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131 Unintentional injuries in native american reservation communities: problems and solutions
  1. Wendy Shields1,
  2. Anne Kenney2
  1. 1US Johns Hopkins Centre for Injury Research and Policy
  2. 2US Johns Hopkins Centre for American Indian Health


Introduction Injuries are the leading cause of death for American Indians (AI) ages 1–44 and the third leading cause of death overall. Despite well documented injury mortality rates among AI reservation communities, there is little published on causes of injury deaths and non-fatal injuries. The overall aim of this study is to describe unintentional injury patterns among AIs living in reservation communities and to describe prevention strategies used to address leading causes of injury.

Methods Existing injury mortality data available in ‘Indian Health Focus: Injuries 2015 Edition’ and injury morbidity data provided by Indian Health Service’s (IHS) Division of Program Statistics was tabulated by age, injury type and IHS service until. Injury morbidity and mortality rates were calculated and descriptive tables were generated. A literature review was conducted to identify injury prevention strategies used in both Native and non-Native communities that address leading causes of injury morbidity and mortality.

Results Between 2007–2009 the unintentional injury death rate among AI/AN communities (156.6/100,000) was 2.4 times higher the rate for US all races (39.2/100,000). The leading cause of injury death was motor vehicle crashes and was highest among AI/AN males. Between 2007–2009 the motor vehicle related death rate among AI/AN males (51.4/100,000) was 2.7 times the rate for US males all races (18.9/100,000). Poisoning was the second leading cause of unintentional injury deaths. The poisoning death rate among AI/AN (29.3/100,000) was 2.7 times the rate for US all race (2.2/100,000). Falls and drowning were the third and fourth leading causes of death. Morbidity data from IHS will also be presented.

Conclusion Findings from this research will directly benefit injury prevention efforts in AI reservation communities, whose leadership has identified the need for ongoing and systematic data analytics to better inform community-based prevention interventions.

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