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Permeable pavements help reduce surface temperatures and have been widely implemented in urban areas. This study utilized an in-use permeable pavement sidewalk in front of a mass rapid transit station in the Taipei city center of Taiwan to determine the actual pavement surface temperature performance. A neighboring asphalt road and impervious pavement were also monitored. With a full year of continuous monitoring, the results showed that the temperature of permeable pavement was 3.7 °C lower than that of impervious pavement and 4.5 °C lower than that of asphalt pavement in the hot season. The frequent rainfall in spring resulted in the smallest temperature differences between the different pavement types. The cooling effects of permeable pavement differed at the different air temperatures. At air temperatures lower than 15 °C, the differences among pavement surface temperatures were noticeable. However, when the air temperature was higher than 35 °C, the surface temperature of permeable pavement was not different from that of impervious pavement and was greater than 55 °C. Field observations were carried out to determine the effects on the apparent temperature and the future surface temperature of climate change scenarios. The results showed that permeable pavement could reduce the average apparent temperature to near the air temperature, and asphalt pavement could increase the apparent temperature by 1.2 °C, assuming that the pavement temperature completely affects the air temperature. With the good prediction ability of the machine learning approach and 15 environmental factors, the preliminary prediction showed the projected surface temperature change in Taipei city in 2033. In the worst-case scenario, the average impervious pavement temperature is as high as 39.12 °C, whereas the average permeable pavement temperature is 32.50 °C.

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Urbanization and its urban-heat-island effect (UHI) have expanding footprints worldwide. The UHI means that urban habitats experience a higher mean and more frequent extreme high temperatures than rural habitats, impacting the ontogeny and resilience of urban biodiversity. However, many organisms occupy different microhabitats during different life stages and thus may experience the UHI differently across their development. While evolutionary changes in heat tolerance in line with the UHI have been demonstrated, it is unknown whether such evolutionary responses can vary across development. Here, using common-garden-reared Chiasmia clathrata moths from urban and rural populations from three European countries, we tested for urban evolution of heat shock tolerance in two life stages: larvae and adults. Our results indicate widespread urban evolution of increased heat tolerance in the adult stage only, suggesting that the UHI may be a stronger selective agent in adults. We also found that the difference in heat tolerance between urban and rural populations was similar to the difference between Mid- and North-European regions, suggesting similarity between adaptation to the UHI and natural, latitudinal temperature variation. Our observations incentivize further research to quantify the impact of these UHI adaptations on fitness during urbanization and climate change, and to check whether life-stage-specific adaptations in heat tolerance are typical of other ectothermic species that manage to survive in urbanized settings.

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The development of urban blue-green spaces is highly recommended as a nature-based solution for mitigating the urban heat island phenomenon, improving urban sustainability, and enhancing resident well-being. However, limited attention has been given to the accumulative impact of the cooling effect and the comparison of different types of landscapes. Based on the maximum and accumulative perspectives, this study selected 375 green spaces, water bodies, and urban parks in 25 cities of the Yangtze River Delta (YRD) region in China to quantify their cooling effect. Correlation and regression analyses were employed to identify the dominant factors influencing the cooling performance. The results indicated that (1) compared to other landscape patches, water areas, and parks exhibited a reduction in daily average air temperature by 3.04 and 0.57 °C, respectively. Urban parks provided the largest cooling area (CA) of 56.44 ha in the YRD region, while water bodies demonstrated the highest cooling effect (CE) of 6.88, cooling intensity (CI) of 0.02, and cooling gradient (CG) of 0.99. (2) From the maximum perspective, the perimeter of the patches played a dominant role in CA and CE for all landscape patch types, contributing more than 40% in CA variation. (3) The dominant factors varied among different landscape types from accumulative perspectives. Green spaces were influenced by road density, shape index, and the proportion of water bodies within the CA, whereas water bodies were primarily affected by the coverage of blue spaces. Vegetation growth and densely populated surroundings contributed the most to the cooling of parks. These findings enhanced the comprehension of the cooling effect in comparable urban contexts and provided valuable insights for sustainable urban management.

