Cities are complex systems and its many components strongly interrelated. Still, urban scaling studies have observed regularities in urban output across multiple national urban systems. Urban scaling studies examine how urban characteristics change systematically with population size. Previous research has shown that socio-economic outputs, such as GDP and patents, typically scale superlinearly, meaning that they increase more than proportionally with population size. In contrast, infrastructural quantities, such as road length, tend to scale sublinearly. Beyond average trends, scaling residuals identify cities that over- or underperform relative to their size, offering insights into additional drivers of urban outcomes and a tool for monitoring policy impacts. While urban scaling research has largely focused on socio-economic and infrastructural features, studies have shown that health indicators such as obesity, smoking, diabetes and influenza also exhibit scaling relationships with city size. Moreover, recent work has found non-linear scaling relationships for well-being indicators in Dutch cities. However, urban well-being scaling has not yet been examined systematically across different national contexts. It therefore remains unknown whether the observed relationships between city size and well-being are the same across different national contexts. Furthermore, the potential of scaling residuals analysis for well-being policy remains to be explored. This study uses a unique dataset provided by Gallup to study urban scaling for well-being for 18 countries, with varying geographical contexts and economic development stages. The dataset covers a range of topics related to well-being. The same questions and methodology are used for all countries, enabling country comparisons. We show that some well-being indicators exhibit scaling relationships and that scaling relationships depend on the country context. In addition, we explore whether out- or underperforming cities share common urban environmental characteristics.With current rapid urbanisation it is important to increase our understanding of urban – well-being interactions. Urban scaling studies of well-being can increase our understanding of well-being patterns and outliers in a system of cities.

Disease cluster studies are at times a controversial, but nevertheless critical, part of quantitative spatial epidemiology. They investigate unusual occurrences of cases, either spatially or spatial‐temporally. Often arising from media alerts, investigations are frequently complicated by incomplete case data, methodological shortcomings, and complex statistical analyses. A large number of disease cluster packages or tools are now available to support analyses. Both infectious and noninfectious diseases can be examined, with the aim to provide clues as to the causation or source of the outbreak. Cluster studies are often seen as a form of pre‐epidemiology, generating hypotheses worthy of follow‐up.

BACKGROUND:Few population-based multilevel analyses examining individual- and neighborhood-level risk factors for schizophrenia have been conducted. METHODS:A study cohort of all persons born in Denmark from 1990 to 1999 was followed for diagnosis with schizophrenia. Follow-up was initiated at 10th birthday and terminated at death, emigration, incident diagnosis, or 31st December 2018, whichever came first. A Danish Composite Deprivation Index was derived using 10-year weighted average neighborhood-level indicators in 1990-1999 categorized into five domains: Income; Employment; Education, Skills & Training; Health & Disability; and Crime. By fitting multilevel log-linear Poisson regression models, neighborhood-level deprivation indicators were examined with and without adjustment for individual-level covariates. RESULTS:Four neighborhood-level deprivation domains, Employment, Education, Skills & Training, Health & Disability, and Crime, as well as the Danish Composite Deprivation Index (adjusted IRR 1.14; 95 % credibility interval 1.10-1.17), were associated with elevated risk independent of individual-level deprivation measures. The specific neighborhood-level indicators linked with the highest adjusted elevations in risk were: Proportion of inhabitants aged 18-22 years who did not complete primary school before age 18 (adjusted IRR 1.23; 1.20-1.27); Proportion of inhabitants convicted for any violent crime (adjusted IRR 1.19; 1.16-1.23); and Proportion of inhabitants convicted for any crime resulting in a custodial sentence (adjusted IRR 1.15; 1.12-1.18). CONCLUSION:This novel population-based multilevel analysis has evidenced the independent associations of neighborhood-level deprivation indicators on schizophrenia risk elevation. Replication is needed in other populations to inform the refinement of preventive strategies.

