ArticleEnvironmental health and preventive medicine2025
Seasonal variations in bathtub drowning deaths and the impact of outdoor temperatures: a nationwide time-series analysis with future projections.
Article in Environmental health and preventive medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Acute Heat Exposure-Related Illness: A Unified Emergency Medicine Framework for Hot Baths, Hot Springs, and Saunas-A Narrative Review.Journal of clinical medicine · 2026Review
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4 authors.
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Abstract
backgroundGlobally, Japan has the highest drowning mortality among older adults, largely because of bathing customs. Although this mortality rate peaks in winter, the nationwide impact of outdoor temperature has not been quantified, and whether specific days carry greater risks for bathtub drowning deaths remains unclear. Therefore, we aimed to address these gaps using nationwide data from Japan.
methodsWe collected daily data on outdoor temperatures and bathtub drowning deaths (from death certificates), along with population data, across 47 prefectures from 1995-2020. A time series regression model incorporating a cyclic spline for day-of-year and a cross-basis function for outdoor temperature was used to estimate seasonality and temperature attributable fractions (AFs). Prefecture-specific estimates were pooled using meta-analysis. National holidays were defined by the Act on National Holidays.
resultsDuring the study period, 99,930 home bathtub drowning deaths were recorded. The AF for seasonality modelled with a cyclic spline for day-of-year was 77.8% (empirical confidence interval [eCI]: 76.7-78.8%), which decreased to 15.3% (eCI: 13.1-18.0%) after adjusting for outdoor temperature, indicating that outdoor temperature accounted for 80.3% of the seasonal effect. Elevated risks were observed on Sundays (relative risk = 1.16, 95% CI: 1.12-1.20), holidays (1.12, 95% CI: 1.08-1.16), New Year's Day (1.72, 95% CI: 1.61-1.84), and New Year's Eve (1.63, 95% CI: 1.52-1.74) in the adjusted model, which included a cyclic spline for day-of-year and a cross-basis function for outdoor temperature.
conclusionOur findings highlight the importance of mitigating the impact of outdoor temperature on bath-related death risk. Identifying high-risk days can be used to help develop targeted preventive strategies.
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