Search

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]

With rapid economic growth, China has witnessed increasingly frequent and severe haze and smog episodes over the past decade, posing serious health impacts to the Chinese population, especially those in densely populated city clusters. Quantification of the spatial and temporal variation of health impacts attributable to ambient fine particulate matter (PM 2.5 ) has important implications for China's policies on air pollution control. In this study, we evaluated the spatial distribution of premature deaths in China between 2000 and 2010 attributable to ambient PM 2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM 2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM 2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM 2.5 concentration, rapid urbanization has attracted large population migration into the more developed eastern coastal urban areas, intensifying the overall health impact. In addition, our analysis implies that health burdens were exacerbated in some developing inner provinces with high population density (e.g. Henan, Anhui, Sichuan) because of the relocation of more polluting and resource-intensive industries into these regions. In order to avoid such national level environmental inequities, China's regulations on PM 2.5 should not be loosened in inner provinces. Furthermore policies should create incentive mechanisms that can promote transfer of advanced production and emissions control technologies from the coastal regions to the interior regions. [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]

The association between area-level disadvantage and health and social outcomes is unequivocal. However, less is known about the health impact of residential mobility, particularly at intra-urban scales. We used an encrypted National Health Index (eNHI) number to link individual-level data recorded in routine national health databases to construct a cohort of 641,532 participants aged 30+ years to investigate the association between moving and CVD hospitalisations in Auckland, New Zealand. Residential mobility was measured for participants according to changes in the census Meshblock of usual residence, obtained from the Primary Health Organisation (PHO) database for every calendar quarter between 1/1/2006 and 31/12/2012. The NZDep2006 area deprivation score at the start and end of a participant's inclusion in the study was used to measure deprivation mobility. We investigated the relative risk of movers being hospitalised for CVD relative to stayers using multi-variable binomial regression models, controlling for age, gender, deprivation and ethnicity. Considered together, movers were 1.22 (1.19–1.26) times more likely than stayers to be hospitalised for CVD. Using the 5 × 5 deprivation origin-destination matrix to model a patient's risk of CVD based on upward, downward or sideways deprivation mobility, movers within the least deprived (NZDep2006 Quintile 1) areas were 10% less likely than stayers to be hospitalised for CVD, while movers within the most deprived (NZDep2006 Q5) areas were 45% more likely than stayers to have had their first CVD hospitalisation in 2006–2012 (RR: 1.45 [1.35–1.55]). Participants who moved upward also had higher relative risks of having a CVD event, although their risk was less than those observed for participants experiencing downward deprivation mobility. This research suggests that residential mobility is an important determinant of CVD in Auckland. Further investigation is required to determine the impact moving has on the risk of CVD by ethnicity. [ABSTRACT FROM AUTHOR]

Theexposome, defined as the totality of an individual's exposures over the life course, is a seminal concept in the environmental health sciences. Although inherently geographic, the exposome as yet is unfamiliar to many geographers. This article proposes a place-based synthesis, genetic geographic information science (genetic GIScience), that is founded on the exposome, genome+, and behavome. It provides an improved understanding of human health in relation to biology (the genome+), environmental exposures (the exposome), and their social, societal, and behavioral determinants (the behavome). Genetic GIScience poses three key needs: first, a mathematical foundation for emergent theory; second, process-based models that bridge biological and geographic scales; third, biologically plausible estimates of space–time disease lags. Compartmental models are a possible solution; this article develops two models using pancreatic cancer as an exemplar. The first models carcinogenesis based on the cascade of mutations and cellular changes that lead to metastatic cancer. The second models cancer stages by diagnostic criteria. These provide empirical estimates of the distribution of latencies in cellular states and disease stages, and maps of the burden of yet to be diagnosed disease. This approach links our emerging knowledge of genomics to cancer progression at the cellular level, to individuals and their cancer stage at diagnosis, and to geographic distributions of cancer in extant populations. These methodological developments and exemplar provide the basis for a new synthesis in health geography: genetic GIScience. [ABSTRACT FROM PUBLISHER]

Abstract: Engineering and improved road safety education has resulted in an overall decrease in road traffic accident numbers in Christchurch, New Zealand. The temporal trends of crash data from 1980 to 2004 reveal that lowering of crash rates is not occurring at a uniform rate throughout the day, with comparative increases in crash rates occurring during morning rush hour, and during the ’school run’. No spatial clustering around schools was identified. This suggests that policies to reduce school travel related road accidents need to be focused on reducing overall traffic levels rather than focusing geographically on areas in the immediate vicinity of schools. [Copyright &y& Elsevier]

Examines the issues surrounding an individual's exposure to potential environmental risk factors which can be implication in the etiology of a disease. Estimation of relative risk for motor neurone disease in Finland; Openshaw's geographical analysis machine; Kernel estimation as a visualization tool.

