Commentary: A road map for future data-driven urban planning and environmental health research.

Recent advances in data science and urban environmental health research utilise large-scale databases (100s-1000s of cities) to explore the complex interplay of urban characteristics such as city form and size, climate, mobility, exposure, and environmental health impacts. Cities are still hotspots of air pollution and noise, suffer urban heat island effects and lack of green space, which leads to disease and mortality burdens preventable with better knowledge. Better understanding through harmonising and analysing data in large numbers of cities is essential to identifying the most effective means of disease prevention and understanding context dependencies important for policy.

Development of land use regression, dispersion, and hybrid models for prediction of outdoor air pollution exposure in Barcelona.

BACKGROUND: Air pollution is the leading environmental risk factor for health. Assessing outdoor air pollution exposure with detailed spatial and temporal variability in urban areas is crucial for evaluating its health effects. AIM: We developed and compared Land Use Regression (LUR), dispersion (DM), and hybrid (HM) models to estimate outdoor concentrations for NO2, PM2.5, black carbon (BC), and PM2.5-constituents (Fe, Cu, Zn) in Barcelona. METHODS: Two monitoring campaigns were conducted. In the first, NO2 concentrations were measured twice at 984 home addresses and in the second, NO2, PM2.5, and BC were measured four times at 34 points across Barcelona. LUR and DM were constructed using conventional techniques, while HM was developed using Random Forest (RF). Model performance was evaluated using leave-one-out cross-validation (LOOCV) and 10-fold cross-validation (10-CV) for LUR and HM, and by comparing DM and LUR estimates with routine monitoring stations. NO2 levels estimated by all models were externally validated using the home monitoring campaign. Agreement between models was assessed using Spearman correlation (rs) and Bland-Altman (BA) plots. RESULTS: Models showed moderate to good performance. LUR exhibited R2LOOCV of 0.62 (NO2), 0.45 (PM2.5), 0.83 (BC), and 0.85 to 0.89 (PM2.5-constituents). DM model comparison showed R2 values of 0.39 (NO2), 0.26 (PM2.5), and 0.65 (BC). HM models had higher R210-CV 0.64 (NO2), 0.66 (PM2.5), 0.86 (BC), and 0.44 to 0.70 (PM2.5-constituents). Validation for NO2 showed R2 values of 0.56 (LUR), 0.44 (DM), and 0.64 (HM). Correlations between models varied from -0.38 to 0.92 for long-term exposure, and - 0.23 to 0.94 for short-term exposure. BA plots showed good agreement between models, especially for NO2 and BC. CONCLUSIONS: Our models varied substantially, with some models performing better in validation samples (NO2 and BC). Future health studies should use the most accurate methods to minimize bias from exposure measurement error.

Health impact assessment of port-sourced air pollution in Barcelona.

INTRODUCTION: Air pollution is a major health risk factor. Ports might be an understudied source of air pollution. METHODS: We conducted a spatial health impact assessment (HIA) of port-sourced air pollution for Barcelona for 2017 at the neighbourhood level. Total NO2 and PM10 and port-sourced NO2, PM10 and PM2.5 concentrations were available through the ADMS-Urban model. Population data, mortality and morbidity data, and risk estimates were obtained. We followed standard HIA methodologies and calculated relative risks and impact fractions for 1.35 million adults living in 73 neighbourhoods. RESULTS: The city-wide mean total NO2 and PM10 concentrations were 37.88 µg/m3 (range: 19.61-52.17 µg/m3) and 21.68 µg/m3 (range: 17.33-26.69 µg/m3), respectively, of which 7% (range: 2-36%) and 1% (range: 0-7%) were port-sourced, respectively. The mean port-sourced PM2.5 concentration was 0.19 µg/m3 (range: 0.06-1.38 µg/m3). We estimated that 1,123 (PI: 0-3,060) and 1,230 (95% CI: 0-2,566) premature deaths were attributable to total NO2 and PM10, respectively, of which 8.1% (91; PI: 0-264) and 1.1% (13; 95% CI 0-29) were attributable to port-sourced NO2 and PM10, respectively. 20 (95% CI: 15-26) premature deaths were attributable to port-sourced PM2.5. Additionally, a considerable morbidity burden and losses in life expectancy were attributable to port-sourced air pollution. Neighbourhoods closest to the port in the south-east were most adversely affected, gradually decreasing towards the north-west. CONCLUSIONS: The port is an understudied air pollution source in Barcelona with strong health impacts. Cities need local insight into health risk factors, their sources, attributable burdens and distributions for defining targeted policies.

