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Updated: Jan 16, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Metabolic health and body mass index phenotypes in adults
Tracey Bushnik1, Rachel Colley1, Joel Barnes1
1Health Analysis and Modelling Division, Statistics Canada.
Background:
To better understand the interplay between adiposity and metabolic health, joint phenotypes have been used to categorize people as being metabolically healthy (MH) or metabolically unhealthy (MU) while having a body mass index (BMI) indicative of obesity, overweight, or normal weight. This study examines the prevalence of these phenotypes in adults, the factors associated with them, and their relationship with adverse health outcomes.
Data And Methods:
Three cycles of the Canadian Health Measures Survey (from 2014 to 2019) were combined to characterize adults aged 20 to 79 years as MU if they had at least three out of five measures of elevated waist circumference, elevated triglycerides, reduced high-density lipoprotein cholesterol, elevated blood pressure, or elevated fasting glucose. Measured BMI, categorized as indicative of normal weight, overweight, or obesity, was combined with MH or MU to produce six joint phenotypes. Phenotype prevalence was examined across selected characteristics and separate multivariable logistic regression models estimated the association with self-reported health status and morbidity indicators.
Results:
One in four Canadian adults was either MU with obesity or MU with overweight. These phenotypes were more prevalent at older ages. Among MH adults, higher BMI was associated with worse self-rated general health. MU adults with obesity were 1.8 times more likely to report worse general health than MH adults with obesity. MU adults with obesity or with overweight were 1.2 times more likely to have higher levels of systemic inflammation than MH adults with obesity or overweight. Higher BMI, regardless of metabolic health, was associated with higher levels of systemic inflammation.
Interpretation:
Gaining insight into the population prevalence of metabolic health and BMI phenotypes and their association with health risks can help improve awareness and inform health promotion strategies.
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