Prevalência e fatores associados a baixos níveis de aptidão aeróbia em adolescentes
Bibliographic record
Abstract
Avaliar a prevalência de baixos níveis de aptidão aeróbia e analisar sua associação com fatores sociodemográficos, estilo de vida e excesso de adiposidade corporal em adolescentes de uma cidade do sul do Brasil. Estudo com 879 adolescentes de 14 a 19 anos de São José, SC, Brasil. A aptidão aeróbia foi avaliada pelo teste canadense modificado de aptidão aeróbia. Variáveis sociodemográficas (cor da pele, idade, sexo, turno de estudo, nível econômico), maturação sexual e estilo de vida (hábitos alimentares, tempo de tela, nível de atividade física, consumo de álcool e de tabaco) foram avaliados por questionário autoadministrado. O excesso de adiposidade corporal foi avaliado pelo somatório das dobras cutâneas do tríceps e subescapular. Empregou‐se a regressão logística para a estimativa de odds ratio e intervalos de confiança de 95%. A prevalência de baixo nível de aptidão aeróbia foi de 87,5%. As garotas que gastavam duas horas ou mais em frente à tela, que consumiam menos de um copo de leite ao dia, as não fumantes e com excesso de adiposidade corporal apresentaram mais chances de ter baixos níveis de aptidão aeróbia. Os garotos de cor de pele branca e que eram pouco ativos fisicamente apresentaram mais chances de ter baixo nível de aptidão aeróbia. Oito em cada dez adolescentes estavam com baixos níveis de aptidão aeróbia. Fatores modificáveis do estilo de vida foram associados com baixos níveis de aptidão aeróbia. Intervenções que enfatizem a mudança de comportamento são necessárias. To evaluate the prevalence of low aerobic fitness levels and to analyze the association with sociodemographic factors, lifestyle and excess body fatness among adolescents of southern Brazil. The study included 879 adolescents aged 14 to 19 years the city of São José/SC, Brazil. The aerobic fitness was assessed by Canadian modified test of aerobic fitness. Sociodemographic variables (skin color, age, sex, study turn, economic level), sexual maturation and lifestyle (eating habits, screen time, physical activity, consumption of alcohol and tobacco) were assessed by a self‐administered questionnaire. Excess body fatness was evaluated by sum of skinfolds triceps and subscapular. We used logistic regression to estimate odds ratios and 95% confidence intervals. Prevalence of low aerobic fitness level was 87.5%. The girls who spent two hours or more in front screen, consumed less than one glass of milk by day, did not smoke and had an excess of body fatness had a higher chance of having lower levels of aerobic fitness. White boys with low physical activity had had a higher chance of having lower levels of aerobic fitness. Eight out of ten adolescents were with low fitness levels aerobic. Modifiable lifestyle factors were associated with low levels of aerobic fitness. Interventions that emphasize behavior change are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".