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

Weight-adjusted waist index as a practical predictor for diabetes, cardiovascular disease, and non-accidental mortality risk

BACKGROUND AND AIM

Identifying a more suitable marker among various measures of adiposity, demonstrating strong associations and predictive ability for clinical use, remains a topic of debate. Weight-adjusted waist index (WWI) has been proposed as a novel index of adiposity, yet its exploration is limited, especially in Chinese populations. This study seeks to examine the associations between body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHTR), weight-adjusted waist index (WWI), waist circumference divided by body mass to the power of 0.333 (WC/M0.333), visceral adiposity index (VAI), lipid accumulation product (LAP), and the incidence of diabetes, cardiovascular disease, and non-accidental mortality in Chinese populations. Furthermore, our goal is to compare the respective predictive values of these measures for these health outcomes.

METHODS AND RESULTS

This prospective cohort study included 21,750 subjects with a 9-year follow-up period. Cox proportional hazard models were used to investigate the relationship between eight anthropometric indexes and the incidence of diabetes, cardiovascular disease, and non-accidental mortality. The predictive value of these eight indexes was compared using the area under the curve metric. Significant positive associations were found between WWI and the risk of diabetes. Using the first quartile (Q1) of WWI as the reference group, hazard ratios with 95% confidence intervals for the risk of diabetes were 1.58 (0.98-2.55) for Q2, 2.18 (1.34-3.35) for Q3, and 2.27 (1.41-3.67) for Q4. Significant associations were observed with the highest quartile of WWI for the risk of cardiovascular disease [Q2: HR 1.45 (95% CI 1.06-1.98); Q3: 1.33 (0.97-1.83); Q4: 1.55 (1.13-2.14)] and risk of non-accidental mortality [Q2: 0.94 (0.80-1.11); Q3: 1.24 (1.04-1.48); Q4: 1.44 (1.16-1.79)]. Receiver operating characteristic analysis revealed that WWI exhibited superior discrimination and accuracy in predicting cardiovascular disease and non-accidental mortality compared to other adiposity indexes (BMI, WC, WHR, WHTR, WC/M0.333, VAI, and LAP).

CONCLUSION

WWI exhibited the most robust and consistent association with the incidence of cardiovascular disease and non-accidental mortality. Given its simplicity and widespread use, WWI emerges as a novel and practical predictor of diabetes, cardiovascular disease, and non-accidental mortality among the eight adiposity indexes investigated in this study.

Association of Visceral Adiposity Index and Handgrip Strength with Cardiometabolic Multimorbidity among Middle-Aged and Older Adults: Findings from Charls 2011-2020

The visceral adiposity index (VAI) and handgrip strength (HGS) are identified as important objectives for the prevention of illness. Nevertheless, there is limited understanding regarding the impact of the VAI and HGS on cardiometabolic multimorbidity (CMM). We aimed to ascertain the impact of the VAI and HGS on CMM among middle-aged and older people. Data spanning from 2011 to 2020 were derived from the China Health and Retirement Longitudinal Study (CHARLS). In total, 7909 individuals aged 45 years and older were included. Cox proportional hazard regression was utilized to examine the correlation among the VAI, HGS, and CMM. Throughout the 10-year follow-up, we determined that both the VAI (HR = 1.330; 95%CI = 1.179-1.500) and HGS (HR = 0.745, 95%CI = 0.645-0.861) exhibited significant associations with CMM risk. Individuals exposed to both a high VAI and low HGS were found to have higher hazards of CMM (HR = 1.377, 95%CI = 1.120-1.694) in contrast to participants exposed to one or none of these conditions. The older (HR = 1.414; 95%CI = 1.053-1.899) and male (HR = 1.586; 95%CI = 1.114-2.256) groups are more likely to experience CMM risk. Our findings suggest that both the VAI and HGS have significant effects on CMM risk. Appropriate interventions focused on vulnerable groups are recommended to prevent the incidence of CMM.

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

Introduction

To study the utility of A Body Shape Index (ABSI) alongside body mass index (BMI) to predict mortality and frailty in an aging community population.

Materials and methods

Participants (n = 1,580) were drawn from the first Israeli national health and nutrition survey of older adults ("Mabat Zahav") conducted from 2005 to 2006, constituting adults aged ≥65 years. Socio-demographic, clinical, behavioral, and psychosocial data were collected. Baseline weight, height, and waist circumference (WC) were measured and expressed as the allometric indices BMI (kg/m2) and ABSI, a BMI-independent measure of abdominal obesity [WC/(BMI2/3*m1/2)]. Mortality follow-up lasted through 2019. Frailty was assessed in 2017-2019 by the Fried Biological Phenotype in a sub-cohort of 554 survivors. Cox and logistic regression models assessed associations of BMI and ABSI with mortality and frailty.

Results

At baseline, mean [SD] age was 74.5 [6.1] years, and 52.4% were women. The correlation between BMI and WC Z scores was 0.71, reduced to -0.11 for BMI and ABSI. Over a median follow-up of 13 years, 757 deaths occurred. The multivariable-adjusted hazard ratios (95% CIs) for mortality per standard deviation increase in BMI and ABSI were 1.07 (0.99;1.17) and 1.13 (1.05;1.21), respectively. Among participants assessed for frailty, 77 (14%) met the frailty criteria. After multivariable adjustment, the odds ratios (95% CIs) for frailty were 0.83 (0.69-1.01) for BMI and 1.55 (1.34-1.79) for ABSI.

Discussion

In a nationwide cohort of older adults, ABSI was independently associated with mortality risk. Furthermore, ABSI, but not BMI, was a strong predictor of frailty.

Obesity and lung cancer - is programmed death ligand-1 (PD-1L) expression a connection?

