The predictive power of conventional and novel obesity indices in identifying metabolic syndrome among the southern Iranian populations: findings from PERSIAN cohort study.

Metabolic syndrome (MetS) contributes to an increased risk of cardiovascular diseases. Traditional metrics like body mass index (BMI) have limitations in discerning fat distribution. The purpose of this study was to evaluate the diagnostic accuracy of traditional and novel anthropometric indices in metabolic syndrome and its components in the south coast of Iran. In this cross-sectional study, 2694 adults aged 35 to 70 were included. Comprehensive anthropometric and biochemical data were collected and analyzed. There were eight anthropometric indices evaluated in this study, including a body shape index (ABSI), body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), body roundness index (BRI), abdominal volume index (AVI), weight-adjusted waist index (WWI) and waist-height ratio (WHtR). WHtR (AUC: 0.766 for males, 0.799 for females), BRI (AUC: 0.766 for males, 0.799 for females), and AVI (AUC: 0.769 for males, 0.793 for females) were the best predictors of MetS. ABSI had the weakest correlation with metabolic variables. AVI, WHtR, BRI, and WHR were superior to other measures as anthropometric indexes for determining MetS and its components. The study contributes valuable insights into the utility of traditional and novel metrics in clinical practice, highlighting the need for standardized diagnostic approaches and further research in diverse populations.

Rahimi A ，Rafati S ，Azarbad A ，Safa H ，Shahmoradi M ，Asl AS ，Niazi M ，Ahi S ，Tabasi S ，Kheirandish M ... -  《-》

Utility of Anthropometric Indexes for Detecting Metabolic Syndrome in Resource-Limited Regions of Northwestern China: Cross-Sectional Study.

Anthropometric indexes offer a practical approach to identifying metabolic syndrome (MetS) and its components. However, there is a scarcity of research on anthropometric indexes tailored to predict MetS in populations from resource-limited regions. This study aimed to examine the association between 8 easy-to-collect anthropometric indexes and MetS, and determine the most appropriate indexes to identify the presence of MetS for adults in resource-limited areas. A total of 10,520 participants aged 18-85 years from Ningxia Hui Autonomous Region, China, were included in this cross-sectional study. Participants were recruited through a stratified sampling approach from January 1, 2020, to December 31, 2021. MetS was defined using the International Diabetes Federation (IDF) criteria. Eight anthropometric indexes were examined, including BMI, waist-to-height ratio (WHtR), weight-adjusted waist index (WWI), conicity index, a body shape index (ABSI), lipid accumulation products (LAP), visceral obesity index (VAI), and the triglyceride-glucose (TyG) index. Logistic regression analysis and restricted cubic splines (RCSs) were applied to identify the association between the anthropometric indexes. The receiver operating characteristic curve and the area under the curve (AUC) were analyzed to identify and compare the discriminative power of anthropometric indexes in identifying MetS. The Youden index was used to determine a range of optimal diagnostic thresholds. Logistic regression analysis was applied to identify the association between the anthropometric indexes. A total of 3324 (31.60%) participants were diagnosed with MetS. After adjusting for age, ethnicity, current residence, education level, habitual alcohol consumption, and tobacco use, all the 8 indexes were positively correlated with the risks of MetS (P<.05). LAP presented the highest adjusted odds ratios (adjOR 35.69, 95% CI 34.59-36.80), followed by WHtR (adjOR 29.27, 95% CI 28.00-30.55), conicity index (adjOR 11.58, 95% CI 10.95-12.22), TyG index (adjOR 5.53, 95% CI 5.07-6.04), BMI (adjOR 3.88, 95% CI 3.71-4.05), WWI (adjOR 3.23, 95% CI 3.02-3.46), VAI (adjOR 2.11, 95% CI 2.02-2.20), and ABSI (adjOR 1.71, 95% CI 1.62-1.80). Significantly nonlinear associations between the 8 indexes and the risk of MetS (all Pnonlinear<.001) were observed in the RCSs. WHtR was the strongest predictor of MetS for males (AUC 0.91, 95% CI 0.90-0.92; optimal cutoff 0.53). LAP were the strongest predictor of MetS for females (AUC 0.89, 95% CI 0.89-0.90; optimal cutoff 28.67). Statistical differences were present between WHtR and all other 7 anthropometric indexes among males and overall (all P<.05). In females, the AUC values between LAP and BMI, WWI, ABSI, conicity index, VAI, and TyG index were significantly different (P<.001). No statistical difference was observed between LAP and WHtR among females. According to 8 anthropometric and lipid-related indices, it is suggested that WHtR and LAP are the most appropriate indexes for identifying the presence of MetS in resource-limited areas.

