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 $$ W $$ ) varies with height (H $$ H $$ ) in adult males and females. Using data on 12 short and 12 tall subjects of each sex, Quetelet established the rule thatW $$ W $$ is approximately proportional (∝ $$ \propto $$ ) to H2 in adults; that is,W ∝ H 2 $$ W\propto {H}^2 $$ whenW ≈ α H 2 $$ W\approx \alpha {H}^2 $$ for some constantα $$ \alpha $$ . Quetelet's Rule (W ∝ H 2 $$ W\propto {H}^2 $$ ), transformed and renamed in the twentieth century to body mass index (BMI = W / H 2 $$ \mathrm{BMI}=W/{H}^2 $$ ), 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 indexBMI = W / H 2 $$ \mathrm{BMI}=W/{H}^2 $$ . 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.

Strengths and Limitations of BMI in the Diagnosis of Obesity: What is the Path Forward?

PURPOSE OF REVIEW

This review aims to discuss strengths and limitations of body mass index (BMI) in diagnosing obesity, the use of alternative anthropometric measurements, and potential new technology that may change the future of obesity diagnosis and management.

RECENT FINDINGS

The diagnosis of obesity requires the anthropometric assessment of adiposity. In clinical settings, this should include BMI with confirmation that elevated BMI represents excess adiposity and a measure of fat distribution (i.e., waist circumference (WC), waist to height ratio (WHtR), or WC divided by height0.5 (WHR.5R). Digital anthropometry and bioelectric impedance (BIA) can estimate fat distribution and be feasibly employed in the clinic. In addition, the diagnosis should include a clinical component assessing the presence and severity of weight-related complications. As anthropometric measures used in the diagnosis of obesity, BMI is generally sufficient if confirmed to represent excess adiposity, and there are advantages to the use of WHtR over WC to assess fat distribution. BIA and digital anthropometry have the potential to provide accurate measures of fat mass and distribution in clinical settings. There should also be a clinical evaluation for the presence and severity of obesity complications that can be used to stage the disease.

Comparative efficacy of anthropometric indices in predicting 10-year ASCVD risk: insights from NHANES data

Background

Cardiovascular diseases remain a leading cause of morbidity and mortality worldwide. Accurately predicting the 10-year risk of Atherosclerotic Cardiovascular Disease (ASCVD) is crucial for timely intervention and management. This study aimed to evaluate the predictive performance of six anthropometric indices in assessing the 10-year ASCVD risk.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) database (1999-2018), the study involved 11,863 participants after applying exclusion criteria. Six anthropometric indices-waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and waist-to-height0.5 ratio (WHT.5R)-were calculated. The 10-year ASCVD risk was assessed using the 2013 ACC/AHA guidelines & pooled cohort equations model. Participants were divided into two groups based on an ASCVD risk threshold of 7.5%. Statistical analysis included chi-square tests, odds ratios, and receiver operating characteristic (ROC) curves.

Results

The study found significant differences in baseline characteristics between participants with ASCVD risk less than 7.5% and those with a risk greater than or equal to 7.5%, stratified by gender. In both male and female groups, individuals with higher ASCVD risk exhibited higher age, waist circumference, BMI, and a higher prevalence of health-compromising behaviors. ABSI emerged as the most accurate predictor of ASCVD risk, with the highest area under the curve (AUC) values in both genders. The optimal cut-off values for ABSI was established for effective risk stratification (cut-off value = 0.08).

Conclusion

The study underscores the importance of anthropometric indices, particularly ABSI, in predicting the 10-year risk of ASCVD. These findings suggest that ABSI, along with other indices, can be instrumental in identifying individuals at higher risk for ASCVD, thereby aiding in early intervention and prevention strategies.

'At risk' waist-to-height ratio cut-off points recently adopted by NICE and US Department of Defense will unfairly penalize shorter adults. What is the solution?

OBJECTIVES

To a) demonstrate that adopting 'at risk' waist-to-height ratio (WHTR) cut-off points, recently approved by National Institute for Health and Care Excellence (NICE) and the United States Department of Defense (USDoD), will unfairly penalize shorter individuals and will be too lenient for taller individuals, b) to confirm that waist circumference (WC) of a sample of US service personnel, scales to approximately height^0.5, supporting the notion that WC, to be independent of height (HT), should be normalized using WC.HT^-0.5 (WHT•5R), and c) to identify the WHT•5R cut-off points that will reduce or eliminate this unwanted bias.

SUBJECTS/METHODS

We employed a three independent cross-sectional sample design. All n = 58,742 participants underwent anthropometric assessment of body mass, stature and waist circumference.

RESULTS

The allometric power-law model WC=a.HT^b for US service personnel identified the height exponent to be b= 0.418 (95 % CI 0.251-0.585), confirming that the simple body-shape index for WC to be independent of HT, should be WC.HT^-0.5. Chi-square tests of independence and for linear trend confirmed that by adopting WHTR cut-off point, shorter individuals (both service personnel and non-service participants) will be over penalized (classified as being 'at risk'). New WC independent-of-height ratio cut-off points were found to resolve this problem.

