Consequences of childhood disadvantage on later-life health among older Brazilians
Bibliographic record
Abstract
A growing literature has explored the relationship between life course factors and health in later life. In particular, childhood circumstances have been shown to be associated with several health outcomes many decades later. Most of this literature has focused on high-income countries and on associations between single events or exposure variables in childhood and individual health outcomes among older adults. Less is known about the combined effect of harmful exposure in childhood on later-life health outcomes and, especially, in lower- and middle-income countries. Also, imperfect strategy identifications in observational studies make difficult to assess the robustness of these associations. This dissertation aims to address this gap in the literature with three separate studies on the relationship between childhood disadvantage and several later-life health outcomes among Brazilians aged 50 and over using data from the baseline assessment of the Brazilian Longitudinal Study of Aging. The first study sheds light on the associations between several potentially harmful exposures in childhood (separately and combined) and the occurrence of chronic conditions, separately and together (multimorbidity). The second study focuses on the impact on distinct theoretically appropriate domains of childhood disadvantage on three measures of cognitive performance. These first two studies also investigate the potential mediation effect of adulthood socioeconomic status (SES) on these relationships. And the last study discusses the appropriateness of a novel sensitivity framework (SenseMakr) to analyze observational studies by analyzing the robustness of 65 hypothesized associations between individual exposure and outcome variables. Results from the first study shows that a childhood disadvantage scale was associated with 8 different chronic conditions as well as the total count of chronic conditions. Mediation analyses suggest that part of the effect of childhood disadvantage (10%) on multimorbidity is mediated by higher SES in adulthood, while extensive sensitivity analyses suggest that omitted confounding is very unlikely. In the second study, we found that childhood disadvantage is associated with low performance in memory tests and semantic verbal fluency tests among older Brazilians. Adulthood SES fully mediated the association between all domains of childhood disadvantage and memory performance and only partially mediated its association with verbal fluency. The last study found that out of the 65 possible associations between single exposure and outcome variables, 24 were found to be statistically significant. Although the SenseMakr framework does not provide thresholds to support any mechanistic conclusion as it is not possible to establish universal cutoff values for its robustness measures, this approach can be highly useful in other observational studies of aging and the life course.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".