Índices antropométricos como indicadores de riesgo cardiometabólico en adultos mexicanos, ENSANUT MC 2016
Anthropometric indices as indicators of cardiometabolic risk in mexican adults, ENSANUT MC 2016
DOI:
https://doi.org/10.15446/rsap.v24n5.98355Palabras clave:
Índice, antropometría, síndrome metabólico, factores de riesgo, México (es)Index, anthropometry, metabolic syndrome, risk factors, Mexico (en)
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Objetivo El presente estudio comparó diferentes índices antropométricos utilizados para la identificación de riesgos metabólicos en adultos mexicanos.
Metodología Estudio basado en la ENSANUT-2016, realizado a personas de 20 y más años. Se aplicó un cuestionario, se recolectaron muestras sanguíneas y se hicieron mediciones antropométricas (peso, talla y circunferencia de cintura). Se aplicaron índices antropométricos (IA) a los que se les calculó sensibilidad, especificidad e intervalos de confianza. Se evaluaron Odds Ratio de cada IA ajustándolos por edad y sexo para identificar la predicción de los puntos de corte.
Resultados En mujeres, el Índice de masa corporal (IMC) predice 2,2 veces más la ocurrencia de glucosa elevada en ayuno, 1,7 veces más la presencia de tensión arterial elevada (TAE), 2,4 veces más el riesgo de colesterol-HDL disminuido y 3,0 veces más la probabilidad de síndrome metabólico (SM) (p=0,000). En hombres, el índice cintura-altura (ICA) predice 2,5 veces más la probabilidad de observar glucosa elevada en ayuno, 0,9 veces más TAE y alta correlación con el perímetro de cintura (75,9 %).
Conclusiones Este es el primer estudio transversal que compara la capacidad de IA en la identificación de factores de riesgo cardiometabólicos (FRC) o SM en adultos mexicanos. El análisis demuestra el poder discriminatorio de los IA para la población mexicana, por lo que se recomiendan para la evaluación de FRC o SM.
Objective The present study aimed to compare various anthropometric indices for identifying metabolic risks among Mexican adults.
Methodology The study was conducted using data from the ENSANUT-2016 survey and focused on individuals aged 20 and above. A questionnaire was administered, and anthropometric measurements (weight, height, and waist circumference) as well as blood samples were collected. Anthropometric indices (AI) were calculated, and sensitivity, specificity, and confidence intervals were determined. The Odds Ratio of each AI was evalua- ted, adjusting for age and sex to assess the predictive value of the cut-off points.
Results Among women, body mass index (BMI) predicts a 2.2-fold increase in the occurrence of high fasting glucose, a 1.7-fold increase in the presence of high blood pressure (HBP), a 2.4-fold increase in the risk of decreased HDL-cholesterol, and a 3.0-fold increase in the probability of metabolic syndrome (MS) (p=0.000). In men, waist-to- height ratio (WHR) predicts a 2.5-fold increase in the probability of elevated fasting glucose, a 0.9-fold increase in HBP, and a strong correlation with waist circumference (75.9 %).
Conclusions This study is the first cross-sectional analysis to compare the effective- ness of anthropometric indices (AI) in identifying cardio-metabolic risk factors (CRF) or MS in Mexican adults. The findings of this analysis highlight the discriminative capability of AI for the Mexican popu- lation, suggesting their usefulness in evaluating CRF or MS. Therefore, it is recommended to utilize these indices for assessing CRF or MS in Mexican adults.
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