Outdoor artificial light-at-night and cardiometabolic disease risk: an urban perspective from the Catalan GCAT cohort study.

We investigated the association between outdoor artificial light-at-night (ALAN) exposure and cardiometabolic risk in the GCAT study. We included 9,752 participants from Barcelona (59% women). We used satellite images (30m resolution) and estimated photopic illuminance and the circadian-regulation relevant melanopic illuminance (melanopic EDI). We explored the association between ALAN exposure and prevalent obesity, hypertension, and diabetes with logistic regressions. We assessed the relationship with incident cardiometabolic diseases ascertained through electronic health records (mean follow-up 6.5 years) with Cox proportional hazards regressions. We observed an association between photopic illuminance and melanopic EDI and prevalent hypertension, Odds ratio (OR) = 1.09 (95% CI, 1.01-1.16) and 1.08 (1.01-1.14) per interquartile range increase (0.59 and 0.16 lux, respectively). Both ALAN indicators were linked to incident obesity (hazard ratio [HR] = 1.29, 1.11-1.48 and 1.19, 1.05-1.34) and haemorrhagic stroke (HR = 1.73, 1.00-3.02 and 1.51, 0.99-2.29). Photopic illuminance was associated with incident hypercholesterolemia in all participants (HR = 1.17, 1.05-1.31) and with angina pectoris only in women (HR = 1.55, 1.03-2.33). Further research in this area and increased awareness on the health impacts of light pollution are needed. Results should be interpreted carefully since satellite-based ALAN data do not estimate total individual exposure.

The impact of urban configuration types on urban heat islands, air pollution, CO2 emissions, and mortality in Europe: a data science approach.

BACKGROUND: The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO2, CO2 per person emissions, and age-standardised mortality. METHODS: We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal-Wallis test followed by a post-hoc Dunn's test. FINDINGS: We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO2 exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. INTERPRETATION: Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health. FUNDING: Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.

The influence of pre- and postnatal exposure to air pollution and green spaces on infant's gut microbiota: Results from the MAMI birth cohort study.

BACKGROUND: Animal and human studies indicate that exposure to air pollution and natural environments might modulate the gut microbiota, but epidemiological evidence is very scarce. OBJECTIVES: To assess the potential impact of pre- and postnatal exposure to air pollution and green spaces on infant gut microbiota assembly and trajectories during the first year of life. METHODS: MAMI ("MAternal MIcrobes") birth cohort (Valencia, Spain, N = 162) was used to study the impact of environmental exposure (acute and chronic) on infant gut microbiota during the first year of life (amplicon-based 16S rRNA sequencing). At 7 days and at 1, 6 and 12 months, residential pre- and postnatal exposure to air pollutants (NO2, black carbon -BC-, PM2.5 and O3) and green spaces indicators (NDVI and area of green spaces at 300, 500 and 1000 m buffers) were obtained. For the association between exposures and alpha diversity indicators linear regression models (cross-sectional analyses) and mixed models, including individual as a random effect (longitudinal analyses), were applied. For the differential taxon analysis, the ANCOM-BC package with a log count transformation and multiple-testing corrections were used. RESULTS: Acute exposure in the first week of life and chronic postnatal exposure to NO2 were associated with a reduction in microbial alpha diversity, while the effects of green space exposure were not evident. Acute and chronic (prenatal or postnatal) exposure to NO2 resulted in increased abundance of Haemophilus, Akkermansia, Alistipes, Eggerthella, and Tyzerella populations, while increasing green space exposure associated with increased Negativicoccus, Senegalimassilia and Anaerococcus and decreased Tyzzerella and Lachnoclostridium populations. DISCUSSION: We observed a decrease in the diversity of the gut microbiota and signs of alteration in its composition among infants exposed to higher levels of NO2. Increasing green space exposure was also associated with changes in gut microbial composition. Further research is needed to confirm these findings.

Citizen science and social innovation as citizen empowerment tools to address urban health challenges: The case of the urban health citizen laboratory in Barcelona, Spain.

