Examining Associations between Sociodemographic, Behavioural, Environmental, Risk Determinants and Multimorbidity
Bibliographic record
Abstract
Multimorbidity, defined as having 2 or more chronic conditions, is a global phenomenon with high prevalence in Canada and the province of Ontario. Multimorbidity has been associated with various social, health and economic costs. While research has been conducted determining key indicators and their associations with multimorbidity; studies using a comprehensive list of determinants, including environmental factors have been far fewer. The overall aim of this thesis was to evaluate potential relationships between sociodemographic, lifestyle behavioural, environmental determinants, and risk conditions, identified by the Chronic Disease Indicator Framework. The first study examined the association between various dimensions of marginalization and multimorbidity. The second study examined multiple indicator variables and their associations with multimorbidity and healthcare utilization costs. The third study examined neighbourhood walkability as part of the built environment, and impact of various exposures, in a time to event analysis (becoming multimorbid) for a period of 16 years. Study findings suggest that nearly a third of the Ontario population are multimorbid. Of the four dimensions identified by the Ontario Marginalization Index, material deprivation was highly correlated with multimorbidity and higher cost chronic conditions. Out of all determinant variables, age, self-perceived health, body mass index and income, were significantly associated with multimorbidity and showed the largest magnitudes. Cost of care has risen by 21% during the study period, with greater morbidity, number of conditions, and healthcare utilization costs, associated with the lowest income populations. There was an observed relationship between most walkable neighbourhoods and lower body mass index. The least walkable neighbourhoods had significantly higher risk for multimorbidity. The high-risk approach currently adopted by the health establishment, which targets patients with health risks and markers for future illness, has not been effective at slowing multimorbidity in the population. A more progressive population strategy is needed, that features more radical measures of prevention to help reduce the rise in chronic illness across the life course. The built environment may be a valuable part of a wider prevention strategy. Walkable neighbourhoods that promote greater physical activity may aid in prevention, by reducing obesity at the population level to reduce incidence of multimorbidity.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".