Identifying Patterns of Lifestyle Behaviors among People with Type 2 Diabetes in Tianjin, China: A Latent Class Analysis

Abstract

Introduction: Lifestyle behaviors are essential elements of diabetes care. The aims of this study were to identify distinct subgroups of people with type 2 diabetes based on personal levels of lifestyle behaviors and explore the different characteristics across these subgroups. Methods: In 2015 and 2016, 1504 outpatients with a diagnosis of type 2 diabetes were selected via two-stage simple random sampling from 10 municipal district hospitals in Tianjin. Participants accepted an invitation by experienced physicians to complete a questionnaire containing demographic and lifestyle content. Clinical data were collected by reviewing medical records. Latent class analysis was applied to identify patterns of lifestyle behaviors. Multinomial logistic regression was used to investigate the characteristics of the subgroups. Results: The final model yielded a four-class solution: the healthy behavioral group, unhealthy diet and less activity group, smoking and drinking group, and sedentary and extremely inactive group. Further analysis found that variables, including age, sex, general/central obesity, treatment modalities, glycemic control, diabetes duration, and diabetes-related complications and comorbidities, were disproportionately distributed across the four latent classes (P < 0.05). Participants in the unhealthy diet and less activity group were more likely to have a longer duration of diabetes, poor glycemic control and more diabetes-related diseases relative to the other three latent classes. Conclusions: Identification and characterization of subgroups based on lifestyle behaviors in individuals with type 2 diabetes can help health care providers to shift to targeted intervention strategies.