Table1_Association between dynamic change patterns of body mass or fat mass and incident stroke: results from the China Health and Retirement Longitudinal Study (CHARLS).docx

ObjectiveTo assess the association between dynamic patterns of change in body mass or fat mass and stroke.MethodsA population-based cohort of participants was selected from the China Health and Retirement Longitudinal Study (CHARLS). Body mass and fat mass were measured using obesity-related indices, including weight, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), lipid accumulation product (LAP), and visceral adiposity index (VAI). Five changed patterns were defined: low-stable, decreasing, moderate, increasing, and persistent-high. Logistic regression analysis was performed to evaluate the association between obesity-related indices and stroke.ResultsA total of 5,834 participants were included, and the median age was 58.0 years. During a 7-years follow-up period, 354 (6.1%) participants developed stroke. The baseline levels of obesity-related indices were significantly associated with incident stroke. Regarding the dynamic change patterns, the low-stable pattern carried the lowest odds for stroke and the persistent-high pattern had the highest odds for stroke, with odds ratios of all the indices ranging from 1.73 to 3.37 (all P

研究目标：评估身体质量或脂肪质量动态变化模式与中风之间的关联。研究方法：从中国健康与养老追踪调查（CHARLS）中选取了一组基于人群的队列参与者。通过肥胖相关指标，包括体重、身体质量指数（BMI）、腰围（WC）、腰高比（WHtR）、脂质堆积产物（LAP）和内脏脂肪指数（VAI）来测量身体质量和脂肪质量。定义了五种变化模式：低稳定型、下降型、中稳定型、上升型和持续高值型。采用逻辑回归分析评估肥胖相关指标与中风之间的关联。研究结果：共有5,834名参与者被纳入研究，中位年龄为58.0岁。在7年的随访期间，354（6.1%）名参与者发生了中风。肥胖相关指标的基础水平与中风事件的发生显著相关。在动态变化模式方面，低稳定型具有最低的中风发生几率，而持续高值型具有最高的中风发生几率，所有指标的几率比范围为1.73至3.37（所有P值均小于0.05）。