Optimal Cut-off Values Of Body Mass Index Research Articles

The prevalence of obesity and relationship between obesity indicators and chronic diseases in Northern Shaanxi, China.

Obesity not only affects human health but also is an important risk factor for a variety of chronic diseases. Therefore, it is particularly important to analyse the epidemic trend of obesity and actively carry out the prevention and control of obesity in the population. A total of 4565 adults were selected by multi-stage stratified random sampling in Shenmu, Shaanxi Province, China. Univariate analysis was used to explore the epidemic characteristics of obesity in this region. Multivariate logistic regression was used to analyse the relationship between obesity and chronic diseases. Finally, the prediction efficiency of different obesity indexes was analysed by drawing receiver operator characteristic curves (ROC). All statistical analysis was completed by SPSS 26.0 software. The prevalence rates of overweight, obesity, and central obesity were 39.9%, 18.2%, and 48.0%, respectively. After adjusting for other confounding factors, multivariate logistic regression analysis showed that overweight and obesity were risk factors for hypertension, dyslipidaemia, and hyperuricaemia. Central obesity is a risk factor for dyslipidaemia and hyperuricaemia. High level of waist-to-height ratio (WHtR) was a risk factor for dyslipidaemia and hyperuricaemia (p < 0.05). Obesity-related indicators: body mass index (BMI), waist circumference (WC), and WHtR, are strongly correlated with the increased risk of chronic diseases in northern Shaanxi, China. The optimal BMI cut-off values for predicting hypertension, dyslipidaemia, and hyperuricaemia were 24.27, 24.04, and 25.54, respectively. The optimal WC cut-off values for predicting dyslipidaemia and hyperuricaemia were 84.5 and 90.5, and WHtR cut-off values were 0.52 and 0.54, respectively. The problem of overweight, obesity, and central obesity in adults is serious in northern Shaanxi, China. Obesity of all types will increase the risk of chronic diseases. Therefore, a variety of preventive and therapeutic measures should be adopted to curb obesity and reduce the incidence of related chronic diseases.

Nutrition and Health in Arab Adolescents (NaHAR): Study protocol for the determination of ethnic-specific body fat and anthropometric cut-offs to identify metabolic syndrome.

The prevalence of adolescent obesity in the Middle-East is considered among the highest in the world. Obesity in adolescents is associated with several cardiometabolic abnormalities, the constellation of which is referred to as the metabolic syndrome (MetS). This multi-country cross-sectional study aims to determine the optimal cut-off values for body fat (BF); body mass index (BMI) z-score; waist circumference (WC) percentile, and mid-upper arm circumference (MUAC) for the prediction of MetS among adolescents from Kingdom of Saudi-Arabia (KSA), Kuwait, Jordan, Lebanon and Syria. A secondary objective is to examine the validity of Bioelectrical Impendence Vector Analysis (BIVA) in estimating BF against the deuterium dilution technique (DDL). In each country, a sample of 210 adolescents will be recruited. Data collection will include demographics, socioeconomic, lifestyle and dietary data using a multi-component questionnaire; anthropometric measurements will be obtained and body composition will be assessed using the DDL and BIVA; blood pressure and biochemical assessment will be performed for the identification of the MetS. Receiver operating characteristic analyses will be undertaken to determine optimal cut-off values of BMI, WC, MUAC and BF in identifying those with MetS. Odds ratios (OR) and their respective 95% confidence interval (CI) for the association of the anthropometric measurements with MetS will be computed based on multiple logistic regression analysis models. The Bland and Altman approach will be adopted to compare BIVA against the reference DDL method for the determination of body composition parameters. This study responds to the need for ethnic-specific anthropometric cut-offs for the identification of excess adiposity and associated cardiometabolic risks in the adolescent population. The adoption of the generated cut-offs may assist policy makers, public health professionals and clinical practitioners in providing ethnic-specific preventive and curative strategies tailored to adolescents in the region.