Introduction

In this retrospective study, the authors evaluated whether obesity-induced immunomodulation impacts the expression of programmed death ligand-1 (PD-1L) in lung cancer cells.Methods: A retrospective cross-sectional study was performed. The study included 67 patients. The data did not have a normal distribution.

Results

For women, using ANOVA test (p = 0.050) with post-hoc analysis, a statistically significant difference in expression was found between women with overweight and women with normal weight (p = 0.040).

Conclusions

Apart from the above, the authors did not find any statistically significant correlation between PD-1L expression on lung cancer cells and body mass index, either in the whole group or in histological subgroups.

Machine learning prediction of hepatic steatosis using body composition parameters: A UK Biobank Study

Non-alcoholic fatty liver disease (NAFLD) has emerged as the most prevalent chronic liver disease worldwide, yet detection has remained largely based on surrogate serum biomarkers, elastography or biopsy. In this study, we used a total of 2959 participants from the UK biobank cohort and established the association of dual-energy X-ray absorptiometry (DXA)-derived body composition parameters and leveraged machine learning models to predict NAFLD. Hepatic steatosis reference was based on MRI-PDFF which has been extensively validated previously. We found several significant associations with traditional measurements such as abdominal obesity, as defined by waist-to-hip ratio (OR = 2.50 (male), 3.35 (female)), android-gynoid ratio (OR = 3.35 (male), 6.39 (female)) and waist circumference (OR = 1.79 (male), 3.80 (female)) with hepatic steatosis. Similarly, A Body Shape Index (Quantile 4 OR = 1.89 (male), 5.81 (female)), and for fat mass index, both overweight (OR = 6.93 (male), 2.83 (female)) and obese (OR = 14.12 (male), 5.32 (female)) categories were likewise significantly associated with hepatic steatosis. DXA parameters were shown to be highly associated such as visceral adipose tissue mass (OR = 8.37 (male), 19.03 (female)), trunk fat mass (OR = 8.64 (male), 25.69 (female)) and android fat mass (OR = 7.93 (male), 21.77 (female)) with NAFLD. We trained machine learning classifiers with logistic regression and two histogram-based gradient boosting ensembles for the prediction of hepatic steatosis using traditional body composition indices and DXA parameters which achieved reasonable performance (AUC = 0.83-0.87). Based on SHapley Additive exPlanations (SHAP) analysis, DXA parameters that had the largest contribution to the classifiers were the features predicted with significant association with NAFLD. Overall, this study underscores the potential utility of DXA as a practical and potentially opportunistic method for the screening of hepatic steatosis.

Associations and predictive performance of 11 anthropometric measures with incident type 2 diabetes: A prospective cohort study from the UK Biobank

OBJECTIVE

The study aim was to investigate associations of 11 anthropometric measures with incident type 2 diabetes and compare their predictive performance.

METHODS

This prospective cohort study included 161,127 White European UK Biobank participants who were free of diabetes at baseline. Anthropometric measures included height, weight, BMI, A Body Shape Index, waist circumference, waist to hip ratio, waist to height ratio (WHtR), hip circumference, visceral adiposity index, hip index, and anthropometric risk index. The associations were examined using Cox proportional hazard models. The differences in C-index were used to compare predictive performance between BMI and other anthropometric measures.

RESULTS

The median follow-up was 10.0 (interquartile range: 9.3-10.8) years, during which 6315 participants developed type 2 diabetes. All markers except height and hip index were positively associated with incident type 2 diabetes. The strongest associations were found for WHtR (hazard ratio per 1-SD increment: 2.27 [95% CI 2.19-2.35] in women; 1.96 [95% CI 1.90-2.01] in men). Compared with BMI, WHtR and anthropometric risk index had significantly better type 2 diabetes risk discrimination.

CONCLUSIONS

Although most adiposity markers were associated with type 2 diabetes, the magnitude of the associations differed. WHtR had the strongest associations and predictive ability for type 2 diabetes and thus could be a more suitable marker for clinical use.

Analysis of the relationship between body habitus and frailty of community adults in Chongqing: a cross-sectional survey study

Objective

Currently, a multitude of studies are underway to investigate the factors affecting the degree of frailty, with a significant focus on the critical role of body mass index (BMI). This study aims to conduct a cross-sectional survey to investigate the multifaceted relationship between multiple body habitus and the factors that influence the degree of frailty.

Methods

A questionnaire survey was conducted among 840 adult residents in Chongqing communities. A total of 723 participants were included in the data analysis, with an effective response rate of 92.0%. Fried's frailty scale was used to classify individuals into fit, pre-frail, or frail. Non-parametric tests and chi-square tests were employed to evaluate the inter-group differences in frailty levels under different influencing factors. Multivariate logistic regression analysis was performed to select the independent variables associated with frailty statistics. According to the results of the parallel line test, ordered or disordered multivariate logistic regression was used to evaluate the impact of a single independent variable on frailty for different variables.

Results

Adult community residents in Chongqing accounted for 29.18 and 5.67% in pre-frailty and frailty, respectively. In multivariate logistic regression analysis, high BMI, and high waist-hip ratio (WHR) were identified as major risk factors for frailty. Furthermore, the process of aging, coupled with moderate to heavy alcohol consumption, active weight loss behavior in the past year, and the presence of comorbidities, emerged as significant contributors to frailty. Conversely, factors such as a positive inclination toward taste, consistent meal timing, habitual breakfast consumption, sound nutritional intake, and the cultivation of healthy dietary practices were recognized as pivotal elements that act as protective factors against frailty.

Conclusion

The integration of both BMI and WHR provides a more comprehensive perspective, effectively capturing the intertwined influence of obesity and sarcopenia on the extent of frailty. To mitigate the risk of community-wide frailty, a multipronged approach is essential, involving the promotion of favorable dietary practices and achieving nutritional equilibrium, diligent management of coexisting medical conditions, moderation in alcohol consumption, and the enhancement of physical functionality.