CONCLUSIONS

Adopting WHTR cut-off thresholds (either 0.5 or 0.55) will lead to shorter adults being unfairly classified as being 'at risk' in terms of their central adiposity and general health status. Adopting new WHT•5R cut-off point thresholds were found to greatly reduce or eliminate this bias.

Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study

BACKGROUND

Previous studies have explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study.

METHODS

Data collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity.

RESULTS

A total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P<0.001). Regardless of general obesity status at baseline, increased WC was associated with a high risk of multimorbidity. Compared to the subjects with baseline BMI<24 kg/m2 and WC<90 (men)/80 (women), the HRs (95% CI) of the baseline BMI<24 kg/m2 and WC≥90 (men)/80 (women) group and BMI≥24 kg/m2 and WC≥90 (men)/80 (women) group were 1.31 (1.08, 1.61) and 1.82 (1.68, 1.97), respectively. In addition, the dynamics of WC could reflect the risk of multimorbidity. When subjects with baseline WC<90 (men)/80 (women) progressed to WC≥90 (men)/80 (women) during follow-up, the risk of multimorbidity significantly increased (HR = 1.78; 95% CI, 1.64, 1.95), while the risk of multimorbidity tended to decrease when people with abnormal WC at baseline reversed to normal at follow-up (HR = 1.40; 95% CI, 1.26, 1.54) compared to those who still exhibited abnormal WC at follow-up (HR = 2.00; 95% CI, 1.82, 2.18).

CONCLUSIONS

Central obesity is an independent and alterable risk factor for the occurrence of multimorbidity in middle-aged and elderly populations. In addition to the clinical measurement of BMI, the measurement of the central obesity index WC may provide additional benefits for the identification of multimorbidity in the Chinese middle-aged and elderly populations.

NICE's recent guidelines on "the size of your waist" unfairly penalizes shorter people

The National Institute for Clinical Excellence (NICE) has just released its latest guidelines to assess and predict health risk, such as type 2 diabetes, hypertension or cardiovascular disease. Their latest advice is "Keep the size of your waist to less than half of your height". We believe this advice is flawed and will seriously and unfairly penalize shorter people and lull taller people into a false sense of security. In this short communication, we provide this evidence. We consider this a serious oversight by NICE and feel strongly that this evidence needs to be made available in the public domain.

BMI is dead; long live waist-circumference indices: But which index should we choose to predict cardio-metabolic risk?

BACKGROUND AND AIMS

There is growing evidence that Body Mass Index (BMI) is unfit for purpose. Waist circumference (WC) indices appear to be the preferred alternative, although it is not clear which WC index is optimal at predicting cardio-metabolic risk (CMR) and associated health outcomes.

METHODS AND RESULTS

We obtained a stratified random probability sample of 53,390 participants from the Health Survey for England (HSE), 2008-2018. The four available CMR factors were; high-density lipoproteins (HDL) cholesterol, glycated haemoglobin (HbA1c), systolic (SBP) and diastolic blood pressure (DBP). Strength of association between the four cardio-metabolic risk factors and competing anthropometric indicators of weight status [BMI, Waist-to-height ratio (WHTR), unadjusted WC, and a new WC index independent of height, WHT·5R = WC/height^0.5] was assessed separately, using simple correlations and ANCOVAs, and together (combined) using MANCOVA, controlling for age, sex and ethnicity. Centile curves for the new index WHT·5R = WC/height^0.5were also provided.

CONCLUSIONS

Waist-circumference indices were superior to BMI when explaining/predicting our CMR factors, before and after controlling for age, sex and ethnicity. No single WC index was consistently superior. Results suggest that WHTR is the strongest predictor of HbA1c, confirming that shorter individuals are at great risk of diabetes. The most appropriate WC index associated with blood pressure was WHT·5R for DBP, or unadjusted WC for SBP. Given HDL cholesterol is independent of height, the best predictor of HDL was WHT.5R. Clearly, "no one size fits all!". MANCOVA identified WHT·5R to be the best single WC index associated with a composite of all four CMR factors.

Identification of the Best Anthropometric Index for Predicting the 10-Year Cardiovascular Disease in Southwest China: A Large Single-Center, Cross-Sectional Study

INTRODUCTION

This population-based cross-sectional study aimed to identify the best predictor of the 10-year cardiovascular (CV) high risk among old and new anthropometric indices.

METHODS

We investigated 76,915 adults older than 18 years of age living in southwest China. Ten obesity indices were calculated. The 10-year cardiovascular disease (CVD) risk was estimated using the Framingham risk score. Receiver operating characteristic curve analysis was performed to assess the ability of the anthropometric index to predict the 10-year high risk of CVD events.

RESULTS

The waist-to-hip ratio (WHR) had the highest area under the curve (AUC) value (0.711; sensitivity: 62.22%, specificity: 42.73%) in men, while the body fat index (BAI) had the lowest AUC value (0.624, sensitivity: 49.07%, specificity: 54.84%). The waist-to-height ratio (WHtR) and the body roundness index (BRI) showed the highest AUC value (0.751, sensitivity: 39.24%, 39.83%, specificity: 75.68%, 68.59%) in women, while the BAI showed the lowest AUC value (0.671, sensitivity: 53.15%, specificity: 57.14%).

