Screen Time from Adolescence to Adulthood and Cardiometabolic Disease: a Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Previous studies have analyzed the relationship between screen time and cardiometabolic disease risk factors among adolescents, but few have examined the longitudinal effects of screen time on cardiometabolic health into adulthood using nationally representative data. OBJECTIVE: To determine prospective associations between screen time and later cardiometabolic disease over a 24-year period using a nationally representative adolescent cohort. DESIGN: Longitudinal prospective cohort data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) collected from 1994 to 2018. PARTICIPANTS: Adolescents aged 11-18 years old at baseline (1994-1995) followed for 24 years. MAIN MEASURES: Predictors: screen time (five repeated measures of self-reported television and video watching from adolescence to adulthood). OUTCOMES: Five repeated measures of body mass index (BMI); two repeated measures of waist circumference, hypertension, hyperlipidemia, and diabetes collected at 15- and 24-year follow-up exams. KEY RESULTS: through follow-up. By 24-year follow-up, 43.4% of participants had obesity, 8.4% had diabetes, 31.8% had hypertension, and 14.9% had hyperlipidemia. In mixed-effects generalized linear models, each additional hour of screen time per day was associated with 0.06 (95% CI 0.04-0.09) within-person increase in BMI. Each additional hour of screen time per day was associated with higher within-person odds of high waist circumference (AOR 1.17, 95% CI 1.09-1.26), obesity (AOR 1.09, 95% CI 1.03-1.15), and diabetes (AOR 1.17, 95% CI 1.07-1.28). Screen time was not significantly associated with hypertension or hyperlipidemia. CONCLUSIONS: In this prospective cohort study, higher screen time in adolescence was associated with higher odds of select indicators of cardiometabolic disease in adulthood.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".