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Background
Various aspects of the urban environment and neighbourhood socio-economic status interact with each other to affect health. Few studies to date have quantitatively assessed intersections of multiple urban environmental factors and their distribution across levels of deprivation.
Objectives
To explore the spatial patterns of urban enviro...
Context in source publication
Context 1
... all 3 cities, greenness was negatively correlated with both walkability (r = −0.51 to −0.63) and NO 2 (r = −0.40 to −0.61), while walkability showed a positive correlation with NO 2 (r = 0.09-0.50) ( Table 2). Table 3 shows the relative prevalence of postal codes in the lowest and highest tertiles of exposure across material deprivation quintiles. ...Similar publications
Few studies have examined the association between air pollution and the trajectory of global health status measures related to the functional impacts of chronic disease. To address this gap, we examined the trajectory of the Health Utilities Index (HUI) over 17 years of follow-up among Canadian National Population Health Survey (NPHS) participants....
Background
Air pollution may be a risk factor for physical inactivity and sedentary behaviour (SED) through discouraging active lifestyles, impairing fitness and contributing to chronic diseases with potentially important consequences for population health.
Methods
Using generalized estimating equations, we examined the associations between long-te...
Introduction: The World Health Organization (WHO) recently revised its health guidelines for Nitrogen dioxide (NO2) air pollution, reducing the annual mean NO2 level to 10 μg/m³ (5.3 ppb) and the 24-h mean to 25 μg/m³ (13.3 ppb). NO2 is a pollutant of global concern, but it is also a criteria air pollutant that varies spatiotemporally at fine resol...
Background
The urban environment is characterised by many exposures that may influence hypertension development from early life onwards, but there is no systematic evaluation of their impact on child blood pressure (BP).
Methods
Systolic and diastolic blood pressure were measured in 4,279 children aged 4–5 years from a multi-centre European cohort...
Air pollution seriously threatens human health and even causes mortality. It is necessary to ex-plore effective prevention methods to mitigate the adverse effect of air pollution. Shaping a reasonable built environment has the potential to benefit human health. In this context, this study quantified the built environment, air pollution, and mortali...
Citations
... It is also important to note that exposure to environmental carcinogens is not evenly distributed across populations, creating environmental inequity. Studies have shown that higher exposures to hazardous air pollutants as well as non-air-pollutant-related hazards, including water contaminants such as lead (21), lack of greenspace (22,23), and poor walkability scores (24,25) among socially and/or economically disadvantaged populations (26)(27)(28)(29)(30)(31)(32)). An assessment of differences in colorectal cancer (CRC) survival between urban and rural areas by Fu et al., revealed a notable difference in CRC survival, highlighting the importance of considering urban-rural disparities in CRC prognosis and the influence of socioeconomic factors on survival outcomes. ...
... A key finding is that these measurement variations may be representative of disagreement, conflation, or confusion on equity-related terminology. This study's recommendation to the urban health field is for future research to clearly understand and label the term 'inequity' to consistently accurately describe how elements of the built environment are distributed and used and how this distribution impacts health [12,26,27,43]. Clear, consistent language is essential for ensuring that the findings in this field are measured, interpreted, and communicated accurately [27]. ...
Accurately measuring spatial inequities in the built environment is essential for meaningful research on how environmental factors influence health. This study aimed to (1) systematically identify how spatial inequities are measured in urban health research and (2) assess the conceptual clarity of studies on spatial inequities and inequalities. A scoping review of four electronic databases (PubMed, Web of Science, GreenFILE, and Global Health) was conducted. From 921 results, 44 full-text articles were reviewed. Studies most frequently measured access to green spaces (n = 20, 45.5%), food environment (n = 7, 15.9%), and walkability (n = 5, 11.4%). Most studies (n = 32, 73%) were conducted in high-income countries. The primary analytical approaches were descriptive (n = 11, 25%). Most studies (n = 43, 97.73%) contained misalignment between concepts they purposed to measure, and variables and analyses used. Concepts such as accessibility (n = 10, 22.72%), environmental justice (n = 5, 11.36%), and spatial equity (n = 3, 6.81%) were prevalent. This study’s results highlight the need for conceptual clarity on spatial inequity and inequality within urban health research. This research highlights the reliance on descriptive methodologies and advocates for robust statistical approaches. With conceptual clarity and improved measurements, researchers and practitioners can better develop strategies to advance urban health policies with the goal of reducing health inequities.
