Association between household food insecurity and mortality in Canada: a population-based retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Food insecurity affects 1 in 8 households in Canada, with serious health consequences. We investigated the association between household food insecurity and all-cause and cause-specific mortality. METHODS: We assessed the food insecurity status of Canadian adults using the Canadian Community Health Survey 2005-2017 and identified premature deaths among the survey respondents using the Canadian Vital Statistics Database 2005-2017. Applying Cox survival analyses to the linked data sets, we compared adults' all-cause and cause-specific mortality hazard by their household food insecurity status. RESULTS: Of the 510 010 adults sampled (3 390 500 person-years), 25 460 died prematurely by 2017. Death rates of food-secure adults and their counterparts experiencing marginal, moderate and severe food insecurity were 736, 752, 834 and 1124 per 100 000 person-years, respectively. The adjusted hazard ratios (HRs) of all-cause premature mortality for marginal, moderate and severe food insecurity were 1.10 (95% confidence interval [CI] 1.03-1.18), 1.11 (95% CI 1.05-1.18) and 1.37 (95% CI 1.27-1.47), respectively. Among adults who died prematurely, those experiencing severe food insecurity died on average 9 years earlier than their food-secure counterparts (age 59.5 v. 68.9 yr). Severe food insecurity was consistently associated with higher mortality across all causes of death except cancers; the association was particularly pronounced for infectious-parasitic diseases (adjusted HR 2.24, 95% CI 1.42-3.55), unintentional injuries (adjusted HR 2.69, 95% CI 2.04-3.56) and suicides (adjusted HR 2.21, 95% CI 1.50-3.24). INTERPRETATION: Canadian adults from food-insecure households were more likely to die prematurely than their food-secure counterparts. Efforts to reduce premature mortality should consider food insecurity as a relevant social determinant.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".