CONCLUSIONS

The WHR was the best anthropometric measure for assessing the 10-year high risk of CVD in men, while the WHtR and BRI were the best measures for women. In men, the WHR should be < 0.88, and in women, the WHtR should be < 0.502 or the BRI should be < 3.41.

Association between Three Waist Circumference-Related Obesity Metrics and Estimated Glomerular Filtration Rates

Studies that have assessed the associations between obesity and the estimated glomerular filtration rate (eGFR) have reported inconsistent results. This cross-sectional study was performed to investigate the associations between three waist circumference (WC)-related obesity metrics (waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and waist-to-height^0.5 ratio (WHt.5R)) and eGFRs. This study included 2133 men and 3443 women who were older than 40 years with eGFRs ≥ 60 mL/min/1.73 m² from the Korean Multi-Rural Communities Cohort. We calculated the residual body mass index (BMI) to reduce multicollinearity among the obesity metrics and performed multiple linear regression. For both sexes, among the adjusted models, most of the general obesity metrics were significantly associated with eGFRs. Particularly for women, the WC-related and general obesity metrics had a stronger effect on eGFRs in the quartile models that included the BMI and the residual BMI, respectively. When WC-related obesity metrics had a stronger effect than the general obesity metric, for both sexes, WHtR showed a significant impact than WHt.5R and WHR on eGFRs. Reducing multicollinearity had an important role in assessing the obesity metrics’ association with eGFRs. Overall, applying the residual method in further studies might help with evaluating the obesity paradox on renal function.

Modelling of human torso shape variation inferred by geometric morphometrics

Traditional body measurement techniques are commonly used to assess physical health; however, these approaches do not fully represent the complex shape of the human body. Three-dimensional (3D) imaging systems capture rich point cloud data that provides a representation of the surface of 3D objects and have been shown to be a potential anthropometric tool for use within health applications. Previous studies utilising 3D imaging have only assessed body shape based on combinations and relative proportions of traditional body measures, such as lengths, widths and girths. Geometric morphometrics (GM) is an established framework used for the statistical analysis of biological shape variation. These methods quantify biological shape variation after the effects of non-shape variation-location, rotation and scale-have been mathematically held constant, otherwise known as the Procrustes paradigm. The aim of this study was to determine whether shape measures, identified using geometric morphometrics, can provide additional information about the complexity of human morphology and underlying mass distribution compared to traditional body measures. Scale-invariant features of torso shape were extracted from 3D imaging data of 9,209 participants form the LIFE-Adult study. Partial least squares regression (PLSR) models were created to determine the extent to which variations in human torso shape are explained by existing techniques. The results of this investigation suggest that linear combinations of body measures can explain 49.92% and 47.46% of the total variation in male and female body shape features, respectively. However, there are also significant amounts of variation in human morphology which cannot be identified by current methods. These results indicate that Geometric morphometric methods can identify measures of human body shape which provide complementary information about the human body. The aim of future studies will be to investigate the utility of these measures in clinical epidemiology and the assessment of health risk.

What is the optimal anthropometric index/ratio associated with two key measures of cardio-metabolic risk associated with hypertension and diabetes?

BACKGROUND

Few studies have investigated the optimal anthropometric index associated with potential cardio-metabolic risk. Using direct measures of standing height, body mass, and waist circumference, we sought to identify the optimal index for detecting cardio-metabolic risk associated with diabetes and hypertension in a nationally representative sample of US adults.

METHODS

Complete (non-missing) cross-sectional data from 8375 US adults aged 18-80+ years were obtained from the 2015-16 and 2017-March 2020 (pre-pandemic) cycles of the National Health and Nutrition Examination Survey. The cardio-metabolic risk was identified using blood pressure and glycohemoglobin (A1c). Allometric models were used to identify the optimal anthropometric indices associated with cardio-metabolic risk. Receiver operating characteristics curves were used to verify the discriminatory ability of the identified index in comparison with other anthropometric measures.

RESULTS

The optimal anthropometric index associated with cardio-metabolic risk was waist circumference divided by body mass to the power of 0.333 (WC/M^0.333). The ability for this new index to discriminate those with diabetes (area under the ROC curve: 0.73 [95%CI: 0.71-0.74]) and hypertension (area under the curve: 0.70 [95%CI: 0.69-0.72]) was superior to all other anthropometric measure/indices investigated in this study (body mass index, waist circumference, waist-to-height ratio, and waist/height^0.5).

CONCLUSIONS

We identified WC/M^0.333 as the optimal anthropometric index for identifying US adults with hypertension and diabetes. Instead of using body mass index (kg/m²), we recommend using WC/M^0.333 in clinical and public health practice to better identify US adults at potential cardio-metabolic risk associated with hypertension and diabetes.

