The predictive ability of ABSI compared to BMI for mortality and frailty among older adults.

Introduction: To study the utility of A Body Shape Index (ABSI) alongside body mass index (BMI) to predict mortality and frailty in an aging community population. Materials and methods: Participants (n = 1,580) were drawn from the first Israeli national health and nutrition survey of older adults ("Mabat Zahav") conducted from 2005 to 2006, constituting adults aged ≥65 years. Socio-demographic, clinical, behavioral, and psychosocial data were collected. Baseline weight, height, and waist circumference (WC) were measured and expressed as the allometric indices BMI (kg/m2) and ABSI, a BMI-independent measure of abdominal obesity [WC/(BMI2/3*m1/2)]. Mortality follow-up lasted through 2019. Frailty was assessed in 2017-2019 by the Fried Biological Phenotype in a sub-cohort of 554 survivors. Cox and logistic regression models assessed associations of BMI and ABSI with mortality and frailty. Results: At baseline, mean [SD] age was 74.5 [6.1] years, and 52.4% were women. The correlation between BMI and WC Z scores was 0.71, reduced to -0.11 for BMI and ABSI. Over a median follow-up of 13 years, 757 deaths occurred. The multivariable-adjusted hazard ratios (95% CIs) for mortality per standard deviation increase in BMI and ABSI were 1.07 (0.99;1.17) and 1.13 (1.05;1.21), respectively. Among participants assessed for frailty, 77 (14%) met the frailty criteria. After multivariable adjustment, the odds ratios (95% CIs) for frailty were 0.83 (0.69-1.01) for BMI and 1.55 (1.34-1.79) for ABSI. Discussion: In a nationwide cohort of older adults, ABSI was independently associated with mortality risk. Furthermore, ABSI, but not BMI, was a strong predictor of frailty.

Cumulative Cigarette Consumption is Associated with Cardio-Ankle Vascular Index (CAVI) Mediated by Abdominal Obesity Assessed by A Body Shape Index (ABSI): A Cross-Sectional Study.

AIM: To elucidate the mechanism by which cigarette smoking causes vascular damage, we examined the relationship between cumulative cigarette consumption and abdominal obesity, and the possible mediating effect of smoking on arterial stiffness. METHODS: Cross-sectional data from 19499 never smokers and 5406 current smokers receiving health screening was analyzed. Abdominal obesity was assessed by ABSI, and arterial stiffness by CAVI. High CAVI was defined as CAVI ≥ 9.0. RESULTS: Current smoker showed higher ABSI than never smokers after propensity score matching. Cumulative cigarette consumption expressed in pack-years correlated with ABSI (Rs: 0.312 in men, 0.252 in women), and was also extracted as an independent factor associated with ABSI by multiple regression analysis. A linear relationship between pack-year and CAVI was observed (Rs: 0.544 in men, 0.423 in women). Pack-year had almost equal discriminatory power in predicting high CAVI in both sexes (C-statistic: 0.774 in men, 0.747 in women), and the best cut-offs of pack-year for high CAVI were 24.5 in men and 14.7 in women. Bivariate logistic regression models revealed that the association between pack-year higher than cut-off and high CAVI was independent of traditional risks. A mediating effect of ABSI (mediation rate: 9.9% in men and 11.2% in women), but not waist circumference (WC), on the association of pack-year with CAVI was observed, after adjusting for traditional risks. CONCLUSION: Cumulative cigarette smoking in pack-years was independently associated with ABSI. ABSI partially mediates the association between pack-year and CAVI, suggesting that abdominal obesity partially mediates smoking-related vascular dysfunction.

Diet Composition, Anthropometrics, and Mortality Risk.

While overeating is considered a cause of the obesity epidemic as quantified by body mass index (BMI), the association of diet with a body shape index (ABSI) and hip index (HI), which are transformations of waist and hip circumference that are independent of BMI and which predict mortality risk, is poorly known. We used data from the Atherosclerosis Risk in Communities (ARIC) study of about 15,000 middle-aged adults to investigate associations between macronutrient intake (energy, carbohydrate, protein, and fat, the latter two divided into plant and animal sources, all based on self-reported food frequency) with anthropometric indices (BMI, ABSI, and HI). We also analyzed the association of diet and anthropometrics with death rate during approximately 30 years of follow-up. High intake of energy and animal fat and protein was generally associated with higher ABSI and lower HI at baseline, as well as greater mortality hazard. BMI was also positively linked with animal fat and protein intake. In contrast, higher intake of carbohydrates and plant fat and protein was associated with lower ABSI and BMI, higher HI, and lower mortality hazard. For example, after adjustment for potential confounders, each standard deviation of additional plant fat intake (as a fraction of total energy) was associated with a 5% decrease in mortality rate, while animal fat intake was associated with a 5% mortality increase per standard deviation. The directions of the associations between diet and anthropometrics are consistent with those found between anthropometrics and mortality without reference to diet.

