[Association of body mass index, waist circumference, and body composition with chronic kidney disease among elderly aged 65 years and above in longevity regions of China]

Abstract

Objective: To investigate the associations of body mass index (BMI), waist circumference, and body composition with chronic kidney disease (CKD) among older adults aged≥65 years in longevity regions of China. Methods: This study was based on cross-sectional data from the 2021 wave of the Healthy Ageing and Biomarkers Cohort Study, including 4 781 participants aged≥65 years. Demographic characteristics, lifestyle factors, disease history, as well as BMI, waist circumference, muscle mass, fat mass, body fat percentage, and visceral fat level were collected. Serum creatinine, urinary creatinine, and urinary albumin were measured to calculate estimated glomerular filtration rate (eGFR) and urinary albumin/creatinine ratio (UACR). CKD was defined as eGFR<60 ml·min^-1·(1.73 m²)^-1 or UACR≥30 mg/g. Multivariable logistic regression was used to assess the associations of measurement indicators with CKD prevalence, restricted cubic spline regression was applied to examine dose-response relationship, and multivariable linear regression was conducted to quantify associations of the indices with eGFR. Subgroup analyses were further performed by sex and age. Results: The mean age of the 4 781 participants was (82.8±10.6) years, with 2 254 males (47.1%), and the prevalence of CKD was 36.5% (1 745 cases). The CKD group had higher age and higher prevalence of hypertension, diabetes, and cognitive impairment compared with the non-CKD group (all P<0.001), while their BMI, waist circumference, muscle mass, and fat mass were significantly lower (all P<0.05). Each 1-standard deviation increase in BMI, waist circumference, and muscle mass was associated with 13.3% (OR=1.133, 95%CI: 1.053-1.219), 12.4% (OR=1.124, 95%CI: 1.019-1.241), and 11.2% (OR=1.112, 95%CI: 1.006-1.228) higher risk of CKD, respectively. Each 1-standard deviation increase in BMI and muscle mass was associated with a decrease of 1.386 ml·min^-1·(1.73 m²)^-1 (β=-1.386, 95%CI:-1.826--0.945) and 1.441 ml·min^-1·(1.73 m²)^-1 (β=-1.441, 95%CI:-2.030--0.853) in eGFR levels, respectively. Restricted cubic spline analyses revealed linear positive associations of BMI and muscle mass with CKD risk (P_{for nonlinearity}=0.19 and 0.18, respectively), and a J-shaped positive association between waist circumference and CKD risk (P_{for nonlinearity}=0.016), with the lowest risk at 79.0 cm cut-off value. Subgroup analyses showed that in men, only BMI (OR=1.218, 95%CI: 1.087-1.365) and waist circumference (OR=1.215, 95%CI: 1.033-1.433) were associated with the risk of CKD, whereas in women, only muscle mass (OR=1.157, 95%CI: 1.035-1.294) was associated with CKD risk. In the age-stratified analysis, only in the younger group (age<80 years) were BMI (OR=1.156, 95%CI: 1.020-1.309) and waist circumference (OR=1.378, 95%CI: 1.140-1.673) associated with CKD risk. Conclusion: Higher BMI, waist circumference, and muscle mass are associated with increased CKD risk in older adults, and these associations differ by sex and age groups.