Comparison of Physical Fitness Profiles Obtained before and during COVID-19 Pandemic in Two Independent Large Samples of Children and Adolescents: DAFIS Project

COVID-19 pandemic restrictions might have negatively affected the health-related physical fitness of children and adolescents. The aim of this study was to contrast the body composition and physical fitness data of two independent samples of children and adolescents obtained from an online database (DAFIS project) before (n = 15,287) and during (n = 2101) the first academic year of the COVID-19 pandemic. The results revealed higher values for the body mass index (p = 0.002), waist circumference (p < 0.001), and waist to hip and waist to height ratios (p < 0.001) during than before the pandemic, particularly in the case of boys. On the other hand, lower muscular fitness was observed for girls during the pandemic. Quantitative and qualitative analysis did not detect relevant changes in cardiorespiratory fitness in children or adolescents (p > 0.05). Our data suggested that pandemic constraints might have affected body composition and muscular fitness of children and adolescents. These results might be of interest for designing specific interventions oriented toward counteracting the negative effects of pandemic restrictions on health-related physical fitness.

IS THE WAIST/HEIGHT RATIO A BETTER PARAMETER THAN BMI IN DETERMINING THE CARDIOMETABOLIC RISK PROFILE OF OBESE PEOPLE?

Background:

The increased prevalence of obesity has led to a significant increase in the occurrence of metabolic syndrome, a recognized risk factor for increased morbidity and mortality from cardiovascular diseases. Hyperglycemia or type 2 diabetes mellitus, dyslipidemia and arterial hypertension are its main components. Since 2015, international guidelines have recognized the benefits of bariatric surgery in each isolated factor of this syndrome.

Aim:

To evaluate the impact of Roux-en-Y gastric bypass in this syndrome comparing pre- and postoperative periods with laboratory analysis and to compare waist/height ratio and BMI in relation to the determination of the cardiometabolic risk profile.

Methods:

A retrospective study was carried out, selecting 80 patients undergoing Roux-en-Y gastric bypass. Total cholesterol, HDL, LDL, triglycerides, fasting glucose, glycated hemoglobin, insulin, body mass index (BMI), vitamin D, vitamin B12, waist circumference and waist/height ratio in three periods were analyzed: the preoperative period from 1 to 6 months, postoperative from 1 to 6 months and postoperative from 1 to 2 years.

Results:

There was an improvement in all parameters of the clinical analyses. The preoperative BMI had a mean value of 39.8, in the preoperative period from 1 to 6 months, the values ​​dropped to 33.2 and in the postoperative period of 1 year, the mean was 26. The perimeter mean values ​​of 118.5 preoperatively, 105.2 postoperatively from 1 to 6 months and 90.3 postoperatively from 1 to 2 years. Waist/height ratio was 0.73, 0.65 and 0.56 in pre, post 1 to 6 months and 1 to 2 years respectively.

Conclusion:

Roux-en-Y gastric bypass improves metabolic syndrome and waist-to-height ratio is superior to BMI in the assessment of the cardiometabolic risk profile.

Analysis of fitness among Korean adults by the cause-effect relation in lump mean scheme

BACKGROUND

The aim of this study was to examine whether the fitness of Korean adults can be analyzed by the cause-effect relation using the linearity or Gaussianity in the lump mean scheme (LMS).

METHODS

This study analyzed previous results for the sit-up test obtained in the LMS by regression analysis in Sigmaplot 14. The effects of the body mass index (BMI) and new waist-to-height ratio (WHT2R) introduced by the present author on fitness were investigated.

RESULTS

The distribution of the sit-up test score with respect to the BMI and WHT2R were interpreted by their Gaussianity and linearity, respectively. This means that the muscular endurance of males is determined by two causes (fat and muscle) when the BMI is a variable and one cause (abdominal fat) when the WHT2R is a variable.

CONCLUSIONS

Personal exercise aims were simpler to establish using WHT2R than using BMI. On the other hand, it was recommended for people with a low BMI to increase their fitness using exercises that increase their muscle mass.

Waist-to-height ratio, waist circumference, body mass index, waist divided by height0.5 and the risk of cardiometabolic multimorbidity: A national longitudinal cohort study

BACKGROUND AND AIMS

Cardiometabolic multimorbidity (CM) is an increasing public health burden. This study aimed to evaluate the association of waist-to-height ratio (WHtR), waist circumference (WC), waist divided by height^0.5 (WHT.5R) and body mass index (BMI) with the risk of CM.

METHODS AND RESULTS

We used data from the China Health and Retirement Longitudinal Study (CHARLS). A total of 10,521 participants aged 45 years and over were recruited, including 8807 individuals with 0 cardiometabolic diseases at baseline (stage I) and 1714 individuals with 1 cardiometabolic disease at baseline (stage II). CM was defined as self-reporting of two or more of the following conditions: stroke, diabetes and heart disease. Logistic regression was conducted to estimate the odds ratios (ORs) and 95% confidence intervals (CIs). The net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to evaluate the incremental predictive value beyond conventional factors. In stage I, an increased risk of CM was observed among participants with WHtR ≥0.5 (OR: 1.76, 95% CI: 1.05-2.97), WC ≥ 90 cm (men) + WC ≥ 80 cm (women) (OR: 2.06, 95% CI: 1.29-3.27), WHT.5R ≥ 6.54 cm^0.5 (OR: 1.81, 95% CI: 1.16-2.83) or BMI ≥24 kg/m² (OR: 1.48, 95% CI: 0.98-2.24). Furthermore, the NRI and IDI of WHtR, WC and WHT.5R were all higher than those of BMI. In stage II, the adjusted ORs (95% CIs) of WHtR, WC, WHT.5R and BMI were 2.04 (1.24-3.35), 1.89 (1.29-2.77), 1.86 (1.24-2.78) and 1.47 (1.06-2.04), respectively. In addition, WC exhibited the highest NRI and IDI.

