The relationship between waist to stature ratio and hypertension, diabetes, and dyslipidemia in Qingdao / 中华内科杂志

ObjectiveTo evaluate the relationship between waist to stature ratio (WSR) and hypertension,diabetes,dyslipidemia in Qingdao. MethodsData were collected from a 2001 - 2007 Qingdao area diabetes survey,population-based cross-sectional study,and 30 712 Chinese adults aged ＞ 18 years old were enrolled.Correlation analysis of BMI,WSR,hip circumference,waist circumference,waist to hip ratio (WHR) with blood glucose,blood pressure,blood lipid were conducted.ROC curve analysis in diabetes,bypertension,dyslipidemia and multivariate logistic regression analysis were also conducted.ResultsAnthropometric indicators were related with hypertension,diabetes and dyslipidemia in both men and women.Comparing with other anthropometric indicators,WSR was found to have the largest area under the ROC curve and the best cut-off point of WSR was 0.52.Multivariate logistic regression analysis showed that, after controlling age, disease history, physicalactivity, sex, thediabeteshypertension and dyslipidemia risk OR of WSR≥0.52 were largest.ConclusionsAnthropometric indicators intimately related with cardiovascular risk factors in Qingdao region,and may predict and evaluate the risk of cardiovascular disease.WSR may be the best index for predicting cardiovascular risk factors in Qingdao area.The optimal WSR cut off point for identifying cardiovascular risk factors clustering is 0.52.

Razón cintura estatura como predictor de riesgo cardiometabólico en niños y adolescentes / Waist-Height ratio as a predictor if cardio-metabolic risk in children

En niños, la obesidad general y visceral se asocian con mayor riesgo cardiometabólico. El aumento en la prevalencia del síndrome metabólico (SM) en niños y adolescentes empeora el riesgo cardiovascular. Necesitamos contar con nuevos marcadores que permitan predecir el SM en niños. Objetivo: Comparar índice de masa corporal (zIMC) con razón cintura estatura (RCE) como predictores de SM en niños chilenos. Método: Estudio transversal en 618 escolares, edad 10.8 +/- 1.9 años, 51.6 por ciento mujeres, 190 eutróficos, 174 sobrepeso, 254 obesos, estrato socioeconómico medio y medio bajo, área urbana de Santiago. Determinamos peso, talla, circunferencia de cintura, presión arterial, perfil lipídico y glicemia. Diagnóstico de SM basado en la presencia de > 3 criterios de Cook. El SM se modeló en función de RCE y z score IMC , con modelos de regresión logística. Se usaron curvas ROC para comparar RCE y zIMC como predictores de SM. Punto de corte según índice de YOUDEN. Resultados: La prevalencia de SM fue 15.37 por ciento. Promedio de z IMC + 1.22 +/- 0.90 y de RCE 0.52 +/-0.07. Punto de corte óptimo para SM: RCE 0.55 (sensibilidad 72 por ciento, especificidad 70 por ciento) yzIMC: 1.76 (sensibilidad 71 por ciento, especificidad 74 por ciento). Conclusión: RCE y zIMC predicen igualmente el riesgo cardiometabólico en niños y adolescentes. Dada la mayor facilidad de calcular RCE, la transforma en mejor herramienta definiendo riesgo en este grupo. El punto de corte > 0.55 sería buen predictor de SM en niños y adolescentes.

Among children both general and visceral obesity are associated with increased cardio-metabolic risk. The increasing prevalence of the metabolic syndrome (MS) in children and adolescents increases cardiovascular risk. Studies of new clinical markers which can easily and accurately predict MS in children and adolescents are needed. Aim: To compare zBMI and waist to height ratio (WHR) as predictors of MS in Chilean children. Method: We performed a crossectional study of 618 schoolchildren, age 11 +/- 2 years, 52 percent females, 190 eutrophic, 174 overweight, 254 obese, from middle and low social economic strata from the Santiago urban area. We determined weight, height, waist circumference, blood pressure and fasting lipids and glycemia. MS diagnosis was based on the presence of > 3 Cook criteria. MS was modeled in function of WHR and z score BMI, through logistic regression models. ROC curves were used to compare zBMI and WHR as predictors of MS. The cut off point by YOUDEN index was used. Results: The prevalence of MS was 15 percent. Mean zBMI was +1.22 +/- 0.90 and WHR 0.52 +/- 0.07. Cut off point for MS were: WHR 0,55 (sensitivity 72 percent, specificity 70 percent)and zBMI: 1.76 (sensitivity 71 percent, specificity 74 percent). Conclusions: Both WHR and zBMI similarly predicted cardio metabolic risk in children and adolescents. The greater feasibility of calculating WHR makes it a good tool for defining risk in this group. A cut off point >0.55 might be a good predictor of MS in children and adolescents.