Optimal scaling of weight and waist circumference to height for maximal association with DXA-measured total body fat mass by sex, age and race/ethnicity

Perceptual body image tasks require ethnically appropriate stimuli

Current body ideals and perceived weight status are often assessed with tests that include images which depict BMI dependent morphological changes in body shape. These images are almost exclusively based on White European (WE) bodies. However, East Asian (EA) and South Asian (SA) people have a different body composition and pattern of adipose deposition for a given BMI. As such, matching someone's body from an EA or SA background to a WE body may lead to errors in estimation, as there are no equivalent bodies to match against. Therefore, we 3D scanned EA, SA and WE female volunteers and constructed computer-generated imagery (CGI) bodies based on a statistical analysis of the size and shape variation specific to each ethnic identity. We then asked participants to make judgements between pairs of bodies of the same or different ethnic identity as themselves. When presented with ethnically different stimuli, EA and SA participants significantly over-estimate body size and WE participants significantly under-estimate. Additionally, ethnically mismatched stimuli lead to significantly greater uncertainty about body size judgements. For the first time, we show that ethnically appropriate stimuli need to be used to assess body judgements and should be developed as a matter of urgency.

The Association of Body Mass Index and Adiposity-Estimating Equations with Measures of Obstructive Sleep Apnea Severity: A Cross-Sectional Study

Background and Purpose

Obesity, a risk factor for obstructive sleep apnea (OSA), is usually estimated by body mass index (BMI). However, other adiposity-estimating equations may better capture variations in fat distribution. This study assessed the relationship between OSA severity and 15 adiposity-estimating equations, compared to BMI, with subgroup analyses by sex and age (<50 vs ≥50).

Patients and Methods

We conducted a cross-sectional cohort study using data from 5021 consecutive adults who underwent a Level 1 polysomnography (2015-2017) in a large academic sleep center in Ottawa, Canada. We assessed correlations between adiposity measures and the apnea-hypopnea index (AHI) and examined discriminative ability for moderate-to-severe (AHI ≥15/h) and severe OSA (AHI >30/h) using univariate logistic regressions.

Results

The mean age was 49.5 years, 46.6% were women; the mean BMI was 30.0 kg/m2 and 12.7% had severe OSA. All adiposity equations showed negligible (Pearson r 0.0 to ±0.3) to low (Pearson r ± 0.30 to 0.50) statistically significant correlations with AHI, with many of the equations having a marginally stronger correlation coefficient than BMI, in total and subgroup analysis. Discriminative ability for severe OSA was generally low, with c-indices ranging from 0.52 to 0.67 in the overall sample. However, in females under 50, several equations (eg, Gallagher 2000, Deurenberg 1991 and 1998, ECORE BF) reached excellent discriminative ability (c-indices 0.81), including BMI (c-index 0.80). This pattern was not observed in other subgroups.

Conclusion

In this clinical cohort, BMI was associated poorly with AHI; however, the other equations did not outperform BMI. Moreover, BMI demonstrated poor discriminative ability for moderate/severe and severe OSA, with none of the other equations performing better in this context. Notable subgroup differences-particularly among younger females-suggest that tailoring screening strategies by age and sex may improve risk stratification and support refining obesity-based screening approaches.

Weight/height2: Mathematical overview of the world's most widely used adiposity index

A footnote in Adolphe Quetelet's classic 1835 Treatise on Man described his algebraic analysis of how body weight ( W ) varies with height ( H ) in adult males and females. Using data on 12 short and 12 tall subjects of each sex, Quetelet established the rule that W is approximately proportional ( ∝ ) to H2 in adults; that is, W ∝ H 2 when W ≈ α H 2 for some constant α . Quetelet's Rule ( W ∝ H 2 ), transformed and renamed in the twentieth century to body mass index ( BMI = W / H 2 ), is now a globally applied phenotypic descriptor of adiposity at the individual and population level. The journey from footnote to ubiquitous adiposity measure traveled through hundreds of scientific reports and many more lay publications. The recent introduction of highly effective pharmacologic weight loss treatments has heightened scrutiny of BMI's origins and appropriateness as a gateway marker for diagnosing and monitoring people with obesity. This contemporary context prompted the current report that delves into the biological and mathematical paradigms that underlie the simple index BMI = W / H 2 . Students and practitioners can improve or gain new insights into their understanding of BMI's historical origins and quantitative underpinning from the provided overview, facilitating informed use of BMI and related indices in research and clinical settings.

Evaluation of Health Associations With Height-Normalised Abdominal Body Composition Indices: A Single-Centre Cross-Sectional Study

BACKGROUND

Traditional metrics such as body mass index (BMI) and waist circumference (WC) fail to accurately assess the health outcomes associated with abdominal adiposity, because they neglect the intricacies of adipose tissue distribution. Notably, the variability in body composition scaled to height remains underexplored in Chinese demographics. This study introduces height-normalised indices of abdominal adiposity using computed tomography (CT) scans and further assesses their associations with various health outcomes.

METHODS

In a large, diverse Chinese population (n = 1054 healthy individuals; n = 1159 with dyslipidemia; n = 803 with diabetes; n = 1289 with cardio-cerebrovascular diseases; n = 1108 with cancers; and n = 509 with abnormal bone mas), abdominal CT scans were performed and allometric growth model analyses were used to derive height-normalised indices (body composition/heightβ). Logistic regression models assessed the associations between these indices and health outcomes.

