Evidence map›Paper›PMID 41088464›Full record

ArticleInjury epidemiology2025

Probabilistic data linkage to study the epidemiology of unintentional fatal drowning in a large metropolitan region.

Rohit P Shenoi, Ned Levine, Elizabeth A Camp, Linh Nguyen, Sandra McKay, Shaila Zaman

Abstract read
In one paragraph

Article in Injury epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Rohit P ShenoiDivision of Emergency Medicine, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, 6621 Fannin St., Suite A 2210, Houston, TX, 77030, USA. rshenoi@bcm.edu.
Ned LevineNed Levine and Associates, Houston, TX, 77025, USA.
Elizabeth A CampDivision of Emergency Medicine, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, 6621 Fannin St., Suite A 2210, Houston, TX, 77030, USA.
Linh NguyenCenter for Population Health Management & Quality, Department of Healthcare Transformation Initiatives, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
Sandra McKayDepartment of Pediatrics at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
Shaila ZamanDivision of Emergency Medicine, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, 6621 Fannin St., Suite A 2210, Houston, TX, 77030, USA.

Funding

Centers for Disease Control and Prevention,United States U01 CE003504-01NCIPC CDC HHS U01 CE003504
6 · The paper itself

Abstract

backgroundIt 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.

methodsThis 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.

resultsData 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%).

conclusionProbabilistic 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.

Indexed as

Drowning burdenDrowning epidemiologyGeocodingProbabilistic data linkage

Identifiers

PMID41088464
PMCPMC12522868

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.