Performance Of Body Mass Index Research Articles

Comparing the performance of body mass index, waist circumference and waist-to-height ratio in predicting Malaysians with excess adiposity

Background Body mass index (BMI) is a widely used surrogate tool to screen for obesity/adiposity, but it cannot differentiate between lean and fat mass. Thus, alternative tools to detect excess adiposity should be identified. Aim This study aimed to compare the performance of BMI, waist circumference (WC) and waist-to-height ratio (WtHR) in predicting Malaysians with excess body fat defined by dual-energy X-ray absorptiometry (DXA). Subjects and methods A total of 399 men and women aged ≥40 years were recruited from Klang Valley, Malaysia. The body composition of the subjects, including body fat percentage, was measured by DXA. The weight, height, WC and WHtR of the subjects were also determined. Results BMI [sensitivity = 55.7%, specificity = 86.1%, area under curve (AUC) = 0.709] and WC (sensitivity = 62.7%, specificity = 90.3%, AUC = 0.765) performed moderately in predicting excess adiposity. Their performance and sensitivity improved with lower cut-off values. The performance of WHtR (sensitivity = 96.6%, specificity = 36.1, AUC = 0.664) was optimal at the standard cut-off value and no modification was required. Conclusion The performance of WC in identifying excess adiposity was greater than BMI and WHtR based on AUC values. Modification of cut-off values for BMI and WC could improve their performance and should be considered by healthcare providers in screening individuals with excess adiposity.

Performance of body mass index and body fat percentage in predicting metabolic syndrome risk factors in diabetic patients of Yazd, Iran

BackgroundBody Fat percentage (BFP) and body mass index (BMI) are used to measure obesity-related metabolic syndrome risk. The present study aimed to determine the values of percent body Fat and body mass index for predicting metabolic syndrome risk factors in diabetic patients of Yazd, Iran.MethodsA total of 1022 (499 males and 523 females) diabetic patients participated in this study. According to Asian BMI criteria, Overweight was diagnosed if a participant had a BMI ≥25 kg/m2 (both male and female) or BFP ≥25% for male and ≥ 32% for female. Based on calculated BMI and BFP and after adjusting for age, height, weight and smoking habits, the participants were classified into group A (normal weight and Non-Fat), group B (overweight and Non-Fat), group C (normal weight and Fat), and group D (overweight and Fat).ResultsAccording to the results, the BMI of 23.4% were normal and BMI of 76.6% were overweight, respectively. Moreover, the BFP of 25.7 and 74.3% of the studied population were considered as Non-Fat and Fat, respectively. A strong relationship was found with respect to sex stratification; R2 = 0.79. For men, BMI can be a better predictor of hypertension and hypertriglyceridemia than BFP. For women, BMI was a better predictor of hyperglycemia than BFP. Moreover, BFP can be regarded as a better predictor of hyperglycemia in male group, while it was a good predictor of hypertension and hypertriglyceridemia and hypo HDL than BMI, in female group.ConclusionSignificant differences were observed between BMI and BFP to predict metabolic syndrome risk factors in diabetic patients across different sexes in our study population. In conclusion, both BMI and BFP should be considered in screening steps.

Improved Prediction of Body Mass Index in Real-World Administrative Healthcare Claims Databases.

To continue closing the gap between the predictive modeling and its real-world application, we report a new data-to-prediction pipeline that advanced the state-of-the-art predictive performance of body mass index (BMI) classifications by integrating siloed claims databases via a common data model. This study adapted the ensemble-based methodology of the baseline prediction model and focused on removing the silos in the claims databases. We applied the Super Learner machine learning algorithm (SLA) to learn a combined dataset consisting of 50% data from the Optum Date of Death database and 50% data from the IBM MarketScan Commercial Claims and Encounters (CCAE), and omitted the commonly used one-hot-encoding step and used multi-categorical variables directly in the feature engineering process. These developments were then optimized via a standard cross-validation scheme and the performance was evaluated on a holdout test set. Sociodemographic and clinical characteristics were used with (denoted as SLA1) and without (denoted as SLA2) baseline BMI values to predict BMI classifications (≥ 30, ≥ 35, and ≥ 40kg/m2). Although the newly implemented SLA1 performed similarly to the previous model, with the area under the receiver operating characteristic curve (ROC AUC) being approximately 88% for all BMI classifications, specificity ranging from 90% to 96%, and accuracy ranging from 88% to 93%. The new SLA2 achieved consistently better performance on all metrics across all BMI classes. In particular, the new SLA2 achieved 77-79% in ROC AUC, increasing from the previously reported level (73%). Its specificity improved to the range of 76-90% from 71-86%. Its accuracy improved to the range of 77-86% from 73-80%. Its recall (i.e., sensitivity) improved to the range of 64-78% from 60-76%. This study demonstrates dramatic improvements in the prediction of BMI across classifications using integrated databases in a common data model for the generation of real-world evidence.

