In order to investigate associations between air pollution and adverse health effects consistent fine spatial air pollution surfaces are needed across large areas to provide cohorts with comparable ...exposures. The aim of this paper is to develop and evaluate fine spatial scale land use regression models for four major health relevant air pollutants (PM2.5, NO2, BC, O3) across Europe.
We developed West-European land use regression models (LUR) for 2010 estimating annual mean PM2.5, NO2, BC and O3 concentrations (including cold and warm season estimates for O3). The models were based on AirBase routine monitoring data (PM2.5, NO2 and O3) and ESCAPE monitoring data (BC), and incorporated satellite observations, dispersion model estimates, land use and traffic data. Kriging was performed on the residual spatial variation from the LUR models and added to the exposure estimates. One model was developed using all sites (100%). Robustness of the models was evaluated by performing a five-fold hold-out validation and for PM2.5 and NO2 additionally with independent comparison at ESCAPE measurements. To evaluate the stability of each model's spatial structure over time, separate models were developed for different years (NO2 and O3: 2000 and 2005; PM2.5: 2013).
The PM2.5, BC, NO2, O3 annual, O3 warm season and O3 cold season models explained respectively 72%, 54%, 59%, 65%, 69% and 83% of spatial variation in the measured concentrations. Kriging proved an efficient technique to explain a part of residual spatial variation for the pollutants with a strong regional component explaining respectively 10%, 24% and 16% of the R2 in the PM2.5, O3 warm and O3 cold models. Explained variance at fully independent sites vs the internal hold-out validation was slightly lower for PM2.5 (65% vs 66%) and lower for NO2 (49% vs 57%). Predictions from the 2010 model correlated highly with models developed in other years at the overall European scale.
We developed robust PM2.5, NO2, O3 and BC hybrid LUR models. At the West-European scale models were robust in time, becoming less robust at smaller spatial scales. Models were applied to 100 × 100 m surfaces across Western Europe to allow for exposure assignment for 35 million participants from 18 European cohorts participating in the ELAPSE study.
•Robust PM2.5, NO2, BC and O3 hybrid LUR models at a 100x100 m resolution for Western Europe were developed•Models included large scale SAT and CTM estimates and fine scale traffic and land use and were further improved with kriging•Models were robust in time at European scale, becoming less robust at smaller spatial scales.
Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary ...linear regression. However, different algorithms have rarely been compared in terms of their predictive ability.
This study compared 16 algorithms to predict annual average fine particle (PM2.5) and nitrogen dioxide (NO2) concentrations across Europe. The evaluated algorithms included linear stepwise regression, regularization techniques and machine learning methods. Air pollution models were developed based on the 2010 routine monitoring data from the AIRBASE dataset maintained by the European Environmental Agency (543 sites for PM2.5 and 2399 sites for NO2), using satellite observations, dispersion model estimates and land use variables as predictors. We compared the models by performing five-fold cross-validation (CV) and by external validation (EV) using annual average concentrations measured at 416 (PM2.5) and 1396 sites (NO2) from the ESCAPE study. We further assessed the correlations between predictions by each pair of algorithms at the ESCAPE sites.
For PM2.5, the models performed similarly across algorithms with a mean CV R2 of 0.59 and a mean EV R2 of 0.53. Generalized boosted machine, random forest and bagging performed best (CV R2~0.63; EV R2 0.58–0.61), while backward stepwise linear regression, support vector regression and artificial neural network performed less well (CV R2 0.48–0.57; EV R2 0.39–0.46). Most of the PM2.5 model predictions at ESCAPE sites were highly correlated (R2 > 0.85, with the exception of predictions from the artificial neural network). For NO2, the models performed even more similarly across different algorithms, with CV R2s ranging from 0.57 to 0.62, and EV R2s ranging from 0.49 to 0.51. The predicted concentrations from all algorithms at ESCAPE sites were highly correlated (R2 > 0.9). For both pollutants, biases were low for all models except the artificial neural network. Dispersion model estimates and satellite observations were two of the most important predictors for PM2.5 models whilst dispersion model estimates and traffic variables were most important for NO2 models in all algorithms that allow assessment of the importance of variables.
Different statistical algorithms performed similarly when modelling spatial variation in annual average air pollution concentrations using a large number of training sites.
•Multiple statistical algorithms with very different assumptions were compared.•Despite the difference in modeling frameworks, predictions among the models exhibit generally good agreement.•The use of an external evaluation dataset strengthens evaluation by cross-validation.