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The audiovisual experience of observing birds in cities provides numerous benefits to residents, but their diversity is endangered by urbanization. Although the magnitude of the surface urban heat island effect (hereafter SUHI) has grown in recent years, its impact on bird diversity has not been adequately investigated. Here, we calculate the SUHI in 336 Chinese cities and we document the implications of the SUHI for avian species richness and functional diversity during the 2001, 2011, and 2019 breeding and non-breeding seasons. We predict that the SUHI will result in greater species richness and functional diversity in urban areas during the non-breeding season, especially for cities located within colder regions of China where the SUHI is more likely to relax thermoregulatory costs and reduce the propensity of some species to migrate. We predict that the SUHI will result in decreased species richness and functional diversity during the breeding season due to increased physiological stress, especially for cities located within warmer regions of China. Our findings showed that the SUHI was associated with lower species richness and lower functional diversity of birds in urban areas compared to suburban areas during both the breeding and non-breeding seasons. These results suggest that the SUHI induced birds to avoid urban areas or to move to cooler suburban areas during both the breeding and non-breeding seasons. This effect persisted irrespective of a city's size or geographical location. Our findings suggest that the SUHI is degrading bird diversity in Chinese cities.

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This paper uses the tourism heat footprint (THF) and a structural vector autoregressive model to investigate how tourism has affected the urban heat island effect in Macao, a typical urban tourism destination. The dynamic relationships between the THF, heat island intensity (HII), and quarterly average temperature (QAT) are investigated. The impulse response function and variance decomposition analysis are used to assess if a long-term causal relationship exists between the three indicators. The results show the following. (1) The hotel industry in Macao is the source of energy consumption and heat release. (2) A Granger causality relationship exists between the THF and QAT but not between the THF and HII. (3) The interaction effect between the growth rate of the THF and QAT is manifested as shocks with the same frequency and regular periodic fluctuations. (4) The heat island effect of this tourism destination is reflected in an increase in local temperature due to the energy consumption and heat release by tourists. Based on the results, policy implications for a sustainable tourism city are provided.

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The global climate warming caused by urbanization has significantly affected the urban environment. Whilst land surface temperature (LST) is an important factor reflecting urban temperature, previous research on LST mostly focused on two-dimensional (2D) factors and rarely mentioned about the role of three-dimensional (3D) factors, particularly the LST variation characteristics of island cities. Therefore, this study examined the seasonal variation characteristics of urban LST by analyzing the impact of 2D and 3D urban morphology factors of different urban block types on LST in Xiamen Island. The main results are as follows. First, compact low layer (CL), a block type with a higher density of low-rise buildings, has a higher LST in any season. Under the same block density (BD), the higher the block average height (BH), the lower the LST. Second, among the 2D urban morphology factors, normalized difference vegetation index (NDVI) was the main factor for cities to reduce urban LST, especially in summer, while normalized difference built-up index (NDBI) was the opposite. Different from land cities, we found a positive correlation between modified normalized difference water body index (MNDWI) and LST in autumn and winter. Third, in the 3D urban morphology factors, sky view factor (SVF) was significantly positively correlated with LST, while building fluctuation (BF) was negatively correlated. The higher the SVF, the worse the radiation shielding effect between buildings. On the contrary, the higher the BF, the higher the building undulation, and the better the building radiation shielding. These findings should provide some quantitative insights for the future construction and planning of island cities, which can be used to improve the thermal environment of island cities and support the sustainable development of cities.

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Climate change and urbanisation are among the most pervasive and rapidly growing threats to biodiversity worldwide. However, their impacts are usually considered in isolation, and interactions are rarely examined. Predicting species' responses to the combined effects of climate change and urbanisation, therefore, represents a pressing challenge in global change biology. Birds are important model taxa for exploring the impacts of both climate change and urbanisation, and their behaviour and physiology have been well studied in urban and non-urban systems. This understanding should allow interactive effects of rising temperatures and urbanisation to be inferred, yet considerations of these interactions are almost entirely lacking from empirical research. Here, we synthesise our current understanding of the potential mechanisms that could affect how species respond to the combined effects of rising temperatures and urbanisation, with a focus on avian taxa. We discuss potential interactive effects to motivate future in-depth research on this critically important, yet overlooked, aspect of global change biology. Increased temperatures are a pronounced consequence of both urbanisation (through the urban heat island effect) and climate change. The biological impact of this warming in urban and non-urban systems will likely differ in magnitude and direction when interacting with other factors that typically vary between these habitats, such as resource availability (e.g. water, food and microsites) and pollution levels. Furthermore, the nature of such interactions may differ for cities situated in different climate types, for example, tropical, arid, temperate, continental and polar. Within this article, we highlight the potential for interactive effects of climate and urban drivers on the mechanistic responses of birds, identify knowledge gaps and propose promising future research avenues. A deeper understanding of the behavioural and physiological mechanisms mediating species' responses to urbanisation and rising temperatures will provide novel insights into ecology and evolution under global change and may help better predict future population responses.

