Bed bug infestations: prevalence, correlates, and cross-sectional association with psychological symptoms in a large sample of tenants in Montreal, Canada
Bibliographic record
Abstract
BACKGROUND: The resurgence of bed bugs is a major challenge to public health and housing authorities and is a social justice issue. Bed bugs are environmentally communicable, cause ill health, and decrease quality of life. Bed bug infestations are socially patterned, disproportionately affecting people facing vulnerability; they are more prevalent in high-density multi-unit housing environments. While bed bugs can cause cutaneous and allergic reactions along with other health reactions, the biggest health impacts of bed bugs appear to be psychological. To contribute to the limited number of studies documenting the prevalence of exposure to bed bugs and mental health impacts in general populations, this study reports on the prevalence of exposure to bed bugs in a large sample of tenants and measures the association between bed bug exposure and psychological symptoms. METHODS: This cross-sectional study set in Montreal, Canada, uses data on 5,000 tenants aged ≥ 18 years from the 2017 Montreal Housing Survey. Exposure to bed bugs in the year preceding the interview was self-reported by tenants. The 2-item Generalized Anxiety Disorder scale and the 2-item Patient Health Questionnaire-2 were used to measure anxiety and depression, respectively. Association between exposure to bed bugs and psychosocial symptoms was assessed using logistic regression adjusted for sociodemographic characteristics and housing conditions. RESULTS: Four percent of tenants reported being exposed to bed bugs in the year preceding the survey. In unweighted analysis, the odds of anxiety (OR: 1.72; 95%CI: 1.12, 2.64), depression (OR: 1.83; 95%CI: 1.20, 2.78), and anxiety and/or depression (OR: 1.69; 95%CI: 1.16, 2.44) were significantly higher for those exposed to bed bugs, independently of the sociodemographic characteristics and housing conditions of the survey respondents. In weighted analysis, the effect sizes were reduced. Exposure to bed bugs was marginally (p = 0.087) associated with higher odds of reporting anxiety and/or depression (OR: 1.53; 95%CI: 0.94, 2.50). CONCLUSIONS: Findings reinforce the significant social inequalities in exposure to bed bugs and contribute to growing evidence that bed bug exposure is a risk factor for psychological symptoms. Coordinated, intersectoral actions that are attentive to social justice issues are needed to monitor and control bed bug infestations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| 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".