RESULTS

Distinct scaling powers were observed for visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and total abdominal adipose tissue (TAT), as well as for sagittal diameter (SAD), with marked sex differences. Powers for VAT were 1.786 ± 1.270 for males and 1.274 ± 0.692 for females. Powers for SAT were 2.266 ± 0.856 for males and 1.656 ± 0.497 for females. Powers for TAT were 2.141 ± 0.967 for males and 1.438 ± 0.489 for females. Powers for SAD were 0.646 ± 0.217 for males and 0.678 ± 0.141 for females. After controlling for age, BMI and WC, VAT/heightβ, TAT/heightβ and SAD/heightβ retained their significantly positive associations with the odds of health outcomes, whereas SAT/heightβ did not.

CONCLUSIONS

Our findings endorse the clinical utility of height-normalised indices, particularly VAT/heightβ, TAT/heightβ and SAD/heightβ, in health outcomes assessment. These indices, grounded in robust empirical data, underscore the necessity of a nuanced approach in obesity-related health evaluations, advocating for a departure from conventional methods like BMI.

Associations of Total Body Fat Mass and Skeletal Muscle Index with All-Cause and Cancer-Specific Mortality in Cancer Survivors

Purpose: The importance of body composition on cancer outcomes is of great clinical interest. Measures of body composition that differentiate fat mass from skeletal muscle mass can help redefine our understanding of body composition for cancer survival. We investigated whether the risk of all-cause and cancer-specific mortality differ by levels of total fat mass and sarcopenia status in cancer survivors. Our secondary aim was a subgroup analysis assessing the role of race within these associations. Methods: Participants included 1682 adult cancer survivors who had undergone a dual-energy X-ray absorptiometry (DXA) examination to measure body composition, from the 1999-2006 and 2011-2018 National Health and Nutrition Examination Survey (NHANES). Total fat mass was categorized into tertiles (we assessed high vs. low tertiles), and sarcopenia was considered as having an appendicular skeletal muscle mass index less than 7.26 kg/m2 for males and less than 5.45 kg/m2 for females. Multivariable Cox proportional hazard models estimated the adjusted hazard ratio (aHR) and 95% confidence interval (CI). Results: The mean age of study participants was 61.9 years, and they were followed up for an average of 9.67 years. The prevalence of sarcopenia was 25.0% (N = 304), and 33.4% (N = 561) had a high total fat mass. Participants with a higher fat mass (aHR = 1.30, 95% CI = 1.06-1.61) and with sarcopenia (aHR = 1.51, 95% CI = 1.22-1.88) had a 30% and 51% increased risk of all-cause mortality compared to participants with a low fat mass and with no sarcopenia, respectively. Further, sarcopenia (aHR = 1.74, 95% CI = 1.23-2.29) was associated with a higher risk of cancer-specific mortality in cancer survivors. The association between sarcopenia and all-cause mortality was twice as strong in Black people (aHR = 2.99, 95% CI = 1.39-6.06) compared to White people (aHR = 1.53, 95% CI = 1.19-1.95). Conclusions: Our findings show the opposing relations of fat mass and appendicular skeletal muscle mass index with mortality in a national sample of cancer survivors, and that the relationships may differ by race. These results emphasize the importance of maintaining a healthy body composition among cancer survivors.

Use of Tri-Ponderal Mass Index in Predicting Late Adolescent Overweight and Obesity in Children Aged 7–18

Background

Current reference systems using body mass index (BMI) or BMI z-scores to estimate overweight and obesity risk in adolescents are complex to use. An easy and effective measure and cutoffs such as the tri-ponderal mass index (TMI) are in need for parents and grassroots health workers.

Objective

The aim of this study was to test whether cohort-derived TMI could be efficient for obesity prediction and to find out whether simplified TMI cutoffs could be used in the prediction.

Methods

Data were obtained from a 12-year retrospective growth cohort generated in Guangdong, China. A total of 17,815 children (53.9% were boys) with 151,879 follow-ups conducted annually between 2005 and 2016 were involved. Late adolescent overweight and obesity were defined based on the BMI z-score (WHO 2007 growth reference) of the last measurement, which happened at the mean age of 17.2 (SD: 0.7) for both sexes. Analysis of the area under the curve (AUC) of the receiver operating characteristic curves was used to find the most appropriate cutoff.

Results

In total, 9,604 boys and 8,211 girls were included in the final analysis. TMI cutoffs performed better than WHO BMI cutoffs in the prediction of late adolescent overweight and obesity, with all corresponding AUCs <0.7. The simplified TMI cutoffs used to predict late adolescent overweight and obesity were 13.1 and 14.1 kg/m³ for children aged 7 to 15 years, respectively, with the corresponding AUCs ranging from 0.7315 (standard error, SE: 0.0132) to 0.9367 (SE: 0.0052). The cutoffs for predicting late adolescent overweight and obesity for children aged 16 to 18 years were 14.0 and 15.8 kg/m³, respectively, with the corresponding AUCs ranging from 0.9189 (SE: 0.0048) to 0.9841 (95% CI: 0.0027).

Conclusion

Tri-ponderal mass index with the ease of administration in practice could be a promising alternative screening tool to BMI for the prediction of late adolescent overweight and obesity.

Measuring body fat—How accurate is the extrapolation of predictive models in epidemiology?