OPTIMAL BMI CUT-OFF VALUES FOR PREDICTING DIABETES, HYPERTENSION AND HYPERCHOLESTEROLEMIA AMONG MALAYSIAN ADULTS’ POPULATION: REVISITING A DECADE OF OLD VALUES

Background: Body Mass Index (BMI) can be used to determine bodyweight categories. This study aimed to re-examine the previous optimal BMI cut-offs in identifying the Non-Communicable Diseases (NCDs) among the Malaysian adults’ population. Data were obtained from the National Health and Morbidity Survey (NHMS) 2019. Methods: It was a cross-sectional, population-based survey that employed a two-stage stratified random sampling design. A total of 10,472 adults aged 18 years and above participated in this survey throughout Malaysia, with the majority aged between 31 to 59 years. Results: The optimal BMI cut-off values for identifying diabetes, hypertension, hypercholesterolemia, and at least one NCD ranged from 22.92 to 24.81 kg/m2 for males. The highest optimal BMI cut-off value for at least one NCD in females was 26.29 kg/m2, while the lowest optimal BMI cut-off value was for hypercholesterolemia in females, which was 22.63 kg/m2. Our study has produced a more reliable and revised BMI cut-off point that can detect NCD at a lower BMI compared to available BMI classification. Conclusion: The findings highlight the importance of recognizing the issue of BMI and obesity to tackle NCD. A new set of modified BMI which is very useful for tertiary care, demonstrates the potential benefit of early detection and intervention in preventing morbidity and mortality. Hence, it would lessen the length and impact of the disease on a person’s quality of life and also reduce complications and lower the mortality rates of certain diseases because early treatment is often the most effective.

Assessment of a proposed BMI formula in predicting body fat percentage among Filipino young adults

Body mass index (BMI), while routinely used in evaluating adiposity, cannot distinguish between fat and lean mass, and thus can misclassify weight status particularly among athletic, physically active, and tall- and short-statured individuals, whose lean-to-fat ratios and body proportions vary considerably from average individuals. Believing that the traditional BMI formula divides weight by too much with short people and by too little with tall people, University of Oxford professor L. N. Trefethen proposed a modified formula in computing BMI. This study was conducted among a sample of Filipino young adults (n = 190) to assess the performance of the modified BMI formula against the traditional one in: (1) predicting body fat percentage (%BF) measured using bioelectric impedance analysis, and (2) diagnosing overweight/obesity. Using robust polynomial regression analysis (covariates: age, waist circumference, smoking history and alcohol intake), the BMI quadratic models had the highest adjusted R2 and the lowest AIC and BIC for both sexes compared to the linear models. The AuROCs of the traditional BMI were higher than those of the proposed BMI, albeit nonsignificant. In conclusion, both traditional and modified BMIs significantly predicted %BF, as well as adequately discriminated between %BF-defined normal and overweight-obese states using optimal BMI cutoff values.

Identification of the most appropriate existing anthropometric index for home-based obesity screening in children and adolescents

Home-based self-screening and monitoring for obesity is particularly valuable for the prevention and control of chronic diseases. This study aimed to identify an anthropometric index suitable for home-based obesity screening in children and adolescents. The design of this study is a cross-sectional study. A total of 14,042 students (6-17 years) from the Qibao Community, Minhang District, Shanghai, were studied in 2018. The percentage body fat (PBF), height, weight, waist circumference (WC) and hip circumference were measured. Body mass index (BMI), triponderal mass index (TMI), body adiposity index (BAI), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) were calculated. Partial correlation analysis was used to evaluate the relationships between these indices and PBF, and receiver operating characteristic (ROC) curves were used to evaluate their performance for obesity screening. BMI, TMI, WC and WHtR were found to strongly correlate with PBF (r≥0.830, all P<0.001). The optimal index for obesity screening in children (6-11 years) was BMI (area under the ROC curve [AUC]=0.980 for boys and 0.981 for girls) and in adolescents (12-17 years) was TIM (AUC=0.976 for boys and 0.945 for girls); however, the optimal cut-off values for BMI and TMI differed among the subgroups. The ROC curve analysis showed that WHtR had similar cut-off values in each subgroup (0.45 for boys of 6-11 years and 0.43 for the other subgroups), excellent performance in children (AUC>0.90) and good performance in adolescents (AUC=0.960 for girls and 0.878 for boys). Owing to its accuracy and stable cut-off value for defining obesity, WHtR should be recommended for home-based obesity screening in children and adolescents.