Changes in Metabolic Health and Sedentary Behavior in Obese Children and Adolescents

Obesity is becoming more common among children and adolescents. As in adults, obesity in the pediatric population is associated with an increased risk of metabolic disorders and diseases. In the related literature, little attention has been devoted to evaluating how metabolic health and sedentary behavior change in the obese pediatric population. Therefore, this study aimed to assess changes in metabolic health and sedentary behavior in obese children aged 7-12 and adolescents aged 13-17. For this single-center hospital-based prospective observational study, we included 202 Polish children and adolescents aged 7-17 years. We performed blood pressure measurements and collected blood samples to assess metabolic health markers. Based on the performed measurements, we also calculated additional indexes and ratios: BMI, WHtR, ABSI, VAI, and HOMA-IR. The analysis of the results showed clear and significant differences between the study groups. The older boys and girls were identified with higher values of anthropometric ratios, blood pressure, time spent sitting, and lower HDL cholesterol values (p < 0.05). The analysis also revealed a strong-to-moderate correlation between age and anthropometric ratios, blood pressure, HDL cholesterol, and sitting time (p < 0.05). Obese children and adolescents included in this study represent poor metabolic health and are at great risk of developing other metabolic diseases such as type 2 diabetes, hypertension, or metabolic syndrome. This risk increases with age; therefore, a number of preventive and therapeutic actions should be taken in overweight and obese children and adolescents to avoid further metabolic complications.

Analysis of Serious Weight Gain in Patients Using Alectinib for ALK-Positive Lung Cancer

INTRODUCTION

Alectinib is a standard-of-care treatment for metastatic ALK+ NSCLC. Weight gain is an unexplored side effect reported in approximately 10%. To prevent or intervene alectinib-induced weight gain, more insight in its extent and etiology is needed.

METHODS

Change in body composition was analyzed in a prospective series of 46 patients with ALK+ NSCLC, treated with alectinib. Waist circumference, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and skeletal muscle were quantified using sliceOmatic software on computed tomography images at baseline, 3 months (3M), and 1 year (1Y). To investigate an exposure-toxicity relationship, alectinib plasma concentrations were quantified. Four patients with more than 10 kg weight gain were referred to Erasmus MC Obesity Center CGG for in-depth analysis (e.g., assessments of appetite, dietary habits, other lifestyle, medical and psychosocial factors, and extensive metabolic and endocrine assessments, including resting energy expenditure).

RESULTS

Mean increase in waist circumference was 9 cm (9.7%, p < 0.001) in 1Y with a 40% increase in abdominal obesity (p = 0.014). VAT increased to 10.8 cm2 (15.0%, p = 0.003) in 3M and 35.7 cm2 (39.0%, p < 0.001) in 1Y. SAT increased to 18.8 cm2 (12.4%, p < 0.001) in 3M and 45.4 cm2 (33.3%, p < 0.001) in 1Y. The incidence of sarcopenic obesity increased from 23.7% to 47.4% during 1Y of treatment. Baseline waist circumference was a positive predictor of increase in VAT (p = 0.037). No exposure-toxicity relationship was found. In-depth analysis (n = 4) revealed increased appetite in two patients and metabolic syndrome in all four patients.

CONCLUSIONS

Alectinib may cause relevant increased sarcopenic abdominal obesity, with increases of both VAT and SAT, quickly after initiation. This may lead to many serious metabolic, physical, and mental disturbances in long-surviving patients.

Relationship between novel anthropometric indices and the incidence of hypertension in Chinese individuals: a prospective cohort study based on the CHNS from 1993 to 2015

BACKGROUND

Recently, novel anthropometric indices (AHIs), including the body roundness index (BRI) and a body shape index (ABSI), were proposed to evaluate a subject's nutritional status and metabolic disorders. In the present study, we mainly analyzed the relationship between AHIs and the incidence of hypertension and preliminarily compared their abilities to discriminate hypertension incidence in the Chinese population from the China Health and Nutrition Survey (CHNS).

METHODS

A total of 12,154 participants were included in this longitudinal study. The age range of this cohort was 18-94 years old (mean age: 40.73 ± 13.85 years old). 4511 participants developed hypertension during a median of 7.00 years of follow-up. Cox regression analysis, stratified analysis, and interaction tests were used to analyze the relationship between AHIs and the incidence of hypertension. Time-dependent receiver operating characteristic (ROC) curves, integrated discrimination improvement (IDI) and net reclassification index (NRI) were calculated to appraise the AHIs' discrimination value of new-onset hypertension.

RESULTS

Kaplan‒Meier curves demonstrated that the participants in higher quartiles of AHIs (ABSI or BRI) at baseline were at greater risk of hypertension incidence during the follow-up. After adjusting for confounding factors, multivariate Cox regression models showed that the quartiles of BRI were significantly associated with an increased risk of hypertension in the whole cohort but were relatively weak for ABSI quartiles (P for trend = 0.387). In addition, ABSI z score (HR = 1.08, 95% CI: 1.04-1.11) and BRI z score (HR = 1.27, 95% CI: 1.23-1.30) were positively associated with increased incident hypertension in the total population. Stratified analysis and interaction tests showed a greater risk of new-onset hypertension in those < 40 years old (HR = 1.43, 95% CI: 1.35-1.50) for each z score increase in BRI and a higher incidence of hypertension in participants who were drinkers (HR = 1.10, 95% CI: 1.04-1.14) for each z score increase in ABSI. In addition, we observed that the area under the curve for identifying hypertension incidence for BRI was significantly higher than that for ABSI at 4, 7, 11, 12, and 15 years (all P < 0.05). However, the AUC of both indices decreased over time. Furthermore, the addition of BRI improved the differentiation and reclassification of traditional risk factors with a continuous NRI of 0.201 (95% CI: 0.169-0.228) and an IDI of 0.021 (95% CI: 0.015-0.028).