Excess fat is a risk factor for many chronic diseases which can lead to premature mortality. Many studies have proposed predictive equations for body fat mass and body fat mass percentage based on anthropometric measures in relation to age and sex. However, the use of these predictive equations on other subject samples may not be relevant. Our objective is to assess whether the predictive equations proposed in the literature are generalizable to any population. We obtained fat mass and fat percentage on a reference population using Absorptiometry DXA. The predictive equations were applied to our population and the mean and individual differences between actual and estimated values were obtained. Predictive equations obtained from a reduced number of subjects have a very high Standard Error of Estimate (>3) and therefore their accuracy is not acceptable. Only the formulae established from a large number of individuals allow the estimation of values whose Standard Error of Estimate is less than 3. These equations, thanks to the large sample size, include a sufficiently large variability in anthropometric measurements covering the diversity of anthropometric values for the same fat value. However, predictive equations based on a large sample size, while exhibiting no current difference in variances, can show a shift in mean values. This mean-shift is the result of differences in DXA devices and needs to be corrected. It means that DXA values from a few individuals in the population under study must be obtained to calculate a corrective factor.

Scaling of computed tomography body composition to height: relevance of height-normalized indices in patients with colorectal cancer

BACKGROUND

Body weight scales to height with a power of ≈2 (weight/height² ), forming the basis of body mass index (BMI). The corresponding scaling of body composition measured by abdominal computed tomography (CT) to height has not been established. The objective of this analysis was to quantify the scaling of body composition measured by a single-slice axial abdominal CT image (skeletal muscle, and visceral, subcutaneous, and total adipose tissue) to height in patients with colorectal cancer (CRC).

METHODS

This cross-sectional study included non-Hispanic white males and females, aged 18-80 years, who were diagnosed with stage I-III CRC at an integrated health care system in North America between January 2006 and December 2011. Body composition was measured by a single-slice axial CT image of the third lumbar vertebra and analysed with a semi-automated threshold segmentation procedure. Allometric regression models were used to quantify height scaling powers (β ± standard error) for each body composition measure, adjusted for age, for males and females. An interaction test was used to determine if height scaling powers were statistically significantly different between males and females.

RESULTS

Among 2036 subjects, the mean (standard deviation) age was 64 ± 11 years, 1008 (49.5%) were female, and the mean (standard deviation) BMI was 27.9 ± 5.4 kg/m² . Powers for skeletal muscle area were 1.06 ± 0.12 for males and 0.80 ± 0.12 for females (P = 0.049). Powers for visceral adipose tissue area were 1.81 ± 0.64 for males and 0.57 ± 0.79 for females (P = 0.16). Powers for subcutaneous adipose tissue area were 2.04 ± 0.42 for males and 0.81 ± 0.45 for females (P = 0.056). Powers for total abdominal adipose tissue area were 1.80 ± 0.46 for males and 0.76 ± 0.50 for females (P = 0.20).

CONCLUSIONS

Body composition measured by single-slice axial abdominal CT, particularly muscle area, scales to height with age-adjusted powers that are different than 2 and are distinct between males and females. These observations may have implications for the development of height-adjusted body composition indices in patients with cancer.

Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review

Obesity is characterized by the accumulation of an excessive amount of fat mass (FM) in the adipose tissue, subcutaneous, or inside certain organs. The risk does not lie so much in the amount of fat accumulated as in its distribution. Abdominal obesity (central or visceral) is an important risk factor for cardiovascular diseases, diabetes, and cancer, having an important role in the so-called metabolic syndrome. Therefore, it is necessary to prevent, detect, and appropriately treat obesity. The diagnosis is based on anthropometric indices that have been associated with adiposity and its distribution. Indices themselves, or a combination of some of them, conform to a big picture with different values to establish risk. Anthropometric indices can be used for risk identification, intervention, or impact evaluation on nutritional status or health; therefore, they will be called anthropometric health indicators (AHIs). We have found 17 AHIs that can be obtained or estimated from 3D human shapes, being a noninvasive alternative compared to X-ray-based systems, and more accessible than high-cost equipment. A literature review has been conducted to analyze the following information for each indicator: definition; main calculation or obtaining methods used; health aspects associated with the indicator (among others, obesity, metabolic syndrome, or diabetes); criteria to classify the population by means of percentiles or cutoff points, and based on variables such as sex, age, ethnicity, or geographic area, and limitations.

Anthropometrics by Three-Dimensional Photonic Scanner in Patients with Obesity Before and After Bariatric Surgery

BACKGROUND

We studied body composition by three-dimensional photonic scanning (3DPS) and metabolic biomarkers in a large ethnically diverse cohort of individuals with severe obesity before and after weight loss by Roux-en-Y gastric bypass (RYGB) or adjustable gastric banding (AGB) surgery.

MATERIALS AND METHODS

Male and female participants (n = 95) underwent 3DPS testing in the weeks preceding bariatric surgery (baseline), and 1 year after either RYGB (n = 34) or AGB (n = 9).

RESULTS

Principal component analysis showed that A1C and HDL cholesterol clustered with waist-to-hip ratio (WHR). Both RYGB and AGB surgeries led to similar improvements in A1C and lipids after 1 year. RYGB led to greater decreases in body weight, and in most anthropometric measures, compared with AGB at 1 year. However, after accounting for weight loss differences, RYGB and AGB groups did not differ in regional decreases in circumferences or volumes; the exception was a greater reduction in lean mass in RYGB compared with AGB.

CONCLUSION

Distribution of weight loss, assessed by 3DPS, did not differ between RYGB and AGB, but surgery type predicted change in lean mass at 1 year.

Environmental Exposures during Puberty: Window of Breast Cancer Risk and Epigenetic Damage

During puberty, a woman’s breasts are vulnerable to environmental damage (“window of vulnerability”). Early exposure to environmental carcinogens, endocrine disruptors, and unhealthy foods (refined sugar, processed fats, food additives) are hypothesized to promote molecular damage that increases breast cancer risk. However, prospective human studies are difficult to perform and effective interventions to prevent these early exposures are lacking. It is difficult to prevent environmental exposures during puberty. Specifically, young women are repeatedly exposed to media messaging that promotes unhealthy foods. Young women living in disadvantaged neighborhoods experience additional challenges including a lack of access to healthy food and exposure to contaminated air, water, and soil. The purpose of this review is to gather information on potential exposures during puberty. In future directions, this information will be used to help elementary/middle-school girls to identify and quantitate environmental exposures and develop cost-effective strategies to reduce exposures.

