Understanding the association between unmet dental care needs and household food security status among older people in Ghana
Bibliographic record
Abstract
The literature recognizes food insecurity as a barrier to access to health care services. However, we know very little about the association between food insecurity and unmet dental care needs among older people in Ghana. To address this void in the literature, this study uses a representative survey of adults aged 60 or older from three regions in Ghana to examine whether older people who experienced household food insecurity differently report unmet dental care needs in comparison to their counterparts without any food insecurity. We find that 40% of older adults reported unmet dental care needs. Results from logistic regression analysis show that older people who experienced severe household food insecurity were more likely to report unmet dental care needs, compared to those who did not experience any type of food insecurity, even after accounting for theoretically relevant variables (OR = 1.94, p < 0.05). Based on these findings, we discuss several implications for policymakers and directions for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".