Relationship between obesity-related anthropometric indicators and cognitive function in Chinese suburb-dwelling older adults

Weibo Ma; Hui Zhang; Ning Wu; Yuewen Liu; Peipei Han; Feng Wang; Jingru Wang; Fandi Xie; Shumeng Niu; Hao Hu; Chenyu Zhang; Nuo Chen; Yichen Zhang; Qi Guo; Ying Yu

doi:10.1371/journal.pone.0258922

Relationship between obesity-related anthropometric indicators and cognitive function in Chinese suburb-dwelling older adults

PLoS One. 2021 Oct 27;16(10):e0258922. doi: 10.1371/journal.pone.0258922. eCollection 2021.

Authors

Weibo Ma^{1

2}, Hui Zhang³, Ning Wu¹, Yuewen Liu¹, Peipei Han¹, Feng Wang¹, Jingru Wang¹, Fandi Xie³, Shumeng Niu³, Hao Hu³, Chenyu Zhang¹, Nuo Chen¹, Yichen Zhang¹, Qi Guo¹, Ying Yu¹

Affiliations

¹ Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences, Shanghai, China.
² Department of Economics and Management, East China Normal University, Shanghai, China.
³ Department of Rehabilitation Clinic, Shanghai Jiangwan Hospital, Shanghai, China.

Abstract

Background: Studies relating obesity to cognition in older people show conflicting results, which may be explained by the choice of obesity indicators.

Objectives: This study aimed to investigate the relationship between obesity-related indicators and cognitive impairment, especially between different age or gender subgroups, and explore whether obesity-related indicators were related to specific cognitive domains.

Methods: This was a cross-sectional study on 1753 participants aged ≥ 60 years (41.0% men; aged 71.36 ± 5.96 years). Obesity-related indicators included body mass index (BMI), waist circumference (WC), calf circumference (CC), waist to hip ratio (WHR), waist to calf circumstance ratio (WCR), fat to fat-free mass ratio (FM/FFM). The Mini-Mental State Examination scale (MMSE) was used to assess cognitive function. Cognitive impairment was defined as a score ≤ 17 for illiterates, ≤ 20 for participants with primary school education, and ≤ 24 for those with junior high school degrees or above. Multiple logistic regression analysis was used to estimate multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Restricted cubic splines were used to analyze and visualize the linear relationships.

Results: The prevalence of cognitive impairment was 18.77%. In the fully adjusted model, CC was negatively associated with cognitive impairment (OR = 0.94, 95% CI: 0.90-0.98). Further analysis showed that CC correlated positively with recall and place orientation. A higher FM/FFM was found to be associated with a higher prevalence of cognitive impairment (OR: 1.44, 95%CI: 0.88-2.35, P for trend = 0.029); this association was notable in women (P for trend = 0.002) and the oldest (P for trend = 0.009), and so did the potential effect of BMI on cognitive impairment (70-80 years: P for trend = 0.011; ≥ 80 years: P for trend = 0.013). No statistically significant association was found between cognitive impairment and WC, WHR, or WCR.

Conclusion: CC and FM/FFM were associated with cognitive impairment in older people. Future research needs to distinguish the effects of fat and muscle mass on cognitive function, with special attention to different ages and genders.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Body Weights and Measures / methods*
China / epidemiology
Cognitive Dysfunction / epidemiology*
Cross-Sectional Studies
Female
Humans
Male
Obesity / epidemiology*
Risk Factors

Grants and funding

The study was funded by Shanghai Sailing Program (20YF1418200). The organization that funded our research was Shanghai Education Science Committee, which gave us a grant of 200,000 RMB. The cost of consumables for anthropometry comes from the funds provided by Shanghai Education Science Committee. There are not any authors who received a salary from my funder. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.