CONCLUSION

WHtR, WC, WHT.5R and BMI are independent predictors of CM in the middle-aged and older Chinese population. WHtR, WC and WHT.5R show better abilities in predicting CM than BMI.

Optimal cut-offs of five anthropometric indices and their predictive ability of type 2 diabetes in a nationally representative Kenyan study

Background

Type 2 diabetes (T2D) is one of the top non-communicable diseases in Kenya and prevention strategies are urgently needed. Intervening to reduce obesity is the most common prevention strategy. However, black populations develop T2D at lower obesity levels and it is unclear which anthropometric cut-offs could provide the best predictive ability for T2D risk. This study, therefore, aimed to determine the optimal anthropometric cut-offs and their predictive ability of T2D in Kenya.

Methods

The study included 2159 participants (59% women) aged 35-70 years from the Kenya STEPwise survey conducted in 2014. Five anthropometric indices were used-body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), waist to height ratio (WHtR) and waist divided by height^0.5(WHt.5R). Diabetes was defined as a fasting blood glucose of ≥7.0 mmol/l or a previous diagnosis by a health worker. Optimal anthropometric cut-offs and their receiver operating characteristics, such as the area under the curve (AUC), were computed.

Results

Overall, the optimal cut-off for BMI, WC, WHR, WHtR and WHt.5R were 24.8 kg.m^-2, 90 cm, 0.88, 0.54 and 6.9. On disaggregation by sex, the optimal cut-off for BMI, WC, WHR WHtR and WHt.5R was 27.1 kg.m^-2, 87 cm, 0.85, 0.55 and 6.9 in women, and 24.8 kg.m^-2, 91 cm, 0.88, 0.54 and 6.9 in men. Overall, WC (AUC 0.71 (95% confidence interval 0.65, 0.76)) WHtR (AUC 0.71 (0.66, 0.76)) and WHt.5R (AUC 0.70 (0.65,0.75)) had a better predictive ability for T2D than BMI (AUC 0.68 (0.62, 0.73)).

Conclusions

WC, WHtR and WHt.5R were better predictors of T2D than BMI and should be used for risk stratification in Kenya. A WC cut-off of 87cm in women and 91cm in men, a WHtR cut-off of 0.54 or a WHt.5R of 6.9 in both men and women should be used to identify individuals at an elevated risk of T2D.

Association Between Obesity and Blood Pressure in Common Korean People

Purpose

The aim of this study was to investigate the associations of high blood pressure (BP) and wide pulse pressure (PP) with obesity among common Korean people.

Materials and Methods

This study analyzed data from the Seventh Korean National Health and Nutrition Examination Survey (2017). The associations of BP with body mass index (BMI) and waist-to-height ratio (WHT2R) were investigated using their lump mean values.

Results

The BPs of males and females increased with BMI, the PP of females increased with BMI and then decreased, and the PP of males is nearly independent of BMI. The BPs of males and females increased to their maximum values with WHT2R and then decreased. The PPs of males and females increased with WHT2R.

Conclusion

BMI can be used as a useful predictor for high BP, and WHT2R can be used as a useful predictor for wide PP.

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.

Percentiles and Principal Component Analysis of Physical Fitness From a Big Sample of Children and Adolescents Aged 6-18 Years: The DAFIS Project

Assessing physical fitness has emerged as a proxy of the health status of children and adolescents and therefore as relevant from a public health point of view. DAFIS is a project included in Plan Galicia Saudable (Healthy Galicia Plan) of the regional government of Galicia (Spain). DAFIS consists of an on-line software devoted to record the results of a standard physical fitness protocol carried out as a part of the physical education curriculum. The aims of this study were: to obtain normative values of physical fitness of the Galician school population evaluated in the DAFIS project, and to identify a reduced number of components and tests able to capture a significant amount of the variability in the physical fitness of children and adolescents. From an initial sample of 27784 records, 15287 cases (7543 males, 7744 females) were considered after filtering. Generalized Additive Models for Location, Scale and Shape were used for obtaining percentile curves and tables for each sex. Furthermore, a principal components analysis was performed, selecting the number of components by applying the Kaiser's rule and selecting a subset of variables considering the correlation between each variable and the components. Percentile curves and normative values are reported for each test and sex. Physical fitness was better in boys than in girls throughout age groups, except for flexibility that was consistently higher in girls. Two main components were detected throughout age groups: the first one representing body composition and partially cardiorespiratory fitness and the second one muscular fitness. For boys and girls, waist to height ratio had the highest correlations with the first component in four out of six age groups. The highest correlation with the second component, was most frequently observed for the handgrip test both in boys and girls (four out of six age groups). This study provides evidence about the utility of school community actions like DAFIS aimed to track the health-related fitness of children and adolescents. The results suggest that fat mass distribution (i.e., waist to height ratio and waist circumference) and muscular performance (mainly handgrip) concentrate a high proportion physical fitness variance.

