Abstract

CALAFAT FAR, Amador; ADROVER ROIG, Daniel; JUAN JEREZ, Montserrat  and  BLAY FRANZKE, Nicole T.. Relationship between alcohol, drug use and traffic accidents related to nightlife among a Spanish youth sample in three Autonomous Communities in 2007. Rev. Esp. Salud Publica [online]. 2008, vol.82, n.3, pp.323-331. ISSN 2173-9110.

Background: The phenomenon known as binge drinking and other drug abuse frequently occurs among young people in nightlife-related areas. This study analyzes the risk behaviours and the accident rate related to alcohol and other drugs among a sample of young people involved in nightlife. Method: A total of 440 young people from 3 Spanish Autonomous Communities took part. The sample size was estimated by means of Respondent Driven Sampling. The statistical analyses mined frequencies and measurements of the relationship of driving risk-related behaviour in relation to the accident rate, number of cases of drunkenness, frequency of accidents during the past month, influence of gender and age, as well as the predictiveness of these variables as regards the accident rate. Results: A total of 50.2% of these young people had gotten into a vehicle with a driver who was drunk and/or under the influence of drugs, 23.2% has driven when drunk and 23.5% under the influence of drugs. The greater the degree of involvement in nightlife, the higher the frequency of drunkenness [ chi² (9)=112.24; p< .000 ] the greater the number of cases of drunkenness, the higher the frequency of thes behaviors: getting into a vehicle with drivers who are drunk or under the influence of drugs [ c²=36,442, (3) p<0.001 ], drunken driving [ chi² =23,748, (3) p<0.001 ] and driving while under the influence of drugs [ chi²=23,816 (3) p<0.001 ]. The regression analysis highlighted drunken driving (odds-ratio=5.4) as the risk behaviour most related to traffic accidents. Conclusions: There is a high incidence of risk behaviours while driving vehicles. Drunkenness, drug use and involvement in nightlife increase the frequency of these behaviours. Drunken driving was the best accident predictor.

Keywords : Accidents; traffic; Accident Prevention; Youth; Alcohol; Illicit drugs; Drinking.

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