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. 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, NO X , NO 2 , O 3 , SO 2 , NH 3 , PPM 2.5 , black carbon, organic carbon, mineral dust, sea salt, secondary inorganic aerosols, SO 4 2-, NO 3 -, NH 4 +, secondary organic aerosols, PM 2.5 , and PM 10 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. In total, 188 439 incident cases of RTI were identified. Exposure to most air pollutants was positively associated with risk of RTI. For example, NO 2 showed an IRR of 1.52 (CI: 1.48–1.55), and PM 2.5 showed an IRR of 1.45 (CI: 1.40–1.50). In contrast, exposure to sea salt, PM 10 , NH 3 , and O 3 was negatively associated with a risk of RTIs. In this nationwide study comprising adults, exposure to air pollution was associated with risk of RTIs and subgroups hereof. Sea salt, PM 10 , NH 3 , and O 3 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. [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]

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]

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]

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]

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]

The article provides information on the impact of urbanization on mental health, specifically focusing on the risk of depression. It discusses how factors such as population density, building height, and building density in urban areas can contribute to depression risks, highlighting the complex relationship between 3D urban form and mental well-being.

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. • Identified distinct childhood area-level socioeconomic status (SES) trajectories. • Downward trajectories posed risk for adolescent depression. • Exposure to area-level mid-SES in early years lessen adulthood anxiety risk. • Mixed evidence of consistent associations between trajectories and mental health. [ABSTRACT FROM AUTHOR]

Adverse health effects from exposure to air pollution are a global challenge and of widespread concern. Recent high ambient concentration episodes of air pollutants in European cities highlighted the dynamic nature of human exposure and the gaps in data and knowledge about exposure patterns. In order to support health impact assessment it is essential to develop a better understanding of individual exposure pathways in people's everyday lives by taking account of all environments in which people spend time. Here we describe the development, validation and results of an exposure method applied in a study conducted in Scotland. A low-cost particle counter based on light-scattering technology — the Dylos 1700 was used. Its performance was validated in comparison with equivalent instruments (TEOM-FDMS) at two national monitoring network sites ( R 2 = 0.9 at a rural background site, R 2 = 0.7 at an urban background site). This validation also provided two functions to convert measured PNCs into calculated particle mass concentrations for direct comparison of concentrations with equivalent monitoring instruments and air quality limit values. This study also used contextual and time-based activity data to define six microenvironments (MEs) to assess everyday exposure of individuals to short-term PM 2.5 concentrations. The Dylos was combined with a GPS receiver to track movement and exposure of individuals across the MEs. Seventeen volunteers collected 35 profiles. Profiles may have a different overall duration and structure with respect to times spent in different MEs and activities undertaken. Results indicate that due to the substantial variability across and between MEs, it is essential to measure near-complete exposure pathways to allow for a comprehensive assessment of the exposure risk a person encounters on a daily basis. Taking into account the information gained through personal exposure measurements, this work demonstrates the added value of data generated by the application of low-cost monitors. [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]

There has been considerable discussion in health geography and related areas of neighbourhood effects on health: the idea that people''s health in one geographical area may be influenced not only by the composition of that area''s population, but also by the area''s geographical context. Hence, the healthiness or otherwise of the neighbourhood may have an important effect on local people''s health. Although neighbourhoods and their boundaries are sometimes obvious to local residents, it is more common to find considerable disagreement on the size and contents of a neighbourhood. In this paper, we use British census Enumeration Districts as building blocks to construct alternative zonal systems, and experiment to see if neighbourhoods defined in different ways have similar implications for health. The well known modifiable areal unit problem shows that analytical conclusions may differ substantially according to how data are aggregated. Boundaries can be drawn to maximize equality of size, compactness of shape, homogeneity in social composition, accordance with ‘natural’ boundaries, and probably many other factors; which of these criteria are more effective in defining zones relevant to health? One conclusion is that the effect of neighbourhood conditions should be looked at using several different ways to define neighbourhoods, and that the size and composition of these neighbourhoods may be different in different parts of a study area. [Copyright &y& Elsevier]

