Factors influencing time-location patterns and their impact on estimates of exposure: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

Abstract

We assessed time-location patterns and the role of individual- and residential-level characteristics on these patterns within the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) cohort and also investigated the impact of individual-level time-location patterns on individual-level estimates of exposure to outdoor air pollution. Reported time-location patterns varied significantly by demographic factors such as age, gender, race/ethnicity, income, education, and employment status. On average Chinese participants reported spending significantly more time indoors and less time outdoors and in transit than white, black, or Hispanic participants. Using a tiered linear regression approach, we predicted time indoors at home and total time indoors. Our model, developed using forward selection procedures, explained 43 percent of the variability in time spent indoors at home, and incorporated demographic, health, lifestyle, and built environment factors. Time-weighted air pollution predictions calculated using recommended time indoors from USEPA(1) overestimated exposures as compared to predictions made with MESA Air participant-specific information. These data fill an important gap in the literature by describing the impact of individual and residential characteristics on time-location patterns and by demonstrating the impact of population-specific data on exposure estimates.

Socioeconomic Disparities and Air Pollution Exposure: a Global Review

“…The observation that communities where high SES groups live have higher concentrations of air pollution does not necessarily mean that the residents are more exposed. High SES individuals have access to more resources that can protect them from increased exposure, such as private transportation versus public, indoor versus outdoor work environments, better constructed housing and potentially, access to climate control, including filtration, for indoor environments [71, 75]. Alternatively, environmental health disparities in Europe could be driven by other environmental hazards, such as noise, second-hand smoke or other work or housing related indicators many of which are also linked to the social environment and disproportionately impact the poor [19].…”

A framework for estimating the US mortality burden of fine particulate matter exposure attributable to indoor and outdoor microenvironments

“…There are three versions of Scenario 1, each of which involved sampling from different distributions to estimate residential PM 2.5 concentrations of both indoor and outdoor origin. We sampled data from (i) the Relationship of Indoor, Outdoor and Personal Air (RIOPA) [13] and (ii) the Multi-Ethnic Study of the Atherosclerosis and Air Pollution (MESA Air) [18,19] studies independently, as well as (iii) both RIOPA and MESA equally. Briefly, the RIOPA study measured indoor and outdoor PM 2.5 concentrations concurrently for 48 h in 212 non-smoking residences in three US cities, while MESA Air measured indoor and outdoor PM 2.5 concentrations concurrently over a 2week period in 208 homes in warm seasons and 264 homes in cold seasons in seven US cities.…”

“…Although epidemiology studies typically use centrally monitored outdoor PM 2.5 concentrations as surrogates for average human exposures to PM 2.5 of outdoor origin, the majority of exposure to PM 2.5 of outdoor origin in the US and other industrialized nations typically occurs in various other microenvironments, including inside residences, offices, schools, and vehicles [10][11][12][13][14][15][16]. This is because people spend the majority of their time in microenvironments other than outdoors [17,18] and outdoor PM 2.5 can infiltrate and persist into different microenvironments with varying efficiencies [19][20][21][22][23][24]. There are also many PM 2.5 sources present in non-smoking indoor microenvironments, including cooking [25][26][27], burning incense and candles [28,29], operating office equipment [30,31], resuspension from settled dust from human activities such as walking and cleaning [32,33], and secondary organic aerosols from oxidation reactions [34].…”

Walkability, complete streets, and gender: Who benefits most?

“…Indeed women have reported that they are especially likely to experience public hassles or incivilities (Bastomski and Smith, 2016) and consequently avoid public spaces (Koskela and Pain, 2000; Valentine, 1990), or certain streets (Pain, 1997). Although female employment has increased in past decades thereby increasing their presence outside the home (Hampton et al, 2015), females still may spend more time at home and less time outside the home than males (Drummond, 2000; Scraton and Watson, 1998; Spalt et al, 2016). Few studies have tracked the gender equity in the use of public spaces such as streets and sidewalks.…”