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- Alemany, S., et al.
(author)
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Associations between air pollution and biomarkers of Alzheimer's disease in cognitively unimpaired individuals
- 2021
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In: Environment International. - : Elsevier BV. - 0160-4120. ; 157
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Journal article (peer-reviewed)abstract
- Background: Air quality contributes to incidence of Alzheimer's disease (AD) although the underlying neurobiological mechanisms are unclear. This study was aimed to examine the association between air pollution and concentrations of cerebrospinal fluid (CSF) AD biomarkers and amyloid-beta (A beta) deposition. Participants and methods The sample included 156 cognitively unimpaired adults aged 57 years (61 at biomarkers assessment) with increased risk of AD from the ALFA + Study. We examined CSF levels of A beta 42, A beta 40, p-Tau, t-Tau, neurofilament light (NfL) and cerebral amyloid load (Centiloid). A Land Use Regression model from 2009 was used to estimate residential exposure to air pollutants including nitrogen dioxide (NO2,) and particulate matter (PM2.5, PM2.5 abs, PM10). This model was considered a surrogate of long-term exposure until time of data collection in 2013-2014. Participants have resided in the same residence for at least the previous 3 years. Multiple linear regression models were used to estimate associations between air pollutants and biomarkers. The effect modification by CSF A beta status and APOE-epsilon 4 carriership was also assessed. Results: A consistent pattern of results indicated that greater exposure to NO2 and PM2.5 absorbance was associated with higher levels of brain A beta deposition, while greater exposure to PM10 and PM(2.5)was associated with higher levels of CSF NfL. Most associations were driven by individuals that were A beta-positive. Although APOE-epsilon 4 status did not significantly modify these associations, the effect of air pollutants exposure on CSF NfL levels was stronger in APOE-epsilon 4 carriers. Conclusion: In a population of cognitively unimpaired adults with increased risk of AD, long-term exposure to air pollution was associated with higher levels in biomarkers of AD pathology. While further research is granted to elucidate the mechanisms involved in such associations, our results reinforce the role of air pollution as an environmental risk factor for AD.
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- White, MP, et al.
(author)
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Associations between green/blue spaces and mental health across 18 countries
- 2021
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1, s. 8903-
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Journal article (peer-reviewed)abstract
- Living near, recreating in, and feeling psychologically connected to, the natural world are all associated with better mental health, but many exposure-related questions remain. Using data from an 18-country survey (n = 16,307) we explored associations between multiple measures of mental health (positive well-being, mental distress, depression/anxiety medication use) and: (a) exposures (residential/recreational visits) to different natural settings (green/inland-blue/coastal-blue spaces); and (b) nature connectedness, across season and country. People who lived in greener/coastal neighbourhoods reported higher positive well-being, but this association largely disappeared when recreational visits were controlled for. Frequency of recreational visits to green, inland-blue, and coastal-blue spaces in the last 4 weeks were all positively associated with positive well-being and negatively associated with mental distress. Associations with green space visits were relatively consistent across seasons and countries but associations with blue space visits showed greater heterogeneity. Nature connectedness was also positively associated with positive well-being and negatively associated with mental distress and was, along with green space visits, associated with a lower likelihood of using medication for depression. By contrast inland-blue space visits were associated with a greater likelihood of using anxiety medication. Results highlight the benefits of multi-exposure, multi-response, multi-country studies in exploring complexity in nature-health associations.
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- Beelen, Rob, et al.
(author)
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Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe : the ESCAPE project
- 2013
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In: Atmospheric Environment. - : Elsevier. - 1352-2310 .- 1873-2844. ; 72, s. 10-23
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Journal article (peer-reviewed)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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- Fuks, Kateryna B., et al.
(author)
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Arterial blood pressure and long-term exposure to traffic-related air pollution : an analysis in the European Study of Cohorts for Air Pollution Effects (ESCAPE)
- 2014
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In: Journal of Environmental Health Perspectives. - : National Institute of Environmental Health Sciences (NIEHS). - 0091-6765 .- 1552-9924. ; 122:9, s. 896-905
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Research review (peer-reviewed)abstract
- BACKGROUND: Long-term exposure to air pollution is hypothesized to elevate arterial blood pressure (BP). The existing evidence is scarce and country-specific. OBJECTIVES: We investigated the cross-sectional association of long-term traffic-related air pollution with BP and prevalent hypertension in European populations. METHODS: Fifteen population-based cohorts, participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE), were analysed. Residential exposure to particulate matter and nitrogen oxides was modelled with land use regression using a uniform protocol. Traffic exposure was assessed with traffic indicator variables. We analysed systolic and diastolic BP in participants medicated and non-medicated with BP lowering medication (BPLM) separately, adjusting for personal and area-level risk factors and environmental noise. Prevalent hypertension was defined as ≥ 140 mmHg systolic, or ≥ 90 mmHg diastolic BP, or intake of BPLM. We combined cohort-specific results using random-effects meta-analysis. RESULTS: In the main meta-analysis of 113,926 participants, traffic load on major roads within 100 m of the residence was associated with increased systolic and diastolic BP in non-medicated participants (0.35 mmHg [95% CI: 0.02-0.68] and 0.22 mmHg [95% CI: 0.04-0.40] per 4,000,000 vehicles × m/day, respectively). The estimated odds ratio for prevalent hypertension was 1.05 [95% CI: 0.99-1.11] per 4,000,000 vehicles × m/day. Modelled air pollutants and BP were not clearly associated. CONCLUSIONS: In this first comprehensive meta-analysis of European population-based cohorts we observed a weak positive association of high residential traffic exposure with BP in non-medicated participants, and an elevated OR for prevalent hypertension. The relationship of modelled air pollutants with BP was inconsistent.
