Relación entre índice cintura cadera, índice cintura talla y la Escala FINDRISC en adultos de Guatemala / Relationship between waist-hip index, waist-height index and the FINDRISC Scale in adults from Guatemala

La diabetes mellitus tipo 2 (DM2) es una amenaza para la salud por las complicaciones derivadas de un diagnóstico tardío, donde la identificación oportuna es primordial. Con el objetivo de establecer la relación entre índice cintura talla (ICT), índice cintura cadera (ICC) y puntaje de la escala FINDRISC (Finnish Diabetes Risk Score) como determinantes del riesgo de padecer DM2 a largo plazo, se realizó este estudio predictivo transversal con adultos de 18 y 60 años atendidos en el Centro de Salud Primero de Julio del municipio de Mixco, Guatemala. Participaron 80 adultos, seleccionados por un muestreo aleatorio simple. El instrumento de recolección de datos estuvo conformado por tres secciones: información general de la persona, parámetros antropométricos y la encuesta de FINDRISC. Se generaron modelos lineales generalizados para identificar relaciones entre índice cintura talla (ICT), índice cintura cadera (ICC) y puntaje de la escala FINDRISC (Finnish Diabetes Risk Score). El 36.2% presentó riesgo de desarrollar DM2 a largo plazo; encontrándose un 21.2% en el nivel de riesgo alto y muy alto. Se comprobó que únicamente existe relación significativa entre el ICT y el puntaje de la escala de FINDRISC como determinante del riesgo de padecer DM2 a largo plazo. Se concluye que la implementación de la medición del ICT constituye una herramienta útil para identificar personas con riesgo de desarrollar DM2, siendo su aplicación sencilla, no invasiva, económica y de fácil acceso en los servicios de salud.

Type 2 diabetes mellitus (T2DM) is a health threat due to the complications derived from a late diagnosis, where timely identification is essential. This study aimed to establish the relationship between waist-height index (WHR), waist-hip index (WHR) and the FINDRISC (Finnish Diabetes Risk Score)scale as determinants of the risk of suffering from T2DM in the long term. A cross-sectional predictive study was carried out with a simple random sample of 80 adults between 18 and 60 years old treated at the Primero de Julio Health Center in Mixco, Guatemala. The data collection instrument was structured into three sections: general information, anthropometric parameters and the FINDRISC survey. Generalized linear models were generated to identify relationships between waist-height ratio (WHR), waist-hip ratio (WHR) and the FINDRISC scale score (Finish Diabetes Risk Score). The results shows that 36.2% of the participants were at risk of developing T2DM in the long term; 21.2% being at the high and very high risk level. It was found that there is only a significant relationship between the WHR and the FINDRISC scale score as a determinant of the risk of suffering from T2DM in the long term. The implementation of the waist height index measurement constitutes a useful tool to identify people at risk of developing T2DM, its application being simple, non-invasive, economical and easily accessible in health services.

Relación entre porcentaje de grasa corporal y otros indicadores antropométricos de obesidad en adultos con hígado graso / Relationship between body fat percentage and other anthropometrics indicators of obesity in adults with fatty liver

El sobrepeso y la obesidad, representan una preocupación para las autoridades de salud, dado que se ha incrementado en los últimos años; particularmente en poblaciones adultas. Objetivo: Relacionar el porcentaje de grasa corporal con la circunferencia de cintura, el índice cintura/talla y el Índice de Masa Corporal, como indicadores de obesidad en sujetos con diagnóstico de hígado graso no alcohólico. Materiales y Métodos: estudio descriptivo, transversal en una muestra de 137 adultos, de 18 a 70 años. Se midieron las variables: Edad, Talla, Peso, Circunferencia de Cintura (CC), Índice de Masa Corporal (IMC), Índice Cintura/Talla (ICT), Índice peso/circunferencia de cintura (IPCC), Porcentaje de Grasa Corporal (%GC). Se determinaron promedios, desviación, correlaciones y prueba t de student. Resultados: Promedio: edad (47,06±13,71 años), peso (77,94±21,99 kg), talla (160,57±9,20 cm), IMC (30,21±7,92 kg/m2), CC (0,96±0,16 cm), ICT (0,60±0,10), IPCC (0,80±0,11), %GC (34,19±10,88). Según IMC, 34,3% sobrepeso y 39,4% obesos. Según CC, Riesgo elevado 19,0% y Riesgo muy elevado 55,5%. Según ICT, sobrepeso 10,9%, sobrepeso elevado 21,2% y obesidad 51,8%. Según IPCC, 54,0% en riesgo. Según %GC, 13,9% en límite y 52,5% obesidad. Alta correlación entre %GC e IMC (r = 0,85) y entre GC% y CC (r = 0,89). Conclusiones: el IMC es un buen indicador de obesidad, pero es importante conocer la cantidad de grasa del organismo. Se sugiere el %GC como complemento para diagnosticar obesidad; además al agregar CC, como indicador de grasa abdominal, se puede hacer un diagnóstico más preciso de la obesidad para garantizar un adecuado tratamiento y mejorar la calidad de vida en el adulto. Palabras clave: Índice de Masa Corporal, Circunferencia de Cintura, Índice Cintura-Talla, Índice Peso-Circunferencia de cintura, Porcentaje de grasa corporal, Sobrepeso, Obesidad(AU)

