AIMSData-driven diabetes subgroups have been proposed as an alternative to address diabetes heterogeneity; changes in trends for these subgroups have not previously been reported. Here, we analyzed trends of diabetes subgroups, stratified by sex, race, education level, and age categories in the U.S.METHODSWe used data from consecutive NHANES cycles spanning the 1988-2018 period. Diabetes subgroups (mild obesity-related [MOD], severe-insulin deficient [SIID], severe-insulin resistant [SIRD], and age-related diabetes [MARD]) were classified using self-normalizing neural networks. SAID was assessed for NHANES-III cycles. Prevalence was estimated using examination sample weights considering 2-year cycles (biannual change [B.C.]) to evaluate trends.RESULTSDiabetes 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 SIID had the highest increase during the studied period. Non-Hispanic Blacks had a sharp increase in MARD and SIID, Mexican Americans in SIID, and non-Hispanic Whites in MARD. Males, subjects with primary school/no-education, and adults aged 40-64 years had the highest increase in MOD prevalence. Trends in diabetes subgroups sustained after stratification by body-mass index categories.CONCLUSIONSThe prevalence of diabetes and its data-driven subgroups in the U.S. has increased from 1988-2018. These trends were different across sex, ethnicities, education, and age categories, indicating significant heterogeneity in diabetes within the U.S. Sex-specific factors, population aging, and socioeconomic aspects, together with obesity prevalence increase, could be implicated in the uprising trends of diabetes in the U.S.RESEARCH IN CONTEXTWhat is already known about this subject?Diabetes is a heterogeneous disease with increasing prevalence worldwide.An approach to characterize diabetes heterogeneity uses data-driven subgroups, including mild obesity-related (MOD), severe-insulin deficient (SIID), severe-insulin resistant (SIRD), severe autoimmune (SAID) and age-related diabetes (MARD).Prevalence trends of data-driven diabetes subgroups in the U.S. remain as an area of opportunity to assess diabetes heterogeneity over time in the U.S.What is the key question?What are the diabetes subgroup prevalence trends in adult subjects from the National Health and Nutrition Examination Survey in the U.S. from 1988 to 2018?What are the new findings?Diabetes prevalence in the U.S. has steadily increased from 1988 to 2018, with Non-Hispanic Blacks and Mexican Americans having the highest diabetes prevalence.MOD, MARD, and SIID had the highest increase during the studied period; SIRD and SAID remained unchanged.Males, subjects with primary school/no-education, and adults aged 40-64 years had sharp increases in MOD.How might this impact on clinical practice in the foreseeable future?The increase in specific diabetes subgroups could help to implement tailored preventive measures depending on age and ethnicity. Targeted treatment and public health measures should be informed using clinical characteristics for each subgroup.