BACKGROUND: We aimed to compare the accuracy of the ponderal index (PI) vs. BMI-forage z-scores transformed (BMIz) in estimating body fat levels and classifying obesity in children and adolescents from a Brazilian urban population. METHODS: This is a cross-sectional study with 1149 participants (53.2% male), aged 6 to 18 years. Body fat percent (BFP) was obtained by multi-frequency bioelectrical impedance. Non-linear regression analysis provided the accuracy of both BMIz and PI in estimating BFP. False positive rate was obtained from the proportion of individuals placed at or above the 95 th percentile for BMIz or PI, whereas their BFP was discordantly below the 95 th percentile. RESULTS: PI and BMIz appeared with similar stability from childhood to adolescence for both boys and girls. The portion of the variability in BFP explained by BMIz (R 2 = 0.74 and R 2 = 0.75) was close to the variability in BFP explained by PI (R 2 = 0.73 and R 2 = 0.75) for boys and girls, respectively. False positive rate was higher for BMIz compared with PI among boys (21.8% vs. 3.9%) and girls (28.5% vs. 17.5%). CONCLUSIONS: PI is a promising index for replacing BMIz in children and adolescents due to its potential to reduce false diagnosis of obesity.

Resumo Verificou-se a relação entre diferentes índices antropométricos e os lipídios plasmáticos. Os dados foram coletados de 2014 a 2016 em 854 escolares (6-18 anos). Foram aferidas a circunferência da cintura (CC), o percentual de gordura corporal (%G) por bioimpedância, o índice de massa corporal (IMC) e relação da cintura/estatura (RCE). Em sangue coletado em jejum mediu-se o colesterol total (CT), HDLc, e triglicerídeos e calculou-se o colesterol não HDL (Não HDLc). Os dados são apresentados por média ± desvio padrão, porcentagens. A comparação de médias foi feita pelo teste t ou ANOVA seguida de teste de Tukey. A associação entre variáveis foi testada por regressão linear. O estudo foi aprovado pelo Comitê de Ética da Universidade Federal do Espírito Santo. Meninos obesos tinham CT, Não HDLc e LDLc mais elevados do que os eutróficos. Em meninas este achado foi apenas para o Não HDLc. Crianças com o %G e RCE inadequados apresentaram LDLc e Não HDLc maiores (p < 0,001), os quais associaram-se positivamente (p < 0,001) com as frações lipídicas (CT e Não HDLc). O excesso de gordura corporal elevou em 21% a probabilidade de ocorrência de colesterol acima da referência (170 mg/dL). O excesso de gordura corporal associou-se com o perfil lipídico aterogênico (maior Não HDLc), principalmente em meninos.