Metabolic Health, Insulin, and Breast Cancer: Why Oncologists Should Care About Insulin

Studies investigating the potential link between adult pre-menopausal obesity [as measured by body mass index (BMI)] and triple-negative breast cancer have been inconsistent. Recent studies show that BMI is not an exact measure of metabolic health; individuals can be obese (BMI > 30 kg/m²) and metabolically healthy or lean (BMI < 25 kg/m²) and metabolically unhealthy. Consequently, there is a need to better understand the molecular signaling pathways that might be activated in individuals that are metabolically unhealthy and how these signaling pathways may drive biologically aggressive breast cancer. One key driver of both type-2 diabetes and cancer is insulin. Insulin is a potent hormone that activates many pathways that drive aggressive breast cancer biology. Here, we review (1) the controversial relationship between obesity and breast cancer, (2) the impact of insulin on organs, subcellular components, and cancer processes, (3) the potential link between insulin-signaling and cancer, and (4) consider time points during breast cancer prevention and treatment where insulin-signaling could be better controlled, with the ultimate goal of improving overall health, optimizing breast cancer prevention, and improving breast cancer survival.

Optimum waist circumference-height indices for evaluating adult adiposity: An analytic review

Phenotyping adults for excess adiposity and related health risks usually include three body size measurements: height, weight and waist circumference (WC). Height and weight are now widely used as components of the body shape measure, body mass index (BMI, weight/height² ), with the height power referred to as the scaling factor, α. At present, WC is usually not adjusted for height or is expressed as WC/height in which α = 1. Although other α values have been proposed, a critical review of these shape measures is lacking. Here, we examine classical pathways by which the scaling exponent for height used in BMI was developed and then apply this strategy to identify the optimum WC index characteristic of adult shape. Our analyses explored anthropometric, body composition and clinically-relevant data from US and Korean National Health and Nutrition Surveys. Our findings provide further support for the WC index of WC/height^0.5 as having the strongest associations with adiposity while having the weakest correlations with height across non-Hispanic white and black, Mexican American and Korean men and women. The WC index, defined as WC/height^0.5 , when combined with BMI, can play an important role when phenotyping adults for excess adiposity and associated health risks in research and clinical settings.

Allometric scaling of weight to height and resulting body mass index thresholds in two Asian populations

BACKGROUND

Body mass index (BMI) represents a normalization of weight to height and is used to classify adiposity. While the capacity of BMI as an adiposity index has been experimentally validated in Caucasians, but there has been little testing Asian populations.

METHODS

To determine whether weight scales to height squared in Asian Indians across the general population and in Asian Indian tribes an allometric analysis on the power law model, W = αHβ, where W is weight (kg) and H is height (m) was performed on cross-sectional weight and height data from India (N = 43,880) collected through the Anthropological Survey of India. The database contained males 18-84 years of age spanning 161 districts of 14 states and including 33 different tribes (N = 5,549). Models were developed that were unadjusted and adjusted for tribe membership. The Korean National Health and Nutrition Examination Survey (KNHANES) was used to compare to height-weight data from the Anthropological Survey of India and to calculate BMI thresholds for obesity status using a receiver operating characteristic.

RESULTS

The unadjusted power was β = 2.08 (s = 0.02). The power for the general population (non-tribal) was β = 2.11 (s = 0.02). Powers when adjusted for tribe ranged from 1.87 to 2.35 with 24 of the 33 tribes resulting in statistically significant (p < 0.05) differences in powers from the general population. The coefficients of the adjusted terms ranged from -0.22 to 0.26 and therefore the scaling exponent does not deviate far from 2. Thresholds for BMI classification of overweight in the KNHANES database were BMI = 21 kg/m2 (AUC = 0.89) for males 18 kg/m2 (AUC = 0.97) for females. Obesity classification was calculated as BMI = 26 kg/m2 (AUC = 0.81) and 23 kg/m2 (AUC = 0.83) for females.

CONCLUSIONS

Our study confirms that weight scales to height squared in Asian Indian males even after adjusting for tribe membership. We also demonstrate that optimal BMI thresholds are lower in a Korean population in comparison to currently used BMI thresholds. These results support the application of BMI in Asian populations with potentially lower thresholds.

A machine learning approach relating 3D body scans to body composition in humans

A long-standing question in nutrition and obesity research involves quantifying the relationship between body fat and anthropometry. To date, the mathematical formulation of these relationships has relied on pairing easily obtained anthropometric measurements such as the body mass index (BMI), waist circumference, or hip circumference to body fat. Recent advances in 3D body shape imaging technology provides a new opportunity for quickly and accurately obtaining hundreds of anthropometric measurements within seconds, however, there does not yet exist a large diverse database that pairs these measurements to body fat. Herein, we leverage 3D scanned anthropometry obtained from a population of United States Army basic training recruits to derive four subpopulations of homogenous body shape archetypes using a combined principal components and cluster analysis. While the Army database was large and diverse, it did not have body composition measurements. Therefore, these body shape archetypes were paired to an alternate smaller sample of participants from the Pennington Biomedical Research Center in Baton Rouge, LA that were not only similarly imaged by the same 3D scanning machine, but also had concomitant measures of body composition by dual-energy X-ray absorptiometry body composition. With this enhanced ability to obtain anthropometry through 3D scanning quickly of large populations, our machine learning approach for pairing body shapes from large datasets to smaller datasets that also contain state-of-the-art body composition measurements can be extended to pair other health outcomes to 3D body shape anthropometry.