•Large prospective cohort study in more than 2 million adult urban residents.•Non-accidental and cardio-respiratory mortality over long-term ten years follow-up.•Various objective and subjective ...green space indicators evaluated.•Inverse relations observed for non-accidental and respiratory mortality.
Epidemiological studies suggest that residing close to green space reduce mortality rates. We investigated the relationship between long-term exposure to residential green space and non-accidental and cardio-respiratory mortality.
We linked the Belgian 2001 census to population and mortality register follow-up data (2001–2011) among adults aged 30 years and older residing in the five largest urban areas in Belgium (n = 2,185,170 and mean follow-up time 9.4 years). Residential addresses were available at baseline. Exposure to green space was defined as 1) surrounding greenness (2006) normalized difference vegetation index (NDVI) and modified soil-adjusted vegetation index (MSAVI2) within buffers of 300 m, 500 m, and 1000 m; 2) surrounding green space (2006) Urban Atlas (UA) and CORINE Land Cover (CLC) within buffers of 300 m, 500 m, and 1000 m; and 3) perceived neighborhood green space (2001). Cox proportional hazards models with age as the underlying time scale were used to probe into cause-specific mortality (non-accidental, respiratory, COPD, cardiovascular, ischemic heart disease (IHD), and cerebrovascular). Models were adjusted for several sociodemographic variables (age, sex, marital status, country of birth, education level, employment status, and area mean income). We further adjusted our main models for annual mean (2010) values of ambient air pollution (PM2.5, PM10, NO2 and BC, one at a time), and we additionally explored potential mediation with the aforementioned pollutants.
Higher degrees of residential green space were associated with lower rates of non-accidental and respiratory mortality. In fully adjusted models, hazard ratios (HR) per interquartile range (IQR) increase in NDVI 500 m buffer (IQR: 0.24) and UA 500 m buffer (IQR: 0.31) were 0.97 (95%CI 0.96–0.98) and 0.99 (95%CI 0.98–0.99) for non-accidental mortality, and 0.95 (95%CI 0.93–0.98) and 0.97 (95%CI 0.96–0.99) for respiratory mortality. For perceived neighborhood green space, HRs were 0.93 (95%CI 0.92–0.94) and 0.94 (95%CI 0.91–0.98) for non-accidental and respiratory mortality, respectively. The observed lower mortality risks associated with residential exposure to green space were largely independent from exposure to ambient air pollutants.
We observed evidence for lower mortality risk in associations with long-term residential exposure to green space in most but not all studied causes of death in a large representative cohort for the five largest urban areas in Belgium. These findings support the importance of the availability of residential green space in urban areas.
•Air pollution was associated with natural cause and cause-specific mortality.•Associations differed between the hybrid, LUR and dispersion models.•Associations of air pollutants estimated by LUR ...were generally weaker.
To characterize air pollution exposure at a fine spatial scale, different exposure assessment methods have been applied. Comparison of associations with health from different exposure methods are scarce. The aim of this study was to evaluate associations of air pollution based on hybrid, land-use regression (LUR) and dispersion models with natural cause and cause-specific mortality.
We followed a Dutch national cohort of approximately 10.5 million adults aged 29+ years from 2008 until 2012. We used Cox proportional hazard models with age as underlying time scale and adjusted for several potential individual and area-level socio-economic status confounders to evaluate associations of annual average residential NO2, PM2.5 and BC exposure estimates based on two stochastic models (Dutch LUR, European-wide hybrid) and deterministic Dutch dispersion models.
Spatial variability of PM2.5 and BC exposure was smaller for LUR compared to hybrid and dispersion models. NO2 exposure variability was similar for the three methods. Pearson correlations between hybrid, LUR and dispersion modeled NO2 and BC ranged from 0.72 to 0.83; correlations for PM2.5 were slightly lower (0.61–0.72). In general, all three models showed stronger associations of air pollutants with respiratory disease and lung cancer mortality than with natural cause and cardiovascular disease mortality. The strength of the associations differed between the three exposure models. Associations of air pollutants estimated by LUR were generally weaker compared to associations of air pollutants estimated by hybrid and dispersion models. For natural cause mortality, we found a hazard ratio (HR) of 1.030 (95% confidence interval (CI): 1.019, 1.041) per 10 µg/m3 for hybrid modeled NO2, a HR of 1.003 (95% CI: 0.993, 1.013) per 10 µg/m3 for LUR modeled NO2 and a HR of 1.015 (95% CI: 1.005, 1.024) per 10 µg/m3 for dispersion modeled NO2.
