Association of Housing Conditions and Social Determinants of Health with Chronic Bronchitis among Seniors in Two Saskatchewan First Nation communities.
Bibliographic record
Abstract
ABSTRACT \nBackground: Respiratory illnesses are common in elderly populations and are strong predictors of death that increase with age. Chronic bronchitis is a common respiratory issue in the senior populations in Canada, with some indication that it may be more prevalent in the senior First Nation population. Poor housing conditions have been identified as a potential determinant of chronic bronchitis, with many reserves having a high proportion of such homes that are overcrowded, have issues with mold growth, and need major repairs. Additionally, other determinants of health such as income, unhealthy habits, and colonization could negatively impact respiratory health. \nMethods: Multivariable logistic regression was used to analyze data collected during the First Nations Lung Health Project (2012-2018), which was conducted in collaboration with two First Nation communities in Saskatchewan. Participants completed household and individual health questionnaires. Household questionnaires collected information about housing condition, dampness, visible mold, and housing repairs due to water damage; individual questionnaires collected information regarding colonization, current health status, and income levels. Data for this thesis came from two cross-sectional studies, collected at two time points: once in 2012 and again in 2016, with 1318 participants overall. Of these 1318 participants, 168 were 55 years and older, which was the senior population from the two communities included in this study. \nResults: The factors that emerged as significant to participants reporting chronic bronchitis or chronic bronchitis symptoms were having not enough or just enough income at the end of any given month, smoking status, people smoking in the house, and attending a residential school. Housing conditions were found to not have significant impact on participants reporting chronic bronchitis diagnosis or symptoms. \nPublic Health Implications: Research on the determinants and outcomes of the health of Indigenous seniors is limited but increasing in response to the recognition that this is a growing demographic about whom there is limited knowledge. This study contributes some information on associations between determinants of health and chronic bronchitis \n\n \n \niv \n \nin First Nation seniors living on reserve, particularly in identifying determinants that are amenable to intervention.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".