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 fromheight, 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

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 () 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 had little correlation with height, weight, or BMI. Death rates increased approximately exponentially with above average baseline ABSI (overall regression coefficient of per standard deviation of ABSI [95% confidence interval: –]), whereas elevated death rates were found for both high and low values of BMI and WC. (–) of the population mortality hazard was attributable to high ABSI, compared to (–) for BMI and (–) 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

Global trends in extreme precipitation: climate models versus observations

Precipitation events are expected to become substantially more intense under global warming, but few global comparisons of observations and climate model simulations are available to constrain predictions of future changes in precipitation extremes. We present a systematic global-scale comparison of changes in historical (1901–2010) annual-maximum daily precipitation between station observations (compiled in HadEX2) and the suite of global climate models contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We use both parametric and non-parametric methods to quantify the strength of trends in extreme precipitation in observations and models, taking care to sample them spatially and temporally in comparable ways. We find that both observations and models show generally increasing trends in extreme precipitation since 1901, with the largest changes in the deep tropics. Annual-maximum daily precipitation (Rx1day) has increased faster in the observations than in most of the CMIP5 models. On a global scale, the observational annual-maximum daily precipitation has increased by an average of 5.73 mm over the last 110 years, or 8.5% in relative terms. This corresponds to an increase of 10% K−1 in global warming since 1901, which is larger than the average of climate models, with 8.3% K−1. The average rate of increase in extreme precipitation per K of warming in both models and observations is higher than the rate of increase in atmospheric water vapor content per K of warming expected from the Clausius–Clapeyron equation. We expect our findings to help inform assessments of precipitation-related hazards such as flooding, droughts and storms

Economic Growth Assumptions in Climate and Energy Policy

The assumption that the economic growth seen in recent decades will continue has dominated the discussion of future greenhouse gas emissions and the mitigation of and adaptation to climate change. Given that long-term economic growth is uncertain, the impacts of a wide range of growth trajectories should be considered. In particular, slower economic growth would imply that future generations will be relatively less able to invest in emissions controls or adapt to the detrimental impacts of climate change. Taking into consideration the possibility of economic slowdown therefore heightens the urgency of reducing greenhouse gas emissions now by moving to renewable energy sources, even if this incurs short-term economic cost. I quantify this counterintuitive impact of economic growth assumptions on present-day policy decisions in a simple global economy-climate model (Dynamic Integrated model of Climate and the Economy (DICE)). In DICE, slow future growth increases the economically optimal present-day carbon tax rate and the utility of taxing carbon emissions, although the magnitude of the increase is sensitive to model parameters, including the rate of social time preference and the elasticity of the marginal utility of consumption. Future scenario development should specifically include low-growth scenarios, and the possibility of low-growth economic trajectories should be taken into account in climate policy analyses

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

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

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

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