Calculate your A Body Shape Index (ABSI) from waist circumference, BMI, and height. ABSI predicts mortality risk independent of BMI.
The A Body Shape Index (ABSI) is an anthropometric measure developed by Nir and Jesse Krakauer in 2012 that evaluates the health risk associated with abdominal obesity independently of overall body size. Unlike BMI, which conflates muscle and fat, or waist circumference, which correlates strongly with body weight, ABSI isolates the component of waist size that is not explained by height and BMI. This "excess" waist circumference is what drives ABSI's predictive power for premature mortality.
The formula normalizes waist circumference by BMI raised to the 2/3 power and height raised to the 1/2 power, effectively removing the effects of overall body size. The resulting index can be compared to population reference values, and an ABSI z-score indicates how far an individual's abdominal shape deviates from the average for their age and sex. Higher ABSI values correspond to a more central fat distribution and increased mortality risk.
ABSI has been validated in large cohort studies (NHANES, European prospective cohorts) and consistently adds predictive value beyond BMI and waist circumference alone, particularly for cardiovascular and all-cause mortality.
ABSI captures a dimension of body shape that BMI misses: abdominal protrusion relative to overall size. Two people with the same BMI and height can have very different waist circumferences, and the one with the larger waist faces higher mortality risk. ABSI quantifies this excess abdominal size. It requires only three measurements that are routinely collected in clinical settings and can be combined with age-sex reference tables to produce a z-score for personalized risk communication.
ABSI = WC / (BMI^(2/3) × Height^(1/2)) Where: • WC = Waist circumference in meters • BMI = Weight (kg) / Height (m)² • Height in meters ABSI z-score = (ABSI − ABSI_mean) / ABSI_sd where ABSI_mean and ABSI_sd are age- and sex-specific population reference values from NHANES data. Mortality hazard ratio increases approximately 13% per standard deviation increase in ABSI z-score.
Result: ABSI = 0.0849
BMI = 85 / 1.75² = 27.76. ABSI = 1.00 / (27.76^(2/3) × 1.75^(1/2)) = 1.00 / (9.20 × 1.323) = 1.00 / 12.17 = 0.0822. Comparing to the NHANES reference mean of ~0.0807 for a 45-year-old male with SD ~0.0036, the z-score is (0.0822 − 0.0807) / 0.0036 ≈ 0.42, indicating a mildly above-average abdominal protrusion with slightly elevated mortality risk.
ABSI was developed by Nir Y. Krakauer and Jesse C. Krakauer and published in PLoS ONE in 2012. The researchers analyzed NHANES data (1999–2004) and follow-up mortality data to create an index where waist circumference is normalized by body size. The key insight was that the allometric scaling exponents of 2/3 for BMI and 1/2 for height effectively removed the dependence of waist circumference on overall body mass, isolating the abdominal shape component.
The raw ABSI value is difficult to interpret in isolation because the range of values (roughly 0.07–0.09) is narrow. Converting to a z-score using age- and sex-specific mean and standard deviation values from NHANES provides a standardized scale. A z-score of 0 represents the population average, +1 is one standard deviation above average (approximately 84th percentile), and −1 is one standard deviation below average (approximately 16th percentile).
Multiple prospective studies have confirmed that ABSI adds predictive value for mortality beyond BMI and waist circumference alone. In a meta-analysis of cohort studies, an increase of one standard deviation in ABSI z-score was associated with a hazard ratio of approximately 1.13 for all-cause mortality. This makes ABSI a valuable additional metric for clinical risk stratification, particularly in patients whose BMI falls in the overweight range but whose actual health risk may vary substantially based on fat distribution.
ABSI does not distinguish between visceral and subcutaneous abdominal fat — both contribute to waist circumference. Population-specific reference values may be needed for non-Western populations where body proportions and fat distribution patterns differ. Ongoing research is exploring dynamic ABSI tracking as a biomarker for the effectiveness of lifestyle interventions.
ABSI is an anthropometric index developed by Krakauer & Krakauer (2012) that measures abdominal obesity relative to overall body size. It divides waist circumference by a power function of BMI and height, isolating the "excess" waist that isn't explained by general body size. Higher ABSI indicates greater central fat accumulation.
BMI measures overall mass relative to height but cannot distinguish fat from muscle or detect where fat is located. ABSI specifically captures abdominal protrusion. Two people with BMI 28 can have very different ABSI values depending on their waist size, and the one with higher ABSI faces greater mortality risk.
ABSI values are small numbers, typically ranging from 0.07 to 0.09. Because absolute values are hard to interpret, ABSI is usually converted to a z-score using age- and sex-specific reference tables from NHANES. A z-score near 0 is average; above +1 is elevated risk; below −1 is lower-than-average risk.
A high positive z-score (e.g., +1 or above) means your waist is larger than expected for your BMI and height, indicating greater central fat deposition. Each standard deviation increase in ABSI z-score is associated with roughly a 13% increase in all-cause mortality hazard ratio, making it a meaningful predictor.
ABSI can be more informative than BMI for muscular individuals because BMI inflates with muscle mass while ABSI focuses on waist relative to body size. An athlete with a BMI of 30 but a normal waist would have a low ABSI, correctly reflecting low abdominal obesity risk. However, ABSI reference tables are based on the general population.
ABSI was originally validated in adults. While the formula can be applied to younger individuals, the NHANES-based z-score reference tables are primarily for adults aged 18+. Pediatric versions with age-appropriate references are still under research development.
ABSI has been associated with all-cause mortality, cardiovascular mortality, and type 2 diabetes in prospective cohort studies. It adds predictive value beyond BMI and waist circumference alone. However, it is a risk indicator, not a diagnostic tool, and should be used alongside clinical evaluations.
Recalculating every 3–6 months is reasonable for tracking body composition trends. Since ABSI depends on waist circumference, BMI, and height, ensure all three are measured accurately each time. Significant changes in waist circumference will be reflected in ABSI changes.