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]

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]

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]

Recent research focused on the interaction between land cover and the development of allergic and respiratory disease has provided conflicting results and the underlying mechanisms are not fully understood. In particular, green space, which confers an overall positive impact on general health, may be significantly contributing to adverse respiratory health outcomes. This study evaluates associations between surrounding residential land cover (green, grey, agricultural and blue space), including type of forest cover (deciduous, coniferous and mixed), and childhood allergic and respiratory diseases. Data from 8063 children, aged 3–14 years, were obtained from nine European population-based studies participating in the HEALS project. Land-cover exposures within a 500 m buffer centred on each child's residential address were computed using data from the Coordination of Information on the Environment (CORINE) program. The associations of allergic and respiratory symptoms (wheeze, asthma, allergic rhinitis and eczema) with land coverage were estimated for each study using logistic regression models, adjusted for sex, age, body mass index, maternal education, parental smoking, and parental history of allergy. Finally, the pooled effects across studies were estimated using meta-analyses. In the pooled analyses, a 10% increase in green space coverage was significantly associated with a 5.9%–13.0% increase in the odds of wheezing, asthma, and allergic rhinitis, but not eczema. A trend of an inverse relationship between agricultural space and respiratory symptoms was observed, but did not reach statistical significance. In secondary analyses, children living in areas with surrounding coniferous forests had significantly greater odds of reporting wheezing, asthma and allergic rhinitis. Our results provide further evidence that exposure to green space is associated with increased respiratory disease in children. Additionally, our findings suggest that coniferous forests might be associated with wheezing, asthma and allergic rhinitis. Additional studies evaluating both the type of green space and its use in relation to respiratory conditions should be conducted in order to clarify the underlying mechanisms behind associated adverse impacts. • Green space is associated with greater odds of childhood wheezing, asthma, and allergic rhinitis. • Living near coniferous forests may increase the risk of wheezing, asthma, and allergic rhinitis. • Agricultural spaces may have a protective effect on childhood allergic and respiratory diseases. • No associations were found between grey space and allergic and respiratory health outcomes. [ABSTRACT FROM AUTHOR]

Phthalate exposure from Vegetables grown in Plastic Greenhouses (VPGs) represents an important source of total daily phthalate exposure in China. However, quantified health risks of phthalates attributable to VPG intake have not been documented. To fill this gap, this study estimates phthalate exposure from VPG intake in western China and calculates the first assessment of the disease burden associated with phthalate exposure from VPG intake in China based on a simple steady-state exposure model and a linear dose-response function between human bio-monitoring phthalates and Type 2 Diabetes (T2D) prevalence. What we present in this paper is a problem identification and screening level risk assessment. We chose Shaanxi province as the research field site due to its large contribution to the total vegetable yield and consumption in western China. Phthalate concentration in VPG samples, phthalate exposure levels from VPG intake, and the T2D burden caused by phthalate attributable to VPG intake for adults were measured or calculated. Di-2-ethylhexyl phthalate (DEHP) was found to represent over 55% of the total phthalate concentration in VPGs, followed by di-n-butyl phthalate (DnBP) and di-isobutyl phthalate (DiBP). Phthalate exposure from VPG intake for urban adults was higher than the level for rural adults. The share of DEHP exposure from VPG intake to urinary total DEHP metabolites were nearly 8% and 15%, and the share of DnBP exposure caused by VPG intake to total daily DnBP metabolites were nearly 4% and 7%, for rural and urban adult populations in Shaanxi, respectively. The adult population with T2D attributable to phthalate exposure from VPG intake was 2561, nearly 6.4% to the T2D burden attributable to total phthalate exposure, and 0.4% to the total adult population with T2D in Shaanxi. The authors recommend policy interventions to protect populations from future risk of phthalate exposure. Unlabelled Image • DEHP was over 55% of the total phthalate concentration in VPGs, followed by DnBP. • Urban adults have higher phthalate exposure from VPG intake than rural adults have. • Urinary DEHP from VPG intake was 15% to total daily DEHP exposure in urban adults. • MBP from VPG intake was 7% to total daily DnBP exposure in urban adults. • T2D burdens associated to phthalate from VPG intake was 0.4% of the total T2D adults. [ABSTRACT FROM AUTHOR]

