Abstract
Normally, bars and restaurants are the preferred locations for drinking. Therefore, there is concern that the roads in bar and restaurant areas could have a higher probability of drink-drivers and alcohol-related road crashes. Many studies have been conducted to model the association between drinking locations and the prevalence of drink-driving, so that cost-effective enforcement strategies can be developed to combat drink-driving. In this study, a cluster analysis approach was applied to model the spatial-temporal variation of drink-driving distribution in Hong Kong. Six spatial-temporal clusters of drink-driving distribution emerged from the data: (i) bar and restaurant area, weekend-overnight; (ii) bar and restaurant area, other timespan; (iii) urban area, weekend-overnight; (iv) urban area, other timespans; (v) rural area, weekend-overnight; and (vi) rural area, other timespans. Next, separate zero-inflated regression models were established to identify the factors contributing to the prevalence of drink-driving for each of the six recognized clusters. The results indicated that drivers in rural areas tend to consume more alcohol than those in urban areas, regardless of the time period. In addition, both seasonal variation and vehicle class were found to determine the breath alcohol concentration (BrAC) levels among drivers.
| Original language | English |
|---|---|
| Pages (from-to) | 415-424 |
| Number of pages | 10 |
| Journal | Accident Analysis and Prevention |
| Volume | 59 |
| DOIs | |
| Publication status | Published - 5 Aug 2013 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Cluster analysis
- Drink-driving
- Random breath test
- Zero-inflated regression model
ASJC Scopus subject areas
- Human Factors and Ergonomics
- Safety, Risk, Reliability and Quality
- Public Health, Environmental and Occupational Health
- Law
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