Do we need to think beyond BMI for estimating population-level health risks?

Yorkshire & HumberMetabolic and Endocrine
Published Date: 4 Apr 2016


Body mass index (BMI) is an important tool used by clinicians, epidemiologists and public health officials for the categorization of individuals based upon their relative weight. It has become the most commonly used measure of weight status due to its simplicity of calculation when collecting data for large population surveys. However, BMI is a measure of weight and height and does not directly measure adiposity, limiting its use for measuring levels of obesity.

Waist circumference has been shown to be a more accurate measure of body fat and therefore would offer an alternative to BMI.2 However, this does not mean that BMI should be discounted. It is important to understand how useful BMI is at estimating risk of health outcomes in comparison to waist circumference. This is important as self-reported data are easier to collect and inexpensive for large populations. More precise techniques for measuring obesity are not practical for large epidemiological studies or routine clinical usage. In this study, a comparison of BMI and waist circumference as measures of risk to multiple health outcomes is examined.

Individual-level data were taken from the Yorkshire Health Study (2010–12; n = 18 562, aged 16–85).3 Logistic regression models using BMI and waist circumference separately (both standardized using z-scores to improve their comparability) as explanatory variables against a series of chronic health conditions, illnesses or disabilities (separate outcomes variables). Unadjusted and adjusted models were produced, controlling for the following confounders of poor health: age, sex, ethnicity, deprivation (measured using the Indices of Deprivation 2010), smoking status, alcohol intake (units per week) and physical exercise levels. Data were self-reported.

Dr. Mark Green