CONCLUSION

Increased ABSI and BRI were associated with an increased risk of hypertension in Chinese individuals. BRI performed better than ABSI in identifying the new onset of hypertension, and the discrimination ability of both indices decreased over time.

Influence of Educational Level and Healthy Habits on the Prevalence of Diabesity in a Spanish Working Population

Background: Diabesity is a growing problem internationally. Taking into account the importance of physical activity and diet in its prevention and treatment, the objective of this study was to delve into the impact of healthy habits on diabesity. Methods: A descriptive, cross-sectional study was carried out in 386,924 Spanish adult workers. Obesity was determined according to eleven different formulas. Life habits were also valued; sociodemographic variables; and educational level; as well as analytical and clinical variables such as blood pressure and blood glucose levels. The association between the different variables was performed using the chi-square and the Student’s t-tests when the samples were independent. A multivariate analysis was performed using the multinomial logistic regression test by calculating the odds ratio and a 95% confidence interval. The Hosmer–Lemeshow goodness-of-fit test was also performed. Results: The overall prevalence of diabesity ranged between 0.3% (95% CI 0.3–0.4) when obesity was assessed according to the abdominal volume index and 8.3% (95% CI 8.2–8.4) when evaluated according to the CUN-BAE (Clínica Universitaria de Navarra Body Adiposity Estimator) formula. The prevalence of diabesity was also higher in workers with a non-heart-healthy diet and in those who did not exercise regularly. Conclusions: The most disadvantaged socioeconomic classes are those with the highest prevalence of diabesity. It is important to prioritise prevention in populations and communities with the most unfavourable social and environmental conditions to reduce the burden of diabesity.

Comparison of six anthropometric measures in discriminating diabetes: A cross-sectional study from the National Health and Nutrition Examination Survey

BACKGROUND

Traditional anthropometric measures, including body mass index (BMI), are insufficient for evaluating the risk of diabetes. This study aimed to evaluate the performance of new anthropometric measures and a combination of anthropometric measures for identifying diabetes.

METHODS

A total of 46 979 participants in the National Health and Nutrition Examination Survey program were included in this study. Anthropometric measures, including weight, BMI, waist circumference (WC), waist-to-height ratio (WtHR), conicity index (CI), and A Body Shape Index (ABSI), were calculated. Logistic regression analysis and restricted cubic splines were used to evaluate the association between the anthropometric indices and diabetes. The receiver operating characteristic (ROC) curve analysis was performed to compare the discrimination of different anthropometric measures.

RESULTS

All anthropometric measures were positively and independently associated with the risk of diabetes. After adjusting for covariates, the per SD increment in WC, WtHR, and CI increased the risk of diabetes by 81%, 83%, and 81%, respectively. In the ROC analysis, CI showed superior discriminative ability for diabetes (area under the curve 0.714), and its optimum cutoff value was 1.31. Results of the combined use of BMI and other anthropometric measures showed that among participants with BMI <30 kg/m² , an elevated level of another metric increased the risk of having diabetes (P < .001). Similarly, at low levels of weight, CI, and ABSI, an elevated BMI increased diabetes risk (P < .001).

CONCLUSIONS

WtHR and CI had the best ability to identify diabetes when applied to the US noninstitutionalized population. Anthropometric measures containing WC information could improve the discrimination ability.

The waist-to-body mass index ratio as an anthropometric predictor for cardiovascular outcome in subjects with established atherosclerotic cardiovascular disease

Obesity is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). However, ‘obesity paradox’ is observed in patients with coronary artery disease while defining obesity by body mass index (BMI). The purpose of this study is to identify a better anthropometric parameter to predict cardiovascular events in patients with ASCVD. The study was conducted using the Taiwanese Secondary Prevention for patients with AtheRosCLErotic disease (T-SPARCLE) Registry. A total of 6,920 adult patients with stable ASCVD, enrolled from January 2010 to November 2014, were included, with a mean age of 65.9 years, 73.9% males, and a mean BMI of 26.3 kg/m² at baseline. These patients were followed up for a median of 2.5 years. The study endpoint was the composite major adverse cardiovascular event (MACE), defined as cardiovascular death, nonfatal myocardial infarction or stroke, or cardiac arrest with resuscitation. Multivariable Cox proportional hazards regression showed a significant positive association between waist-to-BMI ratio and MACE (adjusted hazard ratio 1.69 per cm‧m²/kg increase in waist-to-BMI ratio, 95% CI 1.12–2.49, p = 0.01) after adjusting for potential risk factors and confounders. Traditional anthropometric parameters, such as BMI, weight, waist and waist-hip ratio, or newer waist-based indices, such as body roundness index and a body shape index, did not show any significant linear associations (p = 0.09, 0.30, 0.89, 0.54, 0.79 and 0.06, respectively). In the restricted cubic spline regression analysis, the positive dose–response association between waist-to-BMI ratio and MACE persisted across all the range of waist-to-BMI ratio. The positive dose–response association was non-linear with a much steeper increase in the risk of MACE for waist-to-BMI ratio > 3.6 cm‧m²/kg. In conclusion, waist-to-BMI ratio may function as a positive predictor for the risk of MACE in established ASCVD patients.

Body Shape Index and Cardiovascular Risk in Individuals With Obesity

Introduction: Cardio-metabolic risks are tested to show various anthropometric measurements. This study aimed to evaluate a body shape index (ABSI) of individuals with obesity to determine the role of these measurements in cardiovascular risk prediction.

