Abstract
Background/AimThe exposome includes urban greenspace, which may affect health via a complex set of pathways, including reducing exposure to particulate matter (PM) and noise. We assessed these pathways using indoor exposure monitoring data from the HEALS study in four European urban areas (Edinburgh, UK; Utrecht, Netherlands; Athens and Thessaloniki, Greece). MethodsWe quantified three metrics of residential greenspace at 50 m and 100 m buffers: Normalised Difference Vegetation Index (NDVI), annual tree cover density, and surrounding green land use. NDVI values were generated for both summer and the season during which the monitoring took place. Indoor PM2.5 and noise levels were measured by Dylos and Netatmo sensors, respectively, and subjective noise annoyance was collected by questionnaire on an 11-point scale. We used random-effects generalised least squares regression models to assess associations between greenspace and indoor PM2.5 and noise, and an ordinal logistic regression to model the relationship between greenspace and road noise annoyance. ResultsWe identified a significant inverse relationship between summer NDVI and indoor PM2.5 (−1.27 μg/m3 per 0.1 unit increase [95% CI -2.38 to −0.15]) using a 100 m residential buffer. Reduced (i.e., <1.0) odds ratios (OR) of road noise annoyance were associated with increasing summer (OR = 0.55 [0.31 to 0.98]) and season-specific (OR = 0.55 [0.32 to 0.94]) NDVI levels, and tree cover density (OR = 0.54 [0.31 to 0.93] per 10 percentage point increase), also at a 100 m buffer. In contrast to these findings, we did not identify any significant associations between greenspace and indoor noise in fully adjusted models. ConclusionsWe identified reduced indoor levels of PM2.5 and noise annoyance, but not overall noise, with increasing outdoor levels of certain greenspace indicators. To corroborate our findings, future research should examine the effect of enhanced temporal resolution of greenspace metrics during different seasons, characterise the configuration and composition of green areas, and explore mechanisms through mediation modelling.
Highlights
The exposome represents the comprehensive range of exposures that may interact with the genome throughout the life course (Wild, 2012)
We present three sets of models for confounder adjustment: model 1 – the unadjusted results; model 2 – the effect of greenspace markers adjusted for outdoor PM2.5, season, city, population density, distances to road and rail, and the proportion of surrounding road land use; and model 3 – the effect of greenspace with further adjustment for smoking, use of a fireplace for heating, gas for cooking, the number of occupants, presence of pets, opening windows ≥1/week, and mean temperature and relative humidity
In the case of the present study, a 100 m buffer may have better characterised surrounding greenspace at the local level compared to that based on 50 m, a non-trivial portion of which would have been consumed by the home address; in addition, raster pixel size would have less influence at the larger buffer size
Summary
The exposome represents the comprehensive range of exposures that may interact with the genome throughout the life course (Wild, 2012) Such exposures may interact and modify one another; urban greenspace and greenness have received much focus as environmental features that entail multifaceted pathways to benefit health Surrounding residential greenness has been linked to lower levels of both outdoor and indoor PM2.5 at residences (Dadvand et al, 2012) and schools (Dadvand et al, 2015) Despite these reported associations with improved air quality, vegetation can have its own contribution to ambient pollutant concentrations, including the release of pollen and biogenic volatile organic compounds, which can be precursors to the formation of O3 and secondary organic aerosols; the latter of these compounds contributes to PM2.5 (Salmond et al, 2016)
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