Longitudinal Associations of Age, Anthropometric and Lifestyle Factors with Serum Total Insulin-Like Growth Factor-I and IGF Binding Protein-3 Levels in Black and White Men: the CARDIA Male Hormone Study
Bibliographic record
Abstract
Although several studies have assessed cross-sectional correlates of serum insulin-like growth factor-I (IGF-I) and IGF binding protein-3 (IGFBP-3), there are no longitudinal studies of the correlates of long-term changes in these measures. We examined the 8-year longitudinal associations of age, body mass index (BMI), waist circumference, physical activity, number of cigarettes smoked per day, and alcohol intake with serum total IGF-I and IGFBP-3 concentrations in 622 Black and 796 White male participants of the Coronary Artery Risk Development in Young Adults Study who were ages 20 to 34 years at the time of the first IGF measurement. In generalized estimating equation analyses, IGF-I decreased by 5.6 and 5.9 ng/mL per year increase in age for Black and White men, respectively (P< 0.0001), and there was an age-related decline in IGFBP-3 that was stronger in Whites (P < 0.0001) than Blacks (P = 0.21). Average IGF-I (beta = -17.51 ng/mL) and IGFBP-3 (beta = -355.4 ng/mL) levels across all three exams were lower in Blacks than Whites (P < 0.0001). Increased BMI was associated with decreased IGF-I (P < 0.0002), but was not associated with IGFBP-3. There were no meaningful associations with waist circumference. Increased physical activity was associated with a decrease in IGFBP-3 (P < 0.05), but was not associated with IGF-I. In White men, there were weak inverse associations between the number of cigarettes smoked per day with IGF-I (P=0.15) and with IGFBP-3 (P = 0.19), and in Black men, increased alcohol intake was associated with a decrease in IGF-I (P = 0.011). In conclusion, these results support an age-related decline and Black-White difference in serum IGF-I and IGFBP-3 levels. Importantly, they suggest that IGF-I and/or IGFBP-3 levels could be influenced by changes in BMI, and perhaps by physical activity, alcohol intake, and cigarette smoking.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".