BACKGROUND:The spread of coronavirus disease 2019 (COVID-19) varied among countries. The spatiotemporal trends of COVID-19 in Japan remain understudied. Therefore, this study aimed to conduct a detailed investigation of the spatiotemporal evolution of infections/deaths across prefectures in Japan, to analyze the changing patterns of COVID-19 circulation in metropolitan and nonmetropolitan areas. METHODS:We extracted data from nationally represented open-source data from January 15, 2020, to May 9, 2023, and we calculated the incidence rate of infection and the mortality. Further the ratios were obtained by dividing those rates in prefectural level by those in national level to make them comparable across country. Then, the spatiotemporal trends of COVID-19 were depicted via heatmaps. A Poisson regression model was used to compare the incidence rate ratios (IRRs) of infection and death between nonmetropolitan and metropolitan prefectures. RESULTS:During the study period, Japan experienced eight waves of COVID-19 resulting in 33,738,398 confirmed infections and 74,688 deaths. Both infections and deaths increased significantly overtime. Transmission was initially concentrated in metropolitan prefectures. Nonmetropolitan prefectures were protected and had lower numbers of infections and deaths through June 2022. Thereafter, COVID-19 became more widespread, with more localized surges in nonmetropolitan prefectures. Eventually, during the eighth wave (October 16, 2022-May 9, 2023), there was a marked increase in the IRR in nonmetropolitan prefectures reaching 1.25 (95 % confidence interval (CI), 1.15-1.34) for infection and 1.38 (95 % CI, 1.16-1.65) for death. CONCLUSIONS:In Japan, COVID-19 transmission was suppressed for the first 2 years of the pandemic, especially in nonmetropolitan prefectures, but the trends changed over time, and more infections and deaths were observed from late 2022 in nonmetropolitan prefectures. These findings underscore the importance of addressing the geographical disparities that likely exist between metropolitan and nonmetropolitan prefectures Delaying large surges in nonmetropolitan prefectures may be an important takeaway that could aid in the future management of major infectious disease outbreaks.

Chinese people are experiencing phthalate exposure risks. However, temporal and regional phthalate internal exposure variations amongst Chinese have not been established. To address this gap, we integrated our 69 adult participants' bio-monitored urinary phthalate metabolite (UPM) concentration data by high-performance liquid chromatography with mass spectrometry in Xi'an and Nanjing and the data from 35 literature (total sample size: 18768). Then, we analyzed China's temporal and spatial variations of adult UPM levels from 2005 to 2020 based on multi statistical methods. The results showed that the sum of eight UPM concentrations (i.e., monomethyl phthalate (MMP), mono-ethyl phthalate (MEP), mono-n-butyl phthalate (MNBP), mono-2-isobutyl phthalate, mono-benzyl phthalate, and three metabolites from di-2-ethylhexyl phthalate (DEHPM3)) had slightly increased in 2013-2020 (median: 230 (5th-95th: 73.7-653) ng/mL) compared with the period 2005-2012, which were about two times higher than the levels in most EU countries. The MNBP concentration between 2013 and 2020 (120 ng/mL, shared 52% of the eight UPM concentrations) has significantly increased to over two times the level between 2005 and 2012, followed by the DEHPM3 with a similar trend. Conversely, MEP and MMP concentrations in the later period decreased from the former period. In China, adults had the highest UPM concentrations in the East and the lowest in the Middle. The adults in the East, the North, the South, and the Northeast had higher adverse phthalate exposure risks than the adults in the West and the Middle, and the Hazard index (HI) values were the highest in the East (1.61 (5th-95th: 1.01-3.07)). The adult exposure risks in the West had large heterogeneities (HIs: 0.46 (0.11-2.37). Regional variations in climate, the economy, industrial technology, and living styles could cause phthalate exposure differences. China needs to enhance tight regulation and enforcement of di-n-butyl phthalate (DNBP) (the parent of MNBP) and DEHP to protect public health.

Studies have shown that migrants and ethnic minority groups were disproportionately affected by the COVID-19 pandemic, yet the role of the social environment in shaping their vulnerabilities remains underexplored in Japan. This study explored the experiences of migrants in Japan during the COVID-19 pandemic and examined the association between social environmental factors (i.e., population density, neighborhood deprivation, ethnic density, and social networks) and both COVID-19 infections and vaccination uptake. Two nationwide online surveys were conducted in 2021 and 2023 to capture migrants' experiences and analyze these associations during the middle and waning stages of the pandemic. Modified Poisson regressions with robust standard errors were applied for the analysis. The findings revealed the complex and evolving influence of social environmental factors on infections and vaccination uptake as the pandemic progressed. Larger neighborhood ties with co-nationals were associated with a higher risk of infection in 2021, while neighborhood population density, neighborhood deprivation, and ethnic density showed no significant association with infection in both surveys. Regarding COVID-19 vaccination, more social contacts with Japanese natives were negatively associated with vaccine hesitancy in 2021 and incomplete vaccination in 2023. Additionally, neighborhood deprivation was positively associated with vaccine hesitancy and incomplete vaccination in 2021 before adjusting for other variables. In anticipation of future pandemics, customized programs should be developed to address the unique healthcare needs of migrants and tailored to different stages of the pandemic.

