• Preventive medicine · Dec 2021

    Clustering of obesity-related characteristics: A latent class analysis from the Canadian Longitudinal Study on Aging.

    • Alessandra T Andreacchi, Urun Erbas Oz, Carol Bassim, Lauren E Griffith, Alexandra Mayhew, Marie Pigeyre, Saverio Stranges, Chris P Verschoor, and Laura N Anderson.
    • Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main St. West, Hamilton, Ontario L8S 4L8, Canada.
    • Prev Med. 2021 Dec 1; 153: 106739.

    AbstractMeasures of obesity, including body mass index (BMI) and waist circumference (WC), do not fully capture the complexity of obesity-related health risks. This study identified distinct classes of obesity-related characteristics and evaluated their associations with BMI, WC, and percent body fat (%BF) using cross-sectional data from 30,096 participants aged 45-85 in the Canadian Longitudinal Study on Aging (2011-2015). Sixteen obesity-related variables, including behavioural, metabolic, physical health, and mental health/social factors, were included in a latent class analysis to identify distinct classes of participants. Adjusted odds ratios (OR) were estimated from logistic regression for associations between each class and obesity defined by BMI, WC and %BF. Six latent classes were identified: "low-risk" (39.8%), "cardiovascular risk" (19.4%), "metabolic risk" (16.9%), "sleep and mental health risk" (12.1%), "multiple and complex risk" (6.7%), and "cardiometabolic risk" (5.1%). Compared to "low-risk", all classes had increased odds of BMI-, WC- and %BF-defined obesity. For example, the "complex and multiple risk" class was associated with obesity by BMI (OR: 10.70, 95% confidence interval (CI): 9.51, 12.04), WC (OR: 9.21, 95% CI: 8,15, 10,41) and %BF (OR: 7.54, 95% CI: 6.21, 9.16). Distinct classes of obesity-related characteristics were identified and were strongly associated with obesity defined by multiple measures.Copyright © 2021 Elsevier Inc. All rights reserved.

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