Methods: This cross-sectional study included 368 patients who were evaluated by the researcher in the polyclinic. Sociodemographic information was obtained, and anthropometric measurements were made. Body mass index (BMI), waist circumference, and ABSI were evaluated in all patients. The patient’s risk of developing cardiovascular disease was calculated from the pooled cohort equations risk calculator (PRCAE), Framingham risk score, and systematic coronary risk evaluation (SCORE) risk calculation systems.

Results: Of the 368 patients in the study, 302 (82.1%) were females, and 66 (17.9%) were males. The average age of participants was 46.2 ± 12.0 years. The median BMI of participants was 37.5 (34.0-42.4) kg/m². The median ABSI of participants was 0.0816 (0.0775-0.0849). A positive correlation was found between ABSI and Framingham risk score and PRCAE risk score (r = 0.297, p = 0.000 and r = 0.305, p = 0.000, respectively). A significant relationship was found between ABSI and Framingham, PRCAE, and SCORE risk groups (p = 0.000, p = 0.000, and p = 0.000, respectively).

Conclusions: Our study results revealed a significant association of ABSI with Framingham, PRCAE, and SCORE risk calculation systems, which helps predict cardiovascular risk.

Relationship between body composition, insulin resistance, and hormonal profiles in women with polycystic ovary syndrome

OBJECTIVE

To investigate how body fat influences glucose metabolism and hormone profiles in women with polycystic ovary syndrome (PCOS), compared to women without PCOS.

METHODS

We conducted a cross-sectional study of 166 women with PCOS and 139 age-matched control women at Peking University Third Hospital (Beijing, China) from March 2016 to December 2021. All participants underwent bioimpedance rate assessment of clinical, anthropometric, hormonal, and metabolic features. In particular, body composition parameters were assessed, based on the methods used in a previous study. Homeostasis model assessment-insulin resistance (HOMA-IR) and other indices calculated from fasting glucose and insulin were used to measure insulin resistance. The hormonal profiles [follicle-stimulating hormone (FSH), luteinizing hormone (LH), estrogen (E2), prolactin (PRL), total testosterone (T), and androstenedione (A2)] were assessed by using biochemical methods. Two subgroup analyses were conducted according to waist-to-hip ratio (WHR; < 0.85, non-central obesity and ≥ 0.85, central obesity) and body fat percentage (BFP; < 35% for lean and ≥35% for obesity). The indices above were analyzed using a two-sided t-test or Wilcoxon rank sum test. Linear regression was used to investigate the effects of body composition on metabolism and sex hormones in the PCOS and control groups.

RESULTS

Compared to women without PCOS, women with PCOS and central obesity (P=0.021), PCOS and noncentral obesity (P<0.001), PCOS and high BFP (P<0.001), and PCOS and low BFP (P<0.001) had more severe glucose metabolism evaluated with HOMA-IR. Women with PCOS experienced greater insulin sensitivity impairment than did the normal population for every equal increase in BFP. LH, LH/FSH, total testosterone, and androstenedione were significantly higher in patients with PCOS than in healthy controls, regardless of WHR and BFP stratification. However, negative correlations existed between body fat indices (i.e., BFP and body mass index) and hormone indices (i.e., LH and androstenedione) in the PCOS group, but were absent in the control group.

CONCLUSIONS

Obese and non-obese women with PCOS have more severe insulin resistance and sex-hormone disorders than women without PCOS. The effect of body fat on sex-hormone disorders is only exist in women with PCOS. These findings suggested that PCOS clinical guidelines should be more specific to body fat.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/, Registration No. NCT04264832.

Effectiveness of Body Roundness Index (BRI) and a Body Shape Index (ABSI) in Predicting Hypertension: A Systematic Review and Meta-Analysis of Observational Studies

INTRODUCTION

The body roundness index (BRI) and a body shape index (ABSI) are novel anthropometric indices established to determine both the amount visceral adipose tissue and body fat.

OBJECTIVE

to investigate whether BRI and ABSI are better predictors of hypertension than body mass index (BMI), waist circumference (WC) or waist-to-height ratio (WHtR). Methods: A systematic search was conducted in the Scopus, PubMed and Web of Science databases up until 31 December 2020.

RESULTS

The estimated pooled area under curve [AUC (95% CI)] for BRI [0.67 (0.65-0.70)] for the prediction of hypertension were superior to that of ABSI (0.58 (0.56-0.60)), similar to that of BMI [0.67 (0.64-0.69)], and lower than those WC [0.68 (0.66-0.70)] and WHtR [0.68 (0.66-0.71)]. Nevertheless, the difference of BRI compared to WC and WHtR in the context of predicting hypertension was non-significant. ABSI was significantly lower (p < 0.05) than BRI, BMI, WC and WHtR. Similar findings were observed with the summary receiver operating characteristic curve (AUC-SROC). There were no significant differences between subgroups according to type of population or diagnostic criteria of hypertension. The diagnostic odds ratio (dORs) proved that increased BRI and ABSI were related with an elevated hypertension risk.

CONCLUSIONS

BRI and ABSI have discriminatory power for hypertension in adult women and men from different populations. Although, WHtR and WC provided the best performance when assessing hypertension, no significant differences were found for BRI. Finally, BRI was significantly better predictor of hypertension than ABSI.

Association between anthropometric measures and insulin resistance in Brazilian adolescents: data from the national study of cardiovascular risk factors in adolescents - ERICA

OBJECTIVES

To evaluate anthropometric measures (AM) and insulin resistance (IR) association in adolescents aged 12-17 years and investigates how body mass index (BMI) interrelates with specific indicators of fat distribution in this association.

METHODS

This analysis is from the Study of Cardiovascular Risks in Adolescents (ERICA) study, a national, cross-sectional study. AM was categorized by quartiles, and their means and 95% confidence intervals (95% CI) were estimated. The prevalence of IR was estimated for each AM according to the quartiles. The associations between AM and homeostatic model assessment of insulin resistance (HOMA-IR) levels were analyzed using Poisson models.

RESULTS

37,892 adolescents were included. IR prevalence tended to increase as quartiles increased for each AM. The association of BMI with IR persisted with the adjustment for others AM. The greatest reduction in the association's strength was achieved with the adjustment by the waist circumference (WC) and the waist-to-height ratio (WHtR). Most other AM were also associated with IR.

CONCLUSION

AM has a positive association with the prevalence of IR, and the joint effect of BMI and central adiposity measures should be considered in cardiometabolic risk evaluation in adolescents.

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

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

Anthropometric measures of obesity and associated cardiovascular disease risk in the Eastern Caribbean Health Outcomes Research Network (ECHORN) Cohort Study

BACKGROUND

Accurately defining obesity using anthropometric measures that best capture obesity-related risk is important for identifying high risk groups for intervention. The purpose of this study is to compare the association of different anthropometric measures of obesity with 10-year cardiovascular disease (CVD) risk in adults in the Eastern Caribbean.

METHODS

Data from the Eastern Caribbean Health Outcomes Research Network (ECHORN) Cohort Study (ECS) were analyzed. The ECS is comprised of adults aged 40 and older residing in the US Virgin Islands, Puerto Rico, Barbados, and Trinidad. 10-year CVD risk was calculated using the American Heart Association (ACC/AHA) ASCVD Risk Algorithm and categorized in the following high-risk groups: > 7.5, > 10, and > 20%. Logistic regression was used to examine associations between four anthropometric measures of obesity (BMI, waist circumference, waist-to-hip ratio, waist-to height ratio) and 10-year CVD risk.

RESULTS

Mean age (SD) of participants (n = 1617) was 56.6 years (±10.2), 64% were women, 74% were overweight/obese, and 24% had an ASCVD risk score above 10%. Elevated body mass index (BMI, > 30 kg/m2) and waist circumference were not associated with CVD risk. Elevated waist-to-hip ratio (WHR, > 0.9 men, > 0.85 women) and elevated waist-to-height ratio (> 0.5) were associated with all three categories of CVD risk. Area under the receiver curve was highest for WHR for each category of CVD risk. Elevated WHR demonstrated odds of 2.39, 2.58, and 3.32 (p < 0.0001) for CVD risk of > 7.5, > 10 and > 20% respectively.

CONCLUSION

Findings suggest that WHR is a better indicator than BMI of obesity-related CVD risk and should be used to target adults in the Caribbean, and of Caribbean-descent, for interventions.

The correlation between neck circumference and risk factors in patients with hypertension: What matters

It is necessary to identify the relationship between neck circumference and cardiovascular risk factors in patients with hypertension.Patients with hypertension treated in our hospital were included. The height, weight, neck circumference, waist circumference, fasting blood glucose, 2 h blood glucose (2hPPG), density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and glycated hemoglobin (HbA1c) were analyzed and compared.A total of 2860 patients with hypertension were included. There were significant differences between male and female patients in the neck circumference, waist circumference, fasting blood glucose, Total cholesterol, triacylglycerol, HDL-C, LDL-C, diabetes, metabolic syndrome, dyslipidemia, drinking and smoking (all P < .05); the neck circumference was positively correlated with waist circumference, body mass index (BMI), fasting blood glucose, 2hPPG, HbA1c, triacylglycerol and LDL-C (all P < .05), and negatively correlated with HDL-C (P = .014); as the neck circumference increases, the risk of hypertension, diabetes, metabolic syndrome, abdominal obesity, and dyslipidemia increases accordingly (all P < .05); the area under curve (AUC) was 0.827 and 0.812, and the neck circumference of 37.8 and 33.9 cm was the best cut-off point for male and female patients, respectively.Neck circumference is closely related to cardiovascular risk factors in patients with hypertension, which should be promoted in the screening of cardiovascular diseases.

The Relationship between Food Security Status and Sleep Disturbance among Adults: A Cross-Sectional Study in an Indonesian Population

Background: The relationship between food insecurity and the experience of sleep disturbance has received little attention among researchers, although food insecurity is associated with poor physical and mental health globally. This study aimed to investigate the relationship between food security status and sleep disturbance among adults 20–64 years old. Methods: The study’s population-based sample included 20,212 Indonesian adults who participated in the fifth wave of the Indonesia Family Life Survey (IFLS5) in 2014. Dietary intake data, gathered using a food frequency questionnaire (FFQ), were used to assess the food security status. Sleep disturbance was assessed using the 10-item Patient-Reported Outcomes Measurement Information System (PROMIS) questionnaire. We used multiple linear and logistic regression models to test the study hypothesis. Results: A higher likelihood of experiencing sleep disturbance was recorded in people aged older than 56 years (OR = 1.78, 95% CI: 1.17–2.72, p = 0.007), people with depressive symptoms (OR = 3.57, 95% CI: 2.77–4.61, p < 0.001), and food-insecure people (OR = 1.32, 95% CI: 1.02–1.70, p = 0.036). A lower likelihood of experiencing sleep disturbance was recorded in people with low educational attainment (OR = 0.41, 95% CI: 0.30–0.57, p < 0.001). Sleep disturbance was dependent on the food consumption groups and food security status among men (p = 0.004). Conclusions: Sleep disturbance may be affected by the food-insecure status of adults, and later, may lead to serious health outcomes.