Optimised anthropometric indices as predictive screening tools for metabolic syndrome in adults: a cross-sectional study

OBJECTIVES

We aimed to evaluate the association between metabolic syndrome (MetS) and two latest optimised indices, waist divided by height ^0.5 (WHT.5R) and body mass index (BMI) multiply by the square root of BMI and waist circumference (BMI√WC), and to comprehensively compare the ability of 10 anthropometric indices to identify MetS, including BMI√WC, WHT.5R, abdominal volume index (AVI), waist-to-height ratio (WHtR), Body Roundness Index (BRI).

DESIGN

Cross-sectional study.

SETTING

Ningxia, China.

PARTICIPANTS

A total of 3860 adults aged 18-88 years from Ningxia, China were recruited by a single stratified cluster random sampling method.

METHODS

ORs and 95% CIs for associations between indices and MetS were calculated using binary logistic regression, and areas under the receiver operating characteristic (ROC) curves (AUCs) were performed to compare their predictive capacity for MetS. All results for men and women were analysed and presented separately.

RESULTS

The highest adjusted ORs for MetS were observed for the following indices: AVI (OR 15.22, 95% CI 10.88 to 21.30), WHT.5R (OR 13.83, 95% CI 9.89 to 19.35) and BMI√WC (OR 12.14, 95% CI 8.79 to 16.76) in men, whereas BRI, WHtR (both OR 14.91, 95% CI 10.39 to 21.4), WHT.5R (OR 14.22, 95% CI 9.96 to 20.29) and AVI (OR 14.03, 95% CI 9.91 to 19.87) in women. In ROC analysis, AVI (AUC: 0.767 for men and 0.749 for women) and WHT.5R (AUC: 0.761 for men and 0.747 for women) showed the highest predictive ability for MetS.

CONCLUSIONS

BMI√WC and WHT.5R were significantly positively associated with MetS, and AVI and WHT.5R could be useful screening tools for identifying MetS in both sexes.

Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study

Background & aims

Liver ultrasound scan (US) use in diagnosing Non-Alcoholic Fatty Liver Disease (NAFLD) causes costs and waiting lists overloads. We aimed to compare various Machine learning algorithms with a Meta learner approach to find the best of these as a predictor of NAFLD.

Methods

The study included 2970 subjects, 2920 constituting the training set and 50, randomly selected, used in the test phase, performing cross-validation. The best predictors were combined to create three models: 1) FLI plus GLUCOSE plus SEX plus AGE, 2) AVI plus GLUCOSE plus GGT plus SEX plus AGE, 3) BRI plus GLUCOSE plus GGT plus SEX plus AGE. Eight machine learning algorithms were trained with the predictors of each of the three models created. For these algorithms, the percent accuracy, variance and percent weight were compared.

Results

The SVM algorithm performed better with all models. Model 1 had 68% accuracy, with 1% variance and an algorithm weight of 27.35; Model 2 had 68% accuracy, with 1% variance and an algorithm weight of 33.62 and Model 3 had 77% accuracy, with 1% variance and an algorithm weight of 34.70. Model 2 was the most performing, composed of AVI plus GLUCOSE plus GGT plus SEX plus AGE, despite a lower percentage of accuracy.

Conclusion

A Machine Learning approach can support NAFLD diagnosis and reduce health costs. The SVM algorithm is easy to apply and the necessary parameters are easily retrieved in databases.

The waist-hip ratio: a flawed index

The waist-hip ratio, namely waist circumference (WC) divided by hip circumference (HC), has been referred to in thousands of articles, generally as a correlate and predictor either of health conditions such as cardiovascular disease and diabetes, or of amounts of visceral and subcutaneous abdominal fat. It has been argued that combining WC and HC as a ratio is inappropriate, and yet their individual roles can only be fully elucidated if considered jointly. Whereas WC is positively associated with cardiovascular disease, diabetes and premature mortality, the opposite is true of HC. With health-related measures taken as dependent variables, the present novel approach establishes that WC and HC are far better treated as separate independent variables in multiple regression equations than as their ratio. This necessarily produces closer fits to data. One should then allow for variations in height, or some other such measure of general body size, by including this in the regression equations. The widespread concern with the ratio seems to have distracted attention from HC, for this is discussed notably less often than WC. Given that other body parts, such as the thighs, may share relevant properties with the hips, measurements of these could perhaps replace HC.

How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study

Manual anthropometrics are used extensively in medical practice and epidemiological studies to assess an individual's health. However, traditional techniques reduce the complicated shape of human bodies to a series of simple size measurements and derived health indices, such as the body mass index (BMI), the waist-hip-ratio (WHR) and waist-by-height0.5 ratio (WHT.5R). Three-dimensional (3D) imaging systems capture detailed and accurate measures of external human form and have the potential to surpass traditional measures in health applications. The aim of this study was to investigate how shape measurement can complement existing anthropometric techniques in the assessment of human form. Geometric morphometric methods and principal components analysis were used to extract independent, scale-invariant features of torso shape from 3D scans of 43 male participants. Linear regression analyses were conducted to determine whether novel shape measures can complement anthropometric indices when estimating waist skinfold thickness measures. Anthropometric indices currently used in practice explained up to 52.2% of variance in waist skinfold thickness, while a combined regression model using WHT.5R and shape measures explained 76.5% of variation. Measures of body shape provide additional information regarding external human form and can complement traditional measures currently used in anthropometric practice to estimate central adiposity.

