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Context: 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. Objectives: This study aimed to elucidate the sensory pathways that links landscape attributes to CESs, focusing on the roles of cognitive and affective experiences. Methods: 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). Results: 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. Conclusions: 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. [ABSTRACT FROM AUTHOR]

Key Points: Question: Are certain neighborhood deprivation trajectories and moving during childhood associated with depression in adulthood? Findings: This cohort study found that individuals who lived in neighborhoods during childhood that were more income deprived were more likely to develop depression in adulthood. The experience of moving during childhood, whether living in a deprived or nondeprived neighborhood, was associated with significantly higher rates of depression in adulthood compared with those who did not move. Meaning: This study suggests that rather than solely high neighborhood income deprivation in childhood being associated with onset of depression during adulthood, a settled home environment in childhood may have a protective association. 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. This cohort study comprising more than 1 million individuals evaluates whether changing neighborhood income deprivation and residential moves during childhood are associated with the risk of depression in adulthood. [ABSTRACT FROM AUTHOR]

Background: Suicide risk is complex and nuanced, and how place impacts suicide risk when considered alongside detailed individual risk factors remains uncertain. We aimed to examine suicide risk in Denmark with both individual and neighbourhood level risk factors. Methods: We used Danish register-based data to identify individuals born in Denmark from 1972, with full parental information and psychiatric diagnosis history. We fitted a two-level survival model to estimate individual and neighbourhood determinants on suicide risk. Results: We identified 1723 cases of suicide in Denmark during the follow-up period from 1982 to 2015. Suicide risk was explained mainly by individual determinants. Parental comorbidities, particularly maternal schizophrenia [incidence rate ratio (IRR): 2.29, 95% CI 1.56–3.16] and paternal death (2.29, 95% CI 1.31–3.72) partly explained suicide risk when adjusted for all other determinants. The general contextual effect of suicide risk across neighbourhoods showed a median incidence rate ratio (MRR) of 1.13 (1.01–1.28), which was further reduced with full adjustment. Suicide risk increased in neighbourhoods with a higher proportion of manual workers (IRR: 1.08; 1.03–1.14), and decreased with a higher population density (IRR: 0.89; 0.83–0.96). Conclusion: Suicide risk varies mainly between individuals, with parental comorbidities having the largest effect on suicide risk. Suicide risk was less impacted by neighbourhood, though, albeit to a lesser extent than individual determinants, some characteristics were associated with suicide risk. Suicide prevention policies might consider targeting interventions towards individuals more vulnerable due to particular parental comorbidities, whilst taking into account that some neighbourhood characteristics might exacerbate this risk further. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Being overweight and obesity are emerging public health issues in sub-Saharan Africa. Currently, there is limited knowledge on the temporal trend of the effect of socioeconomic factors and air quality on being overweight or obesity. Using data from the Ugandan Demographic and Health Survey and NASA's Socioeconomic Data and Applications Center (SEDAC), we examined the spatio-temporal effect of individual and contextual factors on overweight and obesity among women in Uganda using cross-sectional data on 15,655 women in Uganda. We employed multilevel mixed-effect analysis and Bayesian hierarchical spatial models to examine the effect of individual socioeconomic status, contextual socioeconomic factors and air quality on women's risk of being overweight or obese as well as investigate spatial heterogeneity in the association. The prevalence of overweight/obesity for the study periods were 17.23% (2000/2001), 15.36% (2006), 19.36% (2011) and 21.93% (2016). The result from the multilevel analysis shows change in the directions of the association between individual factors (educational status and household wealth) and overweight or obese over the years. Women with secondary education were 1.514 times (p = 0.002) more likely to be overweight or obese in the 2000/2001 group but 0.655 times (p = 0.007) less likely to be overweight or obese in the 2016 group. It also reveals temporal consistency in the effect of the air pollutant PM2.5 on overweight or obese. The spatial models reveal spatial heterogeneity in the association between district-level factors and the proportion of overweight or obese women. The findings suggest improving women's socioeconomic status and air quality could reduce the rising obesity epidemic in Ugandan women. [ABSTRACT FROM AUTHOR]

