Epidemiological and Demographic Drivers of Ischemic Stroke attributed to High Fasting Plasma Glucose from 1990 to 2021: Findings from the 2021 Global Burden of Disease Study

Yanwen Dong¹Yangyang Wang^2,3Xiaomei Lan^1,4Huiyan Zeng^5*

• ¹Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, China
• ²The Second Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China
• ³Department of Teaching and Research, Huizhou Third People's Hospital, Guangzhou Medical University, Huizhou, Guangdong Province, China
• ⁴Liwan District People's Hospital of Guangzhou, Guangzhou, Guangdong Province, China
• ⁵The Second Affiliated Hospital, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China

Background: This study aims to analyze the global, regional, and national burden of Ischemic Stroke (IS) attributed to High Fasting Plasma Glucose (HFPG) from 1990 to 2021, identify risk sources in different areas, and develop a platform to assess the disease burden in 204 countries and regions. Methods: Using data from the 2021 Global Burden of Disease study, we analyzed IS-related deaths and disability-adjusted life years (DALYs) attributed to hyperglycemia from 1990 to 2021. We conducted detailed analyses by region, gender, and age. In different Socio-demographic Index (SDI) regions, we used the Age-Period-Cohort (APC) model to evaluate the impact of age, cohort, and period on Age-Standardized Mortality Rate (ASMR) and decomposition analysis to separate the contributions of population, ageing, and epidemiological changes. A visualization platform was built using the Shiny package. Results: In 2021, approximately 18% of all IS-related DALYs and deaths were attributed to HFPG, with an annual percentage change (EAPC) in DALYs of -0.715 (-0.811, -0.620) and deaths of -0.959 (-1.059, -0.859). The primary mortality group was aged 80-84. ASMR, categorized by SDI, showed increases in Low-middle SDI: 0.482 (0.422, 0.542) and Low SDI: 0.287 (0.218, 0.356), particularly in Central Asia, East Asia, North Africa and Middle East, and South Asia. The APC model indicates that age is the primary source of burden in High, High-middle, and Middle SDI regions, with ASMR trends improving over the last five years, contrary to trends in Low-middle and Low SDI regions. Decomposition analysis suggests that ageing and epidemiological changes in High-middle and High SDI regions outweigh population growth. In contrast, in low, low-middle, and middle SDI regions, the population remains the most significant influence, with the impact of ageing increasing. The HFPG-IS platform is accessible at http://116.196.73.86:3838/GBD/HFPG-IS/. Conclusion: There is a significant imbalance in IS health attributed to HFPG globally. In low SDI regions, larger populations face more uneven healthcare distribution, necessitating improvements in healthcare infrastructure, especially in areas like the United Arab Emirates. There should be a focus on metabolic adjustments and attention to high-risk groups, such as those aged 80-84, to reduce health losses.