Air pollution was positively associated with natural cause and cause-specific mortality, but the strength of the associations differed between the three exposure models. Our study documents that the selected exposure model may contribute to heterogeneity in effect estimates of associations between air pollution and health.
Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for ...a range of air pollutants and transportation noise.
Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM
, PM
components (Cu, Fe, S and Zn), NO
, black carbon (BC) and ozone (O
) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges.
During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM
components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m
PM
, 1.050 (1.041, 1.059) per 10 µg/m
NO
, 1.057 (1.048, 1.067) per 0.5 × 10
/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO
, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM
was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m
for PM
and NO
, < 1.5 10
/m BC and < 53 dB Lden total transportation noise. The O
association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC).
Long-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO
, BC and transportation noise.
Purpose of Review
We systematically reviewed the available observational evidence on the association between long-term exposure to residential outdoor greenspace and health at older age and rated the ...evidence as sufficient, limited, or inadequate.
Recent Findings
We identified 59 studies, ranging from poor to very good quality. The health outcomes included mental health (
N
= 12, of which three were longitudinal studies and eight were rated to be of good quality), cognitive function (
N
= 6; two longitudinal studies, five of good/very good quality), physical capability (
N
= 22; five longitudinal studies, six of good/very good quality), cardiometabolic risk (
N
= 9; one longitudinal study, five of good/very good quality), morbidity (
N
= 11; three longitudinal studies, six of good/very good quality) and perceived wellbeing (
N
= 9; all cross-sectional, two of good quality). The evidence for a beneficial association with greenspace was rated limited for morbidity and inadequate for mental health, cognitive function, physical capability, cardiometabolic risk and perceived wellbeing.
Summary
The reviewed studies provided inadequate/limited but suggestive evidence for a beneficial association between greater long-term greenspace exposure and healthy ageing. This review highlights the need of longitudinal studies that assess the association between long-term greenspace exposure and the trajectory of objective indicators of ageing.
The quality characteristics of urban green spaces (UGS) have been suggested to play a critical role in their use and their potentials to exert health effects. However, epidemiological studies ...evaluating such a role are scarce. These studies have generally focused on a limited number of quality dimensions. We studied the association between 10 UGS quality dimensions, assessed through a comprehensive multidimensional tool, and physical activity, overweight/obesity, and UGS use. Our study was based on 2053 adults participating in the Barcelona Health Survey (2016) and the quality of 149 UGS located in Barcelona, Spain. For each participant, we abstracted the average and maximum quality score separately for each of the 10 quality dimensions and an overall quality score for the UGS within 300 m of the participant’s residential address. Data on the study outcomes were obtained through face-to-face interviews. We developed logistic regression and negative binomial models to assess our evaluated associations and conducted mediation analyses between the different outcomes. We observed that the overall quality of UGS was associated with higher likelihood of engaging in moderate-to-vigorous physical activity (OR:1.13; 95% CI:1.00–1.27), lower risk of overweight/obesity (OR: 0.88; 95% CI: 0.79–0.98), and increased use of UGS (exponentiated regression coefficient: 1.08; 95% CI:1.01–1.15). For the quality dimensions, we observed different patterns of associations depending on the outcome; however, bird biodiversity and amenities seem to be relevant to all of our evaluated outcomes. The mediation analysis suggested that UGS use mediate the association between quality and physical activity, while physical activity mediates the association between quality and overweight/obesity. The novel results from this study will allow decision-makers better design UGS and directly pinpoint relevant quality dimensions to promote physical activity, reduce the risk of overweight/obesity and boost the use of UGS amongst citizens.
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•Urban green quality influences physical activity, overweight and urban green use.•Each quality dimension has different associations with the outcomes.•Bird biodiversity and overall quality influence all outcomes.
In addition to underlying health disorders and socio-economic or community factors, air pollution may trigger suicide mortality. This study evaluates the association between short-term variation in ...air pollution and 10 years of suicide mortality in Belgium. In a bidirectional time-stratified case-crossover design, 20,533 suicide deaths registered between January 1st 2002 and December 31st 2011 were matched by temperature with control days from the same month and year. We used municipality-level air pollution particulate matter (PM₁₀) and O₃ concentrations data and meteorology data. We applied conditional logistic regression models adjusted for duration of sunshine and day of the week to obtain odds ratios (OR) and their 95% CI for an increase of 10 µg/m³ in pollutant concentrations over different lag periods (lag 0, 0-1, 0-2, 0-3, 0-4, 0-5, and 0-6 days). Effect modification by season and age was investigated by including interaction terms. We observed significant associations of PM₁₀ and O₃ with suicide during summer (OR ranging from 1.02 to 1.07, p-values <0.05). For O₃, significant associations were also observed during spring and autumn. Age significantly modified the associations with PM₁₀, with statistically significant associations observed only among 5-14 year old children (lag 0-6: OR = 1.45; 95% CI: 1.03-2.04) and ≥85 years old (e.g. lag 0-4: OR =1.17; 95% CI: 1.06-1.29). Recent increases in outdoor air pollutants such as PM₁₀ or O₃ can trigger suicide, particularly during warm periods, even at concentrations below the European thresholds. Furthermore, PM₁₀ may have strong trigger effects among children and elderly population.