The use of functional performance tests and simple anthropomorphic measures to screen for comorbidity in primary care

BACKGROUND

Many older adults are unaware that they have comorbid diseases. Increased adiposity and reduced muscle mass are identified as key contributors to many chronic diseases in older adults. Understanding the role they play in the development of comorbidities in older populations is of prime importance.

OBJECTIVES

To identify the optimal body shape associated with three common functional performance tests and to determine which anthropometric and functional performance test best explains comorbidity in a sample of older adults in Hong Kong.

METHODS

A total of 432 older adults participated in this cross-sectional study. Researchers assessed their body height, body mass index, waist circumference, waist-to-hip ratio, handgrip strength (kg), functional reach (cm) and results in the timed-up-and-go (TUG) test (seconds). The Charlson Comorbidity Index was used to assess comorbidity.

RESULTS

Allometric modelling indicated that the optimal body shape associated with all functional performance tests would have required the participants to be taller and leaner. The only variable that predicted comorbidity was the TUG test. The inclusion of body size/shape variables did not improve the prediction model.

CONCLUSION

Performance in the TUG test alone was found to be capable of identifying participants at risk of developing comorbidities. The TUG test has potential as a screening tool for the early detection of chronic diseases in older adults.

IMPLICATIONS FOR PRACTICE

Many older people are unaware of their own co-existing illnesses when they consult physicians for a medical condition. TUG can be a quick and useful screening measure to alert nurses in primary care to the need to proceed with more detailed assessments. It is an especially useful screening measure in settings with high patient volumes and fiscal constraints. TUG is low cost and easy to learn and is therefore also relevant for nurses and health workers in low-resource, low-income countries.

When is sitting height a better measure of adult body size than total height, and why? The contrasting examples of body mass, waist circumference, and lung volume

OBJECTIVES

We aimed to establish which of sitting height (SH) and total height (Ht) is most appropriately used in the scaling of adult body mass (BM), waist circumference (WC), and forced vital capacity (FVC), considering likely explanations and proposing a suitable index for each.

METHODS

Data were from the US Third National Health and Nutrition Survey for white and black American women and men aged 20 to 50 years. Statistical analysis involved mainly correlation coefficients, the multiple regression of BM, WC, or FVC on SH and leg length (LL), and fitting of allometric regression equations relating each of BM, WC, and FVC to SH or Ht.

RESULTS

BM and WC correlated more strongly with SH than with Ht, and FVC correlated more strongly with Ht. Associations with LL were negative for WC, negative or nonsignificant for BM, and positive for FVC. Using round-number exponents for Ht and SH, the allometric relationships indicated that appropriate indices are BM/SH³ , WC/SH, and FVC/Ht² .

CONCLUSIONS

Contrary to usual practice, BM and WC are better scaled in relation to SH than to Ht. FVC is slightly better scaled in relation to Ht, as is conventional. Interpretations involve the small influence of LL on BM and the influence both of gluteo-femoral fatness on measured SH and of childhood health and nutrition on adult LL, WC, and FVC. It is evident that SH should be measured more often for research purposes.

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.

Association between body mass index and fitness in Korean adults according to the lump mean value and Gaussian fitting

The aim of this study was to determine the body mass index (BMI) for the best fitness and effective exercise. This study analyzed data from the Korean national fitness assessment by the Korea Institute of Sport Science (2017). The fitness tests considered were sit-up, standing long jump (SLJ), 20-m multi-stage shuttle run (20-m MSSR), and 10-m shuttle run (10-m SR) tests. The BMIs for the best fitness and widths of the fitness distributions were calculated using the lump mean value and Gaussian fitting. The values of BMI (kg/m²) associated with the best sit-up, SLJ, 20-m MSSR, and 10-m SR scores were 23.4, 22.6, 22.2, and 22.6 for males and 19.0, 18.5, 18.6, and 18.6 for females. The widths (kg/m²) of the sit-up, SLJ, 20-m MSSR, and 10-m SR distributions were 3.65, 3.42, 3.73, and 2.86 for males and 4.84, 4.88, 4.45, and 4.35 for females. The results show that the BMI can be reduced the most and fitness can be increased effectively by the 20-m MSSR for males and the SLJ for females, which could be used to establish personal exercise aims.

Reducing NAFLD-screening time: A comparative study of eight diagnostic methods offering an alternative to ultrasound scans

BACKGROUND & AIMS

The use of ultrasound scan (US) in non-alcoholic fatty liver disease (NAFLD) screening overloads US waiting lists. We hypothesized and tested a hybrid two-step method, consisting of applying a formula, to exclude subjects at low risk, before US.