Sedimentary records of polycyclic aromatic hydrocarbons (PAHs) and phthalates could reflect energy consumption and industrial production adjustment. However, there is limited knowledge about their effects on variations of PAH and phthalate compositions in the sediment core. The PAH and phthalate sedimentary records in Huguangyan Maar Lake in Guangdong, China were constructed, and random forest models were adopted to quantify the associated impact factors. Sums of sixteen PAH (& sum;16 PAH) and seven phthalate (& sum;7 PAE) concentrations in the sediment ranged from 28.8 to 1110 and 246 -4290 mu g/kg dry weight in 1900 -2020. Pro- portions of 5 -6 ring PAHs to the & sum; 16 PAHs increased from 32.0 % -40.7 % in 1900 -2020 with increased coal and petroleum consumption, especially after 1980. However, those of 2 -3 ring PAHs decreased from 30.7 % to 23.6 % due to the biomass substitution with natural gas. The proportions of bis (2-ethylhexyl) phthalate to the & sum; 7 PAEs decreased from 52.3 % -29.1 % in 1900 -2020, while those of di-isobutyl phthalate increased (13.7 % to 42.3 %). The shift from traditional plasticizers to non -phthalates drove this transformation, though the primary plastic production is increasing. Our findings underscore the effectiveness of optimizing energy structures and updating chemical products in reducing organic pollution in aquatic environments.

Microplastic records from lake cores can reconstruct the plastic pollution history. However, the associations between anthropogenic activities and microplastic accumulation are not well understood. Huguangyan Maar Lake (HML) is a deep-enclosed lake without inlets and outlets, where the sedimentary environment is ideal for preserving a stable and historical microplastic record. Microplastic (size: 10-500 mu m) characteristics in the HML core were identified using the Laser Direct Infrared Imaging system. The earliest detectable microplastics appeared unit in 1955 (1.1 items g(-1)). The microplastic abundance ranged from n.d. to 615.2 items g(-1) in 1955-2019 with an average of 134.9 items g(-1). The abundance declined slightly during the 1970s and then increased rapidly after China's Reform and Opening Up in 1978. Sixteen polymer types were detectable, with polyethylene and polypropylene dominating, accounting for 23.5 and 23.3% of the total abundance, and the size at 10-100 mu m accounted for 80%. Socioeconomic factors dominated the microplastic accumulation based on the random forest modeling, and the contributions of GDP per capita, plastic-related industry yield, and total crop yield were, respectively, 13.9, 35.1, and 9.3% between 1955-2019. The total crop yield contribution further increased by 1.7% after 1978. Coarse sediment particles increased with soil erosion exacerbated microplastics discharging into the sediment.

Dementia is a major global public health concern that is increasingly leading to morbidity and mortality among older adults. While studies have focused on the risk factors and care provision, there is currently limited knowledge about the spatial risk pattern of the disease. In this study, we employ Bayesian spatial modelling with a stochastic partial differential equation (SPDE) approach to model the spatial risk using complete residential history data from the Danish population and health registers. The study cohort consisted of 1.6 million people aged 65 years and above from 2005 to 2018. The results of the spatial risk map indicate high-risk areas in Copenhagen, southern Jutland and Funen. Individual socioeconomic factors and population density reduce the intensity of high-risk patterns across Denmark. The findings of this study call for the critical examination of the contribution of place of residence in the susceptibility of the global ageing population to dementia.

Background The emerging use of biomarkers in research and tailored care introduces a need for information about the association between biomarkers and basic demographics and lifestyle factors revealing expectable concentrations in healthy individuals while considering general demographic differences. Methods A selection of 47 biomarkers, including markers of inflammation and vascular stress, were measured in plasma samples from 9876 Danish Blood Donor Study participants. Using regression models, we examined the association between biomarkers and sex, age, Body Mass Index (BMI), and smoking. Results Here we show that concentrations of inflammation and vascular stress biomarkers generally increase with higher age, BMI, and smoking. Sex-specific effects are observed for multiple biomarkers. Conclusion This study provides comprehensive information on concentrations of 47 plasma biomarkers in healthy individuals. The study emphasizes that knowledge about biomarker concentrations in healthy individuals is critical for improved understanding of disease pathology and for tailored care and decision support tools.