... For example, neighbourhoods with high walkability and active transportation plus low air pollution almost exclusively have high-income residents, both in Metro Vancouver and Minneapolis in the U.S Marshall et al., 2009). This is similar for greenness and NO 2 concentration, where in Toronto, Montreal, and Vancouver in Canada, postal codes with both high greenness and low NO 2 concentration generally have lower material deprivation (Doiron et al., 2020). These studies also highlight the distinct patterns that emerge when considering multiple environmental factors in tandem, an important area for future study. ...
... To capture the interactions between environmental variables, we conduct a two-dimensional environmental assessment to identify the environmental "sweet," "sour," "risky," and "medium" spots in urban areas in Metro Vancouver, which are referred to as sweet and sour spots analysis in the following content (Doiron et al., 2020). "Sweet spots" refer to the DAs in which both environmental variables have favorable performance in terms of impacts on human health: for example, low air pollutant concentration and high walkability. ...
... See Figure S2 in Supporting Information S1 for an illustrative figure for the classification of sweet, sour, and risky spots. Sweet and sour spot analysis is a powerful tool for characterizing the cumulative exposure to two to three variables in the environment considering their interactions (Doiron et al., 2020). Furthermore, it can inform decision-making to prioritize neighborhoods for intervention. ...
The urban environment impacts residents' health and well‐being in many ways. Environmental benefits and risks may be interactively and inequitably distributed across different populations in cities, and these patterns may change over time. Here, we assess the spatial distribution of environmental risks and benefits in pairs, considering synergies and trade‐offs, in an illustrative metropolitan area (Metro Vancouver) in Canada in the years 2006 and 2016. We classify census dissemination areas as sweet, sour, risky, or medium spots based on relative exposures for six environmental combinations: Walkability and NO2; heat stress and NO2; vegetation coverage and NO2; vegetation coverage and heat stress; walkability and accessibility to natural recreational areas; and heat stress and accessibility to natural recreational areas. We evaluate whether different population groups are disproportionately exposed to lower environmental quality based on linear regressions and other metrics. We find that while performance for individual environmental variables improved over the decade, considering their combinations, sweet spots became sweeter and sour spots became sourer. Residents with high material and social deprivation and visible minorities were disproportionately exposed to lower environmental quality in both years for most of the environmental combinations. Further, we find that these inequities were not improving over time for all groups: for instance, South Asian residents in the region faced higher disproportionate burdens or diminished access to benefits in 2016, as compared to 2006. Given these findings, we suggest considerations of cumulative exposure in prioritizing areas for intervention, targeting the sour and risky spots persistently experienced by overburdened populations.
... In this regard, the European context contrasts with other regions such as North America, where air pollution, lack of green space, and poor walkability are consistently more frequent in socioeconomically deprived areas. 16,17 The heterogeneity of associations across cohorts and countries can be related to the large geographical areas included in our study, including urban centers and larger regional/national cohorts. It can also be leveraged in epidemiological studies to examine various confounder structures when investigating socioeconomic determinants of health. ...
Socioeconomic inequalities in the exposome have been found to be complex and highly context-specific, but studies have not been conducted in large population-wide cohorts from multiple countries. This study aims to examine the external exposome, encompassing individual and environmental factors influencing health over the life course, and to perform dimension reduction to derive interpretable characterization of the external exposome for multicountry epidemiological studies. Analyzing data from over 25 million individuals across seven European countries including 12 administrative and traditional cohorts, we utilized domain-specific principal component analysis (PCA) to define the external exposome, focusing on air pollution, the built environment, and air temperature. We conducted linear regression to estimate the association between individual- and area-level socioeconomic position and each domain of the external exposome. Consistent exposure patterns were observed within countries, indicating the representativeness of traditional cohorts for air pollution and the built environment. However, cohorts with limited geographical coverage and Southern European countries displayed lower temperature variability, especially in the cold season, compared to Northern European countries and cohorts including a wide range of urban and rural areas. The individual- and area-level socioeconomic determinants (i.e., education, income, and unemployment rate) of the urban exposome exhibited significant variability across the European region, with area-level indicators showing stronger associations than individual variables. While the PCA approach facilitated common interpretations of the external exposome for air pollution and the built environment, it was less effective for air temperature. The diverse socioeconomic determinants suggest regional variations in environmental health inequities, emphasizing the need for targeted interventions across European countries.