Performance of different adiposity measures for predicting left ventricular remodeling in Chinese hypertensive youth

There is no consistent conclusion on which adiposity measure is best to predict cardiovascular risk factors in youth. The present study aims to assess the performance of body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) in predicting abnormal left ventricular structure in Chinese hypertensive youth. A total of 1180 youth aged 6–17 years with hypertension from the China Child and Adolescent Cardiovascular Health Study were included in this study. Logistic regression model, receiver operator characteristic (ROC) curve analysis and net reclassification improvement (NRI) method were used to assess performance of BMI, WC, and WHtR in predicting left ventricular hypertrophy (LVH) and left ventricular geometry (LVG). A 1-standard deviation increment in any of three indexes in predicting LVH and LVG were similar, e.g., with the odds ratios and 95% confidence intervals of 1.34 (1.16–1.55), 1.25 (1.08–1.45) and 1.40 (1.20–1.62), respectively. In addition, ROC analysis and NRI method confirmed the similar performance of three adiposity indexes in predicting LVH and LVG. In conclusion, BMI, WC and WHtR had similar performance in predicting abnormal left ventricular structure in Chinese hypertensive youth, but all three indexes had limited value in prediction. WHtR is a simple and convenient adiposity index for screening youth at high risk of target organ damage.

Performance of Body Mass Index in Identifying Obesity Defined by Body Fat Percentage and Hypertension Among Malaysian Population: A Retrospective Study.

PurposeBody mass index (BMI) is used universally to define obesity. Many studies have indicated that the current BMI cutoff value for obesity may be inaccurate in identifying individuals with excess body fat (BF) and at risk for cardiovascular diseases (CVD). This study aims to assess the performance of BMI in diagnosing obesity defined by BF percentage (BF%).Patients and MethodsA total of 136 participants who attended an annual health screening programme were recruited. The subjects completed the health examinations, including BMI, BF% and blood pressure measurement. A receiver operating curve (ROC) analysis was conducted to determine the optimal cutoff value of BMI in classifying obesity based on BF% (>25%).ResultsThe ROC analysis revealed that the optimal BMI cutoff value in classifying subjects with obesity based on BF% was 24.8 kg/m2. The agreement between the classification scheme based on the new BMI cutoff (>24.8 kg/m2) and BF% was higher (κ=0.722) compared to the standard BMI cutoff (>27.5 kg/m2) (κ=0.532). BMI 24.8 kg/m2 also had higher sensitivity (80.0%) than 27.5 kg/m2 (56.0%) in detecting subjects with high adiposity. The new BMI cutoff also showed a sensitivity of 63.9% in identifying subjects with hypertension compared to the standard cutoff (36.1%).ConclusionThe current definition of obesity based on BMI value needs to be reassessed by taking BF% into account. A new BMI cutoff point, 24.8 kg/m2 for obesity, can identify a higher percentage of Malaysian at risk for CVD.

Benchmarking the Discriminatory Performance of Body Mass Index and Body Fat for Obesity Detection in Patients Treated by Intragastric Balloon.

