Association of Material Deprivation Status, Access to Health Care Services, and Lifestyle With Screening and Prevention of Disease, Montreal, Canada, 2012
Bibliographic record
Abstract
INTRODUCTION: The objective of this study was to provide information on the effect of disparities in material deprivation, access to health care services, and lifestyle on the likelihood of undergoing screening for disease prevention. METHODS: We used data from a probability sample (N = 10,726) of the Montreal population aged 15 years or older and assessed 6 dependent variables (screening for breast cancer, cervical cancer, colon cancer, blood glucose, and high blood pressure and receipt of the seasonal influenza vaccination), and 3 independent variables (disparities in material deprivation, access to health care services, and personal lifestyle habits). We used logistic regression to analyze data and determine associations. RESULTS: Use of preventive health services increased as material deprivation declined, access to health care improved, and lifestyle habits became healthier. The combined effect of household income, an individual measure, and the material deprivation index (consisting of quintiles representing a range from the most privileged [quintile 1: best education, employment, and income] to the most deprived [quintile 5: least education, employment, and income) an ecological measure, showed that having a Papanicolaou test was significantly associated with high annual household income (≥$40,000) even if the woman resided in a deprived neighborhood (quintiles 4 and 5 of the material deprivation index) (odds ratio [OR], 1.38; 95% confidence interval (95% [CI], 1.04-1.84), whereas odds of having a mammogram or influenza vaccination were significantly associated with living in a privileged neighborhood (quintiles 1, 2, and 3 of the material deprivation index) even among people with a low annual household income (<$40,000) (mammogram: OR, 1.54; 95% CI, 1.00-2.38; influenza vaccination: OR, 1.31; 95% CI, 1.04-1.66). CONCLUSION: In addition to influencing lifestyle habits and access to health care services, disparities in material deprivation influence whether a person uses preventive health services. Public health professionals need to establish screening outreach programs in socioeconomically disadvantaged neighborhoods to enhance public participation in disease prevention programs and reduce disparities in health.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.004 | 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".