Lake sediment is a natural sink for polycyclic aromatic hydrocarbons (PAHs). PAH sedimentation characteristics and their impact factors of Chinese lakes have mainly been qualitative assessed. However, quantitative impacts of PAH sedimentation from different factors have not been well analyzed. To fill this gap, we screened PAH sedimentation records from the literature, for 51 lakes in China and other regions of the world, to identify historical concentration variation and the impact factors of PAHs in different regions, in lake sediment. The results show that PAH concentrations in the sediment core in the selected Chinese lakes (478 ± 812 ng/g dry weight (dw)) were significantly lower than those in North America (5518 ± 6572 ng/g dw) and Europe (3817 ± 4033 ng/g dw). From 1900 to 2015, most of the lakes in China showed an increasing trend of PAH sedimentation concentrations, with the lakes in Southeastern China showed a decreasing trend of PAH concentration in the period of 2001–2015, which was later than the peak times shown in Western countries (1941–1970). The 2-3-ring PAHs were the main components in the sediment core of Chinese lakes, but the proportion to the total PAHs decreased from 72% in 1900–1940 to 55% in 2001–2015. Generalized additive modeling (GAM) was adopted to simulate the associations between PAH sedimentation records and the impact factors. There are large regional variations of economic and industrial development in China. The impact factors of PAH accumulation in the lake sediments differ in different regions. However, population and the consumption of coal, pesticides, and fertilizer were identified to be the most important impact factors influencing PAH sedimentation. The Chinese government needs to strengthen control measures on pollutant discharge to reduce the anthropogenic impact of PAH sedimentation in lakes. [Display omitted] • PAH variations in lake sediment cores in China were analyzed by the literature data. • PAH contents in China's lake sediment were 9 times lower than in Western lakes. • PAH concentrations in most lake sediment cores in China increased from 1900 to 2015. • The share of 2–3 ring PAHs in lake sediment changed from 72% in 1900 to 55% in 2015. • Population and coal & agricultural use mainly impact the PAH sedimentation records. [ABSTRACT FROM AUTHOR]

With frequent severe haze and smog episodes in Chinese cities, an increasing number of studies have focused on estimating the impact of fine particulate matter (PM 2.5) on public health. However, the current use of national and provincial demographic data might mask regional differences and lead to inaccurate estimations of pollution-related health impacts across cities. We applied the Global Burden of Disease methodology to develop a dataset of premature deaths attributed to ambient PM 2.5 in 129 Chinese cities in 2006, 2010 and 2015, based on the information of baseline mortality rates and population densities at the city level. Our results suggested that ambient PM 2.5 pollution led to 631,230 (95% confidence interval: 281,460–873,800) premature deaths in those cities in 2015, which was similar to that in 2010, but 42.8% higher than that in 2006. The reduction of premature deaths was not as obvious as the improvement in air quality in recent years, primarily owing to the aging Chinese population. For large and medium/small cities, the effects of PM 2.5 abatement on alleviating public health burdens were lower than those for megalopolises and metropolises; however, such large and medium/small cities are at risk of increasing future PM 2.5 pollution levels due to rapid development. Significant differences in PM 2.5 -induced premature deaths indicated the need for specific policies to mitigate the health burden of air pollution in different types of Chinese cities. • Health burdens of PM2.5 in 129 Chinese cities during 2006-2015 were calculated. • Ageing population hinders improvement of health benefit from pollution control. • Characteristics of health burden for different types of cities were analyzed. • Regional characteristics should be considered when developing policies. [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]

