IGF‐I in a normal population: relation to psychosocial factors
Bibliographic record
Abstract
OBJECTIVE: IGF-I has important actions on cell division, apoptosis, differentiation and metabolism, as well as on cell proliferation in vascular smooth muscle. Deficiency of GH, an important regulator of IGF-I, is associated with reduced well-being. IGF-I levels have been related to cognitive function in older individuals. The aim of the present study was to investigate the IGF-I concentrations in a normal population of men and women aged 20-74 years and to determine the influence of a variety of behavioural and psychosocial factors as well as metabolic factors on these concentrations. DESIGN: Cross-sectional study. PATIENTS: The study group consisted of 408 randomly selected people who had answered a questionnaire concerning health care utilization and quality of life that was administered to a random sample of 4200 people over age 17 from the northwestern region of greater Stockholm in 1995. Thirty-four men and 34 women were randomly selected from the age group 20-24 and from each 10-year age group between the ages of 25-75 years. Seventy-one per cent of the 408 people invited to come in for an examination agreed to attend, making a total sample size of 288 people. MEASUREMENTS: A medical examination was performed and blood drawn in the morning after subjects had been fasting overnight. Before the examination, they were asked to fill out a questionnaire concerning lifestyle and psychosocial factors. RESULTS: The distribution of IGF-I was positively skewed, but using logarithmically transformed IGF-I, a more symmetrical distribution was obtained. A linear inverse correlation was found between logarithmically transformed IGF-I levels and age which explained more than 40% of the variation in men and women. Linear correlation analysis between IGF-I and different parameters of health and disease, lifestyle and psychosocial factors, resulted in several significant correlations most of which disappeared after controlling for age. In the younger age group (20-44) there were positive correlations between IGF-I and psychosocial factors representing quality of life and psychological well-being. In the middle age group (45-59) higher IGF-I levels were related to better physical health, higher education and higher concentrations of lipoprotein Lp(a). In the older age group (over 59 years) higher levels of low-density lipoprotein-cholesterol (LDL-C) and lower levels of SHBG were associated with higher IGF-I levels. CONCLUSION: In a randomly selected (nondisease) population, IGF-I concentrations show a consistent decrease with age in both men and women, accompanied by different association patterns relevant to disease risk. Levels are related to psychosocial parameters in the younger age group and metabolic impairment associated with increased cardiovascular risk in the older age groups. We speculate on the relative roles of age and cohort differences in rearing conditions in determining these differences.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 0.001 |
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".