Background Urban-rural differences in schizophrenia risk have been widely evidenced across Western countries. However, explanation of these differences is lacking. We aimed to identify contextual risk factors for schizophrenia that explain urban-rural differences in schizophrenia risk. Methods Utilizing Danish population-based registers, we partitioned Denmark into 1885 geographic "neighborhoods" homogeneously sized in terms of population. Information on the entire Danish population from 1981 to 2016 was used to quantify a spectrum of neighborhood-level domains. We subsequently conducted multilevel survival analyses following persons born in Denmark from 1971 to 1982 for the development of schizophrenia allowing for clustering of people within neighborhoods. We used this method to tease apart the effects of individual, specific, and general contextual risk factors for schizophrenia. Results A significant general contextual effect in schizophrenia risk across neighborhoods was estimated (Medium Incidence Rate Ratio (MRR):1.41; 95% CI:1.35–1.48). Most of the specific contextual factors examined were associated with schizophrenia risk. For instance, neighborhood-level proportion of lone adult households (Incidence Rate Ratios (IRR):1.53; 95% CI:1.44–1.63) had largest risk estimate. Adjustment for all individual-level and specific contextual constructs reduced the IRR for urbanicity from 1.98 (95% CI:1.77–2.22) to 1.30 (95% CI:1.11–1.51). Conclusions In the largest prospective multilevel survival analyses of schizophrenia risk conducted to date, multiple neighborhood-level characteristics were associated with raised schizophrenia risk, with these contextual factors explaining most of the elevated risk linked with urbanicity. However, the unexplained heterogeneity that was evident in our multilevel models indicates that our understanding of the role of urbanicity in schizophrenia's etiology remains incomplete. [ABSTRACT FROM AUTHOR]

Globally, it is estimated that about 30% of ever-partnered women have experienced some form of intimate partner violence (IPV)—physical assault, sexual assault, or emotional abuse. The prevalence of IPV in sub-Saharan Africa is considerably higher than the global estimate. In Ghana, it is estimated that 24% of women have experienced physical and/or sexual IPV in their lifetime. Studies point to the association between alcohol misuse by intimate male partners and violence against women. However, there has been no consideration for potential spatial variation or heterogeneity in this association. Using estimates from the 2008 Ghana Demographic and Health Survey Data, we employed geographically weighted regression (GWR) analysis to examine spatial variations in the relationship between male partner's alcohol misuse and IPV among women in Ghana. We fitted three models to assess the relationship using a step-wise approach. The first model has alcohol misuse as the only predictor, whereas the second model included other male partner characteristics, such as post-secondary education and employment status. The final introduced female characteristics as additional covariates. The result of the GWR analysis shows that the effect of alcohol misuse on IPV is elevated in the south-western part of Ghana. The findings suggest the potential influence of place-based or contextual factors on the association between alcohol misuse and women's exposure to IPV. [ABSTRACT FROM AUTHOR]