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Ecosystem-based cooling helps residents cope with the urban heat-island problem. In order to improve the accuracy of traditional heat-island measurements based on comparisons between urban and rural areas, we use an "on-site" method developed with only urban data. The essence of this method is a regression analysis of the relationships among different types of green space and blue space, elevation, vegetation dynamics, and temperature. We then simulate the temperature pattern in a scenario where there is no built-up area (Scenario A), and then in another scenario where there are no ecological spaces (Scenario B). The gap between the actual temperature pattern and the simulated temperature pattern of Scenario A is considered the heat-island effect. Conversely, the gap between the actual temperature pattern and that of Scenario B is considered as the effect of ecosystem-based urban cooling. This method was tested using data from two megacities in China (each had a population of over 10 million people). For Beijing, the average heat-island effect was 4.87 °C and effect of the ecosystem cooling service was 9.07 °C. For Shenzhen, the respective values were 0.8 °C and 2.71 °C. The "on-site" (local small size sampling), "dynamic coefficient", and "no-positive-coefficient rule" are the three defining characteristics of this method. The application of this method to model ecosystem-based urban cooling can aid urban planning and management in improving the residential thermal environment.

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It is imperative to quantitatively analyze the long-term temporal and spatial characteristics of the urban heat island (UHI) effect on cities for applications, such as urban expansion and environmental protection. Owing to the high spatial resolution and availability of long time-series data, remote sensing images from Landsat satellites are widely used for land surface temperature (LST) retrieval. However, limited by the satellite revisit cycle and image quality, the use of multisource Landsat images in a long-term study of the UHI effect is inevitable. Nonetheless, owing to the differences among multisource sensors, such as Landsat-7 and Landsat-8, there may be apparent deviations in the LST results retrieved from different sensor data, which are obtained from the same area and under similar circumstances. Consequently, it is necessary to build a relationship between the LST results generated from multisource Landsat sensors for future research on the UHI effect. In this study, Shenzhen city was studied to explore the fitting relationship between the corresponding LST products from Landsat-7 and Landsat-8 images obtained from adjacent dates with similar climatic conditions. Furthermore, factors affecting the fitting models, such as land cover types, seasonal and inter-annual differences, were analyzed. The constructed fitting model had a strong relationship with land cover types but a relatively weak relationship with seasonal and inter-annual differences; this indicates that a pseudo Landsat-8-based LST product can be generated from a Landsat-7-based LST product using a model fitted by a Landsat-7/8 pair obtained from adjacent years (or different seasons). Finally, by considering the consistency between LST products from multisource Landsat images, the spatiotemporal variations in the UHI effect in Shenzhen can be accurately explored using long time-series data.

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The response of land surface phenology (LSP) to the urban heat island effect (UHI) is a useful biological indicator for understanding how vegetated ecosystems will be affected by future climate warming. However, vegetation cover in rural areas is often dominated by cultivated land, whose phenological timing is considerably influenced by agricultural managements (e.g., timing of sowing and harvesting), leading to biased conclusions derived from the urban-rural LSP differences. To demonstrate this problem, we investigated the crop influence on the phenological response to a warmer environment resulting from the UHI effect. We partitioned cities in the United States into cultivated and non-cultivated categories according to the proportion of crops in rural areas. We then built continuous buffer zones starting from the urban boundary to explore the urban-rural LSP differences considering the UHI effect on them. The results suggest crop inclusion is likely to lead to >14 days of urban-rural differences at both the start of the season (SOS) and the end of the season (EOS) between cultivated and non-cultivated cities. The temperature sensitivity (ST) of SOS is overestimated by approximately 2.7 days/°C, whereas the EOS is underestimated by 3.6 days/°C. Removing crop-dominated pixels (i.e., above 50 %) can minimize the influence of crop planting/harvesting on LSP and derive reliable results. We, therefore, suggest explicit consideration of crop impacts in future studies of phenological differences between urban and rural areas and the UHI effect on LSP in urban domains, as presented by this comprehensive study.

