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

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 < 0.05). The increasing pattern was also associated with a higher odds of stroke, whereas the moderate pattern of weight, BMI, and WHtR was comparable to the low-stable pattern in terms of stroke.ConclusionCurrent status and dynamic changes in body mass and fat mass were significantly associated with incident stroke. Maintaining the low-stable pattern of body mass and fat mass as measured by weight, WC, BMI, WHtR, LAP, and VAI may be an alternative strategy for primary stroke prevention