Objective: To investigate whether tri-ponderal mass index and body mass index Z scores are equivalent for screening children and adolescents with insulin resistance.Methods: Cross-sectional study with 296 children and adolescents enrolled at public schools of Vitória, Espírito Santo, Brazil, aged eight to 14 years. The tri-ponderal mass index was calculated as the ratio between weight and height cubed. The body mass index was calculated as the ratio between weight and height squared. Insulin resistance was defined with the homeostatic model assessment (HOMA-IR).Results: The HOMA-IR was higher in the 4 th quartile of body mass index Z scores and tri-ponderal mass index compared to 1 st and 2 nd quartiles for both girls and boys. The areas under the age-adjusted receiver operating characteristic curves were similar between the indices for girls (body mass index Z scores=0.756; tri-ponderal mass index=0.763) and boys (body mass index Z scores=0.831; tri-ponderal mass index=0.843). In addition, according to the simple linear regression analyses estimations, both body mass index Z scores and tri-ponderal mass index explained a significant fraction of the homeostatic model assessment variability for girls (body mass index Z scores: R 2 =0.269; tri-ponderal mass index: R 2 =0.289; p<0.001) and boys (body mass index Z scores: R 2 =0.175; tri-ponderal mass index: R 2 =0.210; p<0.001). Conclusions: The tri-ponderal mass index and body mass index Z scores were similar to discriminate children and adolescents with Objetivo: Investigar se o índice de massa tri-ponderal e os escores-z do índice de massa corporal são equivalentes na triagem de crianças e adolescentes com resistência à insulina. Métodos: Estudo transversal com 296 crianças e adolescentes matriculados em escolas públicas de Vitória, Espírito Santo, Brasil, com idades entre oito e 14 anos. O índice de massa tri-ponderal foi calculado como a razão entre o peso e a altura ao cubo. O índice de massa corporal foi calculado como a razão entre o peso e a altura ao quadrado. A resistência à insulina foi definida pelo modelo de avaliação da homeostase para resistência à insulina (HOMA-IR).Resultados: O HOMA-IR foi maior no 4 º quartil dos escores-z do índice de massa corporal e do índice de massa tri-ponderal, em relação ao 1 º e 2 º quartis em ambos os sexos. As áreas sob as curvas receiver operating characteristic ajustadas por idade foram semelhantes em meninas (escores-z do índice de massa corporal=0,756; índice de massa tri-ponderal=0,763) e meninos (escores-z do índice de massa corporal=0,831; índice de massa tri-ponderal=0,843). Além disso, de acordo com as estimativas das análises de regressão linear simples, os escores-z do índice de massa corporal e o índice de massa triponderal explicaram uma fração significativa da variabilidade do modelo de avaliação da homeostase para meninas (escores-z do índice de massa corporal: R 2 =0,269; índice de massa tri-ponderal: R 2 =0,289; p<0,001) e meninos (escores-z do índice de massa corporal: R 2 =0,175; índice de massa tri-...

Body fat percentage was better than the indicators of weight status to identify children and adolescents with unfavorable lipid profile, mainly among girls.

No abstract

No abstract

The indicators provided similar discriminatory power for insulin resistance. However, taking into account the cost-benefit ratio, the authors suggest that waist-to-height ratio may be a useful tool to provide screening for insulin resistance in pediatric populations.

Objective. The objective is to analyze the concentration of iodine in Brazilian drinking water and its possible contribution to iodine intake for different groups. Methods. Water samples collected from primary healthcare units in eight locations distributed across all five macroregions of Brazil were analyzed. The quantification of iodine in the water samples was done by spectrophotometry (leuco crystal violet method). To classify the degree of iodine concentration, the recommendation of the Ministry of Health (China) was followed since Brazil lacks a classification standard. To verify the possible contribution of drinking water to iodine intake for different groups, the recommended water intake for each group according to the United States Institute of Medicine (2004) was considered. The percentage of iodine in drinking water and its contribution to iodine intake for different physiological groups were calculated based on the estimated average requirement (EAR) of iodine. A descriptive statistical analysis was performed using SPSS version 21.0 and Statistical Analysis Systems (SAS) version 9.2. Results. Significant differences were found between the maximum and minimum concentrations of iodine in water samples from the same location. In Pinhais (south region), the difference was 44.32 μg⋅ L−1; in Viçosa (southeast region), it was 27.86 μg·L−1; in Rondonópolis (midwest region), it was 12.66 μg·L−1; in São Luís (northeast region), it was 11.82 μg·L−1; in Brasilian Federal District (midwest region), it was 10.98 μg·L−1; in Macaé (southeast region), it was 10.14 μg⋅ L−1; in Palmas (north region), it was 4.22 μg·L−1; and in Vitória (southeast region), it was 1.69 μg·L−1. The maximum concentrations of iodine found in the drinking water of Pinhais and Viçosa can contribute more than 70.0% and 50.0%, respectively, to daily iodine intake for all groups. Conclusion. Monitoring the concentration of iodine in drinking water from different locations in each city or Federal District is a preventive measure against inadequate iodine intake and possible adverse changes in population health.