RESUMOObjetivo: A redução nos níveis de atividade física na população jovem tem sido amplamente descrita em vários países, sobretudo em alguns subgrupos dessa população. O objetivo deste estudo foi determinar a prevalência de inatividade física em adolescentes escolares do ensino médio do município de João Pessoa -PB, e analisar sua associação com indicadores de condição socioeconômica. Metodologia: Participaram do estudo 2.566 adolescentes (1.132 rapazes e 1.434 moças), de 14 a 18 anos de idade (16,5±1,17). Foram levantadas informações demográficas (sexo e idade), socioeconômicas (trabalho, tipo de escola, classe econômica, escolaridade dos pais), e mediu-se o nível de atividade física (kcal/kg/dia), mediante utilização de um diário de atividade física. Foram classificados como fisicamente inativos os adolescentes com demanda energética diária <37kcal/kg/dia. Na análise multivariável recorreu-se à regressão de Poisson, tendo a razão de prevalência como medida de associação. Resultados: Cerca de seis em cada dez adolescentes foram classificados como fisicamente inativos (55,9%, n=1.435), com prevalência estatisticamente mais elevada nas moças (64,2%) do que nos rapazes (45,5%; p<0,001). A prevalência de inatividade física se associou positivamente com a condição socioeconômica, indicando maior prevalência de inatividade física nos adolescentes que não trabalhavam (rapazes RP=2,22; IC95%=1,62-3,04 e moças RP=1,52; IC95%=1,19-1,93), e nas moças cujos pais apresentavam maior nível de escolaridade (RP=1,20; IC95%=1,05-1,35), comparados, respectivamente, aos que trabalham e cujos pais tinham menor nível de escolaridade. Conclusão: A prevalência de inatividade física foi alta, principalmente nas moças. Adolescentes que pertenciam aos estratos socioeconômicos mais privilegiados se mostraram mais expostos à inatividade física, sobretudo as moças.Palavras-chave: adolescente, atividade física, inatividade física, condição socioeconômica. ABSTRACTObjective: The decrease in the levels of physical activity in the young population has been described thoroughly in several countries, above all in some subgroups of that population. The objective of this study was to determine the prevalence of physical inactivity in high school adolescents from the João Pessoa city -PB and to analyze its association with indicators of socio-economic status. Methodology: 2,566 adolescents (1,132 boys and 1,434 girls), ages between 14-18 years (16.5±1.17) participated in this study. Demographic (sex and age) and socio-economic data (work, school type, economic class, and parents' educational background) were raised. Besides that, the level of physical activity (kcal/kg/day) was measured through a diary of physical activity. The adolescents were classified as physically inactive when had daily energy demand <37kcal/kg/day. The ratio prevalence (RP), with respective reliability intervals of 95% (RI95%), was used as association measure. Results: The prevalence of physical inactivity positively associated with the socio-economic status, showing higher...

OBJETIVOS: analisar a validade das medidas auto-referidas de peso e estatura para o diagnóstico do estado nutricional de adolescentes. MÉTODOS: Fizeram parte do estudo 867 adolescentes (433 rapazes e 434 moças), do município de Florianópolis, Santa Catarina, com idades entre 15 e 18 anos (16,2 1,08). Inicialmente, os adolescentes referiram o peso e a estatura; na seqüência, as respectivas medidas foram aferidas pelos pesquisadores. Determinou-se o índice de massa corporal (IMC) com base nas medidas referidas e aferidas. RESULTADOS: ao referirem suas medidas antropométricas, em média, os adolescentes subestimaram o peso em 0,5 kg, superestimaram a estatura em 0,42 cm, e o IMC baseado nessas medidas foi subestimado em 0,3 kg/m². As medidas auto-referidas apresentaram concordância elevada com as medidas aferidas (coeficiente de correlação intraclasse - CCIC = 0,91 a 0,96). Os índices de validade relativa do IMC, determinado a partir das medidas referidas, oscilaram entre 60% e 79,1% para sensibilidade, 98,4% a 99,2% para especificidade, 89,8% e 90% para o valor preditivo positivo. A prevalência de sobrepeso/obesidade foi subestimada em 2,6% quando determinada a partir das medidas referidas (p = 0,18). CONCLUSÕES: as medidas auto-referidas de peso e estatura representam medidas válidas como forma de aproximação aos valores mensurados, podendo ser utilizadas na avaliação do estado nutricional de adolescentes a partir do IMC, em estudos epidemiológicos.