Optimal Cutoff Values for Anthropometric Adiposity Measures of Sri Lankan Adult Women

Anthropometric adiposity measures (AAMs) such as body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) are used to evaluate obesity status. Country-specific cutoff values of AAMs would provide more accurate estimation of obesity prevalence. This cross-sectional study was designed to determine the optimal cutoff values for AAMs, BMI, WC, hip circumference (HC), and WHR, of Sri Lankan adult women. The study was conducted in Galle, Sri Lanka, with 350 healthy community-dwelling middle-aged women aged 30–60 years, divided into two groups (Group A, n = 175 and Group B, n = 175). Total body fat percentage (TBFP) (kg) was measured with DXA. Body weight (kg), height (m), and WC and HC (cm) were measured. BMI (kg/m2) and WHR were calculated. Optimal cutoff values were determined by area under curve (AUC) in Receiver-Operating Characteristic (ROC) curve analysis using TBFP as the criterion at the TBFP level of 33% and 35% using the women in Group A. Then, the prevalence of obesity was determined in Group B while comparing the prevalence based on the cutoff values recommended by the World Health Organization (WHO) for Asians and the newly developed cutoff values for Sri Lankan women. Optimal cutoff values of AAMs which correspond to TBFP 33% are BMI, 24.5 kg/m2; WC, 80 cm; HC, 95 cm; and WHR, 0.83. TBFP 35% corresponds to the optimal cutoff values of BMI, 25.0 kg/m2; WC, 85 cm; HC, 100 cm; and WHR, 0.83. Prevalence of obesity (number, %) according to the WHO and newly defined cutoff values that correspond to TBFP 33% and 35% were as follows: BMI = 83 (47.4%), 98 (56.0%), 83 (47.4%); WC = 106 (60.6%), 106 (60.6%), 72 (41.1%); and WHR = 140 (80.0%), 106 (60.6%), 106 (60.6%). The observed cutoff values of BMI and WC in this study were within the ranges of those described by the WHO for Asian populations which correspond to the 33% and 35% TBFP levels, respectively. However, the WHR cutoff value of WHO (Asians) is lower when compared to the newly determined value for Sri Lankan females while overestimating the prevalence. More studies are needed to confirm these values before clinical use.

Comparison of anthropometric indices for the screening of nonalcoholic fatty liver disease in pre- and postmenopausal women.

Although it has been well-established that menopause causes a shift in body fat, there has been no study conducted yet to examine the best obesity parameters to predict the risk of nonalcoholic fatty liver disease (NAFLD) in this population. Thus, the aim of this study was to clarify the superiority among various obesity indices such as body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) for predicting NAFLD in pre- and postmenopausal women. This cross-sectional analysis included 620 healthy women (318 premenopausal and 302 postmenopausal women) between 20 and 80 years of age recruited from the Health Promotion Center of Korea University Guro Hospital. NAFLD was diagnosed by abdominal ultrasonography. In premenopausal women, there were no statistical differences in the area under the curve values among the three obesity indices, whereas, in postmenopausal women, the area under the curve value of WHR was significantly larger than those of either BMI (difference between area: 0.102, 95% confidence interval: 0.031, 0.173) or WC (difference between area: 0.064, 95% confidence interval: 0.018-0.109). Furthermore, in postmenopausal women, the combination of WHR with BMI or WC significantly increased predictive power of NAFLD when compared to using BMI or WC alone. The optimal cutoff values for BMI, WC, and WHR for detecting NAFLD were 23.9 kg/m, 69 cm, and 0.81 in premenopausal women and 22.9 kg/m, 74 cm, and 0.86 in postmenopausal women, respectively. In premenopausal women, BMI, WC, and WHR hold similar potential in predicting the risk of NAFLD, whereas, in postmenopausal women, WHR is the most useful discriminative indicator for NAFLD. Women's optimal cutoff values for NAFLD were different according to menopausal status.

Association between anthropometric indicators of obesity and cardiovascular risk factors among adults in Shanghai, China