The accuracy of body mass index (BMI) in detecting obesity in patients treated by intragastric balloon (IGB) remains still speculative. We aimed to determine the discriminatory performance of BMI as an estimate of excess body fat (%BF) in an IGB-treated population. Retrospective analysis of prospectively collected data of 476 patients who completed the 6-month IGB treatment period and were subjected to body composition analysis. We evaluated the relationship between BMI and %BF or lean mass and the diagnostic performance of BMI ≥ 30 kg/m2 for adipose tissue detection, stratified by age (< 40 and ≥ 40 years) and gender. Moreover, we identified anthropometric and body composition parameters serving as predictors of obesity according to %BF-based criteria (> 25% in men or > 35% in women). Gender emerged as an effect modifier in the quadratic polynomial relationship between BMI and %BF (R2 = 0.849 for men, R2 = 0.715 for women), while BMI was linearly associated with %BF in both age groups (R2 = 0.435 for men, R2 = 0.474 for women). BMI was strongly correlated with both %BF (r = 0.67) and lean mass (r = - 0.65). The overall area under the ROC curve for BMI ≥ 30 kg/m2 to detect %BF was 0.87 (95%CI 0.85-0.90). A regression model including lean mass, total body water, age, BMI, and female gender explained 0.970 of the variance in %BF. The discriminatory performance of BMI as an estimate of excess body fat is enhanced by the implementation of gender- and age-specific BMI thresholds for defining obesity, in IGB-treated patients.

Diagnostic performance of body mass index in detection of obesity using different cutoff points for excess body fat.

The aim of this study was to assess the diagnostic sensitivity of body mass index (BMI) in detecting obesity according to different cutoff points in order to classify a high body fat percentage (%BF) in adolescents and young adults. This was a cross-sectional study conducted with 2447 adolescents 18 and 19 y of age residing in São Luís, Brazil and 951 young adults 21 to 23 y of age residing in Ribeirão Preto, Brazil. Three references were used to define a high %BF (i.e., those of Williams et al., Ramírez-Vélez et al., and Macias et al.). The area under the receiver operating characteristic area under the curve (AUC) was used to assess the performance of BMI. Sensitivity ranged from 38.3% to 54.1% among boys and from 12.7% to 72.7% among girls. Among young adults, it ranged from 52.3% to 67.1% in men and from 33.7% to 86.6% in women. The AUC ranged from 0.69 to 0.76 among boys, from 0.56 from 0.85 among girls, from 0.75 to 0.80 among men, and from 0.67 to 0.88 among women. The best cutoff points for the BMI were 24.79 to 25.10 kg/m2 for boys, 21.89 to 27.04 kg/m2 for girls, 26.43 to 28.22 kg/m2 for men, and 23.34 to 29.28 kg/m2 for women. The use of different references for the classification of a high %BF implied a difference in the diagnostic sensitivity of the BMI. Higher cutoff points resulted in greater sensitivity and ability to differentiate individuals with and without obesity.

Performance of body mass index and percentage of body fat in predicting cardiometabolic risk factors in Thai adults.

BackgroundBody mass index (BMI) and percentage of body fat (PBF) are used to measure obesity; however, their performance in identifying cardiometabolic risk in Southeast Asians is unclear. Generally, Asian women have higher PBF and lower BMI than do men and other ethnic populations. This study was conducted to address whether a discord exists between these measures in predicting obesity-related cardiometabolic risk in a Thai population and to test whether associations between the measures and risk factors for cardiovascular disease have a sex-specific inclination.MethodsA total of 234 (76 men and 158 women) outpatients were recruited. BMI obesity cutoff points were ≥25.0 and ≥27.0 kg/m2 and PBF cutoff points were ≥35.0% and ≥25.0% for women and men, respectively. Blood samples were analyzed for total cholesterol, triglycerides, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, lipoprotein subclasses, apolipoprotein A-I, apolipoprotein B, glucose, hemoglobin A1c, insulin, high-sensitive C-reactive protein (hsCRP), adiponectin, leptin, and 25-hydroxyvitamin D.ResultsTwenty-five percent of participants classified as normal-BMI had excessive fat, whereas 9% classified as normal-PBF had excessive BMI. Good relationships were found between BMI and PBF using sex stratification (R2 >0.5). The prevalence of metabolic syndrome was markedly increased in overweight and/or excess body fat groups compared with lean group. Logistic regression analyses showed that BMI was the best predictor of hypertension. BMI was an independent predictor of insulin resistance, hyperglycemia, hypertriglyceridemia, and hyperleptinemia in women, whereas PBF was for men. However, PBF proved to be a good indicator for atherogenic lipoprotein particles in both sexes. Notably, neither index predicted increased hsCRP or 25-hydroxyvitamin D insufficiency.ConclusionConsiderable sex-specific variations were observed between BMI and PBF in their associations with and predictability of numerous cardiometabolic biomarkers. No single measure provides a comprehensive risk predication as shown herein with the Thai population, and therefore both should be applied in screening activities.