The strongest epidemiological clue that the environment at the population level has a significant impact on the risk of developing multiple sclerosis is the well established, and in many instances, increasing latitudinal gradient of prevalence, incidence and mortality globally, with prevalence increasing by up to 10-fold between the equator and 60° north and south. The drivers of this gradient are thought to be environmental with latitude seen as a proxy for ultraviolet radiation and thus vitamin D production; however, other factors may also play a role. Several important questions remain unanswered, particularly when in the life course is the gradient established, does lifetime migration mitigate or exacerbate previously reported latitude gradients at location of diagnosis, and do factors such as sex or multiple sclerosis disease phenotype influence the timing or significance of the gradient? Utilizing lifetime residence calendars collected as part of the New Zealand National Multiple Sclerosis Prevalence Study, we constructed lifetime latitudinal gradients for multiple sclerosis from birth to prevalence day in 2006 taking into account migration internally and externally and then analysed by sex and multiple sclerosis clinical course phenotype. Of 2917 individuals living in New Zealand on prevalence day, 7 March 2006, with multiple sclerosis, 2127 completed the life course questionnaire and of these, 1587 were born in New Zealand. All cohorts and sub-cohorts were representative of the overall multiple sclerosis population in New Zealand on prevalence day. We found that the prevalence gradient was present at birth and was, in fact, stronger than at census day, and the slope of the gradient persisted until the age of 12 before gradually declining. We found that internal and external migration into New Zealand had little, if any, effect on the gradient except to decrease the significance of the gradient somewhat. Finally, we found as we had reported previously, that the lifetime prevalence gradients were largely driven by females with relapse onset multiple sclerosis. These findings confirm for the first time the importance of early life environmental exposures in the risk of multiple sclerosis indicating strongly that exposures as early as in utero and at birth drive the latitudinal gradient. Consequently, prevention studies should be focused on high-risk individuals and populations from the earliest possible time points especially, when appropriate, on females. [ABSTRACT FROM AUTHOR]

In this study, we examine the association between social frailty and depression among older adults in Ghana over time. We employed longitudinal data analysis to examine the association between social frailty, socioeconomic status and depression using data from the WHO-SAGE survey. Our descriptive and cross-tabulation analyses show that the prevalence of depression and social frailty among older adults decreased considerably in 2014/2015 compared to 2007/2008. The finding also reveals a huge reduction in social frailty among older adults in northern Ghana–the most deprived regions in Ghana–compared to those in southern Ghana. The multivariate panel data analysis reveals that depression was significantly associated with social isolation, financial needs, and physical needs. The findings suggest an over time decline in social frailty and depression among older adults, as well as, reduction in regional differences in social frailty and depression among older adults in Ghana. [ABSTRACT FROM AUTHOR]

Objectives: In our study, we examine how geographic region of residence may predict childhood malnutrition, expressed as stunting, wasting and underweight, among children under the age of 5 years in Uganda.Methods: Using data from the 2016 Uganda Demographic and Health Survey, we performed an incremental multivariate multilevel mixed-effect modelling to examine the effect of a child, parental and household factors on the association between region of residence and each indicator of childhood malnutrition.Results: Approximately 28%, 3% and 9% of children under age 5 suffered from stunting, wasting and underweight, respectively. The bivariate result shows that the proportion of children suffering from stunting and underweight was relatively lower in the Kampala region compared with the other regions. With the exception of the Northern region (6.44%), wasting was higher (4.12%) among children in the Kampala region. Children in the other regions were more likely to experience stunting and underweight. When controlling for child, parent and household factors, children in the other regions were less likely to suffer from underweight and stunting, compared with those in Kampala region. Children in the other regions, except the Northern region, were less likely to be wasted compared with those in Kampala region.Conclusion: Our finding suggests that child, parental and household characteristics have effects on the association between region of residence and childhood malnutrition. Addressing individual and household socioeconomic disparities may be vital in tackling regional differences in childhood malnutrition. [ABSTRACT FROM AUTHOR]

The International Initiative on Spatial Lifecourse Epidemiology (ISLE) convened its first International Symposium on Lifecourse Epidemiology and Spatial Science at the Lorentz Center in Leiden, Netherlands, 16-20 July 2018. Its aim was to further an emerging transdisciplinary field: Spatial Lifecourse Epidemiology. This field draws from a broad perspective of scientific disciplines including lifecourse epidemiology, environmental epidemiology, community health, spatial science, health geography, biostatistics, spatial statistics, environmental science, climate change, exposure science, health economics, evidence-based public health, and landscape ecology. The participants, spanning 30 institutions in 10 countries, sought to identify the key issues and research priorities in spatial lifecourse epidemiology. The results published here are a synthesis of the top 10 list that emerged out of the discussion by a panel of leading experts, reflecting a set of grand challenges for spatial lifecourse epidemiology in the coming years. [ABSTRACT FROM AUTHOR]