Importance Complex biological, socioeconomic, and psychological variables combine to cause mental illnesses, with mounting evidence that early-life experiences are associated with adulthood mental health. Objective To evaluate whether changing neighborhood income deprivation and residential moves during childhood are associated with the risk of receiving a diagnosis of depression in adulthood. Design, Setting, and Participants This cohort study included the whole population of 1 096 916 people born in Denmark from January 1, 1982, to December 31, 2003, who resided in the country during their first 15 years of life. Individuals were followed up from 15 years of age until either death, emigration, depression diagnosis, or December 31, 2018. Longitudinal data on residential location was obtained by linking all individuals to the Danish longitudinal population register. Statistical analysis was performed from June 2022 to January 2024. Exposures Exposures included a neighborhood income deprivation index at place of residence for each year from birth to 15 years of age and a mean income deprivation index for the entire childhood (aged ≤15 years). Residential moves were considered by defining “stayers” as individuals who lived in the same data zone during their entire childhood and “movers” as those who did not. Main Outcomes and Measures Multilevel survival analysis determined associations between neighborhood-level income deprivation and depression incidence rates after adjustment for individual factors. Results were reported as incidence rate ratios (IRRs) with 95% credible intervals (95% CrIs). The hypotheses were formulated before data collection. Results A total of 1 096 916 individuals (563 864 male participants [51.4%]) were followed up from 15 years of age. During follow-up, 35 098 individuals (23 728 female participants [67.6%]) received a diagnosis of depression. People living in deprived areas during childhood had an increased risk of depression (IRR, 1.10 [95% CrI, 1.08-1.12]). After full individual-level adjustment, the risk was attenuated (IRR, 1.02 [95% CrI, 1.01-1.04]), indicating an increase of 2% in depression incidence for each 1-SD increase in income deprivation. Moving during childhood, independent of neighborhood deprivation status, was associated with significantly higher rates of depression in adulthood compared with not moving (IRR, 1.61 [95% CrI, 1.52-1.70] for 2 or more moves after full adjustment). Conclusions and Relevance This study suggests that, rather than just high or changing neighborhood income deprivation trajectories in childhood being associated with adulthood depression, a settled home environment in childhood may have a protective association against depression. Policies that enable and support settled childhoods should be promoted.

Mental health conditions pose a significant public health challenge, and low area-level socioeconomic status (SES) is a potentially important upstream determinant. Childhood exposure might have influences on later-life mental health. This study, utilises data from the Christchurch Health and Development Study birth cohort, examining the impact of area-level SES trajectories in childhood (from birth to age 16) on mental health at age 16 and from age 18-40 years. Findings revealed some associations between distinct SES trajectories and mental health. The study underscores the importance of using a spatial lifecourse epidemiology framework to understand long-term environmental impacts on later-life health.

Landscape sensation is essential for the delivery of cultural ecosystem services (CESs), yet the pathways through which these services are delivered remain inadequately understood. Exploring how people obtain CESs from landscapes facilitates better understanding of the tradeoffs and synergies between ecosystem services and landscape sustainability. This study aimed to elucidate the sensory pathways that links landscape attributes to CESs, focusing on the roles of cognitive and affective experiences. We analyzed social media comments for the measurement scale of cognition. We employed partial least squares structural equation modeling to integrate sensation, cognition, affect, and satisfaction, using questionnaire data (n = 503). Cognitive comprehensions and affective responses play a crucial role in interpreting CESs while sensory experiences do not directly determine people’s satisfaction with CESs. The effective pathways are achieved through the sole mediator of cognition or by serial mediators of cognition and affect. Of the two mediators, cognition has a more profound mediating effect than affect. Both physical and biological components, such as landscape sensory attributes, as well as cognitive and affective responses, influence human-nature interactions. These components should be considered when promoting the sustainability of human-dominated landscapes.

AIMS:We provide an overview of nationwide environmental data available for Denmark and its linkage potentials to individual-level records with the aim of promoting research on the potential impact of the local surrounding environment on human health. BACKGROUND:Researchers in Denmark have unique opportunities for conducting large population-based studies treating the entire Danish population as one big, open and dynamic cohort based on nationally complete population and health registries. So far, most research in this area has utilised individual- and family-level information to study the clustering of disease in families, comorbidities, risk of, and prognosis after, disease onset, and social gradients in disease risk. Linking environmental data in time and space to individuals enables novel possibilities for studying the health effects of the social, built and physical environment. METHODS:We describe the possible linkage between individuals and their local surrounding environment to establish the exposome - that is, the total environmental exposure of an individual over their life course. CONCLUSIONS:The currently available nationwide longitudinal environmental data in Denmark constitutes a valuable and globally rare asset that can help explore the impact of the exposome on human health.