Which anthropometric measures best indicate type 2 diabetes among Russian, Somali and Kurdish origin migrants in Finland? A cross-sectional study

ObjectivesTo compare the performance of body mass index (BMI), waist-to-height ratio (WHtR), waist circumference (WC) and waist-to-hip ratio (WHR) in detecting type 2 diabetes among Russian, Somali and Kurdish (born...

Diagnostic performance of body mass index to identify excess body fat in children with cerebral palsy.

To assess the diagnostic performance of body mass index (BMI) cut-off values according to recommendations of the World Health Organization (WHO), the World Obesity Federation (WOF), and the German Society for Adiposity (DAG) to identify excess body fat in children with cerebral palsy (CP). The present study was a monocentric retrospective analysis of prospectively collected data among children and adolescents with CP participating in a rehabilitation programme. Excess body fat was defined as a body fat percentage above the 85th centile assessed by dual-energy X-ray absorptiometry. In total, 329 children (181 males, 148 females) with CP were eligible for analysis. The mean age was 12years 4months (standard deviation 2y 9mo). The BMI cut-off values for 'overweight' according to the WHO, WOF, and DAG showed the following sensitivities and specificities for the prediction of excess body fat in our population: WHO: sensitivity 0.768 (95% confidence interval [CI] 0.636-0.870), specificity 0.894 (95% CI 0.851-0.928); WOF: sensitivity 0.696 (95% CI 0.559-0.812), specificity 0.934 (95% CI 0.898-0.960); DAG: sensitivity 0.411 (95% CI 0.281-0.550), specificity 0.993 (95% CI 0.974-0.999). Body mass index showed high specificity, but low sensitivity in children with CP. Thus, 'normal-weight obese' children with CP were overlooked, when assessing excess body fat only using BMI. Excess body fat in children with cerebral palsy (CP) is less common than previously reported. Body mass index (BMI) had high specificity but low sensitivity in detecting excess body fat in children with CP. BMI evaluation criteria of the German Society for Adiposity could be improved in children with CP.

Predictive value of body mass index to metabolic syndrome risk factors in Syrian adolescents

BackgroundObesity has become a serious epidemic health problem in both developing and developed countries. There is much evidence that obesity among adolescents contributed significantly to the development of type 2 diabetes and coronary heart disease in adulthood. Very limited information exists on the prevalence of overweight, obesity, and associated metabolic risk factors among Syrian adolescents. Therefore, the purpose of this study was to determine the relationship between obesity determined by body mass index and the major metabolic risk factors among Syrian adolescents.MethodsA cross-sectional study of a randomly selected sample of 2064 apparently healthy Syrian adolescents aged 18 to 19 years from Damascus city, in Syria, was performed. Body mass index and blood pressure were measured. Serum concentrations of glucose, triglycerides, total cholesterol, high-density lipoprotein-cholesterol, and low-density lipoprotein-cholesterol were determined. Metabolic syndrome was defined using the national criteria for each determined metabolic risk factor. Individuals with a body mass index 25 to 29.9 were classified as overweight, whereas individuals with a body mass index ≥30 were classified as obese.A receiver operating characteristics curve was drawn to determine appropriate cut-off points of the body mass index for defining overweight and obesity, and to indicate the performance of body mass index as a predictor of risk factors.ResultsThe obtained data showed that blood pressure and the overall mean concentrations of fasting blood sugar, triglycerides, cholesterol, low-density lipoprotein-cholesterol, and triglycerides/high-density lipoprotein-cholesterol were significantly higher in overweight and obese adolescent groups (p <0.0001) in comparison with the normal group. Based on receiver operating characteristics calculation for body mass index and some metabolic risks, the data suggest the best body mass index cut-offs ranged between 23.25 and 24.35 kg/m2.ConclusionsA strong association between overweight and obesity as determined by body mass index and high concentrations of metabolic syndrome components has been demonstrated. Although body mass index values were lower than the international cut-offs, these values were good predictors of some metabolic abnormalities in Syrian adolescents; body mass index is a good predictor of these abnormalities in this population.