BackgroundTo determine the optimal cut-off values and evaluate the associations of body mass index (BMI), waist circumference (WC) and waist-height ratio (WHtR) with cardiovascular disease (CVD) risk factors.MethodsA large-scale cross-sectional survey was conducted among 35,256 adults aged 20–74 years in Shanghai between June 2016 and December 2017. Receiver operating characteristic (ROC) analyses were conducted to assess the optimal cut-off anthropometric indices of CVD risk factors including hypertension, diabetes, dyslipidemia and hyperuricemia. Multivariate Logistic regression models were preformed to evaluate the odds ratio of CVD risk factors.ResultsThe area under the curve (AUC) of WHtR was significantly greater than that of BMI or WC in the prediction of hypertension and diabetes, and AUCs were higher in women than men. The optimal cut-off values of WHtR were approximately 0.51 in both sexes, while the cut-off values of BMI and WC were higher for men compared with women. The optimal cutoff values of BMI and WC varied greatly across different age groups, but the difference in WHtR was relatively slight. Among women, the optimal threshold of anthropometric indices appeared to increase with age for hypertension and diabetes. The odds ratio between anthropometric indices and CVD risk factors were attenuated with age. WHtR had the greatest odds ratio for CVD risk factors among adults under 60 years old except for women with hypertension, while among 60–74 years, BMI yielded the greatest odds ratio in terms of all CVD outcomes except for women with diabetes.ConclusionsWHtR had the best performance for discriminating hypertension and diabetes and potentially be served as a standard screening tool in public health. The associations between three anthropometric indices and CVD risk factors differed by sex and decreased with age. These findings indicated a need to develop age- and gender-specific difference and make effective strategies for primary prevention of CVDs.

Reference body mass index values and the prevalence of malnutrition according to the Global Leadership Initiative on Malnutrition criteria

The Global Leadership Initiative on Malnutrition (GLIM) released new criteria for diagnosing and grading malnutrition. This study aimed to investigate the optimal reference values of body mass index (BMI) for discriminating severe malnutrition according to the GLIM criteria, as well as the prevalence of GLIM-defined malnutrition in the clinical setting. This study included 6783 patients aged ≥40 years, who were admitted to an academic hospital. Of the 1987 patients who presented with low BMI in period 1, optimal BMI cut-off values were determined using receiver operating characteristic analyses against in-hospital mortality in younger (aged <70 years) and older age groups. Next, 4796 patients from period 2 were screened using a validated nutritional screening tool. Patients had their nutritional condition assessed after screenings were analyzed using the GLIM criteria, which included body weight changes, BMI, reduced muscle mass, nutritional intake, and disease burden. Additionally, patients diagnosed with malnutrition were classified as having moderate or severe malnutrition, according to the obtained BMI values from the period 1 data. The optimal cut-off BMI values were 17.0kg/m2 for younger patients and 17.8kg/m2 for older patients. Patients at risk of malnutrition included 14.5% and 42.0% of admitted younger and older patients in period 2, respectively. GLIM-defined malnutrition was diagnosed in 18.0% of all patients (10.6% and 25.7% in younger and older patients, respectively). After adapting the BMI cut-off values according to the period 1 results, 9.0% and 9.0% of all patients were diagnosed as having moderate and severe malnutrition, respectively. Patients with GLIM-defined malnutrition showed significantly higher in-hospital mortality compared to those without malnutrition. The Asian reference values of BMI to grade malnutrition severity according to the GLIM criteria, as well as the prevalence of GLIM-defined malnutrition were determined. These reference values will contribute to implementing the GLIM criteria in Asian populations.

Cut-off Value for Body Mass Index in Predicting Surgical Success in Patients with Lumbar Spinal Canal Stenosis.

Study DesignCase-control.PurposeTo determine optimal cut-off value for body mass index (BMI) in predicting surgical success in patients with lumbar spinal canal stenosis (LSCS).Overview of LiteratureBMI is an essential variable in the assessment of patients with LSCS.MethodsWe conducted a prospective study with obese and non-obese LSCS surgical patients and analyzed data on age, sex, duration of symptoms, walking distance, morphologic grade of stenosis, BMI, postoperative complications, and functional disability. Obesity was defined as BMI of ≥30 kg/m2. Patients completed the Oswestry Disability Index (ODI) questionnaire before surgery and 2 years after surgery. Surgical success was defined as ≥30% improvement from the baseline ODI score. Receiver operating characteristic (ROC) analysis was used to estimate the optimal cut-off values of BMI to predict surgical success. In addition, correlation was assessed between BMI and stenosis grade based on morphology as defined by Schizas and colleague in total, 189 patients were eligible to enter the study.ResultsMean age of patients was 61.5±9.6 years. Mean follow-up was 36±12 months. Most patients (88.4%) were classified with grades C (severe stenosis) and D (extreme stenosis). Post-surgical success was 85.7% at the 2-year follow-up. A weak correlation was observed between morphologic grade of stenosis and BMI. Rates of postoperative complications were similar between patients who were obese and those who were non-obese. Both cohorts had similar degree of improvement in the ODI at the 2-year follow-up. However, patients who were non-obese presented significantly higher surgical success than those who were obese. In ROC curve analysis, a cut-off value of ≤29.1 kg/m2 for BMI in patients with LSCS was suggestive of surgical success, with 81.1% sensitivity and 82.2% specificity (area under the curve, 0.857; 95% confidence interval, 0.788–0.927).ConclusionThis study showed that the BMI can be considered a parameter for predicting surgical success in patients with LSCS and can be useful in clinical practice.

