Using real-time data from portable air pollutant sensors and smartphone Global Positioning System trajectories collected in Beijing, China, this study demonstrates how smart technologies and individual activity-travel microenvironments affect the assessment of individual-level pollution exposure in space and time at a very fine resolution. It compares three different types of individual-level exposure estimates generated by using residence-based monitoring station assessment, mobility-based monitoring station assessment, and mobility-based real-time assessment. Further, it examines the differences in personal exposure to PM_2.5 associated with different activity places and travel modes across various environmental conditions. The results show that the exposure estimates generated by monitoring station assessment and real-time sensing assessment vary substantially across different activity locations and travel modes. Individual-level daily exposure for residents living in the same community also varies significantly, and there are substantial differences in exposure levels using different approaches. These results indicate that residence- or mobility-based monitoring station assessments, which cannot account for the differences in air pollutant exposures between outdoor and indoor environments and between different travel-related microenvironments, could generate considerably biased estimates of personal pollution exposure. Key Words: indoor environment, real-time exposure to air pollution, smart technologies, travel modes, the uncertain geographic context problem.

Mental health is an exceedingly prevalent concern for the urban population. Mounting evidence has confirmed the plausibility of high incidences of mental disorders in socioeconomically disadvantaged neighborhoods. However, the association between the neighborhood built environment and individual mental health is understudied and far from conclusive, especially in developing countries such as China. The underlying mechanism requires in-depth analysis combining potential intermediates such as perceived environmental disorder and supportive social relationships. Using a health survey conducted in Beijing in 2017, this study investigates for the first time a socio-environmental pathway through which perceived disorder and social interaction account for the relationship between the built environment and mental health under the very notion of the neighborhood effect. The results from multilevel structural equation models indicate that individual mental health is influenced by the neighborhood-scale built environment through three pathways, independent of neighborhood socioeconomic disadvantages: (1) proximity to parks is the sole indicator directly linked to mental health; (2) population density, road connectivity and proximity to parks are indirectly associated with mental health through interactions with neighbors; and (3) population density, road connectivity and facility diversity are partially associated with perceived neighborhood disorder, which is indirectly correlated with mental health through interactions with neighbors. This study is a preliminary attempt to disentangle the complex relationships among the neighborhood environment, social interaction and mental health in the context of developing megacities. The relevant findings provide an important reference for urban planners and administrators regarding how to build health-supportive neighborhoods and healthy cities.

Adolescence to early adulthood is a period of multiple life transitions. These transitions, along with changing resources and contexts, could contribute to significant changes in diet, which may persist into later adulthood. We investigated diet quality trajectories from age 15 to 31 y and changes in diet quality associated with life transitions by sex. Data from the Project EAT (Eating and Activity in Teens and Young Adults) study in Minnesota, the United States were used to examine diet quality among a longitudinal cohort (n = 2524) across 4 waves (mean ages of 15, 19, 25, and 31 y). Average within-person changes in DASH (Dietary Approaches to Stop Hypertension) scores were analyzed using sex-specific latent growth models, incorporating underlying growth trajectories, 5 life transitions, and baseline sociodemographic and health characteristics. Both sexes followed a quadratic trajectory of DASH scores, showing decreases in diet quality from Wave 1 to 2 followed by increases until Wave 4. However, males had increasingly worse diet quality than females. Compared with no such transition, leaving the parental home between Waves 1 and 2, was associated with transient decreases in diet quality at Wave 2 only for males (β: −2.34; 95% confidence interval [CI]: −3.57, −1.11). For females, cohabitating with a partner and becoming a parent between Waves 3 and 4 were related to decreases (β: −1.96; 95% CI: −3.45, −0.47) and increases (β: 1.85; 95% CI: 0.47, 3.23), respectively, in diet quality at Wave 4. Leaving full-time education and starting full-time employment showed negative and positive associations, respectively, with long-term diet quality for both sexes. Diet quality remained suboptimal throughout adolescence and improved across early adulthood. Targeted dietary interventions are welcome for young people who leave their parental home early or do not enter a structured school or workplace environment and for addressing sex differences in diet quality associated with family-related life transitions.