Residing close to green spaces might reduce diabetes mellitus (DM) risk; however, evidence for diabetes mortality is limited. Moreover, individual and neighbourhood social factors may determine DM ...risk. Exposure to green spaces may also depend on socioeconomic position (SEP). This study examined the associations between residential greenness and diabetes-related mortality, and the role of the social environment in these associations.
We used the 2001 Belgian census linked to mortality register data for the period 2001–2014. We included individuals aged 40–79 years old and residing in the five largest Belgian urban areas at baseline. Exposure to residential greenness was assessed with surrounding greenness using the Normalized Difference Vegetation Index (NDVI) within 500-m of residence (objective indicator), and perceived neighbourhood greenness (subjective indicator). We conducted mixed-effects Cox proportional hazards models to obtain hazard ratios (HR) for diabetes-related mortality per interquartile range (IQR) increments of residential greenness. We assessed effect modification by social factors through stratification.
From 2,309,236 individuals included at baseline, 1.2% died from DM during follow-up. Both residential greenness indicators were inversely associated with diabetes-related mortality after adjustment for individual social factors. After controlling for neighbourhood SEP, the beneficial association with surrounding greenness disappeared HR 1.02 (95%CI:0.99,1.06), but persisted with perceived neighbourhood greenness HR 0.93 (95%CI:0.91,0.95). After stratification the inverse associations with perceived neighbourhood greenness were strongest for women, the lowest educated, and individuals residing in least deprived neighbourhoods.
Our findings suggest that an overall positive perception of neighbourhood green spaces reduces independently the risk of diabetes-related mortality, regardless of the neighbourhood social environment. Nevertheless, neighbourhood SEP may be a strong confounder in the associations between diabetes-related mortality and greenness indicators derived from satellite images. Perception factors not captured by objective measurements of green spaces are potentially relevant in the association with DM, especially among disadvantaged groups.
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•Mortality cohort study over 2.3 million adults in largest Belgian urban areas.•Surrounding greenness not associated with diabetes mortality after full adjustment.•Potential confounding by neighbourhood socioeconomic characteristics.•Perceived greenness independently associated with lower diabetes mortality risk.•Most beneficial for women, low-educated and individuals residing in wealthiest areas.
We systematically reviewed the existing evidence (until end of November 2021) on the association between long-term exposure to greenspace and behavioral problems in children according to the PRISMA ...2020. The review finally reached 29 relevant studies of which, 17 were cross-sectional, 11 were cohort, and one was a case-control. Most of the studies were conducted in Europe (n = 14), followed by the USA (n = 8), and mainly (n = 21) from 2015 onwards. The overall quality of the studies in terms of risk of bias was “fair” (mean quality score = 5.4 out of 9) according to the Newcastle–Ottawa Scale. Thirteen studies (45%) had good or very good quality in terms of risk of bias. The strength and difficulty questionnaire was the most common outcome assessment instrument. Exposure to the greenspace in the reviewed studies was characterized based on different indices (availability, accessibility, and quality), mostly at residential address locations. Association of exposure to different types of greenspace were reported for nine different behavioral outcomes including total behavioral difficulties (n = 16), attention deficit hyperactivity disorder (ADHD) symptoms and severity (n = 15), ADHD diagnosis (n = 10), conduct problems (n = 10), prosocial behavior (n = 10), emotional symptoms (n = 8), peer-relationship problems (n = 8), externalizing disorders (n = 6), and internalizing disorders (n = 5). Most of the reported associations (except for conduct problems) were suggestive of beneficial association of greenspace exposure with children's behaviors; however, the studies were heterogeneous in terms of their exposure indicators, study design, and the outcome definition.
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•Evidence on the association of greenspace exposure with child behavior is accumulating.•We found indications for a beneficial impact of greenspace exposure on child behavior.•Total behavioral difficulties and ADHD showed consistent associations with greenspace.
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