Association between obesity with disease-free survival and overall survival in triple-negative breast cancer: A meta-analysis

OBJECTIVE

To investigate the relationship between obesity and disease-free survival (DFS) and overall survival (OS) of triple-negative breast cancer.

METHODS

Citations were searched in PubMed, Cochrane Library, and Web of Science. Random effect model meta-analysis was conducted by using Revman software version 5.0, and publication bias was evaluated by creating Egger regression with STATA software version 12.

RESULTS

Nine studies (4412 patients) were included for DFS meta-analysis, 8 studies (4392 patients) include for OS meta-analysis. There were no statistical significances between obesity with DFS (P = .60) and OS (P = .71) in triple-negative breast cancer (TNBC) patients.

CONCLUSION

Obesity has no impact on DFS and OS in patients with TNBC.

Obesity and Triple-Negative Breast Cancer: Disparities, Controversies, and Biology

Once considered a problem of Western nations, obesity (body mass index ≥30 kg/m²) has rapidly increased since the 1970s to become a major threat to world health. Since 1970, the face of obesity has changed from a disease of affluence and abundance to a disease of poverty. During the last 10 years, studies have mechanistically linked obesity and an obese tumor microenvironment with signaling pathways that predict aggressive breast cancer biology. For example, in the United States, African American women are more likely than non-Hispanic European American women to be obese and to be diagnosed with triple-negative breast cancer (TNBC). In 2008, the Carolina Breast Study found that obesity (increased waist/hip ratio) was linked to an increased incidence of TNBC in premenopausal and postmenopausal African American women. Subsequently, several groups have investigated the potential link between obesity and TNBC in African American women. To date, the data are complex and sometimes contradictory. We review epidemiologic studies that investigated the potential association among obesity, metabolic syndrome, and TNBC in African American women and mechanistic studies that link insulin signaling to the obese breast microenvironment, tissue inflammation, and aggressive TNBC biology.

Obesity and Triple-Negative Breast Cancer: Disparities, Controversies, and Biology

Once considered a problem of Western nations, obesity (body mass index ≥30 kg/m²) has rapidly increased since the 1970s to become a major threat to world health. Since 1970, the face of obesity has changed from a disease of affluence and abundance to a disease of poverty. During the last 10 years, studies have mechanistically linked obesity and an obese tumor microenvironment with signaling pathways that predict aggressive breast cancer biology. For example, in the United States, African American women are more likely than non-Hispanic European American women to be obese and to be diagnosed with triple-negative breast cancer (TNBC). In 2008, the Carolina Breast Study found that obesity (increased waist/hip ratio) was linked to an increased incidence of TNBC in premenopausal and postmenopausal African American women. Subsequently, several groups have investigated the potential link between obesity and TNBC in African American women. To date, the data are complex and sometimes contradictory. We review epidemiologic studies that investigated the potential association among obesity, metabolic syndrome, and TNBC in African American women and mechanistic studies that link insulin signaling to the obese breast microenvironment, tissue inflammation, and aggressive TNBC biology.

Anthropometric dimensions provide reliable estimates of abdominal adiposity: A validation study

Abdominal fat accumulation is a major risk factor for cardiometabolic morbidity and mortality. The purpose of the study is to assess the possibility of developing accurate estimation equations based on body measurements to determine total abdominal (TFA), subcutaneous (SFA) and visceral fat area (VFA). Hungarian volunteers (n=198) aged between 20 and 81 years were enrolled in the study, which was conducted between July and November 2014. All persons underwent anthropometric measurements and computer tomographic (CT) scanning. Sex-specific multiple linear regression analyses were conducted in a subgroup of 98 participants to generate estimation models, then Bland-Altman's analyses were applied in the cross-validation group to compare their predictive efficiency. The variables best predicting VFA were hip circumference, calf circumference and waist-to-hip ratio (WHR) for males (R²=0.713; SEE=5602.1mm²) and sagittal abdominal diameter (SAD), WHR, thigh circumference and triceps skinfold for females (R²=0.845; SEE=3835.6mm²). The SFA prediction equation included SAD, thigh circumference and abdominal skinfold for males (R²=0.848; SEE=4124.1mm²), body mass index and thigh circumference for females (R²=0.861; SEE=5049.7mm²). Prediction accuracy was the highest in the case of TFA: hip circumference and WHR for males (R²=0.910; SEE=5637.2mm²), SAD, thigh circumference and abdominal skinfold for females (R²=0.915; SEE=6197.5mm²) were used in the equations. The results suggested that deviations in the predictions were independent of the amount of adipose tissue. Estimation of abdominal fat depots based on anthropometric traits could provide a cheap, reliable method in epidemiologic research and public health screening to evaluate the risk of cardiometabolic events.

Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables

Background

The conventional measurement of obesity utilises the body mass index (BMI) criterion. Although there are benefits to this method, there is concern that not all individuals at risk of obesity-associated medical conditions are being identified. Whole-body fat percentage (%FM), and specifically visceral adipose tissue (VAT) mass, are correlated with and potentially implicated in disease trajectories, but are not fully accounted for through BMI evaluation. The aims of this study were (a) to compare five anthropometric predictors of %FM and VAT mass, and (b) to explore new cut-points for the best of these predictors to improve the characterisation of obesity.