... When looking into walking infrastructure in the context of societal or area factors of the social environment, and how it is related to opportunities for PA, we found four studies at the community level, indicating that high-SES areas tended to have higher walkability scores than low-SES areas [25][26][27][28]. A walkability score is a measure of how conducive an area is to walking and is influenced by the walking infrastructure factors. ...
... However, Giles et al. [51] presented a contrasting view on the limited benefits of green spaces in low-SES areas, highlighting the complexity of the relationship between green spaces and PA. Doiron et al. [26] observed that high-deprivation neighbourhoods had less access to greenness, affecting PA. Mears et al. [60] showed that residents from deprived areas in Sheffield made shorter, less active visits to green spaces. ...
Background
The association between social and built environments plays a crucial role in influencing physical activity levels. However, a thorough understanding of their combined impact remains unclear. This scoping review seeks to clarify the interplay between social environments and opportunities for physical activity within different built environments, with a particular focus on the implications of socioeconomic status and urban planning on physical activity participation.
Methods
We conducted a systematic literature search across several databases to identify studies exploring the associations between social factors, built environment characteristics, and physical activity levels. The inclusion criteria were studies published in English between 2000 and 2022, encompassing urban, suburban, and rural contexts. Thematic analysis was employed to categorise studies based on the specific aspects of the built environment they investigated (walking infrastructure, cycling infrastructure, parks and open spaces, and sports facilities) and the social determinants they examined.
Results
A total of 72 studies were included in the review, illustrating a multifaceted relationship between access to physical activity opportunities and social determinants such as socioeconomic status, community engagement, and urban design. The findings highlight the significant role of socioeconomic factors and the quality of PA infrastructure in promoting or hindering PA across communities. Effective urban planning was identified as crucial in providing expanded physical activity opportunities, notably through more pedestrian-friendly environments, comprehensive cycling infrastructure, and accessible green spaces and sports facilities.
Conclusions
This review emphasises the significant impact of socioeconomic status and urban planning on access to physical activity opportunities. This underscores the necessity for urban planning policies to adopt an inclusive approach, considering the varied needs of different population groups to ensure equitable access to physical activity resources. Such strategies are crucial for public health initiatives aimed at enhancing physical activity levels across diverse community sectors, offering a potential avenue to alleviate health disparities associated with inactivity.
... Third, similar to ours, environmental justice studies usually assess exposures one at a time. While unfavorable exposures typically co-occur (Hankey and Marshall, 2017), scholarship considering synergistic and competing effects is warranted to capture possible multi-environmental jeopardy (Doiron et al., 2020). Fourth, some socio-demographics that were found elsewhere to be related to NTL were insignificant in our case. ...
Introduction
Outdoor nighttime light (NTL) is a potential anthropogenic stressor in urban settings. While ecological studies have identified outdoor NTL exposure disparities, uncertainties remain about disparities in individual exposure levels, particularly in Europe.
Aim
To assess whether some populations are disproportionately affected by outdoor NTL at their residences in urban Bulgaria.
Methods
We analyzed 2023 data from a representative cross-sectional survey of 4,270 adults from the five largest Bulgarian cities. Respondents’ annual exposures to outdoor artificial nighttime luminance were measured using satellite imagery and assigned at their places of residence. We calculated the Gini coefficient as a descriptive NTL inequality measure. Associations between respondents’ NTL exposure levels and sociodemographic characteristics were assessed by estimating quantile mixed regression models. Stratified regressions were fitted by gender and for each city.