What is the best anthropometric predictor for identifying higher risk for cardiovascular diseases in afro-descendant Brazilian women? A cross-sectional population-based study.

OBJECTIVES: Excessive adiposity is associated with cardiovascular disease (CVD). Anthropometric indices are useful in screening individuals at higher risk for these diseases. However, there are no studies that show which of these indices has the best discriminatory power among Afro-descendant Brazilian women. The objective of this study was to assess the accuracy of anthropometric indices in identifying risk factors for CVD in Afro-descendant Brazilian women and define the one most suitable for use under the operating conditions prevailing in Quilombola communities. METHODS: A household random sample of 1661 women descendants of African slaves were analyzed. The anthropometric predictors analyzed were waist circumference (WC), body mass index, waist-to-height ratio, conicity index (C-index), body shape index, and percentage of body fat (%BF; estimated by bioimpedance). The assessed risk factors for CVD were arterial hypertension, diabetes mellitus, and dyslipidemias (hypertriglyceridemia; hypercholesterolemia; low high-density lipoprotein). To identify the statistical significance between the differences in the areas under the ROC curves (AUC) obtained with the different predictors and outcomes, was used the Bonferroni test adjusted for multiple analyses by the Sidak method. RESULTS: The AUC obtained with WC was higher (p < .05) or similar (p > .05) to those obtained with the other predictors 29 times out of 30 possibilities (six predictors x five outcomes). Only the AUC obtained with C-index in identifying hypercholesterolemia was significantly higher than that with WC. CONCLUSION: Due to its accuracy and greater operational simplicity, WC was the most adequate predictor for identifying Afro-descendant women at greatest risk for CVD.

Association of X-ray Absorptiometry Body Composition Measurements with Basic Anthropometrics and Mortality Hazard.

Dual-energy X-ray absorptiometry (DEXA) is a non-invasive imaging modality that can estimate whole-body and regional composition in terms of fat, lean, and bone mass. We examined the ability of DEXA body composition measures (whole-body, trunk, and limb fat mass and fat-free mass) to predict mortality in conjunction with basic body measures (anthropometrics), expressed using body mass index (BMI) and a body shape index (ABSI). We used data from the 1999-2006 United States National Health and Nutrition Examination Survey (NHANES), with mortality follow-up to 2015. We found that all DEXA-measured masses were highly correlated with each other and with ABSI and that adjustment for BMI and ABSI reduced these dependencies. Whole-body composition did not substantially improve mortality prediction compared to basic anthropometrics alone, but regional composition did, with high trunk fat-free mass and low limb fat-free mass both associated with elevated mortality risk. These findings illustrate how DEXA body composition could guide health assessment in conjunction with the more widely employed simple anthropometrics.

A Body Shape Index (ABSI) and Hip Index (HI) Adjust Waist and Hip Circumferences for Body Mass Index, But Only ABSI Predicts High Cardiovascular Risk in the Spanish Caucasian Population.

Background: Our aim in this study was to investigate if Hip index (HI) improves the identification of cardiovascular risk (CVR) beyond that achieved with either the waist-to-height ratio (WHtR) or body mass index (BMI)-adjusted waist circumference (A body shape index [ABSI]) in the Spanish Caucasian population. Methods: Three thousand eight hundred forty-four subjects (1754 males, response rate 75.8%) were included. Anthropometric indices (AIs) included were HI, ABSI, and WHtR. CVR was estimated using the Framingham, Systematic COronary Risk Evaluation (SCORE), and American College of Cardiology/American Heart Association (ACC/AHA) charts. Areas under the receiver operating characteristic curve (AUC) were obtained to evaluate the performance of AIs in detecting CVR. We also estimated the AIs' standardized Z-scores and compared them against the CVR. Results: AUC demonstrated that the best AI in males to estimate higher CVR according to Framingham and ACC/AHA charts was WHtR. In females, WHtR also achieved good performance and showed higher prediction capacity than the other AIs. After transforming to Z-scores, ABSI was the best linear predictor for CVR according to SCORE and ACC/AHA, although WHtR also proved to be good. HI did not associate with the measures of CVR. Conclusions: HI does not predict high CVR in the Spanish Caucasian Population. However, ABSI is directly and linearly related to high CVR, with a higher performance than WHtR when standardized and evaluated as a linear predictor.