Investigating biologically plausible mechanisms for the embodiment of context is a key thoroughfare for progressing health geographies of place. Expanding knowledge of bio-processes such as epigenetics is providing a platform for appreciating the dynamic embedding of social relations in bodies over the lifecourse, and so to tracing the development of health inequalities. By providing a geographic lens on the biosocial, health geographers have key contributions to make regarding the theorisation of place. We put forward the exposome as a holistic framework in which to situate a biosocial health geography, placing ideas of dynamic exposure, plasticity and temporality as central. [ABSTRACT FROM AUTHOR]

The United Nations has called on all nations to take immediate actions to fight noncommunicable diseases (NCDs), which have become an increasingly significant burden to public health systems around the world. NCDs tend to be more common in developed countries but are also becoming of growing concern in low- and middle-income countries. Earth observation (EO) technologies have been used in many infectious disease studies but have been less commonly employed in NCD studies. This review discusses the roles that EO data and technologies can play in NCD research, including ( a) integrating natural and built environment factors into NCD research, ( b) explaining individual-environment interactions, ( c) scaling up local studies and interventions, ( d) providing repeated measurements for longitudinal studies including cohorts, and ( e) advancing methodologies in NCD research. Such extensions hold great potential for overcoming the challenges of inaccurate and infrequent measurements of environmental exposure at the level of both the individual and the population, which is of great importance to NCD research, practice, and policy. [ABSTRACT FROM AUTHOR]

Epidemic diffusion is a space-time process, and showing time-series disease maps is a common way to demonstrate an epidemic progression in time and space. Previous studies used time-series maps to demonstrate the animation of diffusion process. Epidemic diffusion patterns were determined subjectively by visual inspection, however. There currently are still methodological concerns in developing effective analytical approaches for profiling diffusion dynamics of disease clustering and epidemic propagation. The objective of this study is to develop a geocomputational algorithm, the modified space-time density-based spatial clustering of application with noise (MST-DBSCAN), for detecting, identifying, and visualizing disease cluster evolution, which takes the effect of the incubation period into account. We also map the MST-DBSCAN algorithm output to visualize the diffusion process. Dengue fever case data from 2014 were used as an illustrative case study. Our results show that compared to kernel-smoothed mapping, the MST-DBSCAN algorithm can better identify the evolution type of any cluster at any epoch. Furthermore, using only one two-dimensional map (and graphs), our approach can demonstrate the same diffusion process that time-series maps or three-dimensional space-time kernel plotting displays but in an easy-to-read manner. We conclude that our MST-DBSCAN algorithm can profile the spatial pattern of epidemic diffusion in detail by identifying disease cluster evolution. [ABSTRACT FROM AUTHOR]

Research into health disparities has long recognized the importance of residential mobility as a crucial factor in determining health outcomes. However, a lack of connectivity between the health and mobility literatures has led to a stagnation of theory and application on the health side, which lacks the detail and temporal perspectives now seen as critical to understanding residential mobility decisions. Through a critical re-think of mobility processes with respect to health outcomes and an exploitation of longitudinal analytical techniques, we argue that health geographers have the potential to better understand and identify the relationship that residential mobility has with health. [ABSTRACT FROM AUTHOR]

