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

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. Multi-nomial 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.