Gender-Specific Associations between Late-Life Disability and Socioeconomic Status: Findings from the International Mobility and Aging Study (IMIAS)
Bibliographic record
Abstract
Disability is a dynamic process and can be influenced by a sociocultural environment. This study aimed to determine whether the associations between socioeconomic status and late-life disability differ by gender in a multi-sociocultural sample from different countries. A cross-sectional study was developed with 1362 older adults from The International Mobility in Aging Study. Late-life disability was measured through the disability component of the Late-Life Function Disability Instrument. Level of education, income sufficiency and lifelong occupation were used as indicators of SES. The results indicated that a low education level β = -3.11 [95% CI -4.70; -1.53] and manual occupation β = -1.79 [95% -3.40; -0.18] were associated with frequency decrease for men, while insufficient income β = -3.55 [95% CI -5.57; -1.52] and manual occupation β = -2.25 [95% CI -3.89; -0.61] played a negative role in frequency for women. For both men β = -2.39 [95% -4.68; -0.10] and women β = -3.39 [95% -5.77; -1.02], insufficient income was the only factor associated with greater perceived limitation during life tasks. This study suggested that men and women had different late-life disability experiences. For men, occupation and education were associated with a decrease in the frequency of participation, while for women this was associated with income and occupation. Income was associated with perceived limitation during daily life tasks for both genders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".