Association of Body Shape Index (ABSI) with Hand Grip Strength.

Hand grip is a leading measure of muscle strength and general health, yet its association with body shape is not well characterized. Here, we examine correlations between grip strength, a body shape index (ABSI), and body mass index (BMI) in the 2011-2014 United States National Health and Nutrition Examination Survey cohorts. Grip strength was found to correlate negatively with ABSI (though positively with BMI), suggesting that those with a more central body profile tend to be weaker than others with the same weight. Individuals with low grip strength, as well as those with high ABSI, were more likely to die during follow up, whereas there was no association of BMI with mortality hazard. Transforming the grip strength, ABSI, and BMI by taking their logarithm prior to standardization did not meaningfully change the associations seen. These findings suggest that combining anthropometrics (ABSI, BMI) with grip strength may better identify individual mortality hazard in research studies and clinical practice.

Can an Exercise-Based Educational and Motivational Intervention be Durably Effective in Changing Compliance to Physical Activity and Anthropometric Risk in People with Type 2 Diabetes? A Follow-Up Study.

AIMS: A nine-month motivational exercise-based intervention was previously offered to subjects with type 2 diabetes (T2D). A year after the end of the intervention, compliance to physical activity (PA) and anthropometric indices of participants were analyzed to evaluate the durability of its effects. METHODS: PA levels, expressed as total energy expenditure per week, were assessed with the International Physical Activity Questionnaire (IPAQ). Changes in Body Mass Index (BMI), A Body Shape Index (ABSI), Hip Index (HI) z-scores, the relative mortality risk related to each of these measures, and a combined Anthropometric Risk Index (ARI) were also evaluated. RESULTS: Of a total of the 52 subjects examined (67.9% males, mean age 61.8 ± 6.0), 46 (88.4%) were still sufficiently active as defined by IPAQ thresholds at follow-up. PA levels, anthropometric indices and related risks improved at follow-up in respect to the baseline and to the end of the intervention, although only PA levels, BMI and related measures, and ARI risk changed significantly. Habitual PA increased significantly after the intervention (p < 0.01) and this increase correlated with changes in BMI z-scores (r = -0.29, p = 0.04). BMI risk was significantly lower (p < 0.01) in participants still active at follow-up. CONCLUSIONS: This study testifies to the persistence of compliance to PA and health benefits of a combined exercise-based and motivational intervention in subjects with T2D.

A body shape index (ABSI) reflects body composition changes in response to testosterone treatment in obese men.

BACKGROUND: Interventions such as testosterone treatment may change body composition and metabolic outcomes without substantial changes in weight and BMI. OBJECTIVES: Using testosterone treatment as a paradigm, we hypothesized that a body shape index (ABSI) reflects body composition changes more accurately than traditional markers, such as weight, BMI and waist circumference. INTERVENTION: Secondary analysis of a 56-week RCT in 100 dieting obese men with low-normal testosterone receiving testosterone treatment or placebo, and subsequent off-treatment follow-up. RESULTS: At the end of the trial period, ABSI-unlike weight, BMI or waist circumference-had significantly decreased in the treatment group, compared with placebo (mean adjusted difference -0.18 [95% CI: -0.32, -0.05] × 10-2 m11/6kg-2/3, overall P<0.001). Changes in ABSI during the active trial phase correlated with changes in fat mass (tau = 0.18, P = 0.02), and not with lean mass (tau = -0.11, P = 0.14), BMI (tau = 0.10, P = 0.17), or visceral fat (tau = 0.07, P = 0.37). ABSI baseline values were positively correlated with waist circumference (tau = 0.21, P = 0.002) and visceral fat (tau = 0.18, P = 0.009), correlated inversely with lean mass (tau = -0.21, P = 0.002), and were uncorrelated with BMI (tau = -0.10, P = 0.15) and fat mass (tau = 0.01, P = 0.83). Two years after cessation of treatment, ABSI again reflected body composition as the between-group differences in all parameters did not persist. CONCLUSIONS: A readily obtainable anthropomorphic measure, ABSI reflects the differential loss of fat mass mediated by testosterone in dieting obese men more closely than BMI or waist circumference. It may serve as a clinically useful marker to monitor body composition changes, particularly in response to interventions.

