OBJECTIVES: Increased arterial stiffness is an important determinant of the risk of cardiovascular disease. Lipid profile impairment, especially hypercholesterolemia, is associated with stiffer blood vessels. Thus, the aim of this study was to determine which of the five circulating lipid components (high-density lipoprotein cholesterol (HDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), low-density lipoprotein cholesterol (LDL), total cholesterol (TC) and triglycerides) is the best predictor of increased arterial stiffness in an urban Brazilian population. METHODS: A random sample of 1,662 individuals from the general population of Vitoria, Brazil (25-64 years), was selected, and lipid components were measured using standard methods. Pulse wave velocity was measured using a non-invasive automatic device, and increased arterial stiffness was defined as a pulse wave velocity ≥10 m/s. RESULTS: In men, only total cholesterol (OR=1.59; CI=1.02 to 2.48, p=0.04) was associated with the risk of increased arterial stiffness. In women, HDL-C (OR=1.99; CI=1.18 to 3.35, p=0.01) and non-HDL-C (OR=1.61; CI=1.01 to 2.56, p=0.04) were good predictors of the risk of increased arterial stiffness. However, these associations were only found in postmenopausal women (OR=2.06; CI=1.00 to 4.26, p=0.05 for HDL-C and OR=1.83; CI=1.01 to 3.33, p=0.04 for non-HDL-C). CONCLUSION: Our findings indicate that both HDL-C and non-HDL-C are good predictors of the risk of increased arterial stiffness in postmenopausal women in an urban Brazilian population and may be useful tools for assessing the risk of arterial stiffness.

Resumo Introdução: Analisa-se co-contração muscular através dos sinais eletromiográficos, os quais são normalizados para permitir comparação entre indivíduos, músculos e estudos. A contração voluntária máxima isométrica (CVMi) e o pico da atividade elétrica (PAE) durante o ato motor são as formas de normalização mais utilizadas. Objetivos: Comparar a variabilidade inter-sujeitos e investigar a associação entre os índices de co-contração, do vasto lateral e bíceps femoral durante a marcha, normalizados pela CVMi e PAE. Métodos: Participaram 30 idosas, idade 70,33 ± 3,69 anos. A atividade elétrica dos músculos durante a CVMi e na marcha foi registrada pelo eletromiógrafo Biopac MP100. A CVMi foi realizada no dinamômetro isocinético Biodex. Para normalização, os sinais foram divididos pelos valores do Root Mean Square da CVMi e pelo PAE da marcha. Resultados: O coeficiente de variação dos dados não normalizados foi 69,3%, e dos normalizados pelo PAE e CVMi foram 30,4% e 48,9% respectivamente. A análise de regressão linear produziu o modelo de predição: PAE = 0,04 + 0,16 x CVMi. O ajuste do modelo de regressão foi estatisticamente significante (p=0,02). O intervalo de confiança (IC95%) para o intercepto foi de 0,02 a 0,29 e para a CVMi foi de 0,03 a 0,06. Conclusão: Os dados normalizados pelo PAE apresentaram menor variação que os normalizados pela CVMi. Uma variação de 100% nos dados normalizados pela CVMi resulta em 16% de variação nos dados normalizados pelo PAE, enquanto a variação da normalização pela CVMi é responsável por 17% de variação da normalização pelo PAE e vice-versa.

Abstract Introduction: Analyze muscle co-contraction using electromyographic signals, which are normalized to compare individuals, muscles and studies. Maximum voluntary isometric contraction (MVIC) and peak electrical activity (PEA) during movement are the most widely used forms of normalization. Objective: Compare inter-subject variability and investigate the association between the co-contraction indices of the vastus lateralis and biceps femoris during gait, normalized by MVIC and PEA. Methods: Thirty elderly women, aged 70.33 ± 3.69 years took part. Electrical muscle activity during MVIC and gait was recorded using a Biopac MP100 electromyograph. MVIC was performed in a Biodex isokinetic dynamometer. For normalization, the signals were divided by the Root Mean Square values of MVIC and PEA of gait. Results: The coefficient of variation of non-normalized data was 69.3%, and those normalized by PEA and MVIC were 30.4% and 48.9% respectively. Linear regression analysis resulted in a prediction model: PEA = 0.04 + 0.16 x MVIC. The goodness of fit of the regression model was statistically significant (p=0.02). The confidence interval (95% CI) for the intercept was between 0.02 and 0.29 and for MVIC between 0.03 and 0.06. Conclusions: The data normalized by PEA showed less variation than those normalized by MVIC. A 100% variation in data normalized by MVIC resulted in a 16% variation in data normalized by PEA, while variation in normalization by MVIC accounts for 17% of the variation in normalization by PEA and vice versa.

Objetivo: Investigar a associação entre os níveis séricos de ácido úrico e a resistência insulínica em crianças e adolescentes com obesidade. Métodos: Estudo transversal, com 245 crianças e adolescentes (134 obesos e 111 controles), entre oito e 18 anos. Foram coletadas variáveis antropométricas (peso, estatura e circunferência abdominal), pressão arterial e parâmetros bioquímicos. As características clínicas dos grupos foram analisadas pelo teste t ou pelo qui-quadrado. Para avaliar a associação entre os níveis de ácido úrico e a resistência insulínica usaram-se o teste de Pearson e regressão logística. A resistência insulínica foi a variável dependente no modelo de regressão. Resultados: A prevalência de resistência insulínica foi de 26,9%. As variáveis antropométricas, a pressão arterial sistólica e diastólica e as variáveis bioquímicas foram maiores no grupo obeso (p<0,001), exceto o colesterol de alta densidade. Foi observada correlação positiva e significativa entre as variáveis antropométricas e o ácido úrico com o HOMA-IR no grupo obeso e no controle. Essa foi maior no grupo obeso e na amostra total. No modelo de regressão logística que incluiu idade, sexo e obesidade, a odds ratio do ácido úrico como fator associado à resistência insulínica foi de 1,91 (IC95% 1,40-2,62; p<0,001). Conclusões: Observa-se que o aumento no nível sérico de ácido úrico apresenta correlação estatística positiva com a resistência insulínica e está associado à elevação no risco em crianças e adolescentes obesos.

Objective: To investigate the association between serum uric acid levels and insulin resistance in children and adolescents with obesity. Methods: Cross-sectional study with 245 children and adolescents (134 obese and 111 controls), aged 8-18 years. The anthropometric variables (weight, height and waist circumference), blood pressure and biochemical parameters were collected. The clinical characteristics of the groups were analyzed by t-test or chi-square test. To evaluate the association between uric acid levels and insulin resistance the Pearson's test and logistic regression were applied. Results: The prevalence of insulin resistance was 26.9%. The anthropometric variables, systolic and diastolic blood pressure and biochemical variables were significantly higher in the obese group (p<0.001), except for the high-density-lipoprotein cholesterol. There was a positive and significant correlation between anthropometric variables and uric acid with HOMA-IR in the obese and in the control groups, which was higher in the obese group and in the total sample. The logistic regression model that included age, gender and obesity, showed an odds ratio of uric acid as a variable associated with insulin resistance of 1.91 (95%CI 1.40-2.62; p<−0.001). Conclusions: The increase in serum uric acid showed a positive statistical correlation with insulin resistance and it is associated with and increased risk of insulin resistance in obese children and adolescents.