Joint Associations of Intensity-Specific Physical Activity and Adiposity With Incident Microvascular Disease Among Prediabetes: A Prospective Cohort Study.

Journal: Journal of physical activity & health
Published Date: Oct 29, 2025

Abstract

BACKGROUND: To examine the independent, stratified, and joint associations of physical activity (PA) and adiposity with microvascular diseases (MVDs) in prediabetes. METHODS: This cohort study included 9063 prediabetic individuals from the UK Biobank. Total PA, light-intensity PA, moderate- to vigorous-intensity PA, and vigorous-intensity PA were measured by wrist-worn AX3 accelerometers and determined through a machine learning approach. Moderate- to vigorous-intensity PA was categorized by the guideline (≥150 min/wk), and the others were categorized by tertiles. Body fat percentage (BF) was measured by bioimpedance and divided into low and high groups according to sex-specific medians. Cox proportional hazards models were used. RESULTS: During a median follow-up of 8.0 years, 700 cases of MVDs were documented. Recommended moderate- to vigorous-intensity PA and high vigorous-intensity PA (median = 18 min/wk) were associated with reduced risks of MVDs across all BF levels, but the protective association of light-intensity PA was only observed in the low BF group (hazard ratio: 0.67; 95% CI, 0.49-0.91). Joint analyses showed that the lowest risks of MVDs were observed in combinations of low BF and high PAs. The findings had no substantial change using body mass index as an indicator of adiposity. CONCLUSIONS: The findings suggested that short-time vigorous-intensity PA (approximate 18 min/wk) may reduce the risk of MVDs in all strata of adiposity, whereas the protective role of high light-intensity PA was mainly prominent in those with low adiposity among prediabetes. These findings highlighted the need to personalize PA advice combined with adiposity management to improve microvascular health.

Authors

  • Lan Yu
    School of Science, China Pharmaceutical University, Nanjing 210009, China.
  • Yinyue Liu
    Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, TJ, China.
  • Xiaolong Xing
    Tianjin Key Laboratory of Food Science and Health, School of Medicine, Nankai University, Tianjin, TJ, China.
  • Meng Wang
    State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150001, China.
  • Bowei Zhang
    Shanghai Key Laboratory of Intelligent Sensing and Detection Technology, School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China.
  • Zonghang Tong
    Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, TJ, China.
  • Guangbin Sun
    Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, TJ, China.
  • Qiang Zhang
    Yunan Provincial Center for Disease Control and Prevention, Kunming 650022, China.
  • Jie V Zhao
    School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, HK, China.
  • Xumei Zhang
    School of Automobile and Traffic Engineering, Wuhan University of Science and Technology, Wuhan 430081, China.
  • Xueli Yang
    Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, 22 Qixiangtai Rd, Tianjin 300070, People's Republic of China.

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