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Urban thermal environments are closely related to habitats, citizens' health, and sustainable development. Based on green view index (GVI), we proposed two new visual indices, construction view index (CVI) and imperious surface view index (R&PVI). Mobile observation was used to obtain urban thermal environment data, images and coordinates synchronously in Xuzhou City in late summer, including urban area (U), scenic area (S), exterior of university campus (E), and university campus inside (CUMT). We analyzed the impacts of the urban composition represented by the visual index on the urban thermal environment. The results showed that, along the sampling line, mean air temperature (Ta) was highest (30.42 ℃) and mean relative humidity (RH) was lowest (40.7%) in urban area, while mean Ta was lowest (29.35 ℃) and mean RH was highest (48.4%) in scenic area. The situation of mean wind-chill temperature (TaW) was the highest (32.95 ℃) in the urban area and the lowest (31.93 ℃) in the scenic area. As for CVI, urban area, university campus inside, exterior of university campus and scenic area ranked in descending order, while GVI showed an opposite pattern. CVI was significantly positively correlated to Ta and TaW, but negatively to RH. GVI was significantly negatively correlated to Ta and TaW, but positively to RH. R&PVI was significantly positively correlated to Ta and TaW, but not correlated to RH. CVI and GVI influenced Ta significantly, with the independent effects being 10.4% and 18.9%, and joint effects being 7.8% and 11.3%, respectively. As for RH, CVI and GVI contributed significantly as well, independent effects were 37.5% and 15.7%, and joint effects were 51.4% and 30.2%, respectively. As for TaW, the three visual indices contributed significantly, but independent and joint effects were lower than those on Ta. Moreover, visual indices contributed more on RH than Ta or TaW. The results could provide ideas for optimizing urban thermal environments and mitigating urban heat island effects, and have practical implications for urban renewal and improvement of the quality of human living environment.

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Land surface temperature (LST) is a joint product of physical geography and socio-economics. It is important to clarify the spatial heterogeneity and binding factors of the LST for mitigating the surface heat island effect (SUHI). In this study, the spatial pattern of UHI in Fuzhou central area, China, was elucidated by Moran's I and hot-spot analysis. In addition, the study divided the drivers into two categories, including physical geographic factors (soil wetness, soil brightness, normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI), water density, and vegetation density) and socio-economic factors (normalized difference built-up index (NDBI), population density, road density, nighttime light, park density). The influence analysis of single factor on LST and the factor interaction analysis were conducted via Geodetector software. The results indicated that the LST presented a gradient layer structure with high temperature in the southeast and low temperature in the northwest, which had a significant spatial association with industry zones. Especially, LST was spatially repulsive to urban green space and water body. Furthermore, the four factors with the greatest influence (q-Value) on LST were soil moisture (influence = 0.792) > NDBI (influence = 0.732) > MNDWI (influence = 0.618) > NDVI (influence = 0.604). The superposition explanation degree (influence (Xi ∩ Xj)) is stronger than the independent explanation degree (influence (Xi)). The highest and the lowest interaction existed in "soil wetness ∩ MNDWI" (influence = 0.864) and "nighttime light ∩ population density" (influence = 0.273), respectively. The spatial distribution of SUHI and its driving mechanism were also demonstrated, providing theoretical guidance for urban planners to build thermal environment friendly cities.

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Urbanization is gaining force globally, which challenges biodiversity, and it has recently also emerged as an agent of evolutionary change. Seasonal phenology and life cycle regulation are essential processes that urbanization is likely to alter through both the urban heat island effect (UHI) and artificial light at night (ALAN). However, how UHI and ALAN affect the evolution of seasonal adaptations has received little attention. Here, we test for the urban evolution of seasonal life-history plasticity, specifically changes in the photoperiodic induction of diapause in two lepidopterans, Pieris napi (Pieridae) and Chiasmia clathrata (Geometridae). We used long-term data from standardized monitoring and citizen science observation schemes to compare yearly phenological flight curves in six cities in Finland and Sweden to those of adjacent rural populations. This analysis showed for both species that flight seasons are longer and end later in most cities, suggesting a difference in the timing of diapause induction. Then, we used common garden experiments to test whether the evolution of the photoperiodic reaction norm for diapause could explain these phenological changes for a subset of these cities. These experiments demonstrated a genetic shift for both species in urban areas toward a lower daylength threshold for direct development, consistent with predictions based on the UHI but not ALAN. The correspondence of this genetic change to the results of our larger-scale observational analysis of in situ flight phenology indicates that it may be widespread. These findings suggest that seasonal life cycle regulation evolves in urban ectotherms and may contribute to ecoevolutionary dynamics in cities.

