention at the population level.

Keywords: BIC-LL, Bayesian information criterion with log likelihood for the number of parameters adjusted; Epidemiology; FFQ, Food frequency questionnaire; LCA, Latent class analysis; LLDS, Lifeline diet score; Lifestyle; Lifestyle patterns; MVPA, Moderate-to-vigorous physical activity; PAF, Population attributable fraction; Public health; SQUASH, Short QUestionnaire to ASsess Health-enhancing physical activity; Type 2 diabetes.