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Sökning: WFRF:(Jerrett M)

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  • Kondo, M. C., et al. (författare)
  • Momentary mood response to natural outdoor environments in four European cities
  • 2020
  • Ingår i: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 134
  • Tidskriftsartikel (refereegranskat)abstract
    • Exposure to natural outdoor environments (NOE) has been shown in population-level studies to reduce anxiety and psychological distress. This study investigated how exposure to one's everyday natural outdoor environments over one week influenced mood among residents of four European cities including Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands) and Kaunas (Lithuania). Participants (n = 368) wore a smartphone equipped with software applications to track location and mood (using mobile ecological momentary assessment (EMA) software), for seven consecutive days. We estimated random-effects ordered logistic regression models to examine the association between mood (positive and negative affect), and exposure to green space, represented by two binary variables indicating exposure versus no exposure to NOE using GPS tracking and satellite and aerial imagery, 10 and 30 min prior to participants’ completing the EMA. Models were adjusted for home city, day of the week, hour of the day, EMA survey type, residential NOE exposure, and sex, age, education level, mental health status and neighbourhood socioeconomic status. In addition, we tested for heterogeneity of effect by city, sex, age, residential NOE exposure and mental health status. Within 10 min of NOE exposure, compared to non-exposure, we found that overall there was a positive relationship with positive affect (OR: 1.39, 95% CI: 1.06, 1.81) of EMA surveys, and non-significant negative association with negative affect (OR: 0.80, 95% CI: 0.58, 1.10). When stratifying, associations were consistently found for Stoke-on-Trent inhabitants and men, while findings by age group were inconsistent. Weaker and less consistent associations were found for exposure 30 min prior to EMA. Our findings support increasing evidence of psychological and mental health benefits of exposure to natural outdoor environments, especially among urban populations such as those included in our study. 
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  • Beelen, Rob, et al. (författare)
  • Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe : the ESCAPE project
  • 2013
  • Ingår i: Atmospheric Environment. - : Elsevier. - 1352-2310 .- 1873-2844. ; 72, s. 10-23
  • Tidskriftsartikel (refereegranskat)abstract
    • Estimating within-city variability in air pollution concentrations is important. Land use regression (LUR) models are able to explain such small-scale within-city variations. Transparency in LUR model development methods is important to facilitate comparison of methods between different studies. We therefore developed LUR models in a standardized way in 36 study areas in Europe for the ESCAPE (European Study of Cohorts for Air Pollution Effects) project.Nitrogen dioxide (NO2) and nitrogen oxides (NOx) were measured with Ogawa passive samplers at 40 or 80 sites in each of the 36 study areas. The spatial variation in each area was explained by LUR modeling. Centrally and locally available Geographic Information System (GIS) variables were used as potential predictors. A leave-one out cross-validation procedure was used to evaluate the model performance.There was substantial contrast in annual average NO2 and NOx concentrations within the study areas. The model explained variances (R2) of the LUR models ranged from 55% to 92% (median 82%) for NO2 and from 49% to 91% (median 78%) for NOx. For most areas the cross-validation R2 was less than 10% lower than the model R2. Small-scale traffic and population/household density were the most common predictors. The magnitude of the explained variance depended on the contrast in measured concentrations as well as availability of GIS predictors, especially traffic intensity data were important. In an additional evaluation, models in which local traffic intensity was not offered had 10% lower R2 compared to models in the same areas in which these variables were offered.Within the ESCAPE project it was possible to develop LUR models that explained a large fraction of the spatial variance in measured annual average NO2 and NOx concentrations. These LUR models are being used to estimate outdoor concentrations at the home addresses of participants in over 30 cohort studies.
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