Results
We found moderate distributive NTL inequalities, as indicated by a 0.214 Gini coefficient. Regression analyses found associations between greater NTL exposure and higher educational attainment. Respondents with incomes perceived as moderate experienced less NTL exposure at the 0.5 and 0.8 quantiles, while unemployed respondents experienced lower exposure at the 0.2 and 0.5 quantiles. We observed null associations for the elderly and non-Bulgarian ethnicities. Regardless of the quantile, greater population density was associated with higher NTL levels. Stratification by sex did not yield substantial differences in the associations. We observed notable city-specific heterogeneities in the associations, with differences in the magnitudes and directions of the associations and the NTL quantiles.
Conclusions
NTL exposures appeared to embody an environmental injustice dimension in Bulgaria. Our findings suggest that some sociodemographic populations experience higher exposure levels to NTL; however, those are not necessarily the underprivileged or marginalized. Identifying populations with high exposure levels is critical to influencing lighting policies to ease related health implications.
... Moreover, further studies have demonstrated the existence of a relationship between material deprivation, health status, and exposure to unfavorable environmental conditions (e.g., air pollution and greenness) [28,29]. In the context of promoting an economic and social recovery inspired by sustainability goals, identifying the areas most critical in terms of material deprivation could also influence the formulation of European green policies. ...
Since the early 2000s, the European Union has increasingly prioritized policies aimed at combating social exclusion, with a focus on efficient fund allocation for social and sustainable cohesion objectives. Given the multidimensional nature of material deprivation, synthetic indicators are frequently employed in the literature to measure this phenomenon. However, these indicators often lack suitability for temporal analysis, which is crucial for understanding the persistence of disadvantaged statuses over time and the effectiveness of national and international policies. This article offers an innovative examination of the trends in material deprivation among European Union Member States during the period of 2005–2022. It provides a structured reconstruction of the phenomenon at the NUTS-1 level, within the context of the major economic and health crises that have characterized the 21st century. This study’s key innovation lies in the creation of a temporal index of material deprivation, employing the AMPI method, which incorporates a partially compensatory aggregative synthesis and allows for the monitoring of the phenomenon over time against a baseline year. This novel approach ensures the capability to analyze the evolution of material deprivation over time and across regions, with 2005 as the reference year. The findings reveal a general improvement in material deprivation levels compared to 2005, despite deteriorating conditions in the Mediterranean and Baltic regions. By maintaining 2005 as the reference year, this index facilitates the ongoing monitoring of the impacts of COVID-19 and the effects of national recovery policies, as well as the resilient and sustainable social policies promoted by the RecoverEU fund.
... coherence and compactness) and deprivation in Isfahan, and found coherence to be positively associated, while compactness not statistically relevant. Similarly, Doiron et al. (2020) investigated the relationship between deprivation and presence of desirable urban features, such as walkability and greenery. Their findings suggest that both qualities were more common in least deprived areas and less so in highly deprived areas, highlighting patterns of environmental inequality. ...
Studies on urban deprivation date back to the 19 th Century but remain important today due to rising levels of inequality and social segregation. However, while social causes of deprivation have been investigated, the role of the built environment remains neglected. Existing studies either provide broad coverage at the expense of detailed morphological descriptions or offer meticulous accounts of small-scale areas without capturing the broader context. This paper addresses this gap by investigating the relationship between urban form, measured at the building level, and deprivation across the entire city of Isfahan, Iran. By doing so, we position this study in the tradition of urban morphology. Operationally, we, first, identify urban types (UTs), that is, distinctive patterns of urban form, by clustering 200+ morphological characters; second, we explore the relationship between proportion of buildings belonging to each UT, in each neighbourhood, and deprivation; third, we offer detailed descriptions of the UTs most strongly associated with deprivation, discuss possible drivers for the observed correlations, and link findings to relevant literature in the field. Twelve UTs are identified, with four showing the strongest impacts on predicting deprivation. This study brings novel insights on the morphology of deprivation of Isfahan, while contextualising them with respect to domain-specific studies, which have predominantly focused on Western cities. The proposed methodology can be replicated to explore morphologies of deprivation in different contexts, further our understanding of the topic, and potentially inform planning and policy making.