Body mass index, waist circumference, and waist-to-height ratio for prediction of multiple metabolic risk factors in Chinese elderly population

The purpose of this study was to compare the predictive ability of five obesity indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHpR) and body adiposity index (BAI), to predict multiple non-adipose metabolic risk factors, including elevated blood pressure (BP), elevated fasting plasma glucose (FPG), elevated triglyceride (TG), reduced high-density lipoprotein cholesterol (HDL-C), elevated serum uric acid (SUA) and non-alcoholic fatty liver disease (NAFLD), in an elderly Chinese population. A total of 5685 elderly Chinese subjects (≥60 years) were recruited into our community-based cross-sectional study. Receiver operating characteristic curve (ROC) analyses were used to compare the predictive ability as well as determine the optimal cut-off values of the obesity indices for multiple metabolic risk factors. According to the areas under the receiver operating characteristic curve (AUC), BMI, WC and WHtR were able to similarly predict high metabolic risk in males (0.698 vs. 0.691 vs. 0.688), while in females, BMI and WC were able to similarly predict high metabolic risk (0.676 vs. 0.669). The optimal cut-off values of BMI, WC and WHtR in males were, respectively, 24.12 kg/m2, 83.5 cm and 0.51, while in females, the values were 23.53 kg/m2 and 77.5 cm.

Frequency of Prediabetes According to Optimal Cut-Points for Body Mass Index in Saudi Population

Background and Objective: The prevalence and incidence of prediabetes are increasing worldwide. Body mass index (BMI) cut-off for prediabetes can vary. The objective of this study is to identify the optimal BMI cut-off that is associated with prediabetes. Methods: For the present study, we analyzed participants who are equal to or older than 18 years old. A total of 5498 were selected to be enrolled for the present study. All patients were from the population of the primary health and diabetic Centers at King Fahad Armed Forces Hospital. Participants were defined as having prediabetes according to selfreport, clinical reports, use of antidiabetic agents and HbA1c (5.7-6.4). All data were collected by personal interview and on the basis of a review of electronic medical data. Weight (kg) and height (cm) were measured by physician and nurse interviewers and recorded. The optimal sensitivity and specificity using different BMI cut-off values to predict the presence of prediabetes were examined by receiver operating characteristic curve analysis. Results: Of the 5498 participants analyzed, 2049 (37.3%) were male and 3449 (62.7%) were female with female to male ratio 1.7:1. Age was 42.7 ± 15.8 (minimum 18 years and maximum 105 years ) and males were significantly older than females (45.3 ± 16.6 vs. 41.1 ± 15.1 respectively, p&lt;0.0001). BMI was 29.6 ± 6.9Vwhere females had higher BMI than males (30.1 ± 7.5 vs. 28.8 ± 5.5 respectively, p&lt;0.0001). Prediabetes was present in 579 (10.5%), 89 (15.4%) were male and 490 (84.6%) were female with female to male ratio 5.5:1. Diagnostic performance of BMI in detecting prediabetes using optimal BMI cut-off values based on the shortest distance in ROC curve showed BMI values ranged from 28.50 to 29.50 in total population, 27.50 to 28.50 in male and from 28.50 to 29.50 in female. The AUC was 0.560 (95% CI, 0.503- 0.617) in male and 0.517 (95% CI, 0.490-0.544) in female. The predictive value of BMI in detecting prediabetes using BMI cut-off values based on the lowest significant association between BMI and the risk factors from the logistic regression analysis showed that the risk of prediabetes was significantly increased at BMI values as low as 21 kg/m2 and has not been increased as BMI increased. Applying this criterion to identify the cut-off values resulted in improvements in sensitivity, false negative rate and worsening in specificity and false positive rate. Using these lower BMI cut-offs resulted in a very small false negative rate ranging from 0.07 to 0.09. A significant positive association for total population was observed with BMI values starting at 21 kg/m2 and non significant association with BMI values for both genders. Conclusion: The diagnostic usefulness of BMI alone in defining obesity as risk for prediabetes is limited among men and women Saudi adults.