Background: There is a growing understanding of the role played by 'neighbourhood' in influencing health status. Various neighbourhood characteristics—such as socioeconomic environment, availability of amenities, and social cohesion, may be combined—and this could contribute to rising health inequalities. This study aims to combine a data-driven approach with clustering analysis techniques, to investigate neighbourhood characteristics that may explain the geographical distribution of the onset of myocardial infarction (MI) risk. Methods: All MI events in patients aged 35–74 years occurring in the Strasbourg metropolitan area (SMA), from January 1, 2000 to December 31, 2007 were obtained from the Bas-Rhin coronary heart disease register. All cases were geocoded to the census block for the residential address. Each areal unit, characterized by contextual neighbourhood profile, included socioeconomic environment, availability of amenities (including leisure centres, libraries and parks, and transport) and psychosocial environment as well as specific annual rates standardized (per 100,000 inhabitants). A spatial scan statistic implemented in SaTScan was then used to identify statistically significant spatial clusters of high and low risk of MI. Result: MI incidence was non-randomly spatially distributed, with a cluster of high risk of MI in the northern part of the SMA [relative risk (RR) = 1.70, p = 0.001] and a cluster of low risk of MI located in the first and second periphery of SMA (RR 0.04, p value = 0.001). Our findings suggest that the location of low MI risk is characterized by a high socioeconomic level and a low level of access to various amenities; conversely, the location of high MI risk is characterized by a high level of socioeconomic deprivation—despite the fact that inhabitants have good access to the local recreational and leisure infrastructure. Conclusion: Our data-driven approach highlights how the different contextual dimensions were inter-combined in the SMA. Our spatial approach allowed us to identify the neighbourhood characteristics of inhabitants living within a cluster of high versus low MI risk. Therefore, spatial data-driven analyses of routinely-collected data georeferenced by various sources may serve to guide policymakers in defining and promoting targeted actions at fine spatial level. [ABSTRACT FROM AUTHOR]

Implementation of greenhouse gas (GHG) abatement strategies often ends up as the responsibility of municipal action rather than national policies. Impacts of local GHG reduction measures were investigated in the EU FP7 funded project Urban Reduction of Greenhouse Gas Emissions in China and Europe (URGENCHE). Kuopio in Finland was one of the case study cities. The assessed reduction measures were (1) increased use of biomass in local heat and power cogeneration plant, (2) energy efficiency improvements of residences, (3) increased biofuel use in traffic, and (4) increased small scale combustion of wood for residential heating. Impact assessment compared the 2010 baseline with a 2020 BAU (business as usual) scenario and a 2020 CO2 interventions scenario. Changes in emissions were assessed for CO2, particulate matter (PM2.5 and PM10), NOx, and SO2, and respective impacts were assessed for PM2.5 ambient concentrations and health effects. The assessed measures would reduce the local CO2 emissions in the Kuopio urban area by over 50% and local emissions of PM2.5 would clearly decrease. However, the annual average ambient PM2.5 concentration would decrease by just 4%. Thus, only marginal population level health benefits would be achieved with these assumed local CO2 abatement actions. [ABSTRACT FROM AUTHOR]

This paper uses random-coefficient models and (a) finds rankings of who are the best formula 1 (F1) drivers of all time, conditional on team performance; (b) quantifies how much teams and drivers matter; and (c) quantifies how team and driver effects vary over time and under different racing conditions. The points scored by drivers in a race (standardised across seasons and Normalised) is used as the response variable in a cross-classified multilevel model that partitions variance into team, team-year and driver levels. These effects are then allowed to vary by year, track type and weather conditions using complex variance functions. Juan Manuel Fangio is found to be the greatest driver of all time. Team effects are shown to be more important than driver effects (and increasingly so over time), although their importance may be reduced in wet weather and on street tracks. A sensitivity analysis was undertaken with various forms of the dependent variable; this did not lead to substantively different conclusions. We argue that the approach can be applied more widely across the social sciences, to examine individual and team performance under changing conditions. [ABSTRACT FROM AUTHOR]

