Visit-to-visit body mass index variability in relation to longitudinal cognitive changes in Chinese adults: a retrospective cohort study.

ABSTRACT:

Background

Body mass index (BMI) affects cognitive health throughout life. BMI variability has emerged as a promising indicator for tracking longitudinal changes in BMI. The association of BMI variability with cognitive impairment remains unclear.

Objective

This study investigated the relationship between BMI variability and cognitive outcomes across age groups defined by a 50-year threshold.

Methods

The current study enrolled 1474 participants (> 18 years) from the China Suboptimal Health Cohort Study (COCAS). Various metrics, including the coefficient of variation (CV), standard deviation (SD), variability independent of the mean (VIM), and average real variability (ARV), were used to measure BMI variability. The main clinical outcome was the incidence of cognitive impairment, which was diagnosed via the Mini-Mental State Examination (MMSE). We stratified the subjects into two groups on the basis of age (> 50 years and ≤ 50 years), and multivariable logistic regression analysis was performed to evaluate the association between BMI variability and cognitive changes in these groups. We further used a latent growth curve model (LGCM) to explore the BMI trajectories of these two groups.

Results

Among those age > 50 years at baseline, stratified analysis revealed that the odds ratio (OR) comparing participants in the highest tertile with those in the lowest tertile of CV was 0.45 (95% confidence interval [CI], 0.30 to 0.96; P for trend = 0.002). Consistent results were observed when the BMI variability indices SD, VIM, and ARV were calculated. There was no association between BMI variability and cognitive performance among those age  ≤50 years. LGCM showed a decline in BMI over time among those age > 50 years, whereas an increase in BMI was noted among those age  ≤50 years.

Conclusions

In the older population, higher BMI variability was inversely associated with cognitive impairment risk, which may be partly explained by healthy weight loss patterns in this population.

SUBMITTER: Guo S 

PROVIDER: S-EPMC12487511 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature