Predictive ability of novel and traditional anthropometric measurement indices for kidney stone disease: a cross-sectional study.

BACKGROUND: The aim of our research was to examine the association of novel anthropometric indices (a body shape index (ABSI), waist-to-height ratio (WtHR), conicity index (CI) and body roundness index (BRI)) and traditional anthropometric indices (body mass index (BMI), and waist (WC)) with prevalence of kidney stone disease (KSD) in the general population of United States (U.S.). METHODS: In this study, we conducted a cross-sectional analysis among the participants in the National Health and Nutrition Examination Survey between the years 2007 and 2020. Weighted multivariable logistic regression analysis, restricted cubic spline (RCS), receiver operating characteristic (ROC) curves, and subgroup analysis were performed to analyze the association of ABSI, BRI, WtHR, CI, BMI and WC with prevalence of KSD. RESULTS: In total, 11,891 individuals were included in our study. The RCS plot shown that the linear positive association was found between ABSI, BRI, WtHR, CI, BMI and WC and KSD risk. Additionally, the ROC curve demonstrated that the area under the curve of ABSI, BRI, WtHR, and CI was significantly higher than traditional anthropometric indices, including BMI and WC. CONCLUSIONS: Our study found that the discriminant ability of ABSI, BRI, WtHR, and CI for KSD was higher than BMI and WC. Consequently, ABSI, BRI, WtHR, and CI have the potential to become new indicators for the detection of KSD risk in clinical practice.

Abdominal obesity as assessed by anthropometric measures associates with urinary incontinence in females: findings from the National Health and Nutrition Examination Survey 2005-2018.

BACKGROUND: Urinary incontinence (UI) is significantly link to abdominal obesity. This study aimed to assess the association between anthropometric indices of abdominal obesity, including body roundness index (BRI), conicity index (CI), and waist-to-height ratio (WHtR), and UI risk in adult females. METHODS: We analyzed data from 10, 317 adult females in the National Health and Nutrition Examination Survey (NHANES) database (2005-2018). Weighted multivariable-adjusted regression analysis was conducted to determine the odds ratio (OR) and 95% confidence intervals (CI) for the association between BRI, CI, WHtR, and UI. Stratified analyses revealed the association based on the population type. Receiver operating characteristic curve (ROC) analyses were used to assess the predictive value of UI. RESULTS: All indices of abdominal obesity investigated were positively and independently associated with the prevalence and severity of three types of UI. After adjusting for all relevant confounding variables, a significantly positive association between BRI and the prevalence of UI were observed (OR quartile 4 vs. quartile 1: urge UI (UUI): 1.93, 95% CI 1.61-2.30; stress UI (SUI): 2.29, 95% CI 1.94-2.70; mixed UI (MUI): 2.26, 95% CI 1.82-2.82; all P < 0.0001, P for trend < 0.0001, respectively), as well as WHtR and CI, which particularly prominent for female in premenopausal. Moreover, a one-unit increment of BRI was significantly associated with an increased severity index of UUI (ß: 0.06, 95% CI 0.04-0.09, P < 0.0001), SUI (ß: 0.10, 95% CI 0.07-0.13, P < 0.0001) and MUI (ß: 0.07, 95% CI 0.04-0.10, P < 0.0001), which this trend was also observed in each subtype of UI for WHtR and CI. Furthermore, the ROC analysis demonstrated a higher diagnostic efficacy of BRI and WHtR compared with BMI in discriminating UI with an AUC of 0.600 for SUI, 0.617 for UUI, and 0.622 for MUI (all P < 0.05). CONCLUSIONS: An increased BRI, CI, and WHtR are significantly associated with higher prevalence and severity of UI in females.

Conicity-index predicts all-cause mortality in Chinese older people: a 10-year community follow-up.

BACKGROUND: Abdominal obesity (AO) has been regarded as the most dangerous type of obesity. The Conicity-index (C-index) had a high ability to discriminate underlying AO. The purpose of this study was to determine the ability of C-index to predict all-cause mortality among non-cancer Chinese older people. METHODS: The participants were residents of the Wanshou Road community in Beijing, China. Receiver operating curve (ROC) curves were used to determine the sensitivity and specificity of the best cut-off values for different anthropometric measures for predicting all-cause mortality. The area under the curve (AUC) of the ROC curves were calculated to compare the relative ability of various anthropometric measures to correctly identify older people in the community where all-cause mortality occurs. Included subjects were grouped according to C-index tertiles. The association between C-index and all-cause mortality was verified using Kaplan-Meier survival analysis and different Cox regression models. RESULTS: During a mean follow-up period of 9.87 years, 1821 subjects completed follow-up. The average age was 71.21 years, of which 59.4% were female. The ROC curve results showed that the AUC of the C-index in predicting all-cause mortality was 0.633. Kaplan-Meier survival curves showed a clear dose-response relationship between C-index and all-cause mortality. With the increase of C-index, the survival rate of the study population showed a significant downward trend (P < 0.05). Adjusted for age, gender, hip circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose (FBG), 2-h postprandial blood glucose (2hPG), glycosylated hemoglobin, high-density lipids protein (LDL), triglyceride, serum creatinine, serum uric acid, urine albumin-creatinine ratio (UACR), Mini-Mental State Examination (MMSE), smoking history, and drinking history, COX regression analysis showed that in the model adjusted for all covariates, the risk of all-cause mortality in tertile 3 was 1.505 times that in tertile 1, and the difference was statistically significant. CONCLUSIONS: The C-index is an independent risk factor for all-cause mortality in the non-cancer Chinese older people.

Predictors of central and general obesity in Iranian preschool children: which anthropometric indices can be used as screening tools?

AIM: To compare the ability of anthropometric indices [waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), neck-to-height ratio (NHR), conicity index (CI), body adiposity index (BAI), tri-ponderal mass index (TMI) and body mass index (BMI)] and,measuerments like neck(NC), hip(HC) and waist circumferences to predict overweight and obesity in Iranian preschool children. MATERIALS AND METHODS: A total of 498 Iranian preschool children were included in this case-control study conducted in Tehran, Iran. The participants were selected using the stratified random sampling procedure based on gender and school. Using sex-based receiver operating curve (ROC) analysis, we compared the area under the curve and defined the cut-off points for detecting central and general obesity for each index in order to identify the most suitable tools in predicting obesity. RESULTS: Boys had significantly higher values for NC, WC, WHR, NHR, CI, TMI and BMI as compared to girls, whereas BAI and HC were higher in girls. The area under the curve was calculated for all the possible predictors of central obesity, i.e., NC (0.841-0.860), WC (0.70-0.679), HC (0.785-0.697), WHR (0.446-0.639) and CI (0.773-0.653) in boys and girls, respectively. And according to the ROC curve analysis, BMI (0.959-0.948), TMI (0.988-0.981), WHtR (0.667-0.553) and NHR (0.785-0.769) were predictors of general obesity and NC (0.841-0.860) as predictor of central obesity in boys and girls, respectively. The optimal cut-off points for TMI (13.80-15.83), NC (28.68-27.5) and for other anthropometric indices were estimated in both boys and girls. CONCLUSION: TMI and NC seem to predict general and central obesity in Iranian preschool children.

Association of anthropometric measures with kidney disease progression and mortality: a retrospective cohort study of pre-dialysis chronic kidney disease patients referred to a specialist renal service.

BACKGROUND: Although elevated body mass index (BMI) is a predictor of better clinical outcomes in dialysis patients, the evidence in pre-dialysis chronic kidney disease (CKD) is conflicting. Clinical measures of central obesity may be better prognostic indicators, although investigation has been limited. The aim of this study was to assess the predictive value of anthropometric measures for kidney failure progression and mortality in stage 3-4 CKD. METHODS: The study included newly referred stage 3-4 CKD patients at a single centre between 1/1/2008 and 31/12/2010. The associations between clinical measures of obesity (BMI, waist circumference [WC] and conicity index [ConI]) and time to a composite primary outcome of doubling of serum creatinine, commencement of renal replacement therapy or mortality were evaluated using the Kaplan-Meier method and multivariable Cox regression models. RESULTS: Over a median follow-up period of 3.3 years, 229 (25.4 %) patients of a total population of 903 experienced the composite primary renal outcome. When compared to normal BMI (18.5-24.9 kg/m(2), n = 174), the risk of the composite primary outcome was significantly lower in both the overweight (BMI 25-29.9 kg/m(2), n = 293; adjusted hazard ratio [HR] 0.50, 95 % CI 0.33-0.75) and obese class I/II groups (BMI 30-39.9 kg/m(2), n = 288; HR 0.62, 95 % CI 0.41-0.93), but not in the obese class III group (BMI ≥40 kg/m(2), n = 72; HR 0.94, 95 % CI 0.52-1.69). All-cause mortality was also lower in the overweight group (HR 0.50, 95 % CI 0.30-0.83). WC and ConI were not associated with either the composite primary outcome or mortality. CONCLUSION: BMI in the overweight range is associated with reduced risks of kidney disease progression and all-cause mortality in stage 3-4 CKD. WC and ConI were not independent predictors of these outcomes in this population.

Prediction of the 10-year incidence of type 2 diabetes mellitus based on advanced anthropometric indices using machine learning methods in the Iranian population.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a growing chronic disease that can lead to disability and early death. This study aimed to establish a predictive model for the 10-year incidence of T2DM based on novel anthropometric indices. METHODS: This was a prospective cohort study comparing people with (n = 1256) and without (n = 5193) diabetes mellitus in phase II of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study. The association of several anthropometric indices in phase I, including Body Mass Index (BMI), Body Adiposity Index (BAI), Abdominal Volume Index (AVI), Visceral Adiposity Index (VAI), Weight-Adjusted-Waist Index (WWI), Body Roundness Index (BRI), Body Surface Area (BSA), Conicity Index (C-Index) and Lipid Accumulation Product (LAP) with T2DM incidence (in phase II) were examined; using Logistic Regression (LR) and Decision Tree (DT) analysis. RESULTS: BMI followed by VAI and LAP were the best predictors of T2DM incidence. Participants with BMI < 21.25 kg/m2 and VAI ≤ 5.9 had a lower chance of diabetes than those with higher BMI and VAI levels (0.033 vs. 0.967 incident rate). For BMI > 25 kg/m2, the chance of diabetes rapidly increased (OR = 2.27). CONCLUSIONS: BMI, VAI, and LAP were the best predictors of T2DM incidence.

Adiposity trajectories and cardiovascular disease risk in women: a population-based cohort study with a focus on menopausal status.

Objectives: A single measurement of adiposity indices could predict the incidence of cardiovascular disease (CVD); nonetheless their long-term pattern and its association with incident CVD are rarely studied. This study aimed to determine distinct trajectories of adiposity indices among participants of Tehran Lipid and Glucose Study (TLGS) and their association with incident CVD. Furthermore, this study aimed to investigate whether this association differed among individuals according to their menopausal status. Method: A total of 6840 women participated in TLGS, aged 20 years and older were included in this study; they were followed for a median of 16 years. Body mass index (BMI), waist circumference (WC), conicity index (CI) and body roundness index (BRI) were included in the analysis as adiposity indices. The cohort outcome panel of medical specialists identified the CVD outcomes. Trajectory analyses were used to identify homogeneous distinct clusters of adiposity indices trajectories. The association between the trajectory group membership and incident CVD were explored by Cox proportional hazard models, with unadjusted and adjusted model for baseline age, physical activity, smoking status, menopause and family history of CVD. Results: Three BMI trajectory groups of low, medium, and high and two trajectories for WC, BRI and CI were identified. Adjusted cox proportional hazard models revealed significant associations between the hazard of CVD experience and the high trajectory group of the BMI (HR: 2.06, 95% CI: 1.38-3.07), WC (HR: 2.71, 95% CI: 1.98-3.70), CI (HR: 1.87, 95% CI: 1.26-2.77) and BRI (HR: 1.55-95% CI: 1.12-2.15), compared to the low trajectory group. Subgroup analysis based on the menopausal status of participants showed that the HR of CVD incidences for all of trajectories adiposity indices, except BMI, was statistically significant. Adjusted cox proportional hazard models, in those women not reached menopause during study, revealed that the HR (95% CI) of CVD incidences for high trajectory of BMI, WC, CI and BRI were 2.80 (1.86-7.05); 2.09 (1.40-6.16); 1.72 (1.42-5.61), and 3.09 (1.06-9.01), respectively. These values for those were menopause at the initiation of the study were 1.40 (1.11, 2.53); 1.65 (1.04-2.75); 1.69 (1.01-2.87), and 1.61 (0.98-2.65), respectively. Conclusion: Our findings suggest that adiposity trajectories, particularly central adiposity index of CI, could precisely predict the CVD risk. Consequently, preventive strategies should be tailored accordingly.

Cut points of the conicity index as an indicator of abdominal obesity in individuals undergoing hemodialysis: An analysis of latent classes.

OBJECTIVES: Abdominal obesity favors the involvement of cardiometabolic complications in renal patients on hemodialysis. Thus, the aim of the study was to identify the cut-points of the conicity index in individuals undergoing hemodialysis. METHODS: This was a cross-sectional study carried out with 953 individuals undergoing hemodialysis in clinics in a metropolitan region of southeastern Brazil. The conicity index was calculated using the following mathematical equation: waist circumference/0.109 × âˆšweight/height. The receiver operating characteristic (ROC) curve was calculated from the analysis of latent classes by cross-validation through a latent variable of abdominal obesity. This latent variable was defined using the response pattern of the observed anthropometric variables considering the presence and absence of abdominal obesity: waist circumference, waist-to-height ratio, and body shape index. The cut-points identified were elucidated by the area under the curve (AUC), Youden index, sensitivity, and specificity. RESULTS: The cut-points for the conicity index found for both sexes were similar, resulting in a cut-point for men of 1.275 (AUC, 0.921; Youden index, 0.666), with a sensitivity and specificity of 83% and 83.6%, and a cut-point for women of 1.285 (AUC, 0.921; Youden index, 0.679), with a sensitivity and specificity of 78.6% and 89.3%, respectively. CONCLUSIONS: The conicity index showed high discriminatory power for the identification of abdominal obesity in hemodialysis patients, therefore it can be a simple and easily accessible tool to be incorporated into clinical practice in this population.

The Novelty of using Obesity Indices as Blood Pressure Predictors.

AIMS: To study the association between selected obesity indices, systolic blood pressure (SBP), and diastolic blood pressure (DBP). METHODS: A cross-sectional study was conducted on 491 Jordanian adults (19-65 years old). The sociodemographic data, anthropometrics, and blood pressure were measured and recorded. Obesity indices (Conicity Index (CI), Abdominal volume index (AVI), Body Roundness Index (BRI), and Weight-adjusted-waist index (WWI)) were calculated using standard validated formulas. RESULTS: Based on age, the SBP had a significant moderate correlation with BRI and AVI in all age groups. In the age group 20 to 34 years, SBP had a significantly moderate correlation with CI, and DBP had a significantly moderate correlation with BRI and AVI. In the age group of 35 to 44 years, DBP had a significantly moderate correlation with CI, BRI, WWI, and AVI. For the age group of 45 to 65 years, the SBP had a significantly moderate correlation with all the obesity indexes, opposite to DBP. Obesity indices explain 23.6 to 24.1 % of the changeability in SBP, and one unit increase in them, increased SBP ranges from 0.61±0.14 to 19.88±4.45. For DBP, obesity indices explained 15.9% to 16.3% of the variability in DBP, and raising them by one unit led to an increase in the DBP range from 0.27±0.11 to 10.08±4.83. CONCLUSION: All the studied obesity indices impacted SBP and DBP with the highest reported effect for AVI and BRI and a lower impact for WWI. The impact of obesity indices on DBP was affected by age group.

Central obesity as assessed by conicity index and a-body shape index associates with cardiovascular risk factors and mortality in kidney failure patients.

Background: Anthropometric indices of central obesity, waist circumference (WC), conicity index (CI), and a-body shape index (ABSI), are prognostic indicators of cardiovascular (CV) risk. The association of CI and ABSI with other CV risk indices, markers of nutritional status and inflammation, and clinical outcomes in chronic kidney disease (CKD) stage 5 (CKD5) patients was investigated. Methods: In a cross-sectional study with longitudinal follow up of 203 clinically stable patients with CKD5 (median age 56 years; 68% males, 17% diabetics, 22% with CV disease, and 39% malnourished), we investigated CI and ABSI and their associations with atherogenic index of plasma (AIP), Framingham CV risk score (FRS), Agatston scoring of coronary artery calcium (CAC) and aortic valve calcium (AVC), handgrip strength (HGS), high sensitivity C-reactive protein (hsCRP) and interleukin-6 (IL-6). CV events (CVE) and all-cause mortality during up to 10-years follow up were analyzed by multivariate survival analysis of restricted mean survival time (RMST). Results: Chronic kidney disease patients with middle and highest CI and ABSI tertiles (indicating greater abdominal fat deposition), compared to those with the lowest CI and ABSI tertiles, tended to be older, more often men and diabetic, had significantly higher levels of hsCRP, IL-6, AIP, FRS, CAC and AVC scores. CI and ABSI were positively correlated with CAC, FRS, AIP, hsCRP and IL-6. Both CI and ABSI were negatively correlated with HGS. In age-weighted survival analysis, higher CI and ABSI were associated with higher risk of CVE (Wald test = 4.92, p = 0.027; Wald test = 4.95, p = 0.026, respectively) and all-cause mortality (Wald test = 5.24, p = 0.022; Wald test = 5.19, p = 0.023, respectively). In RMST analysis, low vs. high and middle tertiles of CI and ABSI associated with prolonged CVE-free time and death-free time, and these differences between groups increased over time. Conclusion: Abdominal fat deposit indices, CI and ABSI, predicted CV outcomes and all-cause mortality, and were significantly associated with the inflammatory status in CKD patients.

Prevalence of associations among sarcopenia, obesity, and metabolic syndrome in Brazilian older adults.

Background: Although aging is a process associated with the development of obesity, metabolic syndrome (MetS), and sarcopenia, the prevalence of these conditions in older adults from São Paulo, Brazil, is unclear. Methods: Therefore, the current study aimed to investigate the prevalence of obesity, sarcopenia, and MetS, both separately and together, in a community-based sample of older adults from São Paulo, Brazil. Data from the medical records of 418 older adults of both genders, aged 60 years or older (mean age 69.3 ± 6.5 years), who were not physically active, were used to conduct this retrospective cross-sectional study. Anthropometric variables were used to determine both body mass index (BMI) and Conicity index (C index). Sarcopenia and MetS were defined according to the criteria of the European Working Group on Sarcopenia in Older People and by the Brazilian Society of Endocrinology and Metabolism, respectively. Results: Based on BMI, the group of older men (n = 91) showed a predominance of adequate weight (n = 49) and the group of older women (n = 327) showed a predominance of obesity (n = 181). In association with obesity, while only the group of older women presented with sarcopenia (n = 5), 52 older women and 9 older men presented with MetS, and two older women presented with sarcopenia + MetS [prevalence ratio = 0.0385, 95% CI (0.007;0.1924)]. Based on the C index, 58 older women and 11 older men presented with MetS, while the occurrence of sarcopenia or MetS + sarcopenia was found in 32 and 5 older women, respectively [prevalence ratio = 0.0910, 95% CI (0.037;0.2241)]. Discussion: Our results suggest that obesity, as measured by BMI or the C Index, was more closely associated with the occurrence of MetS than sarcopenia, regardless of gender, and also that sarcopenic obesity was only found in the group of older women. Additionally, the prevalence ratio of obesity, sarcopenia, and MetS evidenced using the C index was 2.3 times higher than the values found using the BMI classification.

Dietary fat types consumption association with obesity and coronary indices.

This article aims to study the different dietary fat types associated with obesity and coronary indices. A sample of 491 healthy adults was included in a cross-sectional manner. Dietary fats intake, obesity indices (conicity index (CI), body adiposity index (BAI), abdominal volume index (AVI), body roundness index (BRI), and weight-adjusted-waist index (WWI)), and cardiovascular indices (cardiometabolic index (CMI), lipid accumulation product (LAP), and atherogenic index of plasma (AIP)) were calculated and studied. Participants with an acceptable intake of omega-3 had a higher BRI score (1⋅90 ± 0⋅06 v. 1⋅70 ± 0⋅06). Participants with an unacceptable intake of cholesterol had a higher CI (1⋅31 ± 0⋅11 v. 1⋅28 ± 0⋅12; P = 0⋅011), AVI (20⋅24 ± 5⋅8 v. 18⋅33 ± 6⋅0; P < 0⋅001), BRI (2⋅00 ± 1⋅01 v. 1⋅70 ± 1⋅00; P = 0⋅003), WWI (11⋅00 ± 0⋅91 v. 10⋅80 ± 0⋅97; P = 0⋅032), and lower AIP (0⋅46 ± 0⋅33 v. 0⋅53 ± 0⋅33; P = 0⋅024). Total fat, saturated fat (SFA), and polyunsaturated fat (PUFA) intake had a significant moderate correlation with AVI and BRI. The monounsaturated fat (MUFA) intake had a significantly weak correlation with CI, AVI, BRI, WWI, and AIP. Cholesterol and omega-6 had weak correlations with all indices. Similar correlations were seen among male and female participants. The different types of fat intake significantly affected obesity and coronary indices, especially SFA and PUFA, as well as omega-3 and cholesterol. Gender and the dietary type of fat intake have a relationship to influence the indicators of both obesity and coronary indices.

Association of Conicity Index with Different Cardiovascular Disease Risk Factors among Rural Elderly Women of West Bengal, India.

Introduction: In menopause, changes in body fat distribution lead to increasing risk of cardiovascular and metabolic diseases. Therefore, the prediction of cardiovascular disease (CVD) by the presence of risk factors is of importance in elderly women. Objective: To find out the conicity index (CI) and its association with different CVD risk factors among rural elderly women of West Bengal. Materials and Methods: The study was conducted among 236 rural elderly women, selected randomly from 30 villages of Amdanga block, West Bengal. Components of metabolic syndrome (MS), body fat percentage, different lipid profile fractions, CI, and body mass index (BMI) were measured. Statistical tests were calculated using SPSS software version 20.0. P ≤ 0.05 was considered statistically significant. Results: High CI (median 1.25 and interquartile range 1.05-1.45) was found. The proportion of participants with high CI were significantly higher among those with MS (87.95%), waist circumference having 80 cm or more (99.09%), blood pressure having ≥ 130/85 mm of Hg (75.66%), body fat percentage ≥25% (80.14%), and BMI ≥23 (93.18%). Conclusion: High prevalence of CI existed among rural elderly women. Significant correlation existed between CI and different CVD risk factors as well as some of the components of MS indicating a possible coexistence of different CVD risks.

A Body Shape Index (ABSI) as a Variant of Conicity Index Not Affected by the Obesity Paradox: A Cross-Sectional Study Using Arterial Stiffness Parameter.

A body shape index (ABSI) is an abdominal obesity index developed based on epidemiological statistics and designed to correlate minimally with body mass index (BMI). We examined the approximation between ABSI and other abdominal obesity indices based on biophysical concepts. The cross-sectional data from 62,514 Japanese urban residents were analyzed. Body adiposity indices comprising BMI, waist circumference (WC), ABSI, conicity index (CI), waist-to-height ratio (WHtR), and WC/BMI ratio were examined. ABSI and CI more strongly correlated with age and arterial stiffness assessed by cardio-ankle vascular index (CAVI) compared to the other indices. The discriminative power for high CAVI (≥9.0) was the strongest for ABSI followed by CI and other indices, in that order. The range and distribution of WC corresponding to the cutoff of ABSI (0.0801), or CI (1.23) seemed reasonable. The correlation between ABSI and CI was the strongest compared to any other combination of indices. CI correlated moderately with BMI, whereas ABSI correlated minimally with BMI. ABSI correlates strongly and approximates closely with CI. Hence, ABSI may be considered to reflect the degree of body shape change from cylindricity to conicity and is currently the only abdominal obesity index not affected by the obesity paradox.

Cut-off values and clinical efficacy of body roundness index and other novel anthropometric indices in identifying metabolic syndrome and its components among Southern-Indian adults.

CONTEXT: Abdominal obesity (AO) is a definitive link between cardiometabolic complications and metabolic syndrome (MetS). Many traditional and novel anthropometric indices have been identified to determine AO, and their relationship to MetS has been investigated. However, whether these indices are useful in a clinical setting is unknown. Moreover, the cut-off points for these indices to determine MetS have yet to be defined among Southern-Indian adults. AIMS: We aimed to evaluate the cut-off values and clinical efficacy of novel anthropometric indices in identifying MetS and its components. MATERIALS AND METHODS: Subjects (n = 202) were recruited and then grouped into cases (MetS = 106) and controls (healthy = 96). We measured anthropometric data and assayed glycemic and lipid profiles. Using these, we computed a-body shape index (ABSI), abdominal volume index (AVI), body adiposity index (BAI), body roundness index (BRI), conicity index (CI), lipid-accumulation product (LAP), visceral adiposity index (VAI) and waist-triglyceride index (WTI) from published equations. RESULTS: Compared to the control group, all the novel anthropometric indices were noticeably higher in both male and female subjects of the MetS group. The area under the curve values (AUCs) demonstrated that BRI, CI, AVI, and WTI had superior detection power in identifying MetS, and the AUCs varied upon stratification by gender. BRI was strongly associated with the highest odds of having MetS (OR 66.03). CONCLUSIONS: The optimal cut-off and AUC values attained for BRI, CI, AVI, and WTI have a clinical approach in identifying MetS and its components. The efficacy of these indices to identify MetS differed by gender.

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.

Adiposity and Cardiometabolic Risk assessment Among University Students in Saudi Arabia.

Overweight and obesity have become a significant health hazard among adolescents on account of quick growth in its occurrence rate and its common comorbidities like cardiometabolic disease (CMD). The aim of this study was to evaluate the prevalence of adiposity and assess the risk of CMD among university students in Eastern Province, Saudi Arabia. A cross-sectional study was conducted during the academic year 2017-2018, in a sample of 310 subjects (127 males; 183 females). The measurements were taken using standardized instruments including Body Mass Index (BMI), Fat Mass Index (FMI), Body Fat Percentage BFP), Mass of Body Fat (MBF), Visceral Fat Area (VFA), Waist Circumference (WC), and Waist to Hip Ratio (WHR). Moreover, CMD risk indicators were calculated by Conicity index (C index), WC, and WHR. The findings showed that the majority was overweight and obese (16.8% and 21.6%, respectively). While evaluating obesity indicators, males were found to have higher adiposity (obese students 34.6%) compared to female students (12.6%; p < 0.001). Additionally, FMI showed that the mean was significantly higher among males (8.65 ± 6.06) compared to females (7.26 ± 3.30; p < 0.019). Analysis of the predictors' indices for cardiometabolic risk score highlighted a significantly higher percentage of WC, WHR, and C index among male students (50, 38.5, 59) compared to females (16.9, 14.2, 34; p < 0.001). Significant positive correlations were observed between C index quartiles and BMI with the other cardiometabolic indices (p < 0.001). This study highlighted a high prevalence of adiposity and CMD risk among university students. The prediction of CMD in early age is quite helpful in preventing adiposity related health issues. Decision makers need to spread awareness about healthy consumption as well as the relationship between physical inactivity and chronic diseases.

Body Roundness Index, A Body Shape Index, Conicity Index, and Their Association with Nutritional Status and Cardiovascular Risk Factors in South African Rural Young Adults.

BACKGROUND: The study aimed to investigate the association of Body Roundness Index (BRI), A Body Shape Index (ABSI), and Conicity Index with nutritional status and cardiovascular risk factors in South African rural young adults. METHODS: The study included a total of 624 young adults aged 21-30 years from the Ellisras rural area. Anthropometric indices, blood pressure (BP), and biochemical measurements were measured. RESULTS: BRI was significantly correlated with insulin (0.252 males, females 0.255), homeostatic model assessment (HOMA)-ß (0.250 males, females 0.245), and TG (0.310 males, females 0.216). Conicity Index was significantly associated with pulse rate (PR) (ß 0.099, 95% confidence interval (CI) 0.017, 0.143, p < 0.013; ß 0.081, 95% CI 0.000 0.130, p < 0.048), insulin (ß 0.149, 95% CI 0.286 0.908, p < 0.001; ß 0.110, 95% CI 0.123 0.757, p < 0.007). Conicity Index is associated with insulin resistance (IR) (odds ratio (OR) 7.761, 95% CI 5.783 96.442, p < 0.001; OR 4.646, 95% CI 2.792 74.331, p < 0.007), underweight (OR 0.023, 95% CI 0.251 0.433, p < 0.001; OR 0.031, 95% CI 0.411 0.612, p < 0.001), and obesity (OR 1.058, 95% CI 271.5 4.119, p < 0.001; OR 1.271, 95% CI 0.672 1.099, p < 0.001). CONCLUSION: Conicity Index was positively associated with insulin resistance, hypertension and dyslipidaemia. Further investigation of these indices and their association with nutritional status and cardiovascular diseases (CVDs) could assist in efforts to prevent CVD in the rural South African population.

U-Shaped Association between Waist-to-Hip Ratio and All-Cause Mortality in Stage 3-5 Chronic Kidney Disease Patients with Body Mass Index Paradox.

The obesity paradox, referring to the association of high body mass index (BMI) with low all-cause mortality risk, is found in patients with chronic kidney disease (CKD). Central obesity is associated with metabolic syndrome and may have better prognostic value than BMI for all-cause mortality. Whether central obesity is associated with all-cause mortality in cases of obesity paradox in CKD patients remains unknown. We included 3262 patients with stage 3-5 CKD, grouped into five quintiles (Q1-5) by waist-to-hip ratio (WHR). Low WHR and BMI were associated with malnutrition and inflammation. In Cox regression, high BMI was not associated with all-cause mortality, but BMI < 22.5 kg/m2 increased the mortality risk. A U-shaped association between central obesity and all-cause mortality was found: WHR Q1, Q4, and Q5 had higher risk for all-cause mortality. The hazard ratio (95% confidence interval) of WHR Q5 and Q1 for all-cause mortality was 1.39 (1.03-1.87) and 1.53 (1.13-2.05) in male and 1.42 (1.02-1.99) and 1.28 (0.88-1.85) in female, respectively. Waist-to-height ratio and conicity index showed similar results. Low WHR or low BMI and high WHR, but not high BMI, are associated with all-cause mortality in advanced CKD.

Comparative assessment of anthropometric and bioimpedence methods for determining adiposity.

BACKGROUND: Obesity is a risk factor for different chronic conditions. Over the years, obesity has become a pandemic and it is therefore important that effective diagnostic tools are developed. Obesity is a measure of adiposity and it has become increasingly evident that anthropometric measures such as body mass index (BMI) used to estimate adiposity are inadequate. This study therefore examined the ability of different anthropometric measurements to diagnose obesity within a cross-section of Ghanaian women. METHODS: We obtained anthropometric measurements and used that to generate derived measures of adiposity such as body adiposity index (BAI) and conicity index. Furthermore we also measured adiposity using a bioimpedance analyser. Associations between these measurements and percentage body fat (%BF) were drawn in order to determine the suitability of the various measures to predict obesity. The prevalence of obesity was determined using both %BF and BMI. RESULTS: BMI, Waist and hip circumference and visceral fat (VF) were positively correlated with % BF whereas skeletal muscle mass was negatively correlated. Prevalence of obesity was 16% and 31.6% using BMI and %BF respectively. Receiver operating characteristic (ROC) analysis showed that these differences in prevalence was due to BMI based misclassification of persons who have obesity as overweight. Similar, shortfalls were observed for the other anthropometric measurements using ROC. CONCLUSIONS: No single measure investigated could adequately predict obesity as an accumulation of fat using current established cut-off points within our study population. Large scale epidemiological studies are therefore needed to define appropriate population based cut-off points if anthropometric measurements are to be employed in diagnosing obesity within a particular population.