Background: Climate change is a global threat to health and wellbeing. Here we provide findings of an international research project investigating the health and wellbeing impacts of policies to reduce greenhouse gas emissions in urban environments.Methods: Five European and two Chinese city authorities and partner academic organisations formed the project consortium. The methodology involved modelling the impact of adopted urban climate-change mitigation transport, buildings and energy policy scenarios, usually for the year 2020 and comparing them with business as usual (BAU) scenarios (where policies had not been adopted). Carbon dioxide emissions, health impacting exposures (air pollution, noise and physical activity), health (cardiovascular, respiratory, cancer and leukaemia) and wellbeing (including noise related wellbeing, overall wellbeing, economic wellbeing and inequalities) were modelled. The scenarios were developed from corresponding known levels in 2010 and pre-existing exposure response functions. Additionally there were literature reviews, three longitudinal observational studies and two cross sectional surveys.Results: There are four key findings. Firstly introduction of electric cars may confer some small health benefits but it would be unwise for a city to invest in electric vehicles unless their power generation fuel mix generates fewer emissions than petrol and diesel. Second, adopting policies to reduce private car use may have benefits for carbon dioxide reduction and positive health impacts through reduced noise and increased physical activity. Third, the benefits of carbon dioxide reduction from increasing housing efficiency are likely to be minor and co-benefits for health and wellbeing are dependent on good air exchange. Fourthly, although heating dwellings by in-home biomass burning may reduce carbon dioxide emissions, consequences for health and wellbeing were negative with the technology in use in the cities studied.Conclusions: The climate-change reduction policies reduced CO2 emissions (the most common greenhouse gas) from cities but impact on global emissions of CO2 would be more limited due to some displacement of emissions. The health and wellbeing impacts varied and were often limited reflecting existing relatively high quality of life and environmental standards in most of the participating cities; the greatest potential for future health benefit occurs in less developed or developing countries. [ABSTRACT FROM AUTHOR]

Background: Public health is often affected by societal decisions that are not primarily about health. Climate change mitigation requires intensive actions to minimise greenhouse gas emissions in the future. Many of these actions take place in cities due to their traffic, buildings, and energy consumption. Active climate mitigation policies will also, aside of their long term global impacts, have short term local impacts, both positive and negative, on public health. Our main objective was to develop a generic open impact model to estimate health impacts of emissions due to heat and power consumption of buildings. In addition, the model should be usable for policy comparisons by non-health experts on city level with city-specific data, it should give guidance on the particular climate mitigation questions but at the same time increase understanding on the related health impacts and the model should follow the building stock in time, make comparisons between scenarios, propagate uncertainties, and scale to different levels of detail. We tested The functionalities of the model in two case cities, namely Kuopio and Basel. We estimated the health and climate impacts of two actual policies planned or implemented in the cities. The assessed policies were replacement of peat with wood chips in co-generation of district heat and power, and improved energy efficiency of buildings achieved by renovations.Results: Health impacts were not large in the two cities, but also clear differences in implementation and predictability between the two tested policies were seen. Renovation policies can improve the energy efficiency of buildings and reduce greenhouse gas emissions significantly, but this requires systematic policy sustained for decades. In contrast, fuel changes in large district heating facilities may have rapid and large impacts on emissions. However, the life cycle impacts of different fuels is somewhat an open question.Conclusions: In conclusion, we were able to develop a practical model for city-level assessments promoting evidence-based policy in general and health aspects in particular. Although all data and code is freely available, implementation of the current model version in a new city requires some modelling skills. [ABSTRACT FROM AUTHOR]