Living in urban areas is known to increase the risk of psychosocial disorders, including stress, depression, and anxiety. Existing studies suggest that experiential places, including places of interest or favourite places, can mitigate these negative effects on psychological and physical health often associated with urban living. This study aims to model the spatial patterns of the benefits derived from favourite locations in two cities in Denmark: an urban metropolitan area (the capital city) and a provincial commuter town. Additionally, it examines the influence of individual and household socioeconomic factors on the benefits derived from these favourite places. Employing an online Public Participatory Geographic Information System (PPGIS) approach, data on favourite locations, derived benefits, and socioeconomic characteristics of 1400 respondents were collected. Bayesian modelling with Stochastic Partial Differential Equations under the Integrated Nested Laplace Approximation framework (INLA-SPDE) was utilized to predict the spatial patterns of four types of benefits – restorative, physical activity, socializing, and cultural – associated with enjoying favourite places in the two municipalities. This geostatistical approach allows for the identification of specific locations within the cities with perceived benefits and areas lacking such benefits. The findings provide insights into potential inequalities in the spatial distribution of perceived benefits of favourite places in Copenhagen and Roskilde, thereby informing urban planning policies and programs aimed at addressing these disparities.

Objectives: The association between air pollution and risk of respiratory tract infection (RTI) in adults needs to be clarified in settings with low to moderate levels of air pollution. We investigated this in the Danish population between 2004 and 2016. Methods: We included 3 653 490 persons aged 18-64 years in a nested case-control study. Exposure was defined as the average daily concentration at the individual's residential address of CO, NOX, NO2, O3, SO2, NH3, PPM2.5, black carbon, organic carbon, mineral dust, sea salt, secondary inorganic aerosols, SO42-, NO3-, NH4 thorn , secondary organic aerosols, PM2.5, and PM10 during a 3-month exposure window. RTIs were defined by hospitalization for RTIs. Incidence rate ratios (IRRs) and 95% CIs were estimated comparing highest with lowest decile of exposure using conditional logistic regression models.Results: In total, 188 439 incident cases of RTI were identified. Exposure to most air pollutants was positively associated with risk of RTI. For example, NO2 showed an IRR of 1.52 (CI: 1.48-1.55), and PM2.5 showed an IRR of 1.45 (CI: 1.40-1.50). In contrast, exposure to sea salt, PM10, NH3, and O3 was negatively associated with a risk of RTIs.Discussion: In this nationwide study comprising adults, exposure to air pollution was associated with risk of RTIs and subgroups hereof. Sea salt, PM10, NH3, and O3 may be proxies for rural areas, as the levels of these species in Denmark are higher near the western coastlines and/or in rural areas with fewer combustion sources. Kathrine A. Kaspersen, Clin Microbiol Infect 2024;30:122 (c) 2023 The Authors. Published by Elsevier Ltd on behalf of European Society of Clinical Microbiology and Infectious Diseases. This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).

Background Childhood malnutrition is a major public health issue in Sub-Saharan Africa (SSA) and 61.4 million children under the age of five years in the region are stunted. Although insight from existing studies suggests plausible pathways between ambient air pollution exposure and stunting, there are limited studies on the effect of different ambient air pollutants on stunting among children. Objective Explore the effect of early-life environmental exposures on stunting among children under the age of five years. Methods In this study, we used pooled health and population data from 33 countries in SSA between 2006 and 2019 and environmental data from the Atmospheric Composition Analysis Group and NASA’s GIOVANNI platform. We estimated the association between early-life environmental exposures and stunting in three exposure periods – in-utero (during pregnancy), post-utero (after pregnancy to current age) and cumulative (from pregnancy to current age), using Bayesian hierarchical modelling. We also visualise the likelihood of stunting among children based on their region of residence using Bayesian hierarchical modelling. Results The findings show that 33.6% of sampled children were stunted. In-utero PM2.5 was associated with a higher likelihood of stunting (OR = 1.038, CrI = 1.002–1.075). Early-life exposures to nitrogen dioxide and sulphate were robustly associated with stunting among children. The findings also show spatial variation in a high and low likelihood of stunting based on a region of residence. Impact Statement This study explores the effect of early-life environmental exposures on child growth or stunting among sub-Saharan African children. The study focuses on three exposure windows – pregnancy, after birth and cumulative exposure during pregnancy and after birth. The study also employs spatial analysis to assess the spatial burden of stunted growth in relation to environmental exposures and socioeconomic factors. The findings suggest major air pollutants are associated with stunted growth among children in sub-Saharan Africa.

