Latent Class Trajectory Analysis of Risk Factors Uncovers Progression to Type 2 Diabetes

Autor: Qilu Yu, Maurice C. Johnson, Howard A. Fishbein, Rebecca J. Birch, Xiaoshu Zhu, Russ Mardon, Wilson Pace, Holly L. Sawyer, Sunitha M. Mathew, Lori S. Merrill, Keith D. Umbel, Sophia Jang
Rok vydání: 2021
Zdroj: Journal of Endocrinological Science. 3:26-35
ISSN: 2767-5157
DOI: 10.29245/2767-5157/2021/1.1118
Popis: We identified trajectories of diabetes risk factors in the Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) cohort analyzing 8 years of electronic health records on 1.4 million patients, and investigated associations between trajectories and progression to new onset Type 2 diabetes. Design and Methods: Analyzing LEADR data (2010-2016), we applied Latent Class Trajectory Analysis (LCTA) to classify patterns of risk factor change. There were 824,043 patients with BMIs; 955,128 patients with systolic blood pressures; 957,491 patients with diastolic blood pressures; 300,137 patients with HDLs; 267,553 patients with non-HDL cholesterols; and 297,026 patients with triglycerides. Patients had to have data for all risk factors being assessed. Association between trajectories and incidence of type 2 diabetes for 94,551 patients was assessed using negative binomial regression analysis. Results: Compared to a static BMI trajectory, those with a sustained weight increase (25%+ from starting BMI) were at higher risk of type 2 diabetes over 4.8 years of follow-up (range 2.0 to 8.0 years) (adjusted rate ratios ranged 1.53-1.62, p-value
Databáze: OpenAIRE