REPRODUCTIVE AND PARENTAL CORRELATES OF CARDIOMETABOLIC RISK IN GLOBAL POPULATIONS OF OLDER ADULTS
Bibliographic record
Abstract
A substantial body of research investigates potentially-modifiable individual risk factors for cardiovascular (CVD) diseases including tobacco use, physical inactivity, and clustered metabolic risk factors. In older adults, however, many of these “modifiable” factors are conditioned by exposure to a lifetime of socially- and culturally-established determinants. Some of the most intractable are tied to gender norms, which strongly influence reproductive timing and frequency and are among the most life-altering events in the human experience, both physiologically (women) and socially. To date, numerous studies investigate female lifetime parity and CVD, as well as adolescent childbirth and all-cause mortality. Many observe robust associations and attribute the findings to the physiological consequences of pregnancy. Almost all of this research takes place in high-income settings and few interrogate the complex constellation of influences on reproduction and its long-term health consequences. Very few look at male populations. In this symposium, we present findings from middle and high-income populations investigating age at first childbirth (AFB) and number of children on cardiometabolic diseases. We begin with results of a systematic review investigating associations between AFB and CVD. It highlights conceptual and methodological gaps in previous approaches to the topic. The next two studies present results from an international cohort of community-dwelling older adults with sites in Canada and middle-income countries, each characterized by divergent gender norms and human develop indices. Finally, we present results on lifetime number of children in men and women in the United States and associations with heart disease and stroke.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".