Traffic related activity pattern of Chinese adults: a nation-wide population based survey.

Abstract

Traffic-related air pollutants lead to increased risks of many diseases. Understanding travel patterns and influencing factors are important for mitigating traffic exposures. However, there is a lack of national large-scale research. This study aimed to evaluate the daily travel patterns of Chinese adults and provide basic data for traffic exposure and health risk research. We conducted the first nation-wide survey of travel patterns of adults (aged 18 and above) in China during 2011-2012. We conducted a cross-sectional study based on a nationally representative sample of 91, 121 adults from 31 provinces in China. We characterized typical travel patterns by cluster analysis and identified the associated factors of each pattern using multiple logistic regression and generalized linear regression models. We found 115 typical daily travel patterns of Chinese adults and the top 11 accounted for 94% of the population. The interaction of age, urban and rural areas, income levels, gender, educational levels, city population and temperature affect people's choice of travel patterns. The average travel time of Chinese adults is 45 ± 40 min/day, with the longest travel time by the combination of walking and car (70 min/day). Gender has the largest effect on travel time (B = -8.94, 95% CI: -8.95, -8.93), followed by city GDP (B = -4.23, 95% CI: -4.23, -4.22), urban and rural areas (B = -3.62, 95% CI: -3.63, -3.61), age (B = -2.21, 95% CI: -2.21, -2.2), educational levels (B = -1.53, 95% CI: -1.53, -1.52), city area (B = -1.4, 95% CI: -1.4, -1.39) and temperature (B = 1.21, 95% CI: 1.2, 1.21). This study was the first nation-wide study on traffic activity patterns in China, which provides basic data for traffic exposure and health risk research and provides the basis for the state to formulate transportation-related policies.