Urban health faces significant challenges due to the rapid growth of cities and the concentration of population in urban settings that have a strong impact on people's health. The approach to characterize and address these challenges requires increased societal involvement and interdisciplinary solutions to ensure their effectiveness and democratic nature. With this purpose, it is necessary to explore methodologies for citizen participation that foster a critical understanding of the environment and promote their active role in generating scientific knowledge and change. This article describes the creation of a collaborative space for experimentation and learning that, through the intersection of citizen science and social innovation, aims to engage citizens in the research and diagnosis of their local environment, as well as in the design and implementation of local solutions, while raising awareness about the main challenges to urban health. Through a collaborative and participatory framework, the community identified relevant challenges to urban health they wanted to investigate, co-designed and developed the methodology for data collection and analysis, and ultimately, they devised, designed, and implemented innovative solutions based on the scientific evidence obtained. The framework and results of this project hold potential interest for the scientific community, facilities, institutions, and society by offering an innovative and participatory approach to addressing the present and future urban health challenges.

Cities and mental health: The role of the built environment, and environmental and lifestyle factors in Barcelona.

Built environment characteristics and related environmental exposures and behaviors have been, separately, implicated in the development of poor mental health. However, it is unclear how these factors act together in relation to mental health. We studied these factors simultaneously to evaluate the impact of the built environment, and the mediating role of environmental exposures and physical activity, on mental health, while also studying moderation by sex, age, and length of residence. We used a cross-sectional population-based sample of 3145 individuals aged 15-97 years from Barcelona, Spain. Time spent walking and mental health status were assessed with validated questionnaires, administered through a face-to-face interview. We characterized the built environment (e.g., building, population and intersection density and green space), road traffic noise, and ambient air pollution at the residential level using land cover maps, remote sensing, noise maps and land use regression models. Adjusted regression models accounting for spatial clustering were analyzed to study associations between built environment attributes and mental health, and mediation and moderation effects. Density attributes were directly or indirectly, through air pollution and less consistently through walking, associated with poor mental health. Green space indicators were associated with lower prevalence of poor mental health, partly through lower air pollution exposure and more walking. In some cases, these associations differed by sex, age or length of residence. Non-linear associations of density indicators with environmental exposures, and of particulate matter with poor mental health indicated threshold effects. We conclude that living in dense areas with high air pollution concentrations was associated with poor mental health. On the other hand, green areas with lower air pollution concentrations were protective against poor mental health. Greater urban density might benefit health, but might only do so when air pollution concentrations are low.

Environmental health impacts and inequalities in green space and air pollution in six medium-sized European cities.

BACKGROUND: The GoGreenRoutes project aims to introduce co-created nature-based solutions (NBS) to enhance environmental quality in six medium-sized cities (Burgas, Lahti, Limerick, Tallinn, Umeå, and Versailles). We estimated the mortality and economic impacts attributed to suboptimal exposure to green space and air pollution, economic impacts, and the distribution thereof the adult population by socioeconomic status. METHODS: We retrieved data from publicly accessible databases on green space (NDVI and % Green Area), air pollution (NO2 and PM2.5) and population (≥20 years, n = 804,975) at a 250m × 250m grid-cell level, and mortality for each city for 2015. We compared baseline exposures at the grid-cell to World Health Organization's recommendations and guidelines. We applied a comparative risk assessment to estimate the mortality burden attributable to not achieving the recommendations and guidelines. We estimated attributable mortality distributions and the association with income levels. RESULTS: We found high variability in air pollution and green spaces levels. Around 60% of the population lacked green space and 90% were exposed to harmful air pollution. Overall, we estimated age-standardized mortality rates varying from 10 (Umeå) to 92 (Burgas) deaths per 100,000 persons attributable to low NDVI levels; 3 (Lahti) to 38 (Burgas) per 100,000 persons to lack of % Green Area; 1 (Umeå) to 88 (Tallinn) per 100,000 persons to exceedances of NO2 guidelines; and 1 (Umeå) to 206 (Burgas) per 100,000 persons to exceedances of PM2.5 guidelines. Lower income associated with higher or lower mortality impacts depending on whether deprived populations lived in the densely constructed, highly-trafficked city centre or greener, less polluted outskirts. CONCLUSIONS: We attributed a considerable mortality burden to lack of green spaces and higher air pollution, which was unevenly distributed across different social groups. NBS and health-promoting initiatives should consider socioeconomic aspects to regenerate urban areas while providing equally good environments.

