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PA 09-3-0747 The burden of non-fatal unintentional drownings in the united states, 2010–2014
  1. Michael Ballesteros,
  2. Erin M Parker,
  3. Erin K Sauber-Schatz,
  4. Likang Xu
  1. National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, USA


Background Drowning is a well-known leading cause of injury death among young people. Less information about U.S. drowning morbidity has been reported because, compared to fatal data, non-fatal data are less accessible. The purpose of this study was to describe non-fatal drowning in the United States.

Methods We analyzed two databases from the Healthcare Cost and Utilization Project: the Nationwide Emergency Department Sample (NEDS) and the National Inpatient Sample (NIS). These databases yield national estimates for emergency department visits and hospital inpatient stays. We identified non-fatal unintentional drowning cases from 2010–2014 using ICD-9-CM diagnosis and external cause codes (994.1, E830, E832, or E910). Patients who died were excluded. We performed descriptive analyses to estimate case counts and incidence rates per 1 00 000 population by age, sex, and region of the country.

Results Over our study period, we found an average number of 9039 non-fatal drowning emergency departments visits (rate=2.9 per 1 00 000 population) and another 2720 hospitalizations (0.9). Overall numbers and rates did not change substantially over time. Incidence rates for males (NEDS: 3.6; NIS: 1.2) were greater than females (NEDS: 2.2; NIS: 0.6), and rates among those 0–4 years of age (NEDS: 14.0; NIS: 4.4) were over three times greater than all other age groups. Incidence rates were higher in the South (NEDS: 3.0; NIS: 1.1) and West (NEDS: 3.6; NIS: 1.1) compared with other regions of the country. The average length of stay for hospitalized patients was 4.7 days.

Conclusions We found previously unreported outpatient and inpatient burden for non-fatal unintentional drowning in the United States. Understanding the drowning issue requires looking at both mortality and morbidity, and targeting prevention strategies should be based on all available burden data. Our findings underscore the need to tailor interventions by sex, age, and region.

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