Pediatric Bathtub Drownings in Ontario from 2003 to 2022: A Case Series
Bibliographic record
Abstract
In Canada, bathtub-related drowning events account for 10% of all drownings requiring hospitalization, with fatality rates of approximately 1.3 per 1 000 000 persons per year.1 Lack of adequate supervision, co-bathing, bath seats, and medical conditions have been identified as risk factors.2 This study aimed to determine the incidence of fatal unintentional pediatric bathtub drownings in Ontario from 2003 to 2022 and describe demographic and circumstantial factors.This study is a case series of all unintentional fatal pediatric bathtub drownings in Ontario, Canada, between January 1, 2003, and December 31, 2022. Any child (0–18 years) whose cause of death was determined to be the result of drowning in a bathtub was included. Cases were reviewed by forensic pathologists using coroners’ records for all deaths in children attributed to drowning in a bathtub or when the deceased was discovered unresponsive or dead in a bathtub. Coroners’, police, and autopsy reports were used to extract data. Annual crude rates of pediatric bathtub drownings per 1 000 000 children were used to determine incidence rates. The Ontario Marginalization Index was used to determine area-level marginalization quintiles.3 Descriptive statistics were performed. The study was approved by the University of Toronto Human Research Ethics Unit.We identified 47 unintentional childhood/adolescent bathtub drownings during the 20-year period. Fifty-five percent of unintentional pediatric drownings occurred in children aged younger than 24 months and 17% in adolescents aged older than 14 years. Lapse of supervision was reported in all 47 cases. More than a quarter (28%) of the fatalities were among children residing in neighborhoods in the greatest material deprivation quintile (Table 1). The annual incidence rate for unintentional pediatric bathtub drownings ranged from 0 to 2.71 per 1 000 000 children (age 0–14 years) from 2003 to 2022 with a mean incidence rate of 1/1 000 000 (Figure 1). During this study period, 76% of drownings occurred in children aged no more than 5 years. Among children aged 2–5 years, 8 (80%) had a seizure disorder. Two-thirds (18/27) reported a lapse in supervision of no more than 5 minutes, and a lapse of no more than 30 seconds was reported in 4 fatalities. Half of the children in this study were co-bathing with a sibling. Eight adolescents died by unintentional bathtub drowning, of whom 63% had a known seizure disorder. Two had a positive toxicology screen for street drugs, and 2 were noncompliant with their anticonvulsant medications.This is the first study describing all unintentional pediatric bathtub drownings in Canada’s most populous province. This study has four main findings. First, the incidence has remained relatively stable over the last 20 years. Second, lapses in supervision remain a significant risk factor. Third, co-bathing continues to provide false reassurance. Fourth, seizure disorders are common among older children that drown in bathtubs.Although admittedly rare, pediatric bathtub drownings have failed to demonstrate the same decline in incidence when compared with other high-profile public health campaigns in Canada.4–9 The relatively static bathtub drowning rates of the past 20 years raise the question of renewed and revised public health messaging10 to mitigate these rare but preventable fatalities.In 2006, the 20-year single-center review of accidental pediatric bathtub drownings by Somers et al identified lack of adequate supervision, co-bathing, and bath seats as risk factors.2 These same factors persist 20 years later. Lapse in supervision, frequent in many childhood injuries, remains the most important factor to stress in bath safety education.Seizure disorder is a well-described risk factor for fatalities within bodies of water.11,12 In this study, 38% of cases had a known seizure disorder, including 63% of adolescents. Despite widespread education on the importance of water safety among those with a history of seizures,13,14 these data further highlight the importance of safety counselling for children with seizure disorders.The limitations of this study include that police reports, subject to recall bias, often relied on bystander recollection of traumatic events. Also, the lack of standardized reporting may have introduced observation bias.In conclusion, incidence rates in Ontario have remained relatively stable in Ontario from 2003 to 2022. This study highlights that no duration of supervision lapse is safe and co-bathing with an older sibling is not protective. Findings suggest that public health messaging regarding bath safety requires a renewed approach, perhaps using readily accessible online platforms and social media.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".