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The surface urban heat island effect (SUHI) that occurs during rapid urbanization increases the health risks associated with high temperatures. Urban ecological land (UEL) has been shown to play an important role in improving urban heat stress, however, the impact of UEL interactions with the natural-anthropogenic environment on SUHI at the urban agglomeration-scale is less explored. In this study, the Google Earth Engine and GeoDetector were applied to characterize the spatiotemporal patterns of UEL and SUHI in the Guangdong-Hong Kong-Macao Greater Bay Area from 2000 to 2020 by extracting major built-up urban areas and quantifying the impacts of UEL and its interactions with the natural-anthropogenic factors on SUHI. The results show that the evolution of the UEL landscape structure exhibits clear spatiotemporal coupling with SUHI. Specifically, the UEL underwent a dispersion and degradation process in 2000-2015 and a convergence and restoration process in 2015-2020, the SUHI correspondingly transitioned from intensification and continuity to mitigation and contraction. The UEL landscape structure showed a notable impact on the SUHI reduction, and the dominance and richness of the patches explained an average of 19.95% and 16.03% of the SUHI, respectively. Moreover, the interaction between UEL and land urbanization rate and anthropogenic heat release had a dominant effect on SUHI, but this effect significantly declined from 2015 to 2020. With the implementation of ecological restoration projects, the interaction of UEL with topography rapidly increased and the SUHI gradually dominated by the joint interaction of UEL and natural-anthropogenic factors. A synthesis of the varying effects of several factors showed that the dynamic relationship between the development stages of the urban agglomeration's regional system and SUHI may conform to the Environmental Kuznets Curve. SUHI reduction strategies should therefore comprehensively optimize the rational allocation of UEL landscape structures and natural-human elements to promote the well-being of residents.

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We implemented a context-sensitive and prospective framework to assess the global warming potential (GWP) impacts of cool pavement strategies on specific roads for different cities. The approach incorporates several interconnections among different elements of the built environment, such as buildings and urban road segments, as well as the transportation fleet, using specific building and pavement information from an urban area. We show that increasing pavement albedo lowers urban air temperatures but can adversely affect the building energy demand in the areas with high incident radiation exposure. The heating energy savings and the radiative forcing effect improve the GWP savings in cold and humid climate conditions. The total GWP savings intensity is sensitive to the city morphology and road traffic. The probabilistic results show that cool pavement strategies can offset 1.0-3.0% and 0.7-6.0% of the total GHG emissions of the U.S. cities Boston and Phoenix, respectively, for a 50-year analysis period. The worldwide range of savings can be as large as 5.0-44.7 Gt of CO2 eq. A paradigm shift in pavement strategy selection is required in most neighborhoods.

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The main contributing factor of the urban heat island (UHI) effect is caused by daytime heating. Traditional pavements in cities aggravate the UHI effect due to their heat storage and volumetric heat capacity. In order to alleviate UHI, this study aims to understand the heating and dissipating process of different types of permeable road pavements. The Ke Da Road in Pingtung County of Taiwan has a permeable pavement materials experiment zone with two different section configurations which were named as section I and section II for semi-permeable pavement and fully permeable pavement, respectively. The temperature sensors were installed during construction at the depths of the surface course (0 cm and 5 cm), base course (30 cm and 55 cm) and subgrade (70 cm) to monitor the temperature variations in the permeable road pavements. Hourly temperature and weather station data in January and June 2017 were collected for analysis. Based on these collected data, heat storage and dissipation efficiencies with respect to depth have been modelled by using multi regression for the two studied pavement types. It is found that the fully permeable pavement has higher heat storage and heat dissipation efficiencies than semi-permeable pavement in winter and summer monitoring period. By observing the regressed model, it is found that the slope of the model lines are almost flat after the depth of 30 cm. Thus, from the view point of UHI, one can conclude that the reasonable design depth of permeable road pavement could be 30 cm.

