Clusters of lifestyle behaviors associated with atherosclerosis risk factors in children and adolescents with congenital heart disease: Floripa CHild Study
Bibliographic record
Abstract
Secondary cardiovascular disease is the main cause of mortality in congenital heart disease (CHD) patients. The cardiovascular risk could be widely prevented with adherence to a healthy lifestyle; however, clusters of lifestyle behaviors related to atherosclerosis risk factors in children and adolescents with CHD remain unclear. We aimed to describe the clusters of lifestyle behaviors of children and adolescents with CHD and to evaluate their association with atherosclerosis risk factors. We conducted a cross-sectional study on 227 children and adolescents with CHD (median age:10.02 [IQR:7.08-13.02] years). Dietary intake, physical activity (PA), and sedentary behavior (SB) were evaluated. Clusters of lifestyle behaviors were determined using a two-step cluster analysis. Atherosclerosis risk factors evaluated include body fat mass, central obesity, blood pressure, lipid parameters, glucose, C-reactive protein, and carotid intima-media thickness (cIMT). Multiple logistic regressions were used. The "unhealthy: high SB + low PA" cluster was associated with elevated body fat mass, central obesity, and elevated cIMT. Furthermore, the "unhealthy: low PA + unhealthy eating habits" cluster was associated with elevated body fat mass, central obesity, and elevated glucose. The unhealthier lifestyle behavior clusters were associated with atherosclerosis risk factors in children and adolescents with CHD. Multidisciplinary strategies to promote healthy behaviors are needed to prevent cardiovascular disease in later life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".