Analysis and Future Trend Prediction of Disease Burden of Elderly Type 1 Diabetes Mellitus in China and Globally from 1990 to 2021

Background Type 1 diabetes mellitus (T1DM) predominantly affects adolescents, drawing substantial research focus. Conversely, older adults with T1DM receive relatively little attention and research. Consequently, disease burden data for this population are scarce and urgently require filling. Objective To assess the disease burden and projected trends of T1DM among the elderly (age≥60 years) from 1990 to 2021, thereby providing essential evidence for public health decision-making. Methods Data on the incidence and disability-adjusted life years (DALYs) associated with T1DM in the elderly were extracted from the Global Burden of Disease (GBD) 2021 database from 1990 to 2021, focusing on globally, China, and five sociodemographic index (SDI) regions. Taking the GBD 2021 standard population as the reference, age-standardized incidence and DALY rates for elderly individuals with T1DM were calculated based on the direct standardization method. The trend of disease burden was analyzed via Joinpoint regression, with results reported as average annual percent change (AAPC). Subgroup analyses stratified the disease burden by age and sex, respectively. Additionally, a three-factor decomposition method was employed to dissect the relative influences of aging, population growth, and epidemiological change on the shifts in disease burden. Finally, a Bayesian model was utilized to forecast the disease burden of elderly T1DM from 2022 to 2040. Results In 2021, the global and Chinese incidence of T1DM stood at 42 330 and 3 049 cases, respectively, representing increases of 199.47% and 427.50% compared to 1990. The total DALYs of the elderly T1DM reached 659 117 person-years globally and 57 663 person-years in China in 2021, marking increases of 91.80% and 78.25%, respectively, since 1990. Age-standardized DALYs rate exhibited a downward trend globally and within China from 1990 to 2021, with statistically significant differences (P