Yang D ，Ma L ，Cheng Y ，Shi H ，Liu Y ，Shi C ... -  《JMIR Public Health and Surveillance》

Prediction of Hypertension Based on Anthropometric Parameters in Adolescents in Eastern Sudan: A Community-Based Study.

Anthropometric measures such as body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) are associated with elevated blood pressure and hypertension in adolescents. We aimed to assess these anthropometric measures (BMI, WC, and WHtR) and examine their association with hypertension in adolescents. Adolescents' BMI, mid-upper arm circumference (MUAC), WC, body roundness index (BRI), waist-to-hip ratio (WHR), WHtR, and a body shape index(ABSI) values were measured and calculated. Receiver operating characteristic curves (ROCs) were created to determine the discriminatory capacities of these anthropometric parameters for hypertension. The cutoff points for these parameters were identified using Youden's index. A total of 401 adolescents [186(46.4%) were females and 215 (53.6%) were males] were included. The median (interquartile range, IQR) age was 14.0 (12.1‒16.2) years. Thirty-six adolescents were found to have hypertension. Among the anthropometric parameters, MUAC (area under the curve (AUC] = 0.76, at the cutoff 26.1 cm, sensitivity = 61.0, specificity = 83.0), WC (AUC= 0.74, at the cutoff 70.3 cm, sensitivity = 66.7, specificity = 77.0), BMI (AUC= 0.73, at the cutoff 17.4 kg/m2, sensitivity = 83.3, specificity = 59.0), and hip circumference (HC) (AUC= 0.72, at the cutoff 91.0 cm, sensitivity = 55.6, specificity = 83.0) performed fairly in detecting hypertension in adolescents, whereas WHR, WHtR, ABSI, and BRI performed poorly. A univariate analysis showed that, except for WHR, all anthropometric parameters (BMI, MUAC, WC, HC, WHtR, BRI, and ABSI) were associated with hypertension. However, in a multivariate analysis, only increased MUAC (adjusted odds ratio [AOR]= 1.24, 95% CI= 1.03‒1.50) was associated with hypertension. This study showed that MUAC, WC, BMI, and HC could be used to detect hypertension in adolescents. Other parameters,namelyWHR, WHtR, ABSI, and BRI, perform poorly in this regard. Larger studies are needed in the future.

Saad AH ，Hassan AA ，Al-Nafeesah A ，AlEed A ，Adam I ... -  《-》

Association of "a body shape index" with the risk of developing colorectal cancer in U.S. patients with metabolic syndrome: evidence from the NHANES 1999-2018.

Colorectal cancer (CRC) is the third most common cancer worldwide and presents a significant challenge to public health. Metabolic syndrome (MetS) is a condition that is predominantly characterized by abdominal obesity and metabolic abnormalities such as hypertension, hyperglycemia, and hyperlipidemia, and it is one of the critical risk factors for CRC. Traditional anthropometric measures have limitations in accurately assessing the risk associated with abdominal obesity. This study aimed to investigate the association between "A Body Shape Index" (ABSI) and the risk of developing CRC among individuals with MetS utilizing data from the National Health and Nutrition Examination Survey (NHANES). This cross-sectional study conducted a statistical analysis of all adult participants who met the diagnostic criteria for MetS in the NHANES data from 1999 to 2018. The ABSI was calculated to quantify abdominal obesity. ABSI is derived from a formula that incorporates waist circumference (WC), body mass index (BMI), and height, and is calculated as ABSI = WC / (BMI^(2/3) × Height^(1/2)). Multivariate logistic regression modeling was used to examine the independent association between ABSI and CRC incidence. Receiver Operating Characteristic (ROC) curves were employed to analyze the ability of ABSI compared to traditional metrics in identifying CRC risk. This study involved 16,018 MetS patients with a mean age of 51.8 years, of whom 50.3% were male and 49.7% were female. Logistic regression adjusted for confounders revealed a significant association between an elevated ABSI and an increased risk of developing CRC (odds ratio (OR): 1.433, 95% confidence interval (CI): 1.116 to 1.841; P = 0.005). ROC analyses confirmed that the predictive accuracy of the ABSI for the risk of developing CRC area under the curve (AUC): (0.668, 95% CI: 0.624 to 0.713) surpassed that of traditional measurement methods. Among individuals with MetS, the ABSI is linked to an elevated risk of developing CRC. Compared with traditional anthropometric indices, the ABSI is a superior predictive marker for the risk of developing CRC.

Kurexi A ，Peng J ，Yao J ，Wang L ，Wang Q ... -  《BMC GASTROENTEROLOGY》

Predictive ability of anthropometric indices for risk of developing metabolic syndrome: a cross-sectional study.

Chaquila JA ，Ramirez-Jeri G ，Miranda-Torvisco F ，Baquerizo-Sedano L ，Aparco JP ... -  《-》