Anthropometrics, Metabolic Syndrome, and Mortality Hazard.

Independent indices (height, body mass index, a body shape index, and hip index) derived from basic anthropometrics have been found to be powerful predictors of mortality hazard, especially when the attributable risks are summed over these indices to give an anthropometric risk index (ARI). The metabolic syndrome (MS) is defined based on the co-occurrence of anthropometric, clinical, and laboratory criteria and is also widely employed for evaluating disease risk. Here, we investigate correlations between ARI and MS in a general population sample, the United States Third National Health and Nutrition Examination Survey. Baseline values of ARI and MS were also evaluated for their association with mortality over approximately 20 years of follow-up. ARI was found to be positively correlated with each component of MS, suggesting connections between the two entities as measures of cardiometabolic risk. ARI and MS were both significant predictors of mortality hazard. Although the association of ARI with mortality hazard was stronger than that of MS, a combined model with both ARI and MS score as predictors improved predictive ability over either construct in isolation. We conclude that the combination of anthropometrics and clinical and laboratory measurements holds the potential to increase the effectiveness of risk assessment compared to using either anthropometrics or the current components of MS alone.

Untangling Waist Circumference and Hip Circumference from Body Mass Index with a Body Shape Index, Hip Index, and Anthropometric Risk Indicator.

Body mass index (BMI) corrects body weight for height and is well established for diagnosing overweight and obesity and correlating with many medical conditions. Waist circumference (WC) is used to diagnose abdominal obesity. However, the correlation of BMI and WC is high, around 0.9, making the use of BMI and WC in concert challenging. A body shape index (ABSI) is a new measure of risk associated with abdominal size. Derived in 2012, ABSI is analogous to BMI in that it normalizes WC for weight and height (and thus to BMI). A similar derivation led to hip index (HI), normalizing hip circumference for BMI. Hazard ratios (HRs) for univariate risk associations of the independent measures height, BMI, ABSI, and HI can be multiplied to give a combined HR, the anthropometric risk indicator (ARI). Compared to any one anthropometric factor, including BMI and WC, ARI more accurately estimates personalized mortality hazard. Published work on ABSI, HI, and ARI supports their association with many aspects of health, including cardiometabolic conditions related to the metabolic syndrome.

Relationship between "a body shape index (ABSI)" and body composition in obese patients with type 2 diabetes.

BACKGROUND: Obesity is known to be related to the development of type 2 diabetes mellitus (T2D). The most commonly used anthropometric indicator (body mass index [BMI]) presents several limitations such as the lack of possibility to distinguish adipose tissue distribution. Thus, this study examines the suitability of a body shape index (ABSI) for prediction of body composition and sarcopenic obesity in obese or overweight T2D subjects. METHODS: Cross-sectional study in 199 overweight/obese T2D adults. Anthropometric (BMI, ABSI) and body composition (fat mass [FM], fat-free mass [FFM], fat mass index [FMI] and fat-free mass index, and the ratio FM/FFM as an index of sarcopenic obesity) data was collected, as well as metabolic parameters (glycated haemoglobin [HbA1c], mean blood glucose, fasting plasma glucose [FPG], high-density-lipoprotein cholesterol [HDL], low-density-lipoprotein cholesterol, total cholesterol, and triglycerides [TG] levels; the ratio TG/HDL was also calculated as a surrogate marker for insulin resistance). RESULTS: ABSI was significantly associated with age and waist circumference. It showed a statistically significant correlation with BMI exclusively in women. Regarding body composition, in men, ABSI was associated with FM (%), while in women it was associated with both FM and FFM. Both males and females groups with high ABSI scores were significantly older (men: 59.3 ± 10.8 vs 54.6 ± 10.1, p ≤ 0.05; women: 65.1 ± 9.8 vs 58.1 ± 13.3, p ≤ 0.005) and showed lower FFM values (men: 62.3 ± 9.0 vs 66.2 ± 9.3, p ≤ 0.05; women: 48.7 ± 5.6 vs 54.5 ± 8.9, p ≤ 0.001) compared with low-ABSI groups. Multiple linear regression revealed that ABSI independently predict FMI and the FM/FFM ratio in women. Sarcopenic obesity was identified in 70 (36.5%) individuals according to the FM/FFM ratio. The AUROC of ABSI was 63.1% (95% CI 54.6-71.6%; p = 0.003) and an ABSI value of 0.083 m11/6 kg-2/3 was the optimal threshold in discriminating patients with sarcopenic obesity (sensitivity: 48%, specificity: 73%). Moreover, a significant association between ABSI and FPG was found in men. CONCLUSIONS: ABSI could be useful to identify visceral and sarcopenic obesity in overweight/obese adults with T2D, adding some relevant clinical information to traditional anthropometric measures.