Overweight and obesity represent a concern for health authorities, given that it has increased in recent years. Objective: Relate the percentage of body fat with waist circumference, the index size waist and body mass (BMI), as an indicator of obesity. Materials and methods: descriptive, cross-sectional study in a sample of 137 adults, 18 to 70 years. Measured variables: age, height, weight, waist circumference (WC), body mass (BMI), waist height index (WHtR), index weight waist circumference (WWCtR), percentage of body fat (BFP). Determined average, deviation, correlation and test student's t. Results: Average: age (47, 06±13,71 years), weight (77,94±21,99 kg), height (160,57±9,20 cm), BMI (30,21 ± 7,92 kg/m2), WC (0,96±0,16 cm), WHCtR (0,60±0,10), WWCtR (0,80±0,11), BFP(34,19±10,88). According to the BMI, 34.3% obese and 39, 4% overweight. According to WC, high-risk 19.0% and 55.5% very high risk. According to WWCtR, 10, 9% overweight, elevated 21, 2% overweight and obesity 51, 8%. According to WWCtR, 54, 0% at risk. According to BFP, 13, 9% in limit and 52, 5% obesity. High correlation between BMI and BFP (r=0, 85) and between the BFP and WC (r=0, 89). Conclusions: BMI is a good indicator of obesity, but it is important to know the amount of fat in the body. It is suggested the BFP as a complement to diagnose obesity; in addition to add WC, as an indicator of abdominal fat, a more accurate diagnosis of obesity can be to ensure adequate treatment and improve the quality of life in the adult(AU)

Body Adiposity Index in Relation to Body Mass Index and Central Adiposity Measures in Preschool Children from Purulia, West Bengal, India

Many indices are available to evaluate adiposity. A new index, body adiposity index (BAIp) (expressed in % fat) for children [Hip circumference (cm)/ Height (m)0.8) – 38] has been developed (El Aarbaoui et al., 2013). The objective of the present study was to use the index in a sample of preschool children to understand the association between BAIp and other anthropometric characteristics estimating adiposity. Methods: The study was cross-sectional and the participants were 2- to 5-year-old preschoolers (505 boys and 463 girls) from Purulia district in West Bengal, India. Anthropometric measurements recorded were height, weight, waist circumference (WC), hip circumference (HC); derived indices were body mass index (BMI) and adiposity measures including waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), conicity index (CI) and BAIp. Results: Mean age of the participants was 4.03 years. Significant sex differences (p< 0.05) of anthropometric characteristics were found with respect to the mean values of body weight, BMI, HC, WHR, CI, and BAIp. Mean value of BAIp was higher in girls (13.0%fat) than in boys (12.28%fat). The BAIp was highly correlated (p< 0.05) to WHtR (r= 0.87 in boys, 0.86 in girls) than to BMI (r= 0.36 in boys, 0.41 in girls) and CI (r= 0.52 in boys, 0.46 in girls). In linear regression models, adiposity measures were observed to be significantly related to BAIp in preschoolers; age and sex were other predictors; coefficient was highest for WHtR (78.89) and least for WC (0.34). Conclusion: The results confirmed the existing hypothesis that BAIp, as an index for the assessment of children’s body fatness, works with acceptable accuracy.