Prevalence trends of diabetes subgroups in US: A data-driven analysis spanning three decades from NHANES (1988-2018)

ABSTRACT AIMS Data-driven diabetes subgroups were proposed as an alternative to address diabetes heterogeneity. However, changes in trends for these subgroups have not been reported. Here, we analyzed trends of diabetes subgroups, stratified by sex, race, education level, age categories and time since diabetes diagnosis in the U.S. METHODS We used data from consecutive NHANES cycles spanning the 1988-2018 period. Diabetes subgroups (mild obesity-related [MOD], severe-insulin deficient [SIDD], severe-insulin resistant [SIRD], and mild age-related diabetes [MARD]) were classified using validated self-normalizing neural networks. Severe autoimmune-diabetes (SAID) was assessed for NHANES-III. Prevalence was estimated using examination sample weights considering bi-cyclic changes (BC) to evaluate trends and changes over time. RESULTS Diabetes prevalence in the US increased from 7.5% (95%CI 7.1-7.9) in 1988-1989 to 13.9% (95%CI 13.4-14.4) in 2016-2018 (BC 1.09%, 95%CI 0.98-1.31, p<0.001). Non-Hispanic Blacks had the highest prevalence. Overall, MOD, MARD, and SIDD had an increase during the studied period. Particularly, Non-Hispanic Blacks had sharp increases in MARD and SIDD, Mexican Americans in SIDD, and non-Hispanic Whites in MARD. Males, subjects with secondary/high school, and adults aged 40-64 years had the highest increase in MOD prevalence. Trends in diabetes subgroups sustained after stratifying time since diabetes diagnosis. CONCLUSIONS Prevalence of diabetes and its subgroups in the U.S. have increased from 1988-2018. These trends were different across sex, ethnicities, education, and age categories, indicating significant heterogeneity in diabetes within the U.S. Obesity burden, population aging, socioeconomic disparities, and lifestyle aspects could be implicated in the uprising trends of diabetes in the U.S.