The association between a body shape index and cardiovascular risk in overweight and obese children and adolescents.

A Body Shape Index (ABSI) and normalized hip circumference (Hip Index, HI) have been recently shown to be strong risk factors for mortality and for cardiovascular disease in adults. We conducted an observational cross-sectional study to evaluate the relationship between ABSI, HI and cardiometabolic risk factors and obesity-related comorbidities in overweight and obese children and adolescents aged 2-18 years. We performed multivariate linear and logistic regression analyses with BMI, ABSI, and HI age and sex normalized z scores as predictors to examine the association with cardiometabolic risk markers (systolic and diastolic blood pressure, fasting glucose and insulin, total cholesterol and its components, transaminases, fat mass % detected by bioelectrical impedance analysis) and obesity-related conditions (including hepatic steatosis and metabolic syndrome). We recruited 217 patients (114 males), mean age 11.3 years. Multivariate linear regression showed a significant association of ABSI z score with 10 out of 15 risk markers expressed as continuous variables, while BMI z score showed a significant correlation with 9 and HI only with 1. In multivariate logistic regression to predict occurrence of obesity-related conditions and above-threshold values of risk factors, BMI z score was significantly correlated to 7 out of 12, ABSI to 5, and HI to 1. Overall, ABSI is an independent anthropometric index that was significantly associated with cardiometabolic risk markers in a pediatric population affected by overweight and obesity.

ABSI (A Body Shape Index) and ARI (Anthropometric Risk Indicator) in Bariatric Surgery. First Application on a Bariatric Cohort and Possible Clinical Use.

BACKGROUND: BMI (body mass index) is used to identify candidates for bariatric surgery, with a criterion of BMI ≥ 40. For lesser degrees of obesity, BMI 35-39.9, comorbidities are also considered. A Body Shape Index (ABSI) was derived to correct WC (waist circumference) for BMI and height. ABSI has been shown to be a linear predictor of long-term mortality across the range of BMI. Anthropometric risk indicator (ARI) combines the complementary contributions of BMI and ABSI and further improves mortality hazard prediction. We report for the first time ABSI and ARI for a bariatric surgical cohort at baseline and with 3-year follow-up. METHODS: ABSI and BMI were calculated for 101 subjects from our bariatric surgery center database at baseline and after 3 years of follow-up. Raw values for BMI and ABSI were converted to Z scores and ARI values based on sex- and age-specific normals and risk associations from the National Health and Nutrition Examination Survey (NHANES) III sample of the US general population. RESULTS: Baseline scores for the anthropometric variables BMI and ABSI and the corresponding ARI were all higher than for the NHANES population sample. At 3-year post surgery, all three measures decreased significantly. While baseline BMI did not predict the change in mortality risk by ARI, baseline ABSI did (r = - 0.73), as did baseline ARI (r = - 0.94). CONCLUSION: Sleeve gastrectomy lowers ABSI and the associated mortality risk estimated from population studies after 3 years of follow-up. Considering our results, bariatric surgical candidates with BMI in the range of 35 to 39.9 with an increased ABSI-related mortality risk may have considerable survival benefit from bariatric surgery, even in the absence of qualifying comorbidities. TRIAL REGISTRATION NUMBER: 2814.

Association of Body Shape Index (ABSI) with cardio-metabolic risk factors: A cross-sectional study of 6081 Caucasian adults.