Background: Many studies suggest that exposure to natural environments ('greenspace') enhances human health and wellbeing. Benefits potentially arise via several mechanisms including stress reduction, opportunity and motivation for physical activity, and reduced air pollution exposure. However, the evidence is mixed and sometimes inconclusive. One explanation may be that "greenspace" is typically treated as a homogenous environment type. However, recent research has revealed that different types and qualities of natural environments may influence health and wellbeing to different extents. Methods: This ecological study explores this issue further using data on land cover type, bird species richness, water quality and protected or designated status to create small-area environmental indicators across Great Britain. Associations between these indicators and age/sex standardised prevalence of both good and bad health from the 2011 Census were assessed using linear regression models. Models were adjusted for indicators of socio-economic deprivation and rurality, and also investigated effect modification by these contextual characteristics. Results: Positive associations were observed between good health prevalence and the density of the greenspace types, "broadleaf woodland", "arable and horticulture", "improved grassland", "saltwater" and "coastal", after adjusting for potential confounders. Inverse associations with bad health prevalence were observed for the same greenspace types, with the exception of "saltwater". Land cover diversity and density of protected/designated areas were also associated with good and bad health in the predicted manner. Bird species richness (an indicator of local biodiversity) was only associated with good health prevalence. Surface water quality, an indicator of general local environmental condition, was associated with good and bad health prevalence contrary to the manner expected, with poorer water quality associated with better population health. Effect modification by income deprivation and urban/rural status was observed for several of the indicators. Conclusions: The findings indicate that the type, quality and context of 'greenspace' should be considered in the assessment of relationships between greenspace and human health and wellbeing. Opportunities exist to further integrate approaches from ecosystem services and public health perspectives to maximise opportunities to inform policies for health and environmental improvement and protection. [ABSTRACT FROM AUTHOR]

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Background: Many studies suggest that exposure to natural environments (‘greenspace’) enhances human health and wellbeing. Benefits potentially arise via several mechanisms including stress reduction, opportunity and motivation for physical activity, and reduced air pollution exposure. However, the evidence is mixed and sometimes inconclusive. One explanation may be that “greenspace” is typically treated as a homogenous environment type. However, recent research has revealed that different types and qualities of natural environments may influence health and wellbeing to different extents. Methods: This ecological study explores this issue further using data on land cover type, bird species richness, water quality and protected or designated status to create small-area environmental indicators across Great Britain. Associations between these indicators and age/sex standardised prevalence of both good and bad health from the 2011 Census were assessed using linear regression models. Models were adjusted for indicators of socio-economic deprivation and rurality, and also investigated effect modification by these contextual characteristics. Results: Positive associations were observed between good health prevalence and the density of the greenspace types, “broadleaf woodland”, “arable and horticulture”, “improved grassland”, “saltwater” and “coastal”, after adjusting for potential confounders. Inverse associations with bad health prevalence were observed for the same greenspace types, with the exception of “saltwater”. Land cover diversity and density of protected/designated areas were also associated with good and bad health in the predicted manner. Bird species richness (an indicator of local biodiversity) was only associated with good health prevalence. Surface water quality, an indicator of general local environmental condition, was associated with good and bad health prevalence contrary to the manner expected, with poorer water quality associated with better population health. Effect modification by income deprivation and urban/rural status was observed for several of the indicators. Conclusions: The findings indicate that the type, quality and context of ‘greenspace’ should be considered in the assessment of relationships between greenspace and human health and wellbeing. Opportunities exist to further integrate approaches from ecosystem services and public health perspectives to maximise opportunities to inform policies for health and environmental improvement and protection. [ABSTRACT FROM AUTHOR]

Drought conditions in Amazonia are associated with increased fire incidence, enhancing aerosol emissions with degradation in air quality. Quantifying the synergic influence of climate and human-driven environmental changes on human health is, therefore, critical for identifying climate change adaptation pathways for this vulnerable region. Here we show a significant increase (1.2%-267%) in hospitalisations for respiratory diseases in children under-five in municipalities highly exposed to drought. Aerosol was the primary driver of hospitalisations in drought affected municipalities during 2005, while human development conditions mitigated the impacts in 2010. Our results demonstrated that drought events deteriorated children's respiratory health particularly during 2005 when the drought was more geographically concentrated. This indicates that if governments act on curbing fire usage and effectively plan public health provision, as a climate change adaptation procedure, health quality would improve and public expenditure for treatment would decrease in the region during future drought events. [ABSTRACT FROM AUTHOR]

The article discusses a study which investigated whether there is a link between latitude and severity of multiple sclerosis. Topics covered include data acquired in the 2006 New Zealand National Multiple Sclerosis Prevalence Study (NZMSPS), and findings which suggest that there is a strong and direct relationship of latitude with prevalence, but a weak inverse relationship with disease severity.

