Body Shape Index (Risk)

About Body Shape Index (Risk)

A Body Shape Index (ABSI), introduced by Krakauer and Krakauer in 2012, is a waist-based anthropometric index constructed to be statistically independent of BMI and therefore to capture the residual mortality risk associated with abdominal adiposity. The raw ABSI value (computed in the companion ABSI calculator) is most informative when compared to age- and sex-specific population norms, because the relationship between ABSI and mortality varies with age and sex. This calculator takes that comparison one step further by converting the deviation of an individual's ABSI from the population mean into an approximate relative mortality risk multiplier, using the hazard ratios reported in the original Krakauer analyses.

How the formula works

The calculator first computes ABSI = waist(m) / (BMI^(2/3) x height(m)^(1/2)). It then estimates the age- and sex-specific population mean ABSI using a simple linear approximation: for men, mean ABSI rises from about 0.0775 at age 50 by roughly 0.00045 per year; for women, from about 0.0730 at age 50 by roughly 0.00040 per year. The deviation of the individual's ABSI from this mean is then converted to a relative mortality risk using an exponential model based on the hazard ratios reported by Krakauer, in which each standard deviation of ABSI above the population mean approximately doubles mortality risk. The result is a risk multiplier: 1.0 indicates average risk, 2.0 indicates approximately double the average risk, and 0.5 indicates half the average risk.

Evidence and the mortality association

Krakauer and Krakauer derived ABSI from NHANES and validated it against the NHANES mortality follow-up, finding that ABSI predicted all-cause mortality more strongly than BMI. In their analysis, the hazard ratio per standard deviation of ABSI was approximately 1.6 to 2.0, compared with a much weaker and J-shaped association for BMI. Subsequent studies in the British Regional Heart Study, the EPIC cohort, and other populations have largely confirmed that ABSI predicts mortality independently of BMI, though the magnitude of the association and the optimal conversion from ABSI deviation to risk multiplier vary somewhat across populations. The risk multiplier used here is an approximation based on the Krakauer hazard ratios and should be interpreted as a relative indicator rather than a precise individual risk estimate.

Interpretation

A risk multiplier of 1.0 indicates that the individual's ABSI is at the population mean for their age and sex, corresponding to average mortality risk. Values below 0.75 suggest lower-than-average risk; 0.75 to 1.24 average risk; 1.25 to 1.99 elevated risk; and 2.0 or higher high risk. The risk multiplier is driven primarily by waist circumference relative to BMI and height, so it is most informative for individuals whose waist is larger (or smaller) than expected for their body size, particularly those with normal BMI but high waist circumference ('normal weight obesity').

When to use it

The ABSI risk multiplier is useful as a screening indicator of abdominal-obesity-related mortality risk that complements BMI. It is particularly informative for individuals with normal BMI but high waist circumference, in whom BMI would suggest low risk but ABSI correctly identifies elevated mortality risk. It is also useful in epidemiological research as a mortality-predictive anthropometric index.

Limitations

The ABSI risk multiplier is an approximation based on population-level hazard ratios and should not be interpreted as a precise individual risk estimate. The population mean ABSI approximation used here is a simplification of the age- and sex-specific distributions reported by Krakauer, and the conversion from ABSI deviation to risk multiplier assumes an exponential relationship that may not hold at the extremes. ABSI does not directly measure visceral fat (though it correlates with it), and the formula was derived in the U.S. NHANES population and may not generalize perfectly to other populations. The risk multiplier should be used as a relative indicator alongside other risk factors (blood pressure, lipids, glucose, family history) rather than as a stand-alone risk assessment.