Spatial-temporal analysis of drink-driving patterns in Hong Kong

Accid Anal Prev. 2013 Oct;59:415-24. doi: 10.1016/j.aap.2013.06.033. Epub 2013 Jul 4.


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.

Keywords: Cluster analysis; Drink-driving; Random breath test; Zero-inflated regression model.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alcohol Drinking / epidemiology*
  • Alcoholic Intoxication / diagnosis
  • Alcoholic Intoxication / epidemiology*
  • Automobile Driving / statistics & numerical data*
  • Breath Tests
  • Cluster Analysis
  • Ethanol / analysis
  • Female
  • Geographic Mapping
  • Hong Kong / epidemiology
  • Humans
  • Male
  • Regression Analysis
  • Space-Time Clustering
  • Time Factors


  • Ethanol