Background A socioeconomically disadvantaged childhood has been associated with elevated self-harm and violent criminality risks during adolescence and young adulthood. However, whether these risks are modified by a neighbourhood's socioeconomic profile is unclear. The aim of our study was to compare risks among disadvantaged young people residing in deprived areas versus risks among similarly disadvantaged individuals residing in affluent areas. Methods We did a national cohort study, using Danish interlinked national registers, from which we delineated a longitudinal cohort of people born in Denmark between Jan 1, 1981, and Dec 31, 2001, with two Danish-born parents, who were alive and residing in the country when they were aged 15 years, who were followed up for a hospital-treated self-harm episode or violent crime conviction. A neighbourhood affluence indicator was derived based on nationwide income quartiles, with parental income and educational attainment indicating the socioeconomic position of each cohort member's family. Bayesian multilevel survival analyses were done to examine the moderating influences of neighbourhood affluence on associations between family socioeconomic position and sex-specific risks for the two adverse outcomes. Findings 1 084 047 cohort members were followed up for 12 center dot 8 million person-years in aggregate. Individuals of a low socioeconomic position residing in deprived neighbourhoods had a higher incidence of both self-harm and violent criminality compared with equivalently disadvantaged peers residing in affluent areas. Women from a low-income background residing in affluent areas had, on average, 95 (highest density interval 76-118) fewer self-harm episodes and 25 (15-41) fewer violent crime convictions per 10 000 person-years compared with women of an equally low income residing in deprived areas, whereas men of a low income residing in affluent areas had 61 (39-81) fewer selfharm episodes and 88 (56-191) fewer violent crime convictions per 10 000 person-years than men of a low income residing in deprived areas. Interpretation Even in a high-income European country with comprehensive social welfare and low levels of poverty and inequality, individuals residing in affluent neighbourhoods have lower risks of self-harm and violent criminality compared with individuals residing in deprived neighbourhoods. More research is needed to explore the potential of neighbourhood policies and interventions to reduce the harmful effects of growing up in socioeconomically deprived circumstances on later risk of self-harm and violent crime convictions. Funding European Research Council, Lundbeck Foundation Initiative for Integrative Psychiatric Research, and BERTHA, the Danish Big Data Centre for Environment and Health funded by the Novo Nordisk Foundation Challenge Programme. Copyright (c) 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license.

Urban areas are associated with higher depression risks than rural areas. However, less is known about how different types of urban environments relate to depression risk. Here, we use satellite imagery and machine learning to quantify three-dimensional (3D) urban form (i.e., building density and height) over time. Combining satellite-derived urban form data and individual-level residential addresses, health, and socioeconomic registers, we conduct a case-control study (n = 75,650 cases and 756,500 controls) to examine the association between 3D urban form and depression in the Danish population. We find that living in dense inner-city areas did not carry the highest depression risks. Rather, after adjusting for socioeconomic factors, the highest risk was among sprawling suburbs, and the lowest was among multistory buildings with open space in the vicinity. The finding suggests that spatial land-use planning should prioritize securing access to open space in densely built areas to mitigate depression risks.

Overcrowding in densely populated urban areas is increasingly becoming an issue for mental health disorders. Yet, only few studies have examined the association between overcrowding in cities and physiological stress responses. Thus, this study employed wearable sensors (a wearable camera, an Empatica E4 wristband and a smartphone-based GPS) to assess the association between overcrowding and human physiological stress response in four types of urban contexts (green space, transit space, commercial space, and blue space). A case study with 26 participants was conducted in Salzburg, Austria. We used Mask R-CNN to detect elements related to overcrowding such as human crowds, sitting facilities, vehicles and bikes from first-person video data collected by wearable cameras, and calculated a change score (CS) to assess human physiological stress response based on galvanic skin response (GSR) and skin temperature from the physiological data collected by the wristband, then this study used statistical and spatial analysis to assess the association between the change score and the above elements. The results demonstrate the feasibility of using sensor-based measurement and quantitative analysis to investigate the relationship between human stress and overcrowding in relation to different urban elements. The findings of this study indicate the importance of considering human crowds, sitting facilities, vehicles and bikes to assess the impact of overcrowding on human stress at street level.