Public Health Unit Funding Per Capita and Type 2 Diabetes Among Adults in Ontario in 2013/14
Bibliographic record
Abstract
Background: Type 2 diabetes is one of the biggest public health concerns. Area-level and individual-level risk factors can influence the likelihood of an individual developing the disease. In recent years, there have been observational studies in the United States, and to a lesser extent the United Kingdom, on the potential benefits public health funding can have on population health outcomes. Very few studies have looked at this relationship from a Canadian context, with none examining type 2 diabetes as the health outcome. This study will examine the estimated association between public health unit funding per capita and type 2 diabetes risk, and whether an increase in public health unit funding per capita can help improve health equity across income groups. Methods: This cross-sectional study utilized data from the 2013/14 cycle from the Canadian Community Health Survey, an annual population survey from Statistics Canada. Public Health Unit funding data was provided from the 2013 Public Health Funding Model for Mandatory Programs report. Per capita funding figures were created by utilizing the Canadian Census Population Estimates from 2011. To analyze the association between public health unit funding and risk for type 2 diabetes, multilevel logistic regression modelling was utilized via a step-up approach. Cross-level interaction for household income and PHU funding per capita was also tested to examine heterogeneity in the association across sociodemographic groups. Results: The relationship found between public health unit funding and type 2 diabetes was statistically non-significant, with an increase in odds for type 2 diabetes in the fully adjusted model (OR: 1.14; 95% CI: 0.98, 1.34). Cross-level interaction on PHU funding per capita and household income in the final model showed a statistically non-significant association for all income levels except for those at $40,000 to $60,000 (OR: 0.76; 95% CI: 0.61, 0.94). Only the $20,000 to $40,000 income group had an odds ratio over one in the fully adjusted model (OR: 1.07; 95% CI: 0.81, 1.40). Conclusion: Contrary to previous literature, public health unit funding per capita was associated with an increase in odds for type 2 diabetes among adults in Ontario in 2013/14. However, the findings also showed that there might be a potential protective effect with PH funding per capita among those at lower income levels. Further research should be undertaken to have a clearer idea of the relationship between public health funding and type 2 diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".