Fat-to-muscle Ratio: A New Anthropometric Indicator for Predicting Metabolic Syndrome in the Han and Bouyei Populations from Guizhou Province, China / 生物医学与环境科学（英文）

<p><b>OBJECTIVE</b>To investigate the prevalence and possible factors influencing metabolic syndrome in people from Guizhou Province and to explore the predictive value of the fat-to-muscle ratio in diagnosing metabolic syndrome.</p><p><b>METHODS</b>A multistage stratified sampling method was used in this cross-sectional study of 20-80 years old Han and Bouyei populations from Guizhou Province, southwestern China, from October-December 2012. The study included 4,553 cases of metabolic syndrome, that was defined according to 2005 International Diabetes Federation criteria. The receiver operating characteristic curve was used for determining the sensitivity, specificity, and predictive ability of the fat-to-muscle ratio for the diagnosis of metabolic syndrome.</p><p><b>RESULTS</b>The age-standardized prevalence of metabolic syndrome was 11.38% (men: 9.76%; women: 12.72%) for Han and 4.78% (men: 4.43%; women: 5.30%) for Bouyei populations. In Guizhou Province, the cut-off value for the men fat-to-muscle ratio was 0.34, the area under the curve was 0.95, and the sensitivity and specificity were 0.94 and 0.85, respectively. The cut-off value for the women fat-to-muscle ratio was 0.55, the area under the curve was 0.91, and the sensitivity and specificity were 0.93 and 0.79, respectively.</p><p><b>CONCLUSION</b>The fat-to-muscle ratio is highly predictive of metabolic syndrome in Guizhou Province, and a useful reference indicator.</p>

Indicadores antropométricos na predição de síndrome metabólica em crianças e adolescentes: um estudo de base populacional / Anthropometric indicators for prediction of metabolic syndrome in children and adolescents: a population-based study

Avaliar a capacidade dos indicadores antropométricos e pontos de corte na predição da síndrome metabólica (SM) em crianças e adolescentes. Métodos: estudo transversal, envolvendo amostra probabilística de 879 crianças e adolescentes de ambos os sexos. Dados metabólicos, antropométricos e sociodemográficos foram coletados. Para diagnóstico da SM, foi utilizada a definição modificada do National Cholesterol Education Program's Adult Treatment Panel III (NCEP-ATP III). A capacidade dos indicadores antropométricos na predição do SM foi avaliada por meio da curva Receiver Operating Characteristic (ROC). Resultados: a prevalência de SM foi de 6,6 por cento. Na predição da SM, a área sob a curva ROC foi de 0,79 (0,72; 0,85) para índice de massa corporal (IMC), de 0,79 (0,73; 0,85) para circunferência da cintura (CC) e de 0,83 (0,78; 0,89) para circunferência da cintura corrigida pela estatura (RCE). O ponto de corte identificado para RCE na predição da SM foi de 0,448 (ambos os gêneros). Conclusões: todos os indicadores antropométricos utilizados, com pequena superioridade da RCE, foram bons preditores da SM. O ponto de corte identificado para RCE na predição da SM aproxima-se daquele proposto por alguns autores como universal. Sugere-se o uso deste índice dado a sua simples operacionalidade em estudos clínicos e epidemiológicos como preditor da SM...

Objectives: to assess the capacity of anthropometric indicators to predict metabolic syndrome in children and adolescents and to establish cut-off points. Methods: a cross-sectional study was carried out with a probabilistic sample of 879 children and adolescents of both sexes. Metabolic, anthropometric and socio-demographic data were gathered. Diagnosis of metabolic syndrome was carried out using the modified definition of the National Cholesterol Education Program 's Adult Treatment Panel III (NCEP-ATPIII). The capacity of anthropometric indicators to predict metabolic syndrome was assessed using the Receiver Operating Characteristic (ROC) curve. Results: the prevalence of metabolic syndrome was 6.6 percent. For prediction of metabolic syndrome, the area under the ROC curve was 0. 79 (0. 72; 0.85) for body mass index, 0. 79 (0.73; 0.85) for waist circumference and 0.83 (0.78; 0.89) for waist circumference corrected for height. The cut-off point identified for waist circumference corrected for height for prediction of metabolic syndrome was 0.448 (for both sexes). Conclusions: all anthropometric indicators used were good predictors of metabolic syndrome, with slightly better results for waist circumference corrected for height. The cut-off point identified for waist circumference corrected for height for prediction of metabolic syndrome was similar to the standard proposed by other authors. It is suggested that this indicator be used in clinical and epidemiological studies as a predictor of metabolic syndrome, since it is simple to measure...

The Usefulness of Hip to Thigh Ratio as an Anthropometric Indicator for the Incidence of Hip Fracture

PURPOSE: To compare anthropometric indicators around the hip between osteoporotic fracture group and control group. MATERIALS AND METHODS: Thirty patients for osteoporotic hip fracture and the same number of patients for spine fracture who admitted our institute from November 2006 to March 2007 were matched with control patients without osteoporotic fracture. The waist circumference (WC), hip circumference (HC), thigh circumference (TC), and height were measured. From these measurements, waist to hip ratio (WHR), waist to thigh ratio (WTR), hip to thigh ratio (HTR), waist to height ratio (WHtR), hip to height ratio (HHtR), and thigh to height ratio (THtR) were calculated. All these indicators were compared between hip fracture and control group, and between spine fracture and control group. RESULTS: Comparison between spine fracture and control group showed that the WC, WHR, WHtR were statistically significant, but all indicators failed to show accuracy in the ROC analysis. Comparison between hip fracture and control group demonstrated the TC, WTR, HTR, WHtR, HHtR, THtR were statistically significant. However, only the HTR showed fair accuracy in the ROC analysis. The area under the curve (AUC) of the HTR was 0.75 (95% confidence interval, 0.62 to 0.87) (p=0.001). CONCLUSION: The HTR was fairly accurate in predicting the incidence of hip fracture compared with any other anthropometric indicators. Therefore, we can consider that the HTR has clinical usefulness.

Some anthropometric indicator in puplils at Sapa and Yen Binh regions

This cross-sectional study involved 339 students aged 12-15 at 2 boarding schools in Sapa and Yen Binh, determined height, weight, and BMI. Results: there weren’t significant differences between the weights (Sapa’s students: 34.38 kg, and Yen Binh’s students: 33.31 kg), and the average heights of students in 2 regions (p>0.05); but BMI of Sapa’s students is higher than Yen Binh’s students (17.04 vs 16.38, p<0.05)