Body mass index for predicting hyperglycemia and serum lipid changes in Brazilian adolescents

Abstract

Índice de massa corporal para predizer hiperglicemia e alterações lipídicas em adolescentes brasileiros ABSTRACT OBJECTIVE: To determine the best cut-offs of body mass index for identifying alterations of blood lipids and glucose in adolescents. METHODS:A probabilistic sample including 577 adolescent students aged 12-19 years in 2003 (210 males and 367 females) from state public schools in the city of Niterói, Southeastern Brazil, was studied. The Receiver Operating Characteristic curve was used to identify the best age-adjusted BMI cut-off for predicting high levels of serum total cholesterol (≥150mg/dL), LDL-C (≥ 100mg/dL), serum triglycerides (≥100mg/dL), plasma glucose (>100mg/dL) and low levels of HDL-C (< 45mg/dL). Four references were used to calculate sensitivity and specifi city of BMI cut-offs: one Brazilian, one international and two American. RESULTS:The most prevalent metabolic alterations (>50%) were: high total cholesterol and low HDL-C. BMI predicted high levels of triglycerides in males, high LDL-C in females, and high total cholesterol and the occurrence of three or more metabolic alterations in both males and females (areas under the curve range: 0.59 to 0.67), with low sensitivity (57%-66%) and low specifi city (58%-66%). The best BMI cut-offs for this sample (20.3 kg/m² to 21.0 kg/m²) were lower than those proposed in the references studied. CONCLUSIONS:Although BMI values lower than the International cutoffs were better predictor of some metabolic abnormalities in Brazilian adolescents, overall BMI is not a good predictor of these abnormalities in this population.

Avaliação de programa de prevenção de obesidade em adolescentes de escolas públicas

“…Schools were selected by convenience from the 13 schools that participated in the study on prevalence of overweight and obesity and cardiovascular risk factors in adolescents of public schools of Niterói conducted in 2003, 22,23 according to the following criteria: geographic location (schools should be distant from each other to reduce the possibility of exchange of information about intervention activities); similar number of students in the selected grades; presence of a cafeteria in the school; teachers and managers' interest in participating in the program; and similar frequency of overweight/obesity, based on the frequencies observed in a previous study and confi rmed in the two selected schools, before beginning this study. The school receiving the prevention program was randomly selected.…”

“…22 These data warned about the need for strategies that prevent the progression of this problem and also stimulate testing other approaches that may help to curb the obesity epidemic. Thus, the present study aimed to evaluate the effects of an obesity prevention program on the dietary practices of public school adolescents.…”

Consumo de frutas e hortaliças entre usuárias de uma unidade de saúde

“…A influência da idade sobre a qualidade da dieta pode refletir uma mudança de consciência sobre a saúde, interferindo diretamente nas escolhas alimentares pelo grupo de maior idade ou na manutenção dos hábitos em face da menor exposição ao ambiente (31) . A condição financeira é um dos fatores determinantes do estilo da alimentação, isto é, o maior poder aquisitivo está relacionado à maior aquisição de certos tipos de alimentos (32) . A qualidade da dieta varia significativamente de acordo com as características demográficas de sexo e faixa etária, e melhora de acordo com o aumento do nível de escolaridade (31) .…”

Utility of body mass index, waist circumference and waist-to-height ratio as screening tools for hyperglycemia in young people

“…Previous studies analyzing anthropometric measures as predictors of hyperglycemia in children and adolescents also observed poor accuracies, ranging from 0.44 to 0.51 for BMI, from 0.44 to 0.52 for WC, and from 0.50 to 0.57 for WHtR (27)(28)(29)(30). It is well known that excess body fat is associated with different physiological and pathological states, including alterations in glucose metabolism (31).…”