ArticleFrontiers in public health2026
Ethnic cultural influences on driving risk: a mixed-methods analysis of Cantonese, Hakka, and Hoklo drivers in China.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: With the acceleration of globalization and inter-regional traffic, road accidents have become a leading cause of death worldwide. Drivers from outside ethnic cultural areas face greater traffic safety challenges compared to local drivers. While ethnic culture significantly shapes driving habits, its role in traffic safety remains under-researched, particularly within unified legal and infrastructural frameworks. This study addresses this gap by investigating the risk patterns of Cantonese, Hakka, and Hoklo drivers in Guangdong, China. Methods: Using a mixed-methods approach incorporating the induced exposure method to analyze traffic accident data from 2006 to 2010, we evaluate the interplay between individual, vehicle, and cultural factors. Specifically, we applied logistic regression to determine the odds of fault and Qualitative Comparative Analysis (QCA) to identify configurational risk pathways. Results: The logistic model revealed significant behavioral differences among the three ethnic groups, with factors such as occupation, vehicle use, and weather impacting the groups differently. Both regression analysis and QCA indicated that young drivers had a higher accident risk. Although gender, household registration, and occupations were not significant in the logistic models for Hakka and Hoklo groups, QCA showed these factors played crucial roles when combined with other elements. Discussion: This study uncovered multiple patterns in driving behavior across different ethnic cultures, enhancing the understanding of cultural influences on traffic accident risk. The findings reveal distinct cultural footprints in driving risks, offering a concrete basis for targeted, culturally-sensitive traffic interventions.
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