A Body shape index significantly predicts MRI-defined abdominal adipose tissue depots in non-obese Asian Indians with type 2 diabetes mellitus

INTRODUCTION

We aimed to determine the correlations of volumes of subcutaneous abdominal adipose tissue (SCAT) (anterior, posterior, superficial and deep), total SCAT, intraperitoneal adipose tissue, retroperitoneal abdominal adipose tissue (RPAT), total intra-abdominal adipose tissue (IAAT), pancreatic volume, liver span, total body fat (TBF) and truncal fat mass (TFM) with anthropometric indices, viz., A Body Shape Index (ABSI), Hip Index, their Z scores and Anthropometric Risk Index in non-obese (body mass index (BMI) <25 kg/m²) Asian Indians with type 2 diabetes mellitus (T2DM).

RESEARCH DESIGN AND METHODS

Non-obese patients with T2DM (cases; n, 85) and BMI-matched, healthy subjects (controls; n, 38) underwent anthropometry, dual energy X ray absorptiometry (DXA) for estimation of TBF, TFM and 1.5 T MRI for estimation of volumes of abdominal adipose tissue depots, pancreas and liver span. Spearman's correlation analysis and Receiver Operator Characteristic curve analysis were applied.

RESULTS

The Z score of ABSI (Z_ABSI) showed significantly positive correlation with volumes of all depots of abdominal SCAT, total IAAT and RPAT in cases. Area under the curve for Z_ABSI (0.87) showed higher sensitivity: 82.0 %, specificity: 81.5 %, at a predictive cut-off value of 0.49 for abdominal adiposity.

CONCLUSION

In non-obese Asian Indians with T2DM, the Z_ABSI showed significant correlation with IAAT and SCAT and higher predictive accuracy for abdominal adiposity.

HIGHLIGHTS OF THE STUDY

This is the first MRI-based study in the context of ABSI in non-obese (BMI <25 kg/m²) Asian Indians with T2DM. Findings indicate that Z_ABSI has high predictive accuracy for abdominal adiposity in non-obese Asian Indians. The Z_ABSI index showed significantly positive correlation with volumes of adipose tissue depots, viz., abdominal SCAT, total IAAT and RPAT in cases.

Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies

OBJECTIVE

To quantify the association of indices of central obesity, including waist circumference, hip circumference, thigh circumference, waist-to-hip ratio, waist-to-height ratio, waist-to-thigh ratio, body adiposity index, and A body shape index, with the risk of all cause mortality in the general population, and to clarify the shape of the dose-response relations.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed and Scopus from inception to July 2019, and the reference lists of all related articles and reviews.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Prospective cohort studies reporting the risk estimates of all cause mortality across at least three categories of indices of central fatness. Studies that reported continuous estimation of the associations were also included.

DATA SYNTHESIS

A random effects dose-response meta-analysis was conducted to assess linear trend estimations. A one stage linear mixed effects meta-analysis was used for estimating dose-response curves.

RESULTS

Of 98 745 studies screened, 1950 full texts were fully reviewed for eligibility. The final analyses consisted of 72 prospective cohort studies with 2 528 297 participants. The summary hazard ratios were as follows: waist circumference (10 cm, 3.94 inch increase): 1.11 (95% confidence interval 1.08 to 1.13, I2=88%, n=50); hip circumference (10 cm, 3.94 inch increase): 0.90 (0.81 to 0.99, I2=95%, n=9); thigh circumference (5 cm, 1.97 inch increase): 0.82 (0.75 to 0.89, I2=54%, n=3); waist-to-hip ratio (0.1 unit increase): 1.20 (1.15 to 1.25, I2=90%, n=31); waist-to-height ratio (0.1 unit increase): 1.24 (1.12 to 1.36, I2=94%, n=11); waist-to-thigh ratio (0.1 unit increase): 1.21 (1.03 to 1.39, I2=97%, n=2); body adiposity index (10% increase): 1.17 (1.00 to 1.33, I2=75%, n=4); and A body shape index (0.005 unit increase): 1.15 (1.10 to 1.20, I2=87%, n=9). Positive associations persisted after accounting for body mass index. A nearly J shaped association was found between waist circumference and waist-to-height ratio and the risk of all cause mortality in men and women. A positive monotonic association was observed for waist-to-hip ratio and A body shape index. The association was U shaped for body adiposity index.

CONCLUSIONS

Indices of central fatness including waist circumference, waist-to-hip ratio, waist-to-height ratio, waist-to-thigh ratio, body adiposity index, and A body shape index, independent of overall adiposity, were positively and significantly associated with a higher all cause mortality risk. Larger hip circumference and thigh circumference were associated with a lower risk. The results suggest that measures of central adiposity could be used with body mass index as a supplementary approach to determine the risk of premature death.

A Body Shape Index (ABSI) achieves better mortality risk stratification than alternative indices of abdominal obesity: results from a large European cohort

Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI < 18.5 kg/m2) or obese (BMI ≥ 30 kg/m2) categories, while the highest quartile of ABSI separated 18-39% of the individuals within each BMI category, which had 22-55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.

