Índice cintura-talla e índice de masa corporal como predictores de riesgo cardiometabólico en niños y adolescentes
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Date
Subject
Waist-Height Ratio
Body Mass Index
Waist Circumference
Risk Assessment
Metabolic Syndrome
Child Health
relación cintura-estatura
índice de masa corporal
circunferencia de la cintura
medición de riesgo
síndrome metabólico
salud del niño
Body Mass Index
Waist Circumference
Risk Assessment
Metabolic Syndrome
Child Health
relación cintura-estatura
índice de masa corporal
circunferencia de la cintura
medición de riesgo
síndrome metabólico
salud del niño
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Journal Title
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Volume Title
Publisher
Intituto Tecnológico de Santo Domingo (INTEC)
Objetivo: comparar la utilidad del índice cintura-talla y el índice de masa corporal para detectar factores de riesgo cardiometabólicos en niños de 5-18 años, atendidos en la consulta externa del Hospital Infantil Regional Universitario Doctor Arturo Grullón en el período octubre-diciembre del año 2016.
Método: se realizó un estudio observacional, comparativo, de corte transversal y fuente primaria, con una muestra de 118 pacientes. Se midieron las variables sociodemográficas (edad y sexo), antropométricas (peso, talla, IMC, ICT, PC, TA), y laboratorios (glicemia, ALT, colesterol, triglicéridos, HDL, LDL). Para el análisis cuantitativo se calculó el promedio y la desviación estándar, para el análisis cualitativo se utilizó la prueba estadística chi-cuadrado.
Resultados: tanto el ICT como el IMC detectan de manera similar las alteraciones de la presión arterial sistólica (ICT=15.9 %, IMC=15 %), diastólica (ICT=20.4 %, IMC= 21.8 %), obesidad (ICT=69.5 %, IMC=73.7 %), HDL (ICT=6.8 %, IMC=5.6 %). En relación a la evaluación de la obesidad ambos índices arrojaron resultados afines, 69.5 % para ICT y 73.7 % el IMC. En la valoración de los niveles altos de ALT se obtuvieron resultados similares, presentando el ICT un 8.1 % y el IMC un 8.9 %.
Conclusión: se demostró que tanto el ICT como el IMC son buenos predictores de factores de riesgos cardiometabólicos.
Objective: To compare the utility of the WSI and BMI in detecting cardiometabolic risks on children between 5-18 years, during external consult in Hospital Infantil Regional Universitario Dr. Arturo Grullón in the period of October-December 2016. Methods: A cross-sectional, primary source, observational design study was conducted with a sample of 118 patients. The variables measured for this study included sociodemographic (age and sex), anthropometric (weight, height, BMI, ICT, PC), and laboratories (glycemia, ALT, cholesterol, triglycerides, HDL, LDL). The quantitative analysis was carried out by calculating the average and the standard deviation. As for the qualitative analysis, the statistical test χ² was used. Results: Both the WSI and the BMI proved to be effective in detecting changes in Systolic (WSI = 15.9%, BMI = 18.4%) and Diastolic Blood Pressure (WSI = 20.4%, BMI = 18.6%), obesity (WSI = 69.5%, BMI = 73.7%), HDL (WSI = 29.3%, BMI = 29.9%). Regarding the detection of obesity, both rates showed similar results, 69.5% for ICT, and 73.7% for BMI. Comparable results were obtained in the assessment of high levels of ALT, with the ICT at 8.1% and the BMI at 8.9%. Conclusions: WSI and BMI are both useful to detect cardiometabolic risk factors.
Objective: To compare the utility of the WSI and BMI in detecting cardiometabolic risks on children between 5-18 years, during external consult in Hospital Infantil Regional Universitario Dr. Arturo Grullón in the period of October-December 2016. Methods: A cross-sectional, primary source, observational design study was conducted with a sample of 118 patients. The variables measured for this study included sociodemographic (age and sex), anthropometric (weight, height, BMI, ICT, PC), and laboratories (glycemia, ALT, cholesterol, triglycerides, HDL, LDL). The quantitative analysis was carried out by calculating the average and the standard deviation. As for the qualitative analysis, the statistical test χ² was used. Results: Both the WSI and the BMI proved to be effective in detecting changes in Systolic (WSI = 15.9%, BMI = 18.4%) and Diastolic Blood Pressure (WSI = 20.4%, BMI = 18.6%), obesity (WSI = 69.5%, BMI = 73.7%), HDL (WSI = 29.3%, BMI = 29.9%). Regarding the detection of obesity, both rates showed similar results, 69.5% for ICT, and 73.7% for BMI. Comparable results were obtained in the assessment of high levels of ALT, with the ICT at 8.1% and the BMI at 8.9%. Conclusions: WSI and BMI are both useful to detect cardiometabolic risk factors.
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info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/publishedVersion
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Science and Health; Vol. 5 No. 2 (2021): Science and Health, may-August; 77-85
Ciencia y Salud; Vol. 5 Núm. 2 (2021): Ciencia y Salud, mayo-agosto; 77-85
2613-8824
2613-8816
10.22206/cysa.2021.v5i2
Ciencia y Salud; Vol. 5 Núm. 2 (2021): Ciencia y Salud, mayo-agosto; 77-85
2613-8824
2613-8816
10.22206/cysa.2021.v5i2