ABSTRACT
Introdução: O diagnóstico de sobrepeso e obesidade pode ser realizado pela antropometria, por facilidade de execução e baixo custo. Considerando a preocupação com a característica de distribuição de gordura, novas estratégias poderiam ser desenvolvidas para a avaliação da composição corporal partindo de medidas antropométricas. Objetivos: Verificar a correlação do Perímetro Abdominal (PAB) e Perímetro da Cintura (PC) em separado, com o somatório de duas dobras cutâneas (DC), triciptal e subescapular; e incluir o perímetro com os maiores valores de correlação em uma equação de regressão para estimativa do somatório de DC. Métodos: Amostra composta por 1.729 meninos (9 e 14 anos), a avaliação da morfologia corporal foi realizada por medidas antropométricas simples e compostas. Foi utilizada uma correlação de Spearman para determinar a associação entre os PAB e PC com as DC. Foi feita uma análise de regressão linear múltipla com o PAB e idade para estimar o somatório de DC. Resultados: A seguinte equação foi gerada: Somatório de DC = 1,16397 (PAB) 1,414922 (Idade) 36,33021 (R=0,83). O valor da área sob a curva ROC (AUC) foi de 83% para identificar corretamente indivíduos abaixo ou acima do percentil 85 do somatório de DC. Conclusões: O PAB em conjunto com a idade, se torna um bom preditor da gordura corporal, caracterizada como o somatório de DC, em crianças e adolescentes do sexo masculino.
Introduction: The diagnosis of overweight and obesity can be accomplished by anthropometry, for ease of implementation and low cost. Considering the concern for the distribution of fat, new strategies could be developed for the diagnosis of body composition from anthropometric measurements. Objectives: To investigate the association of the abdominal girth (AG) and waist girth (WG) separately, with the sum of two skinfolds (SF), triceps and subscapular; and include the girth with higher correlation levels in a regression equation to estimate the SF sum. Methods: A sample of 1,729 boys (9 and 14), the evaluation of body composition was composed by simple and compound anthropometric measurements. The Spearman correlation was used to determine the association between AG and WG with the sum of SF. A multiple linear regression was applied including AG and age to estimate the sum of SF. Results: The following equation was generated: Sum of SF = 1.16397 (AG) - 1.414922 (age) - 36.33021 (R = 0.83). The area under the ROC curve (AUC) was 83% for correctly identifying individuals below or above the 85th percentile of the SF sum. Conclusions: AG, together with age, becomes a good predictor of body fat, characterized as the sum of two SF in children and adolescent males.
Subject(s)
Humans , Male , Child , Adolescent , Skinfold Thickness , Abdominal Circumference , Subcutaneous Fat/anatomy & histology , Students , Anthropometry/methods , Cross-Sectional Studies , AdiposityABSTRACT
Aims: To study the frequency of occurrence of the components of Metabolic Syndrome [MetS] among MetS patients in urban south Indian population, with a view to suggest preventive measures. Study Design: Descriptive hospital based study. Place and Duration of Study: This study was done at a tertiary care teaching institution at Kozhikode, which is an urban area in south India, between September 2007 and February 2008. Methodology: Subjects aged 20 years and above attending the general health check-up clinic (953 people) were screened and people meeting National Cholesterol Education Program Adult Treatment Panel III [NCEP ATP III] criterion for MetS (257 people) were enrolled for the study. In addition to history taking and clinical examination, relevant laboratory investigations were done. Pearson chi-square test was used for statistical analysis. A P value of <0.05 was considered as statistically significant. Results: The prevalence of MetS in the screened population was 27%, more in females (28.1%) than in males (26.4%) and was found to increase with increasing age, in both genders. The most frequently occurring component of MetS in this study was increased abdominal girth [AG]. The other components in the decreasing order of frequency were low high density lipoproteins [HDL], elevated fasting blood glucose [FBG], raised blood pressure [BP] and raised triglycerides [TG]. In males the most frequently occurring component of MetS was reduced HDL, whereas in females it was increased abdominal girth. The other components in the decreasing order of frequency in males were raised TG, increased AG, elevated FBG and raised BP, whereas in females it was low HDL, elevated FBG, raised BP and raised TG. Presence of increased abdominal girth (P<.001) and low HDL (P=.030) was significantly more in females, whereas raised TG (P<.001) was more in males. Conclusions: Increased AG, which is the most frequently occurring component of MetS in this study, is an easily measurable parameter and may be taken as a proxy indicator for the prevalence of MetS in the population. Presence of increased AG is an indicator to check for the presence of other components of MetS and to advise necessary lifestyle changes to prevent the occurrence of MetS and to reduce the cardio vascular disease (CVD) burden in the population.