Dose-response associations of clinical markers of obesity and duration of exposure to excess weight with chronic musculoskeletal pain: cross-sectional analysis at baseline of ELSA-Brasil Musculoskeletal cohort

The objective of this study is to investigate the association of clinical markers of obesity and weight trajectories with chronic musculoskeletal pain (CMP). This is a cross-sectional study using baseline data from ELSA-Brasil MSK cohort. CMP was evaluated at nine body sites (neck, shoulders, upper back, elbows, lower back, wrists/hands, hips/thighs, knees, ankles/feet), and defined as pain lasting > 6 months in the past year. General and abdominal obesity levels were classified according to accepted cut-offs for body mass index (BMI), waist circumference (WC) and waist-height ratio (WHtR). Binomial and multinomial logistic regressions tested for associations with CMP at any site, at ≥ 3 sites (multisite) and in upper + lower limbs + axial skeleton (generalized). A total of 2899 participants (mean age 56.0 ± 8.93) were included, 55.0% reported CMP, 19.1% had multisite, and 10.3% had generalized CMP. After adjustments for sex, age, education, physical activity and depressive symptoms, nearly all the investigated markers of obesity were associated with any CMP, multisite and generalized CMP, with strongest associations being observed for general obesity level II/III: OR 2.08 (95% CI 1.45-2.99), OR 3.19 (95% CI 2.06-4.94) and OR 3.65 (2.18-6.11), respectively. Having excess weight currently or both at age 20 and currently was also associated with all CMP presentations. Associations of greater magnitude were consistently observed at higher obesity levels and longer exposures to excess weight (dose-response). These results may support the contribution of obesity-derived mechanical and inflammatory mechanisms of CMP, and indicate a role for the accumulation of exposure to excess weight across the adult life course.

Validation of Surrogate Anthropometric Indices in Older Adults: What Is the Best Indicator of High Cardiometabolic Risk Factor Clustering?

The present study evaluated the ability of five obesity-related parameters, including a body shape index (ABSI), conicity index (CI), body roundness index (BRI), body mass index (BMI), and waist-to-height ratio (WtHR) for predicting increased cardiometabolic risk in a population of elderly Colombians. A cross-sectional study was conducted on 1502 participants (60.3% women, mean age 70 ± 7.6 years) and subjects’ weight, height, waist circumference, serum lipid indices, blood pressure, and fasting plasma glucose were measured. A cardiometabolic risk index (CMRI) was calculated using the participants’ systolic and diastolic blood pressure, triglycerides, high-density lipoprotein and fasting glucose levels, and waist circumference. Following the International Diabetes Federation definition, metabolic syndrome was defined as having three or more metabolic abnormalities. All surrogate anthropometric indices correlated significantly with CMRI (p < 0.01). Receiver operating characteristic curve analysis of how well the anthropometric indices identified high cardiometabolic risk showed that WtHR and BRI were the most accurate indices. The best WtHR and BRI cut-off points in men were 0.56 (area under curve, AUC 0.77) and 4.71 (AUC 0.77), respectively. For women, the WtHR and BRI cut-off points were 0.63 (AUC 0.77) and 6.20 (AUC 0.77), respectively. In conclusion, BRI and WtHR have a moderate discriminating power for detecting high cardiometabolic risk in older Colombian adults, supporting the idea that both anthropometric indices are useful screening tools for use in the elderly.

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

AIMS

A nine-month motivational exercise-based intervention was previously offered to subjects with type 2 diabetes (T2D). A year after the end of the intervention, compliance to physical activity (PA) and anthropometric indices of participants were analyzed to evaluate the durability of its effects.

METHODS

PA levels, expressed as total energy expenditure per week, were assessed with the International Physical Activity Questionnaire (IPAQ). Changes in Body Mass Index (BMI), A Body Shape Index (ABSI), Hip Index (HI) z-scores, the relative mortality risk related to each of these measures, and a combined Anthropometric Risk Index (ARI) were also evaluated.

RESULTS

Of a total of the 52 subjects examined (67.9% males, mean age 61.8 ± 6.0), 46 (88.4%) were still sufficiently active as defined by IPAQ thresholds at follow-up. PA levels, anthropometric indices and related risks improved at follow-up in respect to the baseline and to the end of the intervention, although only PA levels, BMI and related measures, and ARI risk changed significantly. Habitual PA increased significantly after the intervention (p < 0.01) and this increase correlated with changes in BMI z-scores (r = -0.29, p = 0.04). BMI risk was significantly lower (p < 0.01) in participants still active at follow-up.

CONCLUSIONS

This study testifies to the persistence of compliance to PA and health benefits of a combined exercise-based and motivational intervention in subjects with T2D.

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

BACKGROUND

Interventions such as testosterone treatment may change body composition and metabolic outcomes without substantial changes in weight and BMI.

OBJECTIVES

Using testosterone treatment as a paradigm, we hypothesized that a body shape index (ABSI) reflects body composition changes more accurately than traditional markers, such as weight, BMI and waist circumference.

INTERVENTION

Secondary analysis of a 56-week RCT in 100 dieting obese men with low-normal testosterone receiving testosterone treatment or placebo, and subsequent off-treatment follow-up.

RESULTS

At the end of the trial period, ABSI-unlike weight, BMI or waist circumference-had significantly decreased in the treatment group, compared with placebo (mean adjusted difference -0.18 [95% CI: -0.32, -0.05] × 10^-2 m^11/6kg^-2/3, overall P<0.001). Changes in ABSI during the active trial phase correlated with changes in fat mass (tau = 0.18, P = 0.02), and not with lean mass (tau = -0.11, P = 0.14), BMI (tau = 0.10, P = 0.17), or visceral fat (tau = 0.07, P = 0.37). ABSI baseline values were positively correlated with waist circumference (tau = 0.21, P = 0.002) and visceral fat (tau = 0.18, P = 0.009), correlated inversely with lean mass (tau = -0.21, P = 0.002), and were uncorrelated with BMI (tau = -0.10, P = 0.15) and fat mass (tau = 0.01, P = 0.83). Two years after cessation of treatment, ABSI again reflected body composition as the between-group differences in all parameters did not persist.

CONCLUSIONS

A readily obtainable anthropomorphic measure, ABSI reflects the differential loss of fat mass mediated by testosterone in dieting obese men more closely than BMI or waist circumference. It may serve as a clinically useful marker to monitor body composition changes, particularly in response to interventions.

Anthropometrics, Metabolic Syndrome, and Mortality Hazard

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