The association of weight status with cognitive impairment in the elderly population of a Shanghai suburb

Asia Pac J Clin Nutr. 2013;22(1):74-82. doi: 10.6133/apjcn.2013.22.1.18.

Abstract

Objective: A population-based survey was conducted to analyze the association of under-weight, blood pressure, glucose and lipid metabolism with cognitive impairment in people, 60 years and over, living in 2 towns of Shanghai.

Methods: Face-to-face interviews were carried out to collect relevant information with questionnaires. Anthropometric indices of height, weight, waist circumference (WC) and hip circumference were measured. Multivariable logistic regression analyses were performed to evaluate the association of weight status with cognitive impairment.

Results: Cognitive impairment were diagnosed in 198 (7.0%) of the 2 809 participants. Compared to the normal BMI category, the under-weight category was significantly associated with the risk of cognitive impairment (OR= 2.47, 95%CI: 1.46-5.23). Subjects with a high WC were 1.5 times (OR= 1.42, 95%CI: 1.10-2.67) more likely and subjects with a high WHR were 1.7 times (OR= 1.68, 95%CI: 1.05-2.84) more likely to be associated with cognitive impairment than the subjects in the reference group. This study demonstrates a significant interaction between hypertension, lipid disorder and WC or WHR on the risk of cognitive impairment in a rural population in Shanghai.

Conclusions: Central obesity was significantly associated with the risk of cognitive impairment. A low BMI may be a risk factor for cognitive impairment. A significant interaction between hypertension, lipid disorder and WC or WHR on the risk of cognitive impairment in Shanghai rural population was found.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Blood Pressure
  • Body Mass Index
  • Body Weight*
  • China / epidemiology
  • Cognition Disorders / epidemiology*
  • Cross-Sectional Studies
  • Female
  • Humans
  • Hypertension / epidemiology*
  • Linear Models
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Obesity, Abdominal / epidemiology*
  • Risk Factors
  • Waist Circumference