Methods

BMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and waist/height^0.5 (WHT.5R) were measured and calculated for 81 adults (40 women, 41 men; mean (SD) age: 38.4 (17.5) years; 94% Caucasian). Total body dual energy X-ray absorptiometry with Corescan (GE Lunar iDXA, Encore version 15.0) was also performed to quantify %FM and VAT mass. Linear regression analysis, stratified by sex, was applied to predict both %FM and VAT mass for each anthropometric variable. Within each sex, we used information theoretic methods (Akaike Information Criterion; AIC) to compare models. For the best anthropometric predictor, we derived tentative cut-points for classifying individuals as obese (>25% FM for men or >35% FM for women, or > highest tertile for VAT mass).

Results

The best predictor of both %FM and VAT mass in men and women was WHtR. Derived cut-points for predicting whole body obesity were 0.53 in men and 0.54 in women. The cut-point for predicting visceral obesity was 0.59 in both sexes.

Conclusions

In the absence of more objective measures of central obesity and adiposity, WHtR is a suitable proxy measure in both women and men. The proposed DXA-%FM and VAT mass cut-offs require validation in larger studies, but offer potential for improvement of obesity characterisation and the identification of individuals who would most benefit from therapeutic intervention.

A structured approach to hypotheses involving continuous exposures over the life course

Background: Epidemiologists are often interested in examining different hypotheses for how exposures measured repeatedly over the life course relate to later-life outcomes. A structured approach for selecting the hypotheses most supported by theory and observed data has been developed for binary exposures. The aim of this paper is to extend this to include continuous exposures and allow for confounding and missing data.

Methods: We studied two examples, the association between: (i) maternal weight during pregnancy and birthweight; and (ii) stressful family events throughout childhood and depression in adolescence. In each example we considered several plausible hypotheses including accumulation, critical periods, sensitive periods, change and effect modification. We used least angle regression to select the hypothesis that explained the most variation in the outcome, demonstrating appropriate methods for adjusting for confounders and dealing with missing data.

Results: The structured approach identified a combination of sensitive periods: pre-pregnancy weight, and gestational weight gain 0-20 weeks and 20-40 weeks, as the best explanation for variation in birthweight after adjusting for maternal height. A sensitive period hypothesis best explained variation in adolescent depression, with the association strengthening with the proximity of stressful family events. For each example, these models have theoretical support at least as strong as any competing hypothesis.

Conclusions: We have extended the structured approach to incorporate continuous exposures, confounding and missing data. This approach can be used in either an exploratory or a confirmatory setting. The interpretation, plausibility and consistency with causal assumptions should all be considered when proposing and choosing life course hypotheses.

Divergent associations of height with cardiometabolic disease and cancer: epidemiology, pathophysiology, and global implications

Among chronic non-communicable diseases, cardiometabolic diseases and cancer are the most important causes of morbidity and mortality worldwide. Although high BMI and waist circumference, as estimates of total and abdominal fat mass, are now accepted as predictors of the increasing incidence of these diseases, adult height, which also predicts mortality, has been neglected. Interestingly, increasing evidence suggests that height is associated with lower cardiometabolic risk, but higher cancer risk, associations supported by mendelian randomisation studies. Understanding the complex epidemiology, biology, and pathophysiology related to height, and its association with cardiometabolic diseases and cancer, is becoming even more important because average adult height has increased substantially in many countries during recent generations. Among the mechanisms driving the increase in height and linking height with cardiometabolic diseases and cancer are insulin and insulin-like growth factor signalling pathways. These pathways are thought to be activated by overnutrition, especially increased intake of milk, dairy products, and other animal proteins during different stages of child development. Limiting overnutrition during pregnancy, early childhood, and puberty would avoid not only obesity, but also accelerated growth in children-and thus might reduce risk of cancer in adulthood.

Why are there race/ethnic differences in adult body mass index-adiposity relationships? A quantitative critical review

Body mass index (BMI) is now the most widely used measure of adiposity on a global scale. Nevertheless, intense discussion centers on the appropriateness of BMI as a phenotypic marker of adiposity across populations differing in race and ethnicity. BMI-adiposity relations appear to vary significantly across race/ethnic groups, but a collective critical analysis of these effects establishing their magnitude and underlying body shape/composition basis is lacking. Accordingly, we systematically review the magnitude of these race-ethnic differences across non-Hispanic (NH) white, NH black and Mexican American adults, their anatomic body composition basis and potential biologically linked mechanisms, using both earlier publications and new analyses from the US National Health and Nutrition Examination Survey. Our collective observations provide a new framework for critically evaluating the quantitative relations between BMI and adiposity across groups differing in race and ethnicity; reveal new insights into BMI as a measure of adiposity across the adult age-span; identify knowledge gaps that can form the basis of future research and create a quantitative foundation for developing BMI-related public health recommendations.

Is there a greater maternal than paternal influence on offspring adiposity in India?