Purpose: The baseline PSA has been proposed as a possible marker for prostate cancer. The PSA determination before 40 years seems interesting because it not suffers yet the drawbacks related to more advanced ages. Considering the scarcity of data on this topic, an analysis of PSA kinetics in this period seems interesting. Materials and Methods: A retrospective assay in a database of a private diagnostic center was performed from 2003 to 2016. All subjects with a PSA before 40 years were included. Results: 92995 patients performed PSA between the ages of 21 – 39. The mean value ranged from 0.66 ng / mL (at age 22) to 0.76 ng / mL (at age 39) and the overall mean was 0.73 ng / mL. As for outliers, 3783 individuals presented a baseline PSA > 1.6 ng / mL (p95). A linear regression model showed that each year there is a PSA increase of 0.0055 ng / mL (β = 0.0055; r 2 = 0.0020; p < 0.001). A plateau in PSA between 23 and 32 years was found and there were only minimal variations among the ages regardless of the evaluated percentile. Conclusion: It was demonstrated that PSA kinetics before 40 years is a very slow and progressive phenomenon regardless of the assessed percentile. Considering our results, it could be suggested that any PSA performed in this period could represent the baseline value without significant distortions.

STRUCTURED ABSTRACT Context Small adjustments in LT4 dose do not appear to provide clinical benefit despite changes in TSH levels within the reference range. We hypothesize that the accompanying changes in serum T3 levels do not reflect the magnitude of the changes in serum TSH. Objective Characterize the relationships of serum FT4 vs T3, FT4 vs TSH, and FT4 vs the T3/FT4 ratio Design Cross-sectional observational study Setting A large clinical database from January 1, 2009, to December 31, 2019 Participants 9850 participants aged 18 years and older treated with LT4 Exposure Treatment with LT4, subdivided by serum FT4 level Main Outcome Measures: Model fitting of the relationships between serum FT4 vs TSH, FT4 vs T3, and FT4 vs T3/FT4. Mean and median values of TSH, T3, and T3/FT4 were calculated. Results The relationships T3 vs FT4 and TSH vs FT4 were both complex and best represented by distinct, segmented regression models. Increasing FT4 levels were linearly associated with T3 levels until an inflection point at a FT4 level of 0.7 ng/dL, after which a flattening of the slope was observed following a convex quadratic curve. In contrast, increasing FT4 levels were associated with steep declines in TSH following two negative sigmoid curves. The FT4 vs T3/FT4 relationship was fit to an asymptotic regression curve supporting less T4 to T3 activation at higher FT4 levels. Conclusions In LT4-treated patients, the relationships between serum FT4 vs TSH and FT4 vs T3 across a range of FT4 levels are disproportionate. As a result, dose changes in LT4 that robustly modify serum FT4 and TSH values may only minimally affect serum T3 levels and result in no significant clinical benefit.

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Introduction: Determination of reference ranges for thyroid function tests, such as TSH, are not a simple task. There are several biological and individual aspects to be considered, one of the most important is age, particularly for the extremes, children and the elderly population. Several studies demonstrated a progressive increase in age-related TSH in older adults. Therefore, the aim of this study is to establish specific reference values for Brazilian population over 60 years old using Big Data strategy. Methods: Data from 10.43 million TSH tests performed in the same method were retrospectively analyzed. All the samples are from the same clinical laboratory, with samples from several regions of Brazil. The samples were selected using the following filters: free T4 concentration within the reference values (RV), absence of anti-thyroid antibodies and of medication use. Groups were divided by age from 18 to 59 years old (under-60), and over 60 up to 107 years old (over-60). Statistical analyzes were performed using R software and EP Evaluator. Both R package ‘boot’ and EP Evaluator nonparametric (CLSI C28-A) were used to estimate the 97.5% confidence interval (IC). Results: After filtering the samples, 306,289 were selected. Mean TSH was similar in both sex. However, there were differences between the two age-groups, in under-60 group, the lower RV was 0.59 mUI/L (95% IC = 0.57, 0.59) and the upper RV was 6.00 mUI/L (95% IC = 5.94, 6.08). Interestingly, in over-60 group the lower RV was 0.36 mUI/L (95% IC = 0.34, 0.38) and the upper RV was 9.38 mUI/L (95% IC = 8.86, 9.44). Furthermore, this upper limit of reference range increases within the older group with TSH of 7.4 mUI/L from 60 to 69, 9.60 mUI/L from 70 to 79 and 12.30 mUI/L above 80 years old. Conclusion: Big data strategy could be a useful tool to reach agreeable population reference values. In particular, for TSH, the higher upper reference limits for adults over 60 years old would be important to avoid overdiagnosis and over-treatment of subclinical hypothyroidism in this population.