A Body Shape Index (ABSI) was specifically developed as a transformation of waist circumference (WC), statistically independent of BMI to better evaluate the relative contribution of WC to central obesity and clinical outcomes. Previous studies have found ABSI is associated with total mortality and cardiovascular events. However, no study has specifically evaluated the joint contribution of ABSI and BMI to cardio-metabolic outcomes (high triglycerides, low HDL, high fasting glucose and high blood pressure). With this aim, we performed a retrospective study on 6081 Caucasian adults. Subjects underwent a medical interview, anthropometric measurements, blood sampling, measurement of blood pressure, and measurement of visceral abdominal fat thickness (VAT) by ultrasound. Generalized linear models (GLM) were used to evaluate the sex and age adjusted association of ABSI with binary and continuous cardio-metabolic risk factors. Four pre-specified GLM were evaluated for each outcome: M1 = ABSI, BMI and ABSI*BMI interaction, M2 = ABSI and BMI, M3 = ABSI alone and M4 = BMI alone. Bayesian Information Criterion (BIC) was calculated and used to identify the best predictive model. ABSI and BMI contributed independently to all outcomes. Compared to BMI alone, the joint use of BMI and ABSI yielded significantly improved associations for having high triglycerides (BIC = 5261 vs. 5286), low HDL (BIC = 5371 vs. 5381), high fasting glucose (BIC = 6328 vs. 6337) but not high blood pressure (BIC = 6580 vs. 6580). The joint use of BMI and ABSI was also more strongly associated with VAT than BMI alone (BIC = 22930 vs. 23479). In conclusion, ABSI is a useful index for evaluating the independent contribution of WC, in addition to that of BMI, as a surrogate for central obesity on cardio-metabolic risk.

Effects of a multidisciplinary weight loss intervention in overweight and obese children and adolescents: 11 years of experience.

AIMS: To evaluate the effects of an outpatient multidisciplinary weight loss intervention in reducing body mass index (BMI) in children and adolescents suffering overweight and obesity, changes in A Body Shape Index (ABSI, waist circumference normalized to height and weight) and Hip Index (HI, normalized hip circumference) during treatment and correlation between the ABSI and HI with change in BMI z score. METHODS: We analyze anthropometric data from pediatric patients affected by overweight and obesity aged 2 to 18 years old who entered our multidisciplinary weight loss intervention, which included medical, psychological and nutritional sessions, from January 1st 2006 to December 31st 2016. Lifestyle modification counselling was delivered. Follow-up visits were planned every month for 3 months and subsequently every 2-4 months. BMI, ABSI, and HI were converted to z scores using age and sex specific population normals. RESULTS: 864 patients entered our intervention. 453 patients (208 males), mean age 11.2 ±3.1 years, 392 with obesity (86%, z-BMI 2.90 ±0.80 SD) and 61 patients with overweight (z-BMI 1.73±0.21 SD) attended at least 1 follow-up visit. The mean number of visits was 3.5 (± 1.8 SD) in overweight subjects and 3.9 (±2.2 SD) in ones with obesity. At the last attended follow-up visit (at 16 ± 12 months SD) we observed a reduction in mean z-BMI in patients with obesity (to 2.52 ±0.71 SD) and patients with overweight (to 1.46 ±0.5 SD). Most patients (80.8%) reduced their BMI z scores. Mean ABSI and HI z scores showed no significant change. 78/392 patients (19.8%) recovered from obese to overweight, 5/392 (1.2%) from obese to normal weight. The recovery rate from overweight to normal weight was 13.1%. In a multivariate model, initial BMI z score and number of follow-up visits were significant predictors of weight change, while age, sex, ABSI, and HI were not significant predictors. CONCLUSIONS: Patients affected by overweight and obesity involved in a multidisciplinary weight loss intervention reduced their mean BMI z score, while ABSI and HI were stable. Weight loss was not predicted by initial ABSI or HI. More visits predict more weight loss, but dropout rates are high. The great majority of patients leave the weight management program before having normalized their BMI.

An Anthropometric Risk Index Based on Combining Height, Weight, Waist, and Hip Measurements.

Body mass index (BMI) can be considered an application of a power law model to express body weight independently of height. Based on the same power law principle, we previously introduced a body shape index (ABSI) to be independent of BMI and height. Here, we develop a new hip index (HI) whose normalized value is independent of height, BMI, and ABSI. Similar to BMI, HI demonstrates a U-shaped relationship to mortality in the Third National Health and Nutrition Examination Survey (NHANES III) population. We further develop a new anthropometric risk index (ARI) by adding log hazard ratios from separate nonlinear regressions of the four indicators, height, BMI, ABSI, and HI, against NHANES III mortality hazard. ARI far outperforms any of the individual indicators as a linear mortality predictor in NHANES III. The superior performance of ARI also holds for predicting mortality hazard in the independent Atherosclerosis Risk in Communities (ARIC) cohort. Thus, HI, along with BMI and ABSI, can capture the risk profile associated with body size and shape. These can be combined in a risk indicator that utilizes complementary information from height, weight, and waist and hip circumference. The combined ARI is promising for further research and clinical applications.