Previous research has provided conflicting evidence regarding fetal roots of adiposity in India. To compare the strength of association between maternal and paternal body mass indexes (BMIs) corrected for height with offspring BMI in India to examine the potential for intrauterine mechanisms to influence offspring adiposity in India, we analysed a sample of 16,528 mother-father-offspring trios from the 2005 to 2006 Indian National Family Health Survey. Children were aged 0-59 months with parents aged 15-49 years (mothers) and 15-54 years (fathers). Linear and logistic regression models, specified in multiple ways, were used to estimate associations between parental BMI* (BMI redefined by power term x (kg/m(x)) to be independent from height), and child BMI/top decile of child BMI. Higher values of maternal BMI and paternal BMI were associated with higher values of offspring BMI. In comparing the effects of maternal BMI and paternal BMI, however, no consistent differences were found in the strength of these parental influences on offspring BMI. In the fully adjusted linear model, the standardised coefficient was 0.131 (95% CI 0.110 to 0.154) for maternal BMI* and 0.079 (95% CI 0.056 to 0.103) for paternal BMI*; with evidence of heterogeneity between maternal-offspring and paternal-offspring associations (p=0.005). This was not robust in the unstandardised regression (β=0.056, 95% CI 0.044 to 0.067 for maternal BMI and β=0.039, 95% CI 0.025 to 0.053 for paternal BMI, p=0.093). Mixed results indicate that compared with paternal BMI, maternal BMI did not have a consistently stronger influence on offspring BMI in India.

Trends in group inequalities and interindividual inequalities in BMI in the United States, 1993-2012

BACKGROUND

Marked increases in mean body mass index (BMI) and prevalence of obesity and overweight in the United States are well known. However, whether these average increases were accompanied by changing dispersion (or SD) remains understudied.

OBJECTIVE

We investigated population-level changes in the BMI distribution over time to understand how changes in dispersion reflect between-group compared with within-group inequalities in weight gain in the United States.

DESIGN

Using data from the Behavioral Risk Factor Surveillance System survey (1993-2012), we analyzed associations between mean, SD, and median BMI and BMI at the 5th and 95th percentiles for 3,050,992 non-Hispanic white, non-Hispanic black, and Hispanic men and women aged 25-64 y.

RESULTS

Overall, an increase of 1.0 in mean BMI (in kg/m²) was associated with an increase of 0.70 (95% CI: 0.67, 0.73) in the SD of BMI. A change of 1.0 in median BMI was associated with a change of 0.18 (95% CI: 0.14, 0.21) in the BMI value at the 5th percentile compared with a change of 2.94 (95% CI: 2.81, 3.07) at the 95th percentile. Quantile-quantile plots showed unequal changes in the BMI distribution, with pronounced changes at higher percentiles. Similar patterns were observed in subgroups stratified by sex, race-ethnicity, and education with non-Hispanic black women and women with less than a high school education having highest mean BMI, SD of BMI, and BMI values at the 5th and 95th percentiles.

CONCLUSIONS

Mean BMI and the percentage of overweight and obese individuals do not fully describe population changes in BMI. Increases in within-group inequality in BMI represent an underrecognized characteristic of population-level weight gain. Crucially, similar increases in dispersion within groups suggest that growing inequalities in BMI at the population level are not driven by these socioeconomic and demographic factors. Future research should focus on understanding factors driving inequalities in weight gain between individuals.

Optimal cutoffs of obesity measures in relation to cancer risk in postmenopausal women in the Women's Health Initiative Study

BACKGROUND

Obesity is a risk factor for several cancers in postmenopausal women. We attempted to determine cutoffs of adiposity measures in relation to risk of obesity-related cancers among postmenopausal women and to examine the effects of hormone therapy (HT) use on the cutoffs, neither of which has been broadly studied.

METHODS

We used data from the Women's Health Initiative cohort (n=144,701) and applied Cox-proportional hazards regressions to each combination of 17 cancer types and 6 anthropometric measures (weight, body mass index [BMI], weight to height ratio, waist circumference, waist to hip ratio [WHR], and waist to height ratio). Interactions between the anthropometric measures and HT use were also examined. Cutoffs were determined by applying a grid search followed by a two-fold cross validation method. Survival ROC analysis of 5- and 10-year incidence followed.

RESULTS

Breast, colorectal, colon, endometrium, kidney, and all cancers combined were significantly positively associated with all six anthropometric measures, whereas lung cancer among ever smokers was significantly inversely associated with all measures except WHR. The derived cutoffs of each obesity measure varied across cancers (e.g., BMI cutoffs for breast and endometrium cancers were 30 kg/m(2) and 34 kg/m(2), respectively), and also depended on HT use. The Youden indices of the cutoffs for predicting 5- and 10-year cancer incidence were higher among HT never users.

CONCLUSION

Using a panel of different anthropometric measures, we derived optimal cut-offs categorizing populations into high- and low-risk groups, which differed by cancer type and HT use. Although the discrimination abilities of these risk categories were generally poor, the results of this study could serve as a starting point from which to determine adiposity cutoffs for inclusion in risk prediction models for specific cancer types.

Scaling of adult body weight to height across sex and race/ethnic groups: relevance to BMI

BACKGROUND

Body mass index (BMI) is formulated on the assumption that body weight (BW) scales to height with a power of 2 (BW∝height(2)), independent of sex and race-ethnicity. Powers differing from 2 are observed in studies of selected samples, thus raising the question if BMI is a generalizable metric that makes BW independent of height across populations.

OBJECTIVES

The objectives were to test the hypothesis that adult BW scales to height with a power of 2 independent of sex and race-ethnicity and to advance an understanding of BMI as a measure of shape by extending allometric analyses to waist circumference (WC).

DESIGN

We conducted cross-sectional subject evaluations, including body composition, from the NHANES and the Korean NHANES (KNHANES). Variations of the allometric model (Y = αX(β)) were used to establish height scaling powers (β ± SE) across non-Hispanic white and black, Mexican American, and Korean men and women.

