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Novel anthropometric indices for predicting type 2 diabetes mellitus.
This study aimed to compare anthropometric indices to predict type 2 diabetes mellitus (T2DM) among first-degree relatives of diabetic patients in the Iranian community.
In this study, information on 3483 first-degree relatives (FDRs) of diabetic patients was extracted from the database of the Endocrinology and Metabolism Research Center of Isfahan University of Medical Sciences. Overall, 2082 FDRs were included in the analyses. A logistic regression model was used to evaluate the association between anthropometric indices and the odds of having diabetes. Furthermore, a receiver operating characteristic (ROC) curve was applied to estimate the optimal cutoff point based on the sensitivity and specificity of each index. In addition, the indices were compared based on the area under the curve (AUC).
The overall prevalence of diabetes was 15.3%. The optimal cutoff points for anthropometric measures among men were 25.09 for body mass index (BMI) (AUC = 0.573), 0.52 for waist-to-height ratio (WHtR) (AUC = 0.648), 0.91 for waist-to-hip ratio (WHR) (AUC = 0.654), 0.08 for a body shape index (ABSI) (AUC = 0.599), 3.92 for body roundness index (BRI) (AUC = 0.648), 27.27 for body adiposity index (BAI) (AUC = 0.590), and 8 for visceral adiposity index (VAI) (AUC = 0.596). The optimal cutoff points for anthropometric indices were 28.75 for BMI (AUC = 0.610), 0.55 for the WHtR (AUC = 0.685), 0.80 for the WHR (AUC = 0.687), 0.07 for the ABSI (AUC = 0.669), 4.34 for the BRI (AUC = 0.685), 39.95 for the BAI (AUC = 0.583), and 6.15 for the VAI (AUC = 0.658). The WHR, WHTR, and BRI were revealed to have fair AUC values and were relatively greater than the other indices for both men and women. Furthermore, in women, the ABSI and VAI also had fair AUCs. However, BMI and the BAI had the lowest AUC values among the indices in both sexes.
The WHtR, BRI, VAI, and WHR outperformed other anthropometric indices in predicting T2DM in first-degree relatives (FDRs) of diabetic patients. However, further investigations in different populations may need to be implemented to justify their widespread adoption in clinical practice.
Sadeghi E
,Khodadadiyan A
,Hosseini SA
,Hosseini SM
,Aminorroaya A
,Amini M
,Javadi S
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《BMC PUBLIC HEALTH》
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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
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《JMIR Public Health and Surveillance》
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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
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《-》
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Using different anthropometric indices of obesity as predictors for type 2 diabetes mellitus in older adults.
There is some evidence that anthropometric measurements can be associated with the risk of type 2 diabetes mellitus (T2DM). Nevertheless, there is no comprehensive consensus on which anthropometric index is the best for evaluating the risk and predicting T2DM, especially in older adults. For this reason, we compared the performance of six indices for detecting T2DM in a population of Colombian older adults.
We conducted a cross-sectional study of 3453 older adults (≥60 years old; 2023 women), analysing demographic characteristics, biochemical markers, and anthropometric indices including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), adiposity index (VAI), conicity index (C-Index), and body roundness index (BRI). T2DM was defined as fasting plasma glucose ≥126 mg/dl (≥7.0 mmol/l). All the anthropometric indices correlated significantly with the presence of T2DM. An analysis of the receiver operating characteristic curve showed that for men the VAI (AUC = 0.71; moderate ES (0.78); OR = 4.13), BMI (AUC = 0.68; moderate ES (0.68); OR = 3.38), and WC (AUC = 0.68; moderate ES (0.68); OR = 3.38) are the best predictors for identifying T2DM. For women, however, the WC (AUC = 0.63; ES = 0.46; OR = 2.34) and C-Index (AUC = 0.63; ES = 0.46; OR = 2.34) were better indicators for predicting T2DM. Cut-off points for all the anthropometric indices were provided.
In summary, the VAI, BMI, and WC in men, and WC and the C-Index in women have a moderate discriminating power for detecting T2DM in Colombian older adults, evidencing that these anthropometric indices are suitable screening tools for use in the elderly.
Ramírez-Vélez R
,Pérez-Sousa MA
,González-Jiménez E
,Correa-Rodríguez M
,Calderón-González JC
,Dávila-Grisales A
,Schmidt-RioValle J
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《-》
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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
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