Changes in air pollution exposure after residential relocation and body mass index in children and adolescents: A natural experiment study.

Air pollution exposure may affect child weight gain, but observational studies provide inconsistent evidence. Residential relocation can be leveraged as a natural experiment by studying changes in health outcomes after a sudden change in exposure within an individual. We aimed to evaluate whether changes in air pollution exposure due to residential relocation are associated with changes in body mass index (BMI) in children and adolescents in a natural experiment study. This population-based study included children and adolescents, between 2 and 17 years, who moved during 2011-2018 and were registered in the primary healthcare in Catalonia, Spain (N = 46,644). Outdoor air pollutants (nitrogen dioxides (NO2), particulate matter <10 µm (PM10) and <2.5 µm (PM2.5)) were estimated at residential census tract level before and after relocation; tertile cut-offs were used to define changes in exposure. Routinely measured weight and height were used to calculate age-sex-specific BMI z-scores. A minimum of 180 days after moving was considered to observe zBMI changes according to changes in exposure using linear fixed effects regression. The majority of participants (60-67% depending on the pollutant) moved to areas with similar levels of air pollution, 15-49% to less polluted, and 14-31% to more polluted areas. Moving to areas with more air pollution was associated with zBMI increases for all air pollutants (ß NO2 = 0.10(95%CI 0.09; 0.12), ß PM2.5 0.06(0.04; 0.07), ß PM10 0.08(0.06; 0.10)). Moving to similar air pollution areas was associated with decreases in zBMI for all pollutants. No associations were found for those moving to less polluted areas. Associations with moving to more polluted areas were stronger in preschool- and primary school-ages. Associations did not differ by area deprivation strata. This large, natural experiment study suggests that increases in outdoor air pollution may be associated with child weight gain, supporting ongoing efforts to lower air pollution levels.

Nature contact and general health: Testing multiple serial mediation pathways with data from adults in 18 countries.

The role of neighbourhood nature in promoting good health is increasingly recognised in policy and practice, but consistent evidence for the underlying mechanisms is lacking. Heterogeneity in exposure methods, outcome measures, and population characteristics, little exploration of recreational use or the role of different types of green or blue space, and multiple separate mediation models in previous studies have limited our ability to synthesise findings and draw clear conclusions. We examined multiple pathways linking different types of neighbourhood nature with general health using a harmonised international sample of adults. Using cross-sectional survey data from 18 countries (n = 15,917), we developed a multigroup path model to test theorised pathways, controlling for sociodemographic variables. We tested the possibility that neighbourhood nature (e.g. greenspace, inland bluespace, and coastal bluespace) would be associated with general health through lower air pollution exposure, greater physical activity attainment, more social contact, and higher subjective well-being. However, our central prediction was that associations between different types of neighbourhood nature and general health would largely be serially mediated by recent visit frequency to corresponding environment types, and, subsequently, physical activity, social contact, and subjective well-being associated with these frequencies. Several subsidiary analyses assessed the robustness of the results to alternative model specifications as well as effect modification by sociodemographics. Consistent with this prediction, there was statistical support for eight of nine potential serial mediation pathways via visit frequency which held for a range of alternative model specifications. Effect modification by financial strain, sex, age, and urbanicity altered some associations but did not necessarily support the idea that nature reduced health inequalities. The results demonstrate that across countries, theorised nature-health linkages operate primarily through recreational contact with natural environments. This provides arguments for greater efforts to support use of local green/blue spaces for health promotion and disease prevention.

Spatial and sector-specific contributions of emissions to ambient air pollution and mortality in European cities: a health impact assessment.