RESULTS

Exploratory analyses in population samples established age and adiposity as important independent determinants of height scaling powers (i.e., β). After age and adiposity in the next series of analyses were controlled for, BW scaling powers were nonsignificantly different between race/ethnic groups within each sex group; WC findings were similar in women, whereas small but significant between-race differences were observed in the men. Sex differences in β values were nonsignificant except for BW in non-Hispanic blacks and WC in Koreans (P < 0.05). Nationally representative powers for BW were (NHANES/KNHANES) 2.12 ± 0.05/2.11 ± 0.06 for men and 2.02 ± 0.04/1.99 ± 0.06 for women and for WC were 0.66 ± 0.03/0.67 ± 0.05 for men and 0.61 ± 0.04/0.56 ± 0.05 for women.

CONCLUSIONS

Adult BW scales to height with a power of ∼2 across the 8 sex and race/ethnic groups, an observation that makes BMI a generalizable height-independent measure of shape across most populations. WC also follows generalizable scaling rules, a finding that has implications for defining body shape in populations who differ in stature.

Genome-wide association study of height-adjusted BMI in childhood identifies functional variant in ADCY3

OBJECTIVE

Genome-wide association studies (GWAS) of BMI are mostly undertaken under the assumption that "kg/m(2) " is an index of weight fully adjusted for height, but in general this is not true. The aim here was to assess the contribution of common genetic variation to a adjusted version of that phenotype which appropriately accounts for covariation in height in children.

METHODS

A GWAS of height-adjusted BMI (BMI[x] = weight/height(x) ), calculated to be uncorrelated with height, in 5809 participants (mean age 9.9 years) from the Avon Longitudinal Study of Parents and Children (ALSPAC) was performed.

RESULTS

GWAS based on BMI[x] yielded marked differences in genomewide results profile. SNPs in ADCY3 (adenylate cyclase 3) were associated at genome-wide significance level (rs11676272 (0.28 kg/m(3.1) change per allele G (0.19, 0.38), P = 6 × 10(-9) ). In contrast, they showed marginal evidence of association with conventional BMI [rs11676272 (0.25 kg/m(2) (0.15, 0.35), P = 6 × 10(-7) )]. Results were replicated in an independent sample, the Generation R study.

CONCLUSIONS

Analysis of BMI[x] showed differences to that of conventional BMI. The association signal at ADCY3 appeared to be driven by a missense variant and it was strongly correlated with expression of this gene. Our work highlights the importance of well understood phenotype use (and the danger of convention) in characterising genetic contributions to complex traits.

Obesity and adiposity indicators, asthma, and atopy in Puerto Rican children

BACKGROUND

Whether adiposity indicators other than body mass index (BMI) should be used in studies of childhood asthma is largely unknown. The role of atopy in "obese asthma" is also unclear.

OBJECTIVES

To examine the relationship among adiposity indicators, asthma, and atopy in Puerto Rican children, and to assess whether atopy mediates the obesity-asthma association.

METHODS

In a study of Puerto Rican children with (n = 351) and without (n = 327) asthma, we measured BMI, percent of body fat, waist circumference, and waist-to-hip ratio. The outcomes studied included asthma, lung function, measures of atopy, and, among cases, indicators of asthma severity or control. We performed mediation analysis to assess the contribution of atopy to the relationship between adiposity and asthma.

RESULTS

BMI, percent of body fat, and waist circumference were associated with increased odds of asthma. Among cases, all 3 measures were generally associated with lung function, asthma severity/control, and atopy; however, there were differences depending on the adiposity indicator analyzed. Atopy considerably mediated the adiposity-asthma association in this population: allergic rhinitis accounted for 22% to 53% of the association with asthma, and sensitization to cockroach mediated 13% to 20% of the association with forced vital capacity and 29% to 42% of the association with emergency department visits for asthma.

CONCLUSIONS

Adiposity indicators are associated with asthma, asthma severity/control, and atopy in Puerto Rican children. Atopy significantly mediates the effect of adiposity on asthma outcomes. Longitudinal studies are needed to further investigate the causal role, if any, of adiposity distribution and atopy on "obese asthma" in childhood.

Evidence that an HMGA1 gene variant associates with type 2 diabetes, body mass index, and high-density lipoprotein cholesterol in a Hispanic-American population

BACKGROUND

High-mobility group AT-hook 1 (HMGA1) is an important regulator of the insulin receptor gene. We have previously shown in three populations of white European ancestry that the HMGA1 gene variant rs146052672 (also designated IVS5-13insC) is associated with type 2 diabetes mellitus (T2DM). The aim of this study was to measure the frequency of this variant and to determine the degree of the association with T2DM and other features of the metabolic syndrome in a replication cohort of Hispanic Americans.

METHODS

This was a retrospective cohort study of well-characterized Hispanic-American participants analyzed in the Genomic Resource in Atherosclerosis (GRA) (Cardiovascular Research Institute, University of California, San Francisco). A total of 1144 individuals were studied, 320 of whom had T2DM. We examined associations of the rs146052672 SNP with T2DM, plasma lipids, lipoproteins, and body mass index (BMI).

RESULTS

In this Hispanic-American cohort, the HMGA1 rs146052672 minor allele (C-insertion) frequency (MAF) was 21.4% with a carrier frequency of 37.4%, considerably higher than we previously observed among GRA white Europeans (MAF 3.1%). The prevalence of the IVS5-13insC variant was significantly higher in those with T2DM compared to controls [42.2% vs. 35.5%; odds ratio (OR) 1.44 95% confidence interval (CI) 1.09-1.90, P=0.011). The variant was also associated with BMI (positively, P=0.045) and plasma high-density lipoprotein cholesterol (HDL-C) (negatively, P=0.047).

CONCLUSIONS

As we saw previously among white Europeans, a functional HMGA1 variant was associated with T2DM in individuals of Hispanic-American ethnicity and was present at a much higher frequency.