Performance of different adiposity measures for predicting cardiovascular risk in adolescents

This study aims to compare the performance of body mass index (BMI), waist circumference (WC), and waist-to-height-ratio (WHtR) to predict the presence of at least 3 main CV risk factors in US adolescents. A total of 3621 adolescents (boys: 49.9%) aged 12–17 years from the US National Health and Nutrition Examination Survey (1999–2012) were included in this study. Measured CV risk factors included systolic/diastolic blood pressure, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and fasting plasma glucose. The AUC of BMI-z score, WC-z score and WHtR-z score to predict at least three CV risk factors were similar (~0.85), irrespective of criteria used to define abnormal levels of CV risk factors. A 1-SD increase in any of three indices to predict CV risk was also similar for the three adiposity scores. For instance, a 1-SD increase risk in BMI-z score, WC-z score and WHtR-z score was 3.32 (95%CI 2.53–4.36), 3.43 (95%CI 2.64–4.46), and 3.45 (95%CI 2.64–4.52), respectively, in the total population using the International Diabetes Federation definition. In addition, the most efficient WHtR cut-off for screening CV risk was ~0.50 in US adolescents. In summary, BMI, WC and WHtR performed similarly well to predict the presence of at least 3 main CV risk factors among US adolescents.

Diagnostic performance of Body Mass Index, Waist Circumference and the Waist-to-Height Ratio for identifying cardiometabolic risk in Scottish pre-adolescents

Background: Limited studies have examined the diagnostic performance of body mass index (BMI), waist circumference (WC) or waist-to-height ratio (WHtR) for identifying cardiometabolic risk (increased clustered glucose, triglycerides, mean arterial pressure and inv-HDL-cholesterol) in pre-adolescent youth.Aim: To compare the utility of BMI, WC and WHtR as predictors of cardiometabolic risk (CMR) in Scottish pre-adolescent children.Subjects and methods: A cross-sectional analysis of 223 Scottish children (55.2% boys, mean age =8.4 years) was undertaken. BMI, WC and WHtR were used as exposure variables within multivariate logistic regression analysis and ROC analysis to examine the utility of these anthropometrical indices in identifying those at cardiometabolic risk.Results: Individuals with an elevated WHtR, WC and BMI were 3.51 (95% CI = 1.71–7.23; p < .001); 2.34 (95% CI = 1.35–4.06; p = .002) and 2.59 (95% CI = 1.42–4.73; p = .002) times more likely to be at cardiometabolic risk, respectively. The areas under the curves [AUC] to identify children with cardiometabolic risk were significant and similar among anthropometric indices (AUC’s = 0.60–0.65). When stratified by BMI, both WC and WHtR demonstrated a fair-to-good ability for identifying those at cardiometabolic risk (AUC = 0.75–0.81).Conclusions: Findings suggest that the combination of BMI with either WC or WHtR may provide an added benefit in the assessment of cardiometabolic risk amongst pre-adolescents.

Optimal anthropometric measures and thresholds to identify undiagnosed type 2 diabetes in three major Asian ethnic groups.

To identify optimal anthropometric measures and cutoffs to identify undiagnosed diabetes mellitus (UDM) in three major Asian ethnic groups (Chinese, Malays, and Asian-Indians). Cross-sectional data were analyzed from 14,815 ethnic Chinese, Malay, and Asian-Indian participants of the Singapore National Health Surveys, which included anthropometric measures and an oral glucose tolerance test. Receiver operating characteristic curve analyses were used with calculation of the area under the curve (AUC) to evaluate the performance of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHTR) for the identification of UDM. BMI performed significantly worse (AUCMEN = 0.70; AUCWOMEN = 0.75) than abdominal measures, whereas WHTR (AUCMEN = 0.76; AUCWOMEN = 0.79) was among the best performing measures in both sexes and all ethnic groups. Anthropometric measures performed better in Chinese than in Asian-Indian participants for the identification of UDM. A WHTR cutoff of 0.52 appeared optimal with a sensitivity of 76% in men and 73% in women and a specificity of 63% in men and 70% in women. Although ethnic differences were observed in the performance of anthropometric measures for the identification of UDM, abdominal adiposity measures generally performed better than BMI, and WHTR performed best in all Asian ethnic groups.

Diagnostic performance of body mass index to identify adiposity in women.

The aim of this study was to determine the diagnostic performance of body mass index (BMI) and to detect the optimal BMI cutoff points to define adiposity in women of various ages. A total of 2409 women participated. Fat mass was measured using a multifrequency bioelectrical impedance analysis. The diagnostic performance of BMI to identify adiposity was evaluated using a fat mass percentage cutoff point of ⩾35%. Although 40% of women were overfat, the BMI-based obesity prevalence was 21%. In the total sample, BMI had low overall performance, which resulted in a sensitivity of 51.9% (95% confidence interval (CI): 48.7-55.2%) and a specificity of 99.2% (95% CI: 98.7-99.6%). BMI failed to identify overfat women with intermediate BMI ranges. An analysis of the receiver operating characteristic curves of all of the subjects demonstrated that optimal cutoff point corresponded to a BMI value of 26.4 kg/m(2). The diagnostic performance of BMI did not differ as age increased. BMI has a high specificity but a low sensitivity to detect adiposity, and it fails to identify nearly half of women with excess fat mass. We provide evidence that a commonly used BMI cutoff value to diagnose obesity is too high among women.

Diagnostic Performance Of Anthropometric Indices In Assessing Excess Fat Among Hong Kong Chinese Children And Adolescents

In large-scale population surveys and public health screenings, the use of simple anthropometric indices has become popular for identifying children and adolescents who are overweight and obesity. However, The relationship between these anthropometric indices and body fat percentage (%BF) is not well established for children and adolescents, including those in Hong Kong. PURPOSE: The aim of the present study is to investigate the performance of body mass index (BMI) weight-for-height (PWH), waist circumference (WC) and waist-for-height ratio (WHtR) as diagnostic tests in screening excess body fat among Hong Kong children and adolescents, METHODS: A total of 2134 Chinese children and adolescents aged 9-19 years old (1135 boys and 999 girls) participated in the study. %BF was assessed by Tanita TBF-543 BIA analyser, excess body fat was defined as over 25% body fat for boys and over 30% for girls. The area under the ROC (AUC) was used as a measure of the overall accuracy of BMI, PWH, WC, and WHtR in detecting excess body fat. RESULTS: Among boys, no significant difference was found in AUC among the measures for BMI-SDS, WC-SDS, WHtR-SDS, and PWH. The values of AUC indicate that these measures have excellent accuracy in screening excessive %BF among boys (AUC>0.9). However, among girls, BMI-SDS and PWH had a larger AUC than WC-SDS and WHtR-SDS (X2=30.90, p0.9), while WC-SDS and WHtR-SDS have moderate accuracy in screening excessive %BF (0.7<AUC<0.9). CONCLUSIONS: Good and comparable diagnostic performance in screening excess body fat was shown among BMI, PWH, WC, and WHtR for boys Hong Kong Chinese children and adolescents. Among girls, the well and comparable diagnostic performance in screening excess body fat was found between BMI and PWH, but not in WC and WHtR.

Diagnostic performance of body mass index using the Western Pacific Regional Office of World Health Organization reference standards for body fat percentage.

Associations between body mass index (BMI), body fat percentage (BF%), and health risks differ between Asian and European populations. BMI is commonly used to diagnose obesity; however, its accuracy in detecting adiposity in Koreans is unknown. The present cross-sectional study aimed at assessing the accuracy of BMI in determining BF%-defined obesity in 6,017 subjects (age 20-69 yr, 43.6% men) from the 2009 Korean National Health and Nutrition Examination Survey. We assessed the diagnostic performance of BMI using the Western Pacific Regional Office of World Health Organization reference standard for BF%-defined obesity by sex and age and identified the optimal BMI cut-off for BF%-defined obesity using receiver operating characteristic curve analysis. BMI-defined obesity (≥25 kg/m(2)) was observed in 38.7% of men and 28.1% of women, with a high specificity (89%, men; 84%, women) but poor sensitivity (56%, men; 72% women) for BF%-defined obesity (25.2%, men; 31.1%, women). The optimal BMI cut-off (24.2 kg/m(2)) had 78% sensitivity and 71% specificity. BMI demonstrated limited diagnostic accuracy for adiposity in Korea. There was a -1.3 kg/m(2) difference in optimal BMI cut-offs between Korea and America, smaller than the 5-unit difference between the Western Pacific Regional Office and global World Health Organization obesity criteria.

The discriminatory performance of body mass index, waist circumference, waist-to-hip ratio and waist-to-height ratio for detection of metabolic syndrome and their optimal cutoffs among Iranian adults.

The superiority of either of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) for prediction of metabolic syndrome (MetS) is remained controversial in Asian population. The objective of this study was to compare the discriminative capacity of either of these measures in prediction of non-adipose components of MetS. In this population-based cross sectional study, 1000 representative samples of adults were recruited in Babol, northern Iran. The demographic, anthropometric measures and blood pressure were determined by standard method. Fasting plasma glucose (FPG), triglycerides (TG), total cholesterol (CHL), high density lipoprotein (HDL) cholesterol levels were measured with enzymatic methods by an auto analyzer. The presence of two or more any of four non-obese components were considered as MetS. The diagnostic accuracies (AUCs) of four different measures were rather similar. While AUC for BMI (AUC=0.684; 95% CI: 0.633, 0.736) slightly tended to be higher than that of WC (AUC=0.640; 95% CI: 0.587, 0.693) and WHtR (AUC=0.649; 95% CI: 0.596, 0.701) in men but the accuracy of WC (equivalently WHtR (AUC=0.708; 95% CI: 0.664, 0.751) is tended to be greater than that of BMI in women. The optimal cut-off value for WC was higher in men compared with women. Overall, BMI, WC and WHtR were significant predictors of MetS equally but WC (equivalently WHtR) was a better predictor than BMI and WHR in women. The optimal cut-offs of WC are lower compared with western population for men but not for women.

Diagnostic performance of body mass index to identify obesity as defined by body adiposity in children and adolescents: a systematic review and meta-analysis.

The ideal means of identifying obesity in children and adolescents has not been determined although body mass index (BMI) is the most widely used screening tool. We performed a systematic review and meta-analysis of studies assessing the diagnostic performance of BMI to detect adiposity in children up to 18 years. Data sources were EMBASE, MEDLINE, Cochrane, Database of Systematic Reviews Cochrane CENTRAL, Web of Science and SCOPUS up to March 2013. Studies providing measures of diagnostic performance of BMI and using body composition technique for body fat percentage measurement were included. Thirty-seven eligible studies that evaluated 53 521 patients, with mean age ranging from 4 to 18 years were included in the meta-analysis. Commonly used BMI cut-offs for obesity showed pooled sensitivity to detect high adiposity of 0.73 (confidence interval [CI] 0.67-0.79), specificity of 0.93 (CI 0.88-0.96) and diagnostic odds ratio of 36.93 (CI 20.75-65.71). Males had lower sensitivity. Moderate heterogeneity was observed (I(2) = 48%) explained in meta-regression by differences across studies in race, BMI cut-off, BMI reference criteria (Center for Disease Control vs. International Obesity Task Force) and reference standard method assessing adiposity. BMI has high specificity but low sensitivity to detect excess adiposity and fails to identify over a quarter of children with excess body fat percentage.

Validity of body mass index and waist circumference to detect excess fat mass in children aged 7–14 years

To evaluate the screening performance of body mass index (BMI) and waist circumference (WC) for excess adiposity. In addition, the diagnostic accuracy of cutoffs from different international and national reference systems based on BMI and WC was investigated. Data from 2132 Jena children aged 7-14 years conducted in 2005/2006 were analyzed. Receiver operating characteristic (ROC) curves were constructed to assess BMI and WC, as screening measures for excess adiposity (derived from skinfolds). Sensitivity, specificity and positive predictive values (PPVs) were calculated for two BMI-based classification systems (IOTF and German reference) and sample-based WC cutoffs. The BMI as well as the WC performed well in detecting excess fat mass, indicated by areas under the ROC curve (AUC) close to 1.0, with slightly greater AUCs for BMI than for WC in both sexes. The specificity of all reference systems was high for both sexes (95 to 98%). However, their sensitivities were low (53-67% in boys; 51-67% in girls). PPV were higher for the German reference and the sample-based WC cutoffs than for the IOTF reference, and higher in girls than in boys. The setting in which the reference system should be used is important for the selection of the reference system. The results support the use of the BMI-based references for monitoring in epidemiological studies. The sample-based cutoffs for WC should be refined for clinical use on national level.