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Using Rural⁻Urban Continuum Codes (RUCCS) to Examine Alcohol-Related Motor Vehicle Crash Injury and Enforcement in New York State.
Pressley, Joyce C; Hines, Leah M; Bauer, Michael J; Oh, Shin Ah; Kuhl, Joshua R; Liu, Chang; Cheng, Bin; Garnett, Matthew F.
Afiliação
  • Pressley JC; Departments of Epidemiology and Health Policy and Management and Center for Injury Epidemiology and Prevention at Columbia, Columbia University, New York, NY 10032, USA. jp376@cumc.columbia.edu.
  • Hines LM; Bureau of Occupational Health and Injury Prevention, New York State Department of Health, Albany, NY 12237, USA. leah.hines@health.ny.gov.
  • Bauer MJ; Bureau of Occupational Health and Injury Prevention, New York State Department of Health, Albany, NY 12237, USA. Michael.bauer@health.ny.gov.
  • Oh SA; Department of Epidemiology, Columbia University, New York, NY 10032, USA. so2461@caa.columbia.edu.
  • Kuhl JR; Department of Epidemiology, Columbia University, New York, NY 10032, USA. jkuhl650@gmail.com.
  • Liu C; Department of Epidemiology, Columbia University, New York, NY 10032, USA. nkchangliu@gmail.com.
  • Cheng B; Department of Biostatistics, Columbia University, New York, NY 10032, USA. bc2159@cumc.columbia.edu.
  • Garnett MF; Bureau of Occupational Health and Injury Prevention, New York State Department of Health, Albany, NY 12237, USA. matthew.garnett@health.ny.gov.
Article em En | MEDLINE | ID: mdl-30991657
ABSTRACT
Rural areas of New York State (NYS) have higher rates of alcohol-related motor vehicle (MV) crash injury than metropolitan areas. While alcohol-related injury has declined across the three geographic regions of NYS, disparities persist with rural areas having smaller declines. Our study aim was to examine factors associated with alcohol-related MV crashes in Upstate and Long Island using multi-sourced county-level data that included the Crash Outcome Data Evaluation System (CODES) with emergency department visits and hospitalizations, traffic citations, demographic, economic, transportation, alcohol outlets, and Rural-Urban Continuum Codes (RUCCS). A cross-sectional study design employed zero-truncated negative binominal regression models to assess relative risks (RR) with 95% confidence interval (CI). Counties (n = 57, 56,000 alcohol-related crashes over the 3 year study timeframe) were categorized by mean annual alcohol-related MV injuries per 100,000 population low (24.7 ± 3.9), medium (33.9 ± 1.7) and high (46.1 ± 8.0) (p < 0.0001). In multivariable analyses, alcohol-related MV injury was elevated for non-adjacent, non-metropolitan counties (RR 2.5, 95% CI 1.6-3.9) with higher citations for impaired driving showing a small, but significant protective effect. Less metropolitan areas had higher alcohol-related MV injury with inconsistent alcohol-related enforcement measures. In summary, higher alcohol-related MV injury rates in non-metropolitan counties demonstrated a dose-response relationship with proximity to a metropolitan area. These findings suggest areas where intervention efforts might be targeted to lower alcohol-related MV injury.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: População Rural / População Urbana / Ferimentos e Lesões / Consumo de Bebidas Alcoólicas / Acidentes de Trânsito / Aplicação da Lei / Intoxicação Alcoólica Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: População Rural / População Urbana / Ferimentos e Lesões / Consumo de Bebidas Alcoólicas / Acidentes de Trânsito / Aplicação da Lei / Intoxicação Alcoólica Idioma: En Ano de publicação: 2019 Tipo de documento: Article