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Urbanization is a major anthropogenic driver of decline for ecologically and economically important taxa including bees. Despite their generally negative impact on pollinators, cities can display a surprising degree of biodiversity compared to other landscapes. The pollinating communities found within these environments, however, tend to be filtered by interacting local and landscape features that comprise the urban matrix. Landscape and local features exert variable influence on pollinators within and across taxa, which ultimately affects community composition in such a way that contributes to functional trait homogenization and reduced phylogenetic diversity. Although previous results are not easily generalizable, bees and pollinators displaying functional trait characteristics such as polylectic diet, cavity-nesting behavior, and later emergence appear most abundant across different examined cities. To preserve particularly vulnerable species, most notably specialists that have become underrepresented within city communities, green spaces like parks and urban gardens have been examined as potential refuges. Such spaces are scattered across the urban matrix and vary in pollinator resource availability. Therefore, ensuring such spaces are optimized for pollinators is imperative. This review examines how urban features affect pollinators in addition to ways these green spaces can be manipulated to promote greater pollinator abundance and diversity.

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Climate change driven increases in the frequency of extreme heat events (EHE) and extreme precipitation events (EPE) are contributing to both infectious and non-infectious disease burden, particularly in urban city centers. While the share of urban populations continues to grow, a comprehensive assessment of populations impacted by these threats is lacking. Using data from weather stations, climate models, and urban population growth during 1980-2017, here, we show that the concurrent rise in the frequency of EHE, EPE, and urban populations has resulted in over 500% increases in individuals exposed to EHE and EPE in the 150 most populated cities of the world. Since most of the population increases over the next several decades are projected to take place in city centers within low- and middle-income countries, skillful early warnings and community specific response strategies are urgently needed to minimize public health impacts and associated costs to the global economy.

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This paper assesses the influence of land development patterns on intra-urban thermal variation in a densely-developed subtropical city, considering joint effect from greenspace pattern and built-up geometry. Despite growing research on urban climates, research at a scale that can support urban planning with scientificallyinformed strategies is still not as well documented for warm climate cities as for temperate cities. In response, this paper uses land surface temperature and geoinformation to assess the subtropical city of Taipei, Taiwan. Results show cooler environments are not only associated with natural surfaces, but also their interrelation with different spatial arrangement of buildings. An open layout tends to have lower temperature at low- to mid-rise buildings, whereas a compact layout is the coolest form for high-rise buildings. Cooling benefit from open layouts is, however, related to an increase in greenery. Clustering distribution of greenspaces produces more notable cooling. Accordingly, this paper proposes four heat mitigation strategies for Taipei: 1) increasing the amount of water bodies and vegetation, with greater coverage and coherence; 2) taking building height and shadow into account during regeneration/development; 3) increasing spacing and greenery between low- to midrise buildings; and 4) avoiding construction of compact low-rise buildings with corrugated iron steel.

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Numerous studies have demonstrated the relationship between summer temperatures and increased heat-related deaths. Epidemiological analyses of the health effects of climate exposures usually rely on observations from the nearest weather station to assess exposure-response associations for geographically diverse populations. Urban climate models provide high-resolution spatial data that may potentially improve exposure estimates, but to date, they have not been extensively applied in epidemiological research. We investigated temperature-mortality relationships in the city of Barcelona, and whether estimates vary among districts. We considered georeferenced individual (natural) mortality data during the summer months (June-September) for the period 1992-2015. We extracted daily summer mean temperatures from a 100-m resolution simulation of the urban climate model (UrbClim). Summer hot days (above percentile 70) and reference (below percentile 30) temperatures were compared by using a conditional logistic regression model in a case crossover study design applied to all districts of Barcelona. Relative Risks (RR), and 95% Confidence Intervals (CI), of all-cause (natural) mortality and summer temperature were calculated for several population subgroups (age, sex and education level by districts). Hot days were associated with an increased risk of death (RR = 1.13; 95% CI = 1.10-1.16) and were significant in all population subgroups compared to the non-hot days. The risk ratio was higher among women (RR = 1.16; 95% CI= 1.12-1.21) and the elderly (RR = 1.18; 95% CI = 1.13-1.22). Individuals with primary education had similar risk (RR = 1.13; 95% CI = 1.08-1.18) than those without education (RR = 1.10; 95% CI= 1.05-1.15). Moreover, 6 out of 10 districts showed statistically significant associations, varying the risk ratio between 1.12 (95% CI = 1.03-1.21) in Sants-Montjuïc and 1.25 (95% CI = 1.14-1.38) in Sant Andreu. Findings identified vulnerable districts and suggested new insights to public health policy makers on how to develop district-specific strategies to reduce risks.

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