Monitoring long-term landslide activity is of importance for risk assessment and land management. Daytime airborne drones or very high-resolution optical satellites are often used to create landslide maps. However, such imagery comes at a high cost, making long-term risk analysis cost-prohibitive. Despite the widespread use of open-access 30 m Landsat imagery, their utility for landslide detection is often limited due to low classification accuracy. One of the major challenges is to separate landslides from other anthropogenic disturbances. Here, we produce landslide maps retrospectively from 1998 to 2017 for landslide-prone and highly populated Taiwan (35,874 km2). To improve classification accuracy of landslides, we integrate nighttime light imagery from the Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite (VIIRS), with multi-seasonal daytime optical Landsat time-series, and digital elevation data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). We employed a non-parametric machine-learning classifier, random forest, to classify the satellite imagery. The classifier was trained with data from three years (2005, 2010, and 2015), and was validated with an independent reference sample from twelve years. Our results demonstrated that combining nighttime light data and multi-seasonal imagery significantly improved the classification (p < 0.001), compared to conventional methods based on single-season optical imagery. The results confirmed that the developed classification model enabled mapping of landslides across Taiwan over a long period with annual overall accuracy varying between 96% and 97%, user's and producer's accuracies between 73% and 86%. Spatiotemporal analysis of the landslide inventories from 1998 to 2017 revealed different temporal patterns of landslide activities, showing those areas where landslides were persistent and other areas where landslides tended to reoccur after vegetation regrowth. In sum, we provide a robust method to detect long-term landslide activities based on freely available satellite imagery, which can be applied elsewhere. Our mapping effort of landslide spatiotemporal patterns is expected to be of high importance in developing effective landslide remediation strategies. • Free satellite imagery accurately mapped large-scale historical landslides. • VIIRS and DMSP nighttime light data boosted landslide detection accuracy. • Multi-seasonal Landsat imagery improved landslide mapping accuracy. • A north-south gradient of landslide occurrence identified in Taiwan over 20 years. [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]

Abstract Exposure to ambient ozone (O 3) is a risk factor for public health and causes damage to vegetation, including agricultural crops. In this study, we performed a comprehensive estimate of the spatial distribution of premature deaths and main crop yield losses attributed to ambient O 3 , across China in 2014, by applying the Global Burden of Diseases approach and AOT40 metric (i.e., above a threshold of O 3 concentration of 40 ppb). Our results show that China's total premature deaths in 2014 due to COPD attributed to O 3 exposure were 89,391 (CI95: 32,225–141,649) with spatial variation across provinces. O 3 induced production losses from all crops were 78.4 million metric tons, and the relative yield losses ranged from 8.5 to 14.0% for winter wheat, 3.9–15.0% for rice, and 2.2–5.5% for maize. The top four Chinese provinces (Sichuan, Shandong, Henan and Hunan) for premature deaths attributed to O 3 pollution also suffered severe losses in yields of winter wheat and rice. Our results provide quantitative evidence of O 3 induced impacts on both the public health and crop yields across Chinese provinces, which have important policy implications for the government to alleviate O 3 pollution in addition to PM 2.5 pollution that is currently being addressed. Highlights • Impacts of O 3 on both public health and crop yield were analyzed for China. • Premature deaths attributed to ambient O 3 were 89,391 in 2014. • O 3 induced reductions of winter wheat, rice and maize reached 78.4 Mt in 2014. • Top provinces of O 3 induced health burden also suffered serious crop yield losses. • More attention should be paid to exacerbated O 3 impacts in some inner provinces. [ABSTRACT FROM AUTHOR]

With increasing consumption of Vegetables planted in Plastic Greenhouses (VPGs) in China, phthalate exposure from VPGs represents an overlooked source of total daily exposure, since VPGs are not included in current phthalate exposure scenarios. For this reason, current exposure scenario modeling may underestimate the daily phthalate exposure in relation to adverse health impacts. Thus, in this paper we estimated the oral intake exposure to phthalates from VPGs by studying four provinces ranging from the north to the south in eastern China, based on published data. Exposures to di(2-ethylhexyl)-phthalate (DEHP) and dibutyl phthalate (DBP) were assessed for various population groups differentiated by age, sex, income, and region. Younger children experienced the highest exposure from VPG intake (mean 1.55 (0.19 and 6.20) (2.5th and 97.5th percentiles) μg/kg/body weight (bw)/day), followed by older children, teenagers, and adults (0.53 (0.06 and 1.80)). Exposures in urban populations were significantly higher than those in rural areas, and when examined by income, urban populations with low-income had the lowest exposures and the upper-middle income group was associated with the highest levels. Exposures in northeastern and southern provinces were higher than the levels in middle provinces due to regional disparities in dietary habits. Proportions of the mean oral intake exposures to DEHP and DBP from VPGs to the total daily exposure by modeling different exposure pathways and media were over 10% for all age groups. The DEHP and DBP exposure from VPG intake in China were found to be much higher than the levels in western countries. For example, exposures of older children to DBP and DEHP were respectively 17 and 4 times higher than European levels. The authors recommend policy interventions to protect populations from future risk of phthalate exposure. [ABSTRACT FROM AUTHOR]