METHODS

The sample included 2970 males and females (937 with NAFLD) diagnosed by US. We selected eight formulas: Fatty Liver Index (FLI), Hepatic Steatosis Index (HIS), body mass index (BMI), waist circumference (WC), Abdominal Volume Index (AVI), waist-to-height ratio (WHtR), waist/height^0.5 (WHT.5R) and Body Roundness Index (BRI), and calculated their performance in the two-step method evaluating percentage reduction of the number of liver US (US reduction percentage), percentage of false negative and percentage of NAFLD identified.

RESULTS

The US reductions percentage were 52.2% (WHtR), 52.1% (HIS), 51.8% (FLI), 50.8% (BRI), 50.7% (BMI and WHt_5R), 46.5% (WC) and 45.2% (AVI). The false negative percentage were 8.5% (WHtR), 7.9% (BRI), 7.3% (WHt_5R), 7.2% (BMI), 6.7% (HIS), 6.6% (FLI), 5.6% (WC) and 5.2% (AVI). The best percentage of NALFD identified was obtained using AVI (83.6%) before US, then WC (82.2%), FLI (79%), HIS (78.9%), BMI (77.3%), WHt_5R (76.9%), BRI (74.8%) and WHtR (73%).

CONCLUSION

The best formula to use in two-step diagnostic NAFLD screening was AVI, which showed a low false negative rate and a higher percentage of identified NAFLD. Other studies evaluating the economic advantages of this screening method are warranted.

A new waist-to-height ratio predicts abdominal adiposity in adults

Our aim was to identify the best anthropometric index associated with waist adiposity. The six weight-status indices included body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHTR), and a new waist-by-height^0.5 ratio (WHT.5R). The association between three waist skinfolds and the six anthropometric indices was conducted using ANCOVA, MANCOVA, allometric modelling and non-linear regression. The strongest predictors of waist adiposity were (1^st) WHT.5R, (2^nd) WHTR, (3^rd) waist circumference (WC), (4^th) BMI, (5^th) WHR, and lastly (6^th) a body shape index ABSI = WC/(BMI^2/3 * height^1/2). The allometric and non-linear regression analyses identified the optimal waist-to-height ratio associated with waist adiposity to be (waist * height ^-0.6). The 95% confidence intervals of the height exponents encompassed -0.5 but excluded -1.0 assumed by WHTR. Assuming that excess waist adiposity is an important cardiovascular risk factor, we recommend that the new WHT.5R be used to advise people how to maintain a "healthy" weight.

Associations between anthropometric indicators of adiposity and body fat percentage in normal weight young adults

The purpose of this cross-sectional study was to determine the associations between various anthropometric adiposity screening indices and body fat percentage estimated by bioelectrical impedance analysis (BIA). A total of 186 (95 male and 91 female) normal weight (body mass index [BMI] = 18.5- 24.9 kg/m2) young adults (mean age= 20.96 ± 2.03 years) were measured on body fat percentage, body height, body mass, waist and hip circumferences. Abdominal volume index, body adiposity index, BMI, body roundness index, conicity index, reciprocal ponderal index, waist to height ratio, waist to height 0.5 ratio, and waist to hip ratio were calculated accordingly. Results revealed significant gender effects in all main anthropometric measurements. Except for waist to hip ratio, results indicated significant associations between anthropometric indices and BIA in both male and female participants. BIA results were found to be largely associated with BMI and abdominal volume index in both genders. Bland- Altman analysis showed good agreements between these indices and BIA. Considerable associations and agreements highlight the potential importance and the use of several anthropometric proxies to estimate body adiposity among male and female non-overweight/obese young adults. Despite continuing discussion regarding its accuracy, BMI seems to be useful for monitoring body adiposity within this cohort.

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.

Scaling children's waist circumference for differences in body size

OBJECTIVES

Both waist circumference (WC) and body size (height) increase with age throughout childhood. Hence, there is a need to scale WC in children to detect differences in adiposity status (eg, between populations and different age groups), independent of body size/height.

METHODS

Using two culturally different samples, 1 English (10-15.9 years n = 9471) and 2 Colombian (14-15 years, n = 37,948), for WC to be independent of height (HT), a body shape index was obtained using the allometric power law WC = a.HT^b . The model was linearized using log-transformation, and multiple regression/ANCOVA to estimate the height exponents for WC controlling for age, sex, and any other categorical/population differences.

RESULTS

In both samples, the power-law height exponent varied systematically with age. In younger children (age 10-11 years), the exponent was approximately unity, suggesting that pre-pubertal children might be geometrically similar. In older children, the height exponent declined monotonically to 0.5 (ie, HT^0.5 ) in 15+ year-olds, similar to the exponent observed in adults. UK children's height-adjusted WC revealed a "u" shaped curve with age that appeared to reach a minimum at peak-height velocity, different for boys and girls. Comparing the WC of two populations (UK versus Colombian 14-15-year-old children) identified that the gap in WC between the countries narrowed considerably after scaling for height.

CONCLUSIONS

Scaling children's WC for differences in height using allometric modeling reveals new insights into the growth and development of children's WC, findings that might well have been be overlooked if body size/height had been ignored.

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.