Combining Body Mass and Shape Indices in Clinical Practice.

We present preliminary clinical experience with combined consideration of the commonly used BMI (body mass index) and the newly developed ABSI (a body shape index) using a point of care anthropometric calculator for comparisons of index values and associated relative risks to population normals. In a series of 282 patients, BMI and ABSI were close to being independently distributed, supporting the value of considering both indices. Three selected cases illustrate scenarios where assessment of ABSI together with BMI could inform patient care and counseling. These data suggest that combined assessment of BMI and ABSI may prove useful in clinical practice.

Dynamic association of mortality hazard with body shape.

BACKGROUND: A Body Shape Index (ABSI) had been derived from a study of the United States National Health and Nutrition Examination Survey (NHANES) 1999-2004 mortality data to quantify the risk associated with abdominal obesity (as indicated by a wide waist relative to height and body mass index). A national survey with longer follow-up, the British Health and Lifestyle Survey (HALS), provides another opportunity to assess the predictive power for mortality of ABSI. HALS also includes repeat observations, allowing estimation of the implications of changes in ABSI. METHODS AND FINDINGS: We evaluate ABSI z score relative to population normals as a predictor of all-cause mortality over 24 years of follow-up to HALS. We found that ABSI is a strong indicator of mortality hazard in this population, with death rates increasing by a factor of 1.13 (95% confidence interval, 1.09-1.16) per standard deviation increase in ABSI and a hazard ratio of 1.61 (1.40-1.86) for those with ABSI in the top 20% of the population compared to those with ABSI in the bottom 20%. Using the NHANES normals to compute ABSI z scores gave similar results to using z scores derived specifically from the HALS sample. ABSI outperformed as a predictor of mortality hazard other measures of abdominal obesity such as waist circumference, waist to height ratio, and waist to hip ratio. Moreover, it was a consistent predictor of mortality hazard over at least 20 years of follow-up. Change in ABSI between two HALS examinations 7 years apart also predicted mortality hazard: individuals with a given initial ABSI who had rising ABSI were at greater risk than those with falling ABSI. CONCLUSIONS: ABSI is a readily computed dynamic indicator of health whose correlation with lifestyle and with other risk factors and health outcomes warrants further investigation.

A new body shape index predicts mortality hazard independently of body mass index.

BACKGROUND: Obesity, typically quantified in terms of Body Mass Index (BMI) exceeding threshold values, is considered a leading cause of premature death worldwide. For given body size (BMI), it is recognized that risk is also affected by body shape, particularly as a marker of abdominal fat deposits. Waist circumference (WC) is used as a risk indicator supplementary to BMI, but the high correlation of WC with BMI makes it hard to isolate the added value of WC. METHODS AND FINDINGS: We considered a USA population sample of 14,105 non-pregnant adults (age ≥ 18) from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 with follow-up for mortality averaging 5 yr (828 deaths). We developed A Body Shape Index (ABSI) based on WC adjusted for height and weight: ABSI ≡ WC/(BMI(2/3)height(1/2)). ABSI had little correlation with height, weight, or BMI. Death rates increased approximately exponentially with above average baseline ABSI (overall regression coefficient of +33% per standard deviation of ABSI [95% confidence interval: +20%-+48%), whereas elevated death rates were found for both high and low values of BMI and WC. 22% (8%-41%) of the population mortality hazard was attributable to high ABSI, compared to 15% (3%-30%) for BMI and 15% (4%-29%) for WC. The association of death rate with ABSI held even when adjusted for other known risk factors including smoking, diabetes, blood pressure, and serum cholesterol. ABSI correlation with mortality hazard held across the range of age, sex, and BMI, and for both white and black ethnicities (but not for Mexican ethnicity), and was not weakened by excluding deaths from the first 3 yr of follow-up. CONCLUSIONS: Body shape, as measured by ABSI, appears to be a substantial risk factor for premature mortality in the general population derivable from basic clinical measurements. ABSI expresses the excess risk from high WC in a convenient form that is complementary to BMI and to other known risk factors.