Background: Little is known regarding the association between weight change and accelerated aging. Objectives: This study aimed to estimate the influence of weight change across adulthood on biological aging acceleration in middle-aged and older adults in the United States. Methods: We used data of 5553 adults (40–84 y) from the National Health and Nutrition Examination Survey 1999–2010. Weight change patterns (i.e., stable normal, maximal overweight, obese to nonobese, nonobese to obese, and stable obese) and absolute weight change groups across adulthood (i.e., from young to middle adulthood, young to late adulthood, and middle to late adulthood) were defined. A biological aging measure (i.e., phenotypic age acceleration [PhenoAgeAccel]) at late adulthood was calculated. Survey analysis procedures with the survey weights were performed. Results: Across adulthood, maximal overweight, nonobese to obese, and stable obesity were consistently associated with higher PhenoAgeAccel. For instance, from young to middle adulthood, compared with participants who had stable normal weight, participants experiencing maximal overweight, moving from the nonobese to obese, and maintaining obesity had 1.71 (standard error [SE], 0.21; P < 0.001), 3.62 (SE, 0.28; P < 0.001), and 6.61 (SE, 0.58; P < 0.001) higher PhenoAgeAccel values, respectively. From young to middle adulthood, relative to absolute weight loss or gain of <2.5 kg, weight loss of ≥2.5 kg was marginally associated with lower PhenoAgeAccel (P = 0.054), whereas an obese to nonobese pattern from middle to late adulthood was associated with higher PhenoAgeAccel (P < 0.001). Conclusions: Maximal overweight, nonobese to obese, and stable obesity across adulthood, as well as an obese to nonobese pattern from middle to late adulthood, were associated with accelerated biological aging. In contrast, weight loss from young to middle adulthood was associated with decelerated biological aging. The findings highlight the potential role of weight management across adulthood for aging. Monitoring weight fluctuation may help identify the population at high risk of accelerated aging.
