Clustering of obesity-related characteristics and associations with body mass index, waist circumference, and body fatness

Obesity is a leading cause of morbidity and mortality in Canada. The wide range of characteristics associated with obesity suggest there may be distinct subtypes. Understanding these subtypes may be important to tailoring interventions for the treatment and prevention of obesity. The primary objective of this study is to identify the clustering of obesity-related characteristics and to evaluate the association of these distinct obesity-related clusters with body mass index (BMI) and body fatness, among adults in the Canadian Longitudinal Study of Aging (CLSA). The secondary objectives are to evaluate the role of genetics, age and sex differences, and the impact of these obesity-related clusters on healthcare use. A cross-sectional study will be conducted using the CLSA comprehensive cohort. Given the rigorous methodology and comprehensive data collection from the CLSA, this study will be in the unique position to evaluate the complexity of obesity in Canada at the population level.

The findings from this research provided important insights regarding the wide variation in body size measures and health impacts among people with obesity. This research also highlights the limitations of measurements based only on body size, such as body mass index (BMI) and waist circumference (WC) to define obesity. There are several key findings to highlight. First, we compared BMI and WC to more sophisticated measures of body fat obtained through DXA scans, and our results revealed that: a) the proportion of people considered to have obesity varies substantially depending on the measure used (BMI, WC or body fat), and b) there is substantial misclassification across measures. For example, people with high body fat were frequently misclassified as not having obesity when defined based on BMI. Second, all measures of obesity were strongly associated with increased healthcare utilization among middle-aged but not older adults. Third, we investigated the clustering of obesity-related risk factors, and we identified 6 distinct classes of obesity-related characteristics, these included unique clusters based on metabolic, cardiovascular, and mental health, plus a high-risk cluster of people with numerous obesity-related health concerns. Only 40% of study participants were in the low-risk or ‘healthy’ group based on obesity risk factors. This research has informed additional studies to improve the measurement of obesity in Canada and understand how obesity impacts on aging.