Frequency of Metabolic Syndrome According to Optimal CutPoints for Body Mass Index in Saudi Population

Background and Objective: The prevalence of metabolic syndrome (MetS) are increasing worldwide. Body mass index (BMI) cut-off for MetS can vary. The objective of this study is to identify the optimal BMI cut-off that is associated with MetS. Methods: For the present study, we analyzed participants who are equal to or older than 18 years old. A total of 5498 were analyzed at the present study. Patients were recruited from the population of the primary health care department at King Fahad Armed Forces Hospital. Metabolic risk factors were defined using the 2006 International Diabetes Federation criteria. We collected data personal interview and electronic medical chart review. Physician and nurse interviewers measured the weight (kg) and height (cm) of the participants and BMI was calculated. Receiver operating characteristic curve analysis was used to obtain the optimal sensitivity and specificity using different BMI cut-off values to predict the presence of diabetes. Results: Of the 5498 participants analyzed, 2049 (37.3%) were male and 3449 (62.7%) were female with female to male ratio 1.7:1. Age was 42.7 ± 15.8 (minimum 18 years and maximum 105 years). MetS was present in 1967 cases (35.8%) where 673 cases (38.8%) were male and 1204 cases (61.2%) were female with female to male ratio 1.6:1, P=0.08. Males were significantly older than females in MetS patients (45.5±12.8 vs. 36.1±13.3 respectively, p&lt;0.0001). BMI was significantly higher in MetS patients (31.9±6.6 vs. 28.3±6.7 respectively, p&lt;0.0001). Optimal BMI cut-off values ranged from 28.50 to 29.50 in total population, 27.50 to 28.50 in male and from 28.50 to 29.50 in female. The AUC was 0.615 (95% CI, 0.590-0.639) in male and 0.686 (95% CI, 0.668-0.704) in female. Regression analysis showed that the risk of MetS was significantly increased at BMI values as low as ≤15.0 kg/m2 and increased progressively as BMI increased for both genders. Applying this criterion to identify the cut-off values resulted in improvements in sensitivity, false negative rate and worsening in specificity and false positive rate. A very small false negative rate ranging from 0.001 to 0.005 resulted by using these lower BMI cut-offs. Conclusion: The diagnostic usefulness of BMI alone in defining obesity in patients with MetS is limited among men and women Saudi adults.

Body mass index and contralateral ratio predict outcome following unilateral adrenalectomy in primary aldosteronism.

The effect of unilateral adrenalectomy on blood pressure (BP) outcome in primary aldosteronism (PA) is diverse. Therefore, we sought to investigate the preoperative factors contributing to postoperative BP outcome. Data for 96 PA patients who underwent unilateral adrenalectomy at our institution from January 2000 to February 2015 were retrospectively collected. Based on postoperative BP after a 12-month follow-up period, the patients were categorized into two groups: cured (C) (<140/90 mm Hg with no antihypertensive drug) and not cured (NC) (if not normotensive). Patient demographics, blood and urine data, data of loading tests and adrenal vein sampling were evaluated. In all, 46 patients were categorized as C and 50 patients as NC. There were significantly more males in the NC group. Age, body mass index (BMI), number of antihypertensive drugs prescribed, serum uric acid concentration and contralateral ratio (CR) after adrenocorticotropic hormone stimulation were significantly higher in the NC group. In the multivariate model, BMI and CR significantly correlated with resolution outcome. The optimal cutoff values were 23.3 kg m-2 for BMI and 0.5 for CR, and when both parameters were used as predictors, the most optimal cutoff values for BMI and CR were 25.2 kg m-2 and 0.1, respectively. BMI and CR significantly correlated with BP outcome after adrenalectomy. To our knowledge, this is the first report to show that in addition to BMI, CR is a factor in postoperative BP outcome and to determine the optimal cutoff values of BMI and CR and calculate their sensitivities and specificities.

Obesity Markers as Predictors for Colorectal Neoplasia.

