Risk factors for cytomegalovirus seropositivity in a population of day care educators in Montréal, Canada
Bibliographic record
Abstract
BACKGROUND: Horizontal transmission of cytomegalovirus (CMV) is common in the day care setting. Day care educators appear to be at a high risk of infection; however, studies are limited. AIMS: To determine the proportion of CMV-seropositive female educators in the day care setting and to identify associated risk factors. METHODS: Educator- and day care-level risk factors for CMV seropositivity were obtained by questionnaires from day care educators and directors, respectively. Sera were collected from educators and analyzed by enzyme-linked immunosorbent assay. Significant independent risk factors for CMV seropositivity were determined using a multivariable logistic regression model which was fitted using the generalized estimating equation method. RESULTS: CMV seroprevalence in 473 female educators from 81 day care centers in Montréal, Canada, was 57%. Significant risk factors for CMV seropositivity were (i) increasing age (OR5-yr = 1.19; 95% CI = 1.05-1.35), (ii) low-income country of birth (OR = 10.23; 95% CI = 2.64-39.50) or middle-income country of birth (OR = 4.99; 95% CI = 2.39-10.40), (iii) having > or =2 children of their own (OR = 1.98; 95% CI = 1.19-3.31) and (iv) child-to-educator ratio >6 (18-35 months old) in a day care center (OR = 1.87; 95% CI = 1.25-2.81). CONCLUSIONS: Day care educators have risks for CMV infection related to their work in the day care setting, as well as personal risk factors. A review of current guidelines for the prevention of CMV infection in day care is needed to ensure that recommendations are evidence based.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".