Cardiometabolic Health in Adolescents with Obesity: The Role of Protein Intake, Diet Quality, and Physical Activity
Bibliographic record
Abstract
Background: Although adolescents with obesity have an increased risk of cardiometabolic disease, a subset maintains a healthy cardiometabolic profile. Unhealthy lifestyle behaviors may determine cardiometabolic risk. We aimed to characterize the lifestyle behaviors of adolescents with obesity, compare differences between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO), and assess associations between lifestyle behaviors and cardiometabolic profiles. Methods: Participants aged 10–18 years with body mass index (BMI) ≥ 95 th percentile were included. Dietary intake (DI) was estimated from 3-day food records, and diet quality (DQ) was assessed using the Healthy Eating Index-Canadian Adaptation. Physical activity (PA), body composition, anthropometrics, blood markers, and blood pressure (BP) were objectively measured. MUO was defined as having high triglycerides, BP, glucose, or low high-density lipoprotein. Regression analyses were performed between lifestyle behaviors and cardiometabolic markers. Results: Thirty-nine participants (BMI z-score 2.8 [2.5–3.5], age 12.5 [10.9–13.5] years, 56.4% female) were included. A high proportion of participants failed to meet lifestyle recommendations, particularly for DQ (94.7%, n = 36), fiber (94.7%, n = 36), and PA (90.9%, n = 30). No differences in lifestyle behaviors were found between MUO (59.0%, n = 22) and MHO (41.0%, n = 16). Protein intake was negatively associated with BMI and waist circumference z-scores, fat mass index, insulin resistance, low-density lipoprotein, and C-reactive protein, whereas higher DQ was associated with lower C-reactive protein. Higher light PA levels were associated with lower total cholesterol and triglycerides. Conclusion: Adolescents with either MUO or MHO displayed low adherence to DQ, DI, and PA recommendations; no differences in lifestyle behaviors were found. Protein intake, DQ, and PA were associated with a healthier cardiometabolic profile.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".