Environmental epidemiology and health risk and impact assessment have long grappled with problems of uncertainty in data and their relationships. These uncertainties have become more challenging because of the complex, systemic nature of many of the risks. A clear framework defining and quantifying uncertainty is needed. Three dimensions characterise uncertainty: its nature, its location and its level. In terms of its nature, uncertainty can be both intrinsic and extrinsic. The former reflects the effects of complexity, sparseness and nonlinearity; the latter arises through inadequacies in available observational data, measurement methods, sampling regimes and models. Uncertainty occurs in three locations: conceptualising the problem, analysis and communicating the results. Most attention has been devoted to characterising and quantifying the analysis—a wide range of statistical methods has been developed to estimate analytical uncertainties and model their propagation through the analysis. In complex systemic risks, larger uncertainties may be associated with conceptualisation of the problem and communication of the analytical results, both of which depend on the perspective and viewpoint of the observer. These imply using more participatory approaches to investigation, and more qualitative measures of uncertainty, not only to define uncertainty more inclusively and completely, but also to help those involved better understand the nature of the uncertainties and their practical implications. [ABSTRACT FROM AUTHOR]

Study objective: Previous research provides preliminary evidence of spatial variations of mental disorders and associations between neighbourhood social context and mental health. This study expands past literature by (1) using spatial techniques, rather than multilevel models, to compare the spatial distributions of two groups of mental disorders (that is, disorders due to psychoactive substance use, and neurotic, stress related, and somatoform disorders); and (2) investigating the independent impact of contextual deprivation and neighbourhood social disorganisation on mental health, while assessing both the magnitude and the spatial scale of these effects. Design: Using different spatial techniques, the study investigated mental disorders due to psychoactive substance use, and neurotic disorders. Participants: All 89 285 persons aged 40-69 years residing in Malmö, Sweden, in 2001, geolocated to their place of residence. Main results: The spatial scan statistic identified a large cluster of increased prevalence in a similar location for the two mental disorders in the northern part of Malmö. However, hierarchical geostatistical models showed that the two groups of disorders exhibited a different spatial distribution, in terms of both magnitude and spatial scale. Mental disorders due to substance consumption showed larger neighbourhood variations, and varied in space on a larger scale, than neurotic disorders. After adjustment for individual factors, the risk of substance related disorders increased with neighbourhood deprivation and neighbourhood social disorganisation. The risk of neurotic disorders only increased with contextual deprivation. Measuring contextual factors across continuous space, it was found that these associations operated on a local scale. Conclusions: Taking space into account in the analyses permitted deeper insight into the contextual determinants of mental disorders. [ABSTRACT FROM AUTHOR]

In this study, we examine the concepts of spatial dependence and spatial heterogeneity in the effect of macro-level and micro-level factors on stunting among children aged under five in Uganda. We conducted a cross-sectional analysis of 3624 Ugandan children aged under five, using data from the 2016 Ugandan Demographic and Health Survey. Multilevel mixed-effect analysis, spatial regression methods and multi-scale geographically weight regression (MGWR) analysis were employed to examine the association between our predictors and stunting as well as to analyse spatial dependence and variability in the association. Approximately 28% of children were stunted. In the multilevel analysis, the effect of drought, diurnal temperature and livestock per km2 on stunting was modified by child, parent and household factors. Likewise, the contextual factors had a modifiable effect on the association between child's sex, mother's education and stunting. The results of the spatial regression models indicate a significant spatial error dependence in the residuals. The MGWR suggests rainfall and diurnal temperature had spatial varying associations with stunting. The spatial heterogeneity of rainfall and diurnal temperature as predictors of stunting suggest some areas in Uganda might be more sensitive to variability in these climatic conditions in relation to stunting than others. [ABSTRACT FROM AUTHOR]