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- Jacquemin, Benedicte, et al.
(author)
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Ambient Air Pollution and Adult Asthma Incidence in Six European Cohorts (ESCAPE)
- 2015
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In: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 123:6, s. 613-621
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Journal article (peer-reviewed)abstract
- BACKGROUND: Short-term exposure to air pollution has adverse effects among patients with asthma, but whether long-term exposure to air pollution is a cause of adult-onset asthma is unclear. OBJECTIVE: We aimed to investigate the association between air pollution and adult onset asthma. METHODS: Asthma incidence was prospectively assessed in six European cohorts. Exposures studied were annual average concentrations at home addresses for nitrogen oxides assessed for 23,704 participants (including 1,257 incident cases) and particulate matter (PM) assessed for 17,909 participants through ESCAPE land-use regression models and traffic exposure indicators. Meta-analyses of cohort-specific logistic regression on asthma incidence were performed. Models were adjusted for age, sex, overweight, education, and smoking and included city/area within each cohort as a random effect. RESULTS: In this longitudinal analysis, asthma incidence was positively, but not significantly, associated with all exposure metrics, except for PMcoarse. Positive associations of borderline significance were observed for nitrogen dioxide [adjusted odds ratio (OR) = 1.10; 95% CI: 0.99, 1.21 per 10 mu g/m(3); p = 0.10] and nitrogen oxides (adjusted OR = 1.04; 95% CI: 0.99, 1.08 per 20 mu g/m(3); p = 0.08). Nonsignificant positive associations were estimated for PM10 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 10 mu g/m(3)), PM2.5 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 5 mu g/m(3)), PM2.5absorbance (adjusted OR = 1.06; 95% CI: 0.95, 1.19 per 10(-5)/m), traffic load (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 4 million vehicles x meters/day on major roads in a 100-m buffer), and traffic intensity (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 5,000 vehicles/day on the nearest road). A nonsignificant negative association was estimated for PMcoarse (adjusted OR = 0.98; 95% CI: 0.87, 1.14 per 5 mu g/m(3)). CONCLUSIONS: Results suggest a deleterious effect of ambient air pollution on asthma incidence in adults. Further research with improved personal-level exposure assessment (vs. residential exposure assessment only) and phenotypic characterization is needed.
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- Nieuwenhuijsen, Mark, et al.
(author)
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The Superblock model : A review of an innovative urban model for sustainability, liveability, health and well-being
- 2024
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In: Environmental Research. - : Elsevier. - 0013-9351 .- 1096-0953. ; 251
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Research review (peer-reviewed)abstract
- IntroductionCurrent urban and transport planning practices have significant negative health, environmental, social and economic impacts in most cities. New urban development models and policies are needed to reduce these negative impacts. The Superblock model is one such innovative urban model that can significantly reduce these negative impacts through reshaping public spaces into more diverse uses such as increase in green space, infrastructure supporting social contacts and physical activity, and through prioritization of active mobility and public transport, thereby reducing air pollution, noise and urban heat island effects. This paper reviews key aspects of the Superblock model, its implementation and initial evaluations in Barcelona and the potential international uptake of the model in Europe and globally, focusing on environmental, climate, lifestyle, liveability and health aspects.MethodsWe used a narrative meta-review approach and PubMed and Google scholar databases were searched using specific terms.ResultsThe implementation of the Super block model in Barcelona is slow, but with initial improvement in, for example, environmental, lifestyle, liveability and health indicators, although not so consistently. When applied on a large scale, the implementation of the Superblock model is not only likely to result in better environmental conditions, health and wellbeing, but can also contribute to the fight against the climate crisis. There is a need for further expansion of the program and further evaluation of its impacts and answers to related concerns, such as environmental equity and gentrification, traffic and related environmental exposure displacement. The implementation of the Superblock model gained a growing international reputation and variations of it are being planned or implemented in cities worldwide. Initial modelling exercises showed that it could be implemented in large parts of many cities.ConclusionThe Superblock model is an innovative urban model that addresses environmental, climate, liveability and health concerns in cities. Adapted versions of the Barcelona Superblock model are being implemented in cities around Europe and further implementation, monitoring and evaluation are encouraged. The Superblock model can be considered an important public health intervention that will reduce mortality and morbidity and generate cost savings for health and other sectors.
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