BackgroundThe goal of this study was to determine the relations between the risk of colorectal neoplasia and obesity markers: body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR).MethodsThe subjects who underwent screening colonoscopies at a Kyungpook National University Hospital in Daegu from July to December 2010 were enrolled. We defined colorectal neoplasia as tubular adenoma, advanced adenoma, or cancer. We performed a logistic regression analysis to investigate the correlations between obesity and colorectal neoplasia and a receiver operating characteristic (ROC) curve analysis to determine the cut-off obesity marker values for detecting colorectal neoplasia.ResultsAmong the total of 268 subjects, 83 (31.0%) subjects had colorectal neoplasia. Subjects with neoplasia had higher BMI, WC, and WHtR than the subjects without any neoplasia. The adjusted odds ratio (aOR) of WHtR ≥0.5 with the association of neoplasia was 1.927 (95% confidence interval [CI], 1.041–3.569) in the total subjects. In women, the obesity markers of WC ≥85 cm (aOR 4.611; 95% CI, 10.166–18.240) and WHtR ≥0.5 (aOR 1.747; 95% CI, 1.149–19.617) were significantly related to neoplasia; however, there was no significant result in men. The ROC analysis showed the optimal cut-off values of BMI as >23.14 kg/m2 (P=0.002), WHtR as >0.50 (P<0.001), and WC as>82.5 cm (P=0.650) in men and >77 cm in women (P<0.001).ConclusionObesity is significantly associated with the increased risk of colorectal neoplasia. WC and WHtR have more significant correlations with neoplasia; thus, obese people should undergo regular colonoscopy screenings to detect colorectal neoplasia.

Ethnic and sex-specific cut-off values for adult obesity in the Suriname Health Study

Sex-specific body mass index (BMI) and waist circumference (WC) cut-off values have been validated for a limited number of ethnic groups. We aimed to derive these cut-off values for Amerindians, Creoles, Hindustani, Javanese, Maroons and Mixed living in Suriname. Data from individuals aged 20-65, in the Suriname Health Study was used to derive optimal cut-off values for BMI and WC for the prediction of hypertension (n=4910) and cardio-metabolic risk (n=2924). Results from the analysis with Receiver Operating Curves were calculated and compared these with recommended values. The area under the ROC curve was consistently higher for WC compared to BMI among Creoles, Hindustani, Maroons and Mixed. The BMI cut-off values ranged from 24.8kg/m2 for Creole men and 26.9kg/m2 for Maroon women to 28.4kg/m2 and 30.2kg/m2 for Amerindian men and women, respectively. The WC cut-off values ranged from 80.7cm for Maroon men, 86.7cm for Javanese women to 90.8cm for Hindustani men and 95.7cm for Amerindian women. Optimal BMI cut-off values approximated Asian cut-off values from the World Health Organization whilst those of WC for men approximated and for women exceeded cut-off values from the International Diabetes Federation. In most ethnic groups, we found better discriminatory power for WC compared to BMI in the relation with cardiovascular risk factors. The estimated BMI and WC cut-off values differed between ethnic groups. Further studies are needed to identify cut-off values related to the future risk of cardiovascular disease and mortality.

Risk Factors for Wound Complications After Direct Anterior Approach Hip Arthroplasty

Previous studies have suggested that wound complications may be higher after direct anterior approach (DAA) hip arthroplasty, but, specific risk factors have not been closely examined. We conducted a retrospective case-control study of 651 consecutive DAA hip arthroplasty surgeries performed by 2 surgeons over a 3-year period. Outcome measures included any postoperative wound problem (including prolonged drainage, wound dehiscence, wound necrosis, suture granuloma, and superficial infection) requiring additional intervention or reoperation. Univariate odds ratios (ORs) were calculated, and multivariate logistic regression analysis was performed to determine risk correlation. Receiver operator characteristic (ROC) curves were created to determine disease predictability. A total of 75 patients (11.5%) experienced wound complications requiring additional intervention, of which, 13 (1.9%) required reoperation. Multivariate regression analysis found that development of wound complications was significantly and independently associated with body mass index (BMI) 30-35 kg/m2 (OR 2.05; 95% confidence interval [CI] 1.08-3.88), BMI 35-40 kg/m2 (OR 3.40; 95% CI 1.42-8.26), BMI > 40 kg/m2 (OR 7.28; 95% CI 2.55-20.78), and diabetes mellitus (OR 2.97; 95% CI 1.46-6.07). Reoperation for wound complication was significantly associated with BMI > 40 kg/m2 (OR 5.68; 95% CI 1.17-27.48) and diabetes mellitus (OR 13.08; 95% CI 3.97-43.11). Optimal cutoff values for BMI were found through receiver operator characteristic curve analysis to be 28.0 kg/m2 for development of wound complications and 28.2 kg/m2 for reoperation for wound complications. Obesity and diabetes mellitus are significantly associated with postoperative wound-healing complications and the need for reoperation for these wound complications after DAA hip arthroplasty.