Serious air pollution has caused about one million premature deaths per year in China recently. Besides cross-border atmospheric transport of air pollution, trade also relocates pollution and related health impacts across China as a result of the spatial separation between consumption and production. This study proposes an approach for calculating the health impacts of emissions due to a region's consumption based on a multidisciplinary methodology coupling economic, atmospheric, and epidemiological models. These analyses were performed for China's Beijing and Hebei provinces. It was found that these provinces' consumption-based premature deaths attributable to ambient PM 2.5 were respectively 22,500 and 49,700, which were 23% higher and 37% lower than the numbers solely within their boundaries in 2007. The difference between the effects of trade and trade-related emissions on premature deaths attributable to air pollution in a region has also been clarified. The results illustrate the large and broad impact of domestic trade on regional air quality and the need for comprehensive consideration of supply chains in designing policy to mitigate the negative health impacts of air pollution across China. [ABSTRACT FROM AUTHOR]

Research has suggested that children who move home report poorer mental health than those who remain residentially stable. However, many previous studies have been based on cross sectional data and have failed to consider major life events as confounders. This study uses longitudinal data from ALSPAC, a UK population based birth cohort study, and employs within-between random effect models to decompose the association between moving in childhood and poor mental health. Results suggest that while unobserved between-individual differences between mobile and non-mobile children account for a large portion of this association, within-individual differences remain and indicate that moving may have a detrimental impact upon subsequent mental health. There is heterogeneity in children's response to moving, suggesting that a dichotomy of movers vs stayers is overly simplistic. [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]

A large literature exists suggesting that residential mobility leads to increased participation in risky health behaviours such as cannabis use amongst youth. However, much of this work fails to account for the impact that underlying differences between mobile and non-mobile youth have on this relationship. In this study we utilise multilevel models with longitudinal data to simultaneously estimate between-child and within-child effects in the relationship between residential mobility and cannabis use, allowing us to determine the extent to which cannabis use in adolescence is driven by residential mobility and unobserved confounding. Data come from a UK cohort, The Avon Longitudinal Study of Parents and Children. Consistent with previous research we find a positive association between cumulative residential mobility and cannabis use when using multilevel extensions of conventional logistic regression models (log odds: 0.94, standard error: 0.42), indicating that children who move houses are more likely to use cannabis than those who remain residentially stable. However, decomposing this relationship into within- and between-child components reveals that the conventional model is underspecified and misleading; we find that differences in cannabis use between mobile and non-mobile children are due to underlying differences between these groups (between-child log odds: 3.56, standard error: 1.22), not by a change in status of residential mobility (within-child log odds: 1.33, standard error: 1.02). Our findings suggest that residential mobility in the teenage years does not place children at an increased risk of cannabis use throughout these years. [ABSTRACT FROM AUTHOR]

Public open space (POS) plays a significant role in fostering human health and wellbeing in cities. A major limitation of current research on POS and health is that there is little attention on the role of various urban features on people's mental health, in different urban context. This study employed wearable sensors (a wearable camera, Empatica 4 wristband and a GPS device) to measure human physiological responses to urban indicators, objectively. To do this, we selected six kinds of public open space (water area, transit area, green area, commercial area, motor traffic area and mixed office and residential area) and recruited 86 participants for an experimental study. Next, we detected urban features by using Microsoft Cognitive Services (MCS) and calculated a change score to assess human physiological stress responses based on galvanic skin response (GSR) and skin temperature from the wristband. Lastly, we applied random effect model and geographically weighted regression analysis to examine the relationship between urban indicators and human physiological stress responses. The findings show that urban flow (vehicles, bikes and people), waterbodies, greenery and places to sit are associated with the changes of human physiological stress response. The findings indicate that the type of urban context may confound the effect of green and blue urban features; i.e., the effect on physiological stress response can be positive or negative depending on the context. The paper highlights the relevance of considering urban context in research on associations between urban features and stress response. [ABSTRACT FROM AUTHOR]

Background Elevated temperature and air pollution have been associated with increased mortality. Exposure to heat and air pollