Language
English
Publication Date
10-14-2025
Journal
Injury Epidemiology
DOI
10.1186/s40621-025-00623-8
PMID
41088464
PMCID
PMC12522868
PubMedCentral® Posted Date
10-14-2025
PubMedCentral® Full Text Version
Post-print
Abstract
Background: It is difficult to study the epidemiology of drowning at the regional level because of multiple data sources, many of which have a high degree of unstandardized and missing data. We aimed to link multiple datasets to identify demographics and geographic locations of unintentional fatal drowning in a metropolitan region and compare linked data with vital statistic data.
Methods: This cross-sectional study included unintentional drowning fatalities among persons of all ages in metropolitan Houston between 2016 and 2022. Probabilistic linking was used to link multiple datasets and geographical mapping to identify drowning locations. The effectiveness of data linkage was assessed by the recall, precision, and F1-score (harmonic mean of precision and recall). Geographic location of drownings by aquatic body was studied. Drowning burden by demographics, county and aquatic body were compared between linked data and vital statistic data using Chi-square tests.
Results: Data from 8 datasets were linked. The linkage metrics were Recall (0.88-1.00), Precision (0.91-1.00), and F1-score (0.91-1.00) for datasets. There were 790 drowning fatalities. The median age was 40 years (IQR: 18.5,60); 71% were males. Children aged 0-17 years constituted 24% of drowning fatalities. Drownings occurred in swimming pools (27%), bathtubs (19%) natural water (27%), flood control structures (20%), and during flooding events (6%). Adults commonly drowned in natural water, flood control structures, bathtubs, and during flooding events whereas most toddlers drowned in swimming pools and hot tubs. No significant differences in counts by age group, sex, county of drowning and body of water were observed between linked and vital statistic data. Drowning locations were geocoded in 769 of 790 records (97%).
Conclusion: Probabilistic data linkage can accurately determine the epidemiology of fatal drowning in a metropolitan region. Identification of high-risk drowning subpopulations and locations can inform drowning countermeasures at the regional level.
Keywords
Probabilistic data linkage, Drowning burden, Geocoding, Drowning epidemiology
Published Open-Access
yes
Recommended Citation
Shenoi, Rohit P; Levine, Ned; Camp, Elizabeth A; et al., "Probabilistic Data Linkage to Study the Epidemiology of Unintentional Fatal Drowning in a Large Metropolitan Region" (2025). Faculty and Staff Publications. 5798.
https://digitalcommons.library.tmc.edu/baylor_docs/5798