Predictive value of body mass index and waist circumference for metabolic syndrome in 6–12‐year‐olds

To determine the predictive value of body mass index (BMI) and waist circumference (WC) and their optimal cut-off points for metabolic syndrome (MetS), and also the incidence of MetS. This study included 888 children, aged 6-12 years, who were followed for a mean of 6.6 years. BMI, WC and their optimal cut-off points to predict MetS were investigated. The cumulative incidence of MetS was 10.7%. The adjusted ORs for age, sex and family history to predict MetS for BMI and WC z-scores were 2.6 (95% CI, 2.0-3.5) and 2.6 (95% CI, 1.9-3.5), respectively. In their correspondent models, area under the receiver operating characteristic (ROC) curve was 0.73 (95% CI, 0.68-0.79) for BMI z-scores and 0.72 (95% CI, 0.67-0.78) for WC z-scores with no statistically significant difference. The optimal cut-off values for BMI were 16.5 kg/m(2) for boys and 16.3 kg/m(2) for girls and those for WC were 57.5 cm for boys and 56.5 cm for girls. Our findings suggest that both BMI and WC have the same power to predict MetS and also children with higher BMI or WC are more susceptible to MetS. Moreover, a high incidence of MetS in children highlights the importance of interventional strategies during early childhood.

Optimal cut-off levels of body mass index and waist circumference in relation to each component of metabolic syndrome (MetS) and the number of MetS component

There is an ethnic difference of obesity index to diagnose metabolic syndrome. The authors explored the optimal cut-off levels for body mass index (BMI) and waist circumference (WC) in relation to each component of metabolic syndrome. Receiver operating characteristics (ROC) analysis was used to determine the optimal cut-off levels for each component of metabolic syndrome. This study included 4572 workers aged 42.5±9.9 years. The optimal BMI cut-off values for diabetes mellitus, hypertension or dyslipidemia varied from 23.0 to 24.3 kg/m(2). As for WC, the optimal cut-off values varied from 83.0 to 83.7 cm. The optimal BMI cut-off values relating with one to three components of metabolic syndrome varied from 23.2 to 25.3 kg/m(2). As for WC, the optimal cut-off values varied from 83.0 to 85.0 cm. Pair-wise comparison of ROC curves showed that WC has an advantage in relation to metabolic syndrome and its components compared with BMI. By logistic regression analysis, odds ratios of obesity indices for hypertension, dyslipidemia or the number of metabolic component were all significantly increased. As for diabetes mellitus, odds ratios of BMI ≥25 and WC ≥85 significantly increased, respectively. Japanese criteria of obesity in metabolic syndrome in man may be appropriate for diabetes mellitus. Ethnic difference in criteria of obesity in Asian metabolic syndrome exists, and mutual comparisons in the prevalence of metabolic syndrome have a difficulty to conduct.

New Body Mass Index Criteria of Central Obesity for Male Japanese

In recent years, intra-abdominal visceral fat leads to obesity-related complications. A simple indicator that reflects the mass of visceral fat is also needed to enable practical screening of patients. The present study was designed to establish new body mass index (BMI) criteria of central obesity for male Japanese. The subjects were 516 men aged from 19 to 80 years old who were examined at the physical examination center in the regular health check conducted by their company. Correlations between visceral fat area (VFA) or subcutaneous fat area (SFA) and BMI in the subjects were investigated. Receiver Operating Characteristics (ROC) curve was used to find out the optimal cut-off values of BMI to predict central obesity. We compared the percentile ranks corresponding to VFA of 100 cm2, BMI of 25 kg/m2 and new BMI criteria to check to see whether the present BMI criteria classify correctly Japanese men as central obesity. Further evidence for the effectiveness of BMI for VFA is needed. The correlation coefficient between VFA or SFA and BMI was 0.59 or 0.67, respectively. At the cut-off for BMI that maximized sensitivity and specificity for predicting central obesity was 24 kg/m2. Moreover, the percentile value corresponding to VFA of 100 cm2, BMI of 24 kg/m2, and BMI of 25 kg/m2 was the 53, 50 and 61 percentile, respectively. It is necessary to lower a cut-off point for central obesity from BMI of 25 kg/m2 to 24 kg/m2.