... Chronic disease morbidity and mortality are linked with urban environmental exposures and attributes including air quality [1], neighborhood greenness [2], urban heat islands [3], healthy food availability [4], and the extent to which individuals can walk and cycle to their destinations (i.e., active transportation) [5]. Lower socioeconomic status (SES) neighborhoods are correlated with less beneficial environmental conditions such as higher air pollution concentrations and summer temperatures, and lower neighborhood greenness, walkability, and active transportation opportunities, which in turn negatively affect health outcomes [6][7][8][9][10]. ...
Urban environmental factors such as air quality, heat islands, and access to greenspaces and community amenities impact public health. Some vulnerable populations such as low-income groups, children, older adults, new immigrants, and visible minorities live in areas with fewer beneficial conditions, and therefore, face greater health risks. Planning and advocating for equitable healthy urban environments requires systematic analysis of reliable spatial data to identify where vulnerable populations intersect with positive or negative urban/environmental characteristics. To facilitate this effort in Canada, we developed HealthyPlan.City (https://healthyplan.city/), a freely available web mapping platform for users to visualize the spatial patterns of built environment indicators, vulnerable populations, and environmental inequity within over 125 Canadian cities. This tool helps users identify areas within Canadian cities where relatively higher proportions of vulnerable populations experience lower than average levels of beneficial environmental conditions, which we refer to as Equity priority areas. Using nationally standardized environmental data from satellite imagery and other large geospatial databases and demographic data from the Canadian Census, HealthyPlan.City provides a block-by-block snapshot of environmental inequities in Canadian cities. The tool aims to support urban planners, public health professionals, policy makers, and community organizers to identify neighborhoods where targeted investments and improvements to the local environment would simultaneously help communities address environmental inequities, promote public health, and adapt to climate change. In this paper, we report on the key considerations that informed our approach to developing this tool and describe the current web-based application.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11524-024-00855-x.
... However, existing research that studies multi-exposure interactions seldom considers spatial autocorrelation among exposures or health outcomes. In urban areas, there is often a co-location and clustering of multiple environmental exposures; for example, areas with low vegetation coverage may exhibit high concentrations of air pollution and high temperatures (Doiron et al., 2020;Yang et al., 2020;Dadvand et al., 2012). Such co-located, interactive exposures might be spatially correlated (de Keijzer et al., 2017;Browning and Rigolon, 2018;Verbeek, 2019;Elliott and Wartenberg, 2004). ...
Background
Although studies have provided negative impacts of air pollution, heat or cold exposure on mortality and morbidity, and positive effects of increased greenness on reducing them, a few studies have focused on exploring combined and synergetic effects of these exposures in predicting these health outcomes, and most had ignored the spatial autocorrelation in analyzing their health effects. This study aims to investigate the health effects of air pollution, greenness, and temperature exposure on premature mortality and morbidity within a spatial machine-learning modeling framework.
Methods
Years of potential life lost reflecting premature mortality and comparative illness and disability ratio reflecting chronic morbidity from 1673 small areas covering Greater Manchester for the year 2008–2013 obtained. Average annual levels of NO2 concentration, normalized difference vegetation index (NDVI) representing greenness, and annual average air temperature were utilized to assess exposure in each area. These exposures were linked to health outcomes using non-spatial and spatial random forest (RF) models while accounting for spatial autocorrelation.
Results
Spatial-RF models provided the best predictive accuracy when accounted for spatial autocorrelation. Among the exposures considered, air pollution emerged as the most influential in predicting mortality and morbidity, followed by NDVI and temperature exposure. Nonlinear exposure-response relations were observed, and interactions between exposures illustrated specific ranges or sweet and sour spots of exposure thresholds where combined effects either exacerbate or moderate health conditions.
Conclusion
Air pollution exposure had a greater negative impact on health compared to greenness and temperature exposure. Combined exposure effects may indicate the highest influence of premature mortality and morbidity burden.
