Household Food Insecurity Among Older People in Canada: the Exploration of a Public Health Issue Rendered Invisible
Bibliographic record
Abstract
Food insecurity, an issue of inadequate or insecure access to food due to financial constraints, is under-researched among older people. Of this limited literature, the relevance of aging to food insecurity remains unclear. My goals with this thesis were to: i) synthesize and critically examine the literature on food insecurity and aging; ii) contribute a profile of food insecurity among older people to the population estimates of food insecurity in Canada; and iii) examine more closely key predictors of food insecurity among older people in Canada. I undertook a scoping study, and characterized this collection of literature by methodological, empirical, and conceptual contributions. Population estimates varied greatly between studies, with an overall emphasis on individual risk and experience, alongside attempts to explicate a perceived complexity of this issue with respect to health. Of the very limited inclusion or application of theory overall, most emphasis was placed on frameworks of disease and disability, with many assumptions made about how aging relates to food insecurity. Taken together, these findings suggest a strong tendency towards biomedicalization. The two subsequent empirical studies involved the use of data from the Canadian Community Health Survey (CCHS). In the second manuscript I found the overall prevalence of food insecurity among older Canadians to be 2.4%, and using a generalized linear model in the second manuscript, I found sex, age, racial background, self-perceived health, marital status, living arrangement, and low household income to be predictive of food insecurity. In the third manuscript, logistic regression revealed that women are at greater risk of food insecurity and this inequity largely operates through household income. Younger old people were most vulnerable to food insecurity, and age modified the relationship between household income and food insecurity. In the discussion chapter I offer a brief political-historical context of hunger and aging in Canada, explore the relevance and implications of the major findings from each study, and demonstrate the connection between consistent monitoring of food insecurity in exploring the geographic heterogeneity of this issue. Overall, I argue that, like younger populations, food insecurity among older people is an income-based issue.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.013 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".