By Caitlin Dow, Student Blogger
As Cyndi Thomson, PhD, RD, a professor in the College of Public Health at the University of Arizona points out, “BMI was meant for population evaluation and we keep applying it to individuals.” BMI is useful when we study populations. It predicts risk for development of a number of chronic diseases (2). However, applying BMI to individuals, which is likely not what Quetelet had in mind when he created it, creates a number of issues. While BMI correlates well with fat mass on a population (but not necessarily on an individual level), it certainly does not consider distribution of fat. This is important because plenty of data indicate that abdominal fat predisposes people to a number of health risks more so than fat distributed evenly throughout the body (2). Furthermore, associations between BMI and various outcomes like risk for disease or mortality are assumed to be linear. That is, as BMI increases, risk for disease also increases. However, some cross-sectional, epidemiological studies have shown a “U-shaped” relation between BMI and mortality (3,4), meaning that people with very low or very high BMIs are at elevated risk of dying within a given period of time than those in the middle (generally overweight) range. The increased mortality risk with normal BMIs later in life is actually probably due to smoking or weight loss due to disease (like cancer), but this hasn’t stopped the media from concluding that “being overweight is good for you!” Due to these shortcomings of BMI, it is high time to consider/develop some type of index that (a) has a linear relation with mortality for ease of interpretation; (b) considers fat mass and/or distribution; and (c) can be used easily in both research and clinical settings.
To address this need, new adiposity indices are being studied that may provide more clinical and scientific utility than BMI. A body shape index (ABSI) considers waist circumference (a surrogate measure of abdominal adiposity), adjusted for height and weight and was first developed by Krakauer, et al (5). Cyndi Thomson and colleagues recently published a paper in Obesity evaluating the relation between ABSI and mortality risk in a very large cohort study (6). The analysis included over 77,500 postmenopausal women enrolled in the Women’s Health Initiative Observational Study. Anthropometrics were measured at baseline and the women were followed for an average of 13.5 years. Similar to previous findings, a U-shaped association between BMI and mortality was demonstrated. However, ABSI was strongly and positively associated with mortality, such that those in the highest quintile of ABSI had a 37% increased risk of death compared with those in the lowest quintile.
I discussed the implications of these findings with Dr. Thomson over the phone. The results from this study that indicate that ABSI is associated with mortality in postmenopausal women support similar findings from a smaller cohort from the British Health and Lifestyle Survey (7). However, while ABSI may be a more robust index describing the effect of adiposity on mortality risk, it’s not ready for clinical implementation. First, because it is so new, there are no standard reference values or categorical values that correspond with normal or excessive adiposity. As Dr. Thomson says, “ABSI may provide some additional information that informs on risk, but I think we still have the issue of people not measuring waist circumference [clinically].” Because waist circumference requires more than standing on a scale, it has been difficult to implement. Clinicians have to be trained on how to properly measure waist circumference, and while it is inexpensive and not overly complicated to learn, accuracy and inter-individual measurement techniques are an issue. Despite these current setbacks, she remains optimistic: “The measurements haven’t gotten there, but they will.”
Another important aspect of using ABSI (or any index of body composition) will be validating it across a range of races and ethnicities. Thomson notes that in a preliminary analysis that has yet to be published, the ABSI and mortality risk does indeed differ between races and ethnicities. Because of that, “one clinician may use one [adiposity index] while another may use something else, depending on their patient population.”
Although still in the preliminary stages of research, ABSI may pan out as a useful measure of adiposity that could replace or complement BMI. It will need to be rigorously tested across age groups, race/ethnicities, genders and in its associations with a variety of chronic diseases. Stay tuned as this very young area of research unfolds!