BACKGROUND: Ambient air pollution is a major risk to health and wellbeing in European cities. We aimed to estimate spatial and sector-specific contributions of emissions to ambient air pollution and evaluate the effects of source-specific reductions in pollutants on mortality in European cities to support targeted source-specific actions to address air pollution and promote population health. METHODS: We conducted a health impact assessment of data from 2015 for 857 European cities to estimate source contributions to annual PM2·5 and NO2 concentrations using the Screening for High Emission Reduction Potentials for Air quality tool. We evaluated contributions from transport, industry, energy, residential, agriculture, shipping, and aviation, other, natural, and external sources. For each city and sector, three spatial levels were considered: contributions from the same city, the rest of the country, and transboundary. Mortality effects were estimated for adult populations (ie, ≥20 years) following standard comparative risk assessment methods to calculate the annual mortality preventable on spatial and sector-specific reductions in PM2·5 and NO2. FINDINGS: We observed strong variability in spatial and sectoral contributions among European cities. For PM2·5, the main contributors to mortality were the residential (mean contribution of 22·7% [SD 10·2]) and agricultural (18·0% [7·7]) sectors, followed by industry (13·8% [6·0]), transport (13·5% [5·8]), energy (10·0% [6·4]), and shipping (5·5% [5·7]). For NO2, the main contributor to mortality was transport (48·5% [SD 15·2]), with additional contributions from industry (15·0% [10·8]), energy (14·7% [12·9]), residential (10·3% [5·0]), and shipping (9·7% [12·7]). The mean city contribution to its own air pollution mortality was 13·5% (SD 9·9) for PM2·5 and 34·4% (19·6) for NO2, and contribution increased among cities of largest area (22·3% [12·2] for PM2·5 and 52·2% [19·4] for NO2) and among European capitals (29·9% [12·5] for PM2·5 and 62·7% [14·7] for NO2). INTERPRETATION: We estimated source-specific air pollution health effects at the city level. Our results show strong variability, emphasising the need for local policies and coordinated actions that consider city-level specificities in source contributions. FUNDING: Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making 2023-2026 Horizon Europe project.

Long-Term Exposure to Air Pollution and COVID-19 Vaccine Antibody Response in a General Population Cohort (COVICAT Study, Catalonia).

BACKGROUND: Ambient air pollution has been associated with COVID-19 disease severity and antibody response induced by infection. OBJECTIVES: We examined the association between long-term exposure to air pollution and vaccine-induced antibody response. METHODS: This study was nested in an ongoing population-based cohort, COVICAT, the GCAT-Genomes for Life cohort, in Catalonia, Spain, with multiple follow-ups. We drew blood samples in 2021 from 1,090 participants of 2,404 who provided samples in 2020, and we included 927 participants in this analysis. We measured immunoglobulin M (IgM), IgG, and IgA antibodies against five viral-target antigens, including receptor-binding domain (RBD), spike-protein (S), and segment spike-protein (S2) triggered by vaccines available in Spain. We estimated prepandemic (2018-2019) exposure to fine particulate matter [PM ≤2.5µm in aerodynamic diameter (PM2.5)], nitrogen dioxide (NO2), black carbon (BC), and ozone (O3) using Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) models. We adjusted estimates for individual- and area-level covariates, time since vaccination, and vaccine doses and type and stratified by infection status. We used generalized additive models to explore the relationship between air pollution and antibodies according to days since vaccination. RESULTS: Among vaccinated persons not infected by SARS-CoV-2 (n=632), higher prepandemic air pollution levels were associated with a lower vaccine antibody response for IgM (1 month post vaccination) and IgG. Percentage change in geometric mean IgG levels per interquartile range of PM2.5 (1.7 µg/m3) were -8.1 (95% CI: -15.9, 0.4) for RBD, -9.9 (-16.2, -3.1) for S, and -8.4 (-13.5, -3.0) for S2. We observed a similar pattern for NO2 and BC and an inverse pattern for O3. Differences in IgG levels by air pollution levels persisted with time since vaccination. We did not observe an association of air pollution with vaccine antibody response among participants with prior infection (n=295). DISCUSSION: Exposure to air pollution was associated with lower COVID-19 vaccine antibody response. The implications of this association on the risk of breakthrough infections require further investigation. https://doi.org/10.1289/EHP11989.

An urban green space intervention with benefits for mental health: A health impact assessment of the Barcelona "Eixos Verds" Plan.

BACKGROUND: Mental health disorders account for over 30% of the global burden of disease. There is a positive association between green space exposure and better mental health, and therefore urban greening can be an effective public health tool. Barcelona is a compact city with one of the highest population and traffic densities in Europe, with limited green spaces. Under the umbrella of the Superblock model, the Barcelona City council is implementing the Eixos Verds Plan for extensive street greening. We estimated the potential mental health benefits of this plan. METHODS: We performed a quantitative health impact assessment at the Barcelona grid-cell level (n = 1,096). We compared the baseline green space situation (2015) with the proposed plan and translated the increase in green space into a) percentage of green area (%GA) and b) NDVI. We combined exposure data with Barcelona-specific mental health risk estimates, adult population (n = 1,235,375), and mental health data, and calculated preventable cases. FINDINGS: Under the Eixos Verds Plan, we estimated an average increase of 5·67 %GA (range: 0·00% - 15·77%) and 0·059 NDVI (range: 0·000 - 0·312). We estimated that with the Eixos Verds Plan implementation, 31,353 (95%CI: 18,126-42,882) cases of self-perceived poor mental health (14·03% of total), 16,800 (95%CI: 6828-25,700) visits to mental health specialists (13·37% of total), 13,375 (95%CI: 6107-19,184) cases of antidepressant use (13·37% of total), and 9476 (95%CI: 802-16,391) cases of tranquilliser/ sedative use (8·11% of total) could be prevented annually, along corresponding to over 45 M € annual savings in mental health costs annually. INTERPRETATION: Our results highlight the importance of urban greening as a public health tool to improve mental health in cities. Similar results for green interventions in other cities could be expected.

Cooling cities through urban green infrastructure: a health impact assessment of European cities.

BACKGROUND: High ambient temperatures are associated with many health effects, including premature mortality. The combination of global warming due to climate change and the expansion of the global built environment mean that the intensification of urban heat islands (UHIs) is expected, accompanied by adverse effects on population health. Urban green infrastructure can reduce local temperatures. We aimed to estimate the mortality burden that could be attributed to UHIs and the mortality burden that would be prevented by increasing urban tree coverage in 93 European cities. METHODS: We did a quantitative health impact assessment for summer (June 1-Aug 31), 2015, of the effect of UHIs on all-cause mortality for adults aged 20 years or older in 93 European cities. We also estimated the temperature reductions that would result from increasing tree coverage to 30% for each city and estimated the number of deaths that could be potentially prevented as a result. We did all analyses at a high-resolution grid-cell level (250 × 250 m). We propagated uncertainties in input analyses by using Monte Carlo simulations to obtain point estimates and 95% CIs. We also did sensitivity analyses to test the robustness of our estimates. FINDINGS: The population-weighted mean city temperature increase due to UHI effects was 1·5°C (SD 0·5; range 0·5-3·0). Overall, 6700 (95% CI 5254-8162) premature deaths could be attributable to the effects of UHIs (corresponding to around 4·33% [95% CI 3·37-5·28] of all summer deaths). We estimated that increasing tree coverage to 30% would cool cities by a mean of 0·4°C (SD 0·2; range 0·0-1·3). We also estimated that 2644 (95% CI 2444-2824) premature deaths could be prevented by increasing city tree coverage to 30%, corresponding to 1·84% (1·69-1·97) of all summer deaths. INTERPRETATION: Our results showed the deleterious effects of UHIs on mortality and highlighted the health benefits of increasing tree coverage to cool urban environments, which would also result in more sustainable and climate-resilient cities. FUNDING: GoGreenRoutes, Spanish Ministry of Science and Innovation, Institute for Global Health, UK Medical Research Council, European Union's Horizon 2020 Project Exhaustion.

The evaluation of the 3-30-300 green space rule and mental health.

BACKGROUND AND AIMS: Urban green space has many health benefits, but it is still unclear how much actually is needed for better health. Recently a new 3-30-300 rule of thumb for urban forestry and urban greening has been proposed, but this rule has not been evaluated for benefits on health. The rule requires that every citizen should be able to see at least three trees from their home, have 30 percent tree canopy cover in their neighbourhood and not live more than 300 m away from the nearest park or green space. The aim of this study was to evaluate the relationship between the 3-30-300 green space rule and its components in relation to mental health. METHODS: We conducted a cross-sectional study based on a population-based sample of 3145 individuals aged 15-97 years from in Barcelona, Spain who participated in the Barcelona Health Survey (2016-2017). We created 3-30-300 green space indicators using questionnaire data, GIS, remote sensing and land cover maps. Mental health status was assessed with the 12-item General Health Questionnaire (GHQ-12) and also the use of tranquilizer/sedatives or antidepressants and psychiatrist or psychologist visits. Analyses were conducted using mixed effects logistic regression models with districts as the random effect, adjusted for relevant covariates. RESULTS: We found that people in Barcelona had relatively little exposure to green space, whether through window view, living in an area with sufficient greenness, or access to a major green space, and only 4.7% met a surrogate 3-30-300 green space rule. Residential surrounding greenness, but not tree window view or access to major green space, was significantly associated with better mental health, less medication use, and fewer psychologist or psychiatrist visits. Meeting the full surrogate 3-30-300 green space rule was associated with better mental health, less medication use, and fewer psychologist or psychiatrist visits, but only for the latter combined the association was statistically significant (Odds ratio = 0.31, 95% CI: 0.11, 0.91). CONCLUSION: Few people achieved the 3-30-300 green space in Barcelona and we used a surrogate measure. We observed health benefits when the full surrogate rule was met.

Air pollution and green spaces in relation to breast cancer risk among pre and postmenopausal women: A mega cohort from Catalonia.

BACKGROUND: The association between air pollution and green spaces with breast cancer risk stratified by menopausal status has not been frequently investigated despite its importance given the different impact of risk factors on breast cancer risk depending on menopausal status. OBJECTIVES: To study the association between air pollution, green spaces and pre and postmenopausal breast cancer risk. METHODS: We conducted a population-based cohort study using electronic primary care records in Catalonia. We included women aged 17-85 years free of cancer at study entry between 2009 and 2017. Our exposures were particulate matter <2.5 µm (PM2.5) & <10 µm (PM10), nitrogen dioxide (NO2), normalized difference vegetation index (NDVI), and percentage of green spaces estimated at the census tract level. Breast cancer was identified with ICD-10 code C50. We estimated cause-specific hazard ratios (HR) for the relationship between each individual exposure and pre and postmenopausal breast cancer risk, using linear and non-linear models. RESULTS: Of the 1,054,180 pre and 744,658 postmenopausal women followed for a median of 10 years, 6,126 and 17,858 developed breast cancer, respectively. Among premenopausal women, only very high levels of PM10 (≥46 µg/m3) were associated with increased cancer risk (compared to lower levels) in non-linear models. Among postmenopausal women, an interquartile range increase in PM2.5 (HR:1.03; 95%CI:1.01-1.04), PM10 (1.03; 1.01-1.05), and NO2 (1.05; 1.02-1.08) were associated with higher cancer risk. NDVI was negatively associated with decreased cancer risk only among postmenopausal women who did not change residence during follow-up (0.84; 0.71-0.99) or who were followed for at least three years (0.82; 0.69-0.98). DISCUSSION: Living in areas with high concentrations of PM2.5, PM10, and NO2 increases breast cancer risk in postmenopausal women while long-term exposure to green spaces may decrease this risk. Only very high concentrations of PM10 increase breast cancer risk in premenopausal women.

Urban environment and physical activity and capacity in patients with chronic obstructive pulmonary disease.

BACKGROUND: Physical activity and exercise capacity are key prognostic factors in chronic obstructive pulmonary disease (COPD) but their environmental determinants are unknown. OBJECTIVES: To test the association between urban environment and objective physical activity, physical activity experience and exercise capacity in COPD. METHODS: We studied 404 patients with mild-to-very severe COPD from a multi-city study in Catalonia, Spain. We measured objective physical activity (step count and sedentary time) by the Dynaport MoveMonitor, physical activity experience (difficulty with physical activity) by the Clinical visit-PROactive (C-PPAC) instrument, and exercise capacity by the 6-min walk distance (6MWD). We estimated individually (geocoded to the residential address) population density, pedestrian street length, slope of terrain, and long-term (i.e., annual) exposure to road traffic noise, nitrogen dioxide (NO2) and particulate matter (PM2.5). We built single- and multi-exposure mixed-effects linear regressions with a random intercept for city, adjusting for confounders. RESULTS: Patients were 85% male, had mean (SD) age 69 (9) years and walked 7524 (4045) steps/day. In multi-exposure models, higher population density was associated with fewer steps, more sedentary time and worse exercise capacity (-507 [95% CI: 1135, 121] steps, +0.2 [0.0, 0.4] h/day and -13 [-25, 0] m per IQR). Pedestrian street length related with more steps and less sedentary time (156 [9, 304] steps and -0.1 [-0.1, 0.0] h/day per IQR). Steeper slope was associated with better exercise capacity (15 [3, 27] m per IQR). Higher NO2 levels related with more sedentary time and more difficulty in physical activity. PM2.5 and noise were not associated with physical activity or exercise capacity. DISCUSSION: Population density, pedestrian street length, slope and NO2 exposure relate to physical activity and capacity of COPD patients living in highly populated areas. These findings support the consideration of neighbourhood environmental factors during COPD management and the attention to patients with chronic diseases when developing urban and transport planning policies.

Impacts of changes in environmental exposures and health behaviours due to the COVID-19 pandemic on cardiovascular and mental health: A comparison of Barcelona, Vienna, and Stockholm.

Responses to COVID-19 altered environmental exposures and health behaviours associated with non-communicable diseases. We aimed to (1) quantify changes in nitrogen dioxide (NO2), noise, physical activity, and greenspace visits associated with COVID-19 policies in the spring of 2020 in Barcelona (Spain), Vienna (Austria), and Stockholm (Sweden), and (2) estimated the number of additional and prevented diagnoses of myocardial infarction (MI), stroke, depression, and anxiety based on these changes. We calculated differences in NO2, noise, physical activity, and greenspace visits between pre-pandemic (baseline) and pandemic (counterfactual) levels. With two counterfactual scenarios, we distinguished between Acute Period (March 15th - April 26th, 2020) and Deconfinement Period (May 2nd - June 30th, 2020) assuming counterfactual scenarios were extended for 12 months. Relative risks for each exposure difference were estimated with exposure-risk functions. In the Acute Period, reductions in NO2 (range of change from -16.9 µg/m3 to -1.1 µg/m3), noise (from -5 dB(A) to -2 dB(A)), physical activity (from -659 MET*min/wk to -183 MET*min/wk) and greenspace visits (from -20.2 h/m to 1.1 h/m) were largest in Barcelona and smallest in Stockholm. In the Deconfinement Period, NO2 (from -13.9 µg/m3 to -3.1 µg/m3), noise (from -3 dB(A) to -1 dB(A)), and physical activity levels (from -524 MET*min/wk to -83 MET*min/wk) remained below pre-pandemic levels in all cities. Greatest impacts were caused by physical activity reductions. If physical activity levels in Barcelona remained at Acute Period levels, increases in annual diagnoses for MI (mean: 572 (95% CI: 224, 943)), stroke (585 (6, 1156)), depression (7903 (5202, 10,936)), and anxiety (16,677 (926, 27,002)) would be anticipated. To decrease cardiovascular and mental health impacts, reductions in NO2 and noise from the first COVID-19 surge should be sustained, but without reducing physical activity. Focusing on cities' connectivity that promotes active transportation and reduces motor vehicle use assists in achieving this goal.

Impact of road traffic noise on annoyance and preventable mortality in European cities: A health impact assessment.

BACKGROUND: Road traffic is the main source of environmental noise in European cities and one of the main environmental risks to health and wellbeing. In this study we aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe. METHODS: We conducted the analysis for 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24 h day-evening-night noise level indicator (Lden) starting at exposure levels of 55 dB Lden - based on data availability - for the adult population aged 20 and over (n = 123,966,346). For the adults exposed to noise levels above 55 dB Lden we estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53 dB Lden. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Exposure Response Functions (ERFs) relating road traffic noise exposure to annoyance and IHD mortality were retrieved from the literature. Uncertainties in input parameters were propagated using Monte Carlo simulations to obtain point estimates and empirical 95% Confidence Intervals (CIs). Lastly, the noise maps were categorized as high, moderate and low quality following a qualitative approach. RESULTS: Strategic noise map data was delivered in three distinct formats (i.e. raster, polygon or polyline) and had distinct noise ranges and levels of categorization. The majority of noise maps (i.e. 83.2%) were considered of moderate or low quality. Based on the data provided, almost 60 million adults were exposed to road traffic noise levels above 55 dB Lden, equating to a median of 42% (Interquartile Range (IQR): 31.8-64.8) of the adult population across the analysed cities. We estimated that approximately 11 million adults were highly annoyed by road traffic noise and that 3608 deaths from IHD (95% CI: 843-6266) could be prevented annually with compliance of the WHO recommendation. The proportion of highly annoyed adults by city had a median value of 7.6% (IQR: 5.6-11.8) across the analysed cities, while the number preventable deaths had a median of 2.2 deaths per 100,000 population (IQR: 1.4-3.1). CONCLUSIONS: Based on the provided strategic noise maps a considerable number of adults in European cities are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase noise and disease data availability at the city level are needed. These would allow for a more accurate and comprehensive assessment of the health impacts and further help local governments to address the adverse health effects of road traffic noise.