Determinants of Mortality Among Older Adults by Area-Level Material and Social Deprivation
Bibliographic record
Abstract
Abstract Although social inequalities are increasing worldwide, few studies have examined their consequences on mortality among older adults. The aim of this research was to examine determinants of mortality among older adults at the individual, health system and area level. Data come from the ESA-Services study conducted in 2011-2013 in Quebec including 1,765 adults aged ≥65 years. Mortality 3 years after the survey interview was obtained from vital statistics data. Material and social deprivation of area of residence was determined using the Pampalon index categorized into quintiles as follows: least deprived (1st quintile), middle quintiles (2nd, 3rd, 4th quintiles), most deprived (5th quintile). Other variables included clinical, psycho-behavioural, socio-economic and demographic factors. Cox regressions were used to examine the determinants of mortality while stratifying by level of area deprivation. Compared to most deprived areas, mortality was higher for those living in middle quintiles of deprivation. In the overall analyses, age, chronic conditions, social support and continuity of care were associated with mortality. When examining mortality by area of deprivation, results showed higher mortality ratios with cognitive impairment in middle and least deprived areas. In least deprived areas, female sex, the presence of bipolar disorder and dementia were associated with mortality. The strong associations between mortality, cognition, dementia, bipolar disorder and female sex in least deprived areas might be partially explained by a closer follow-up and earlier detection of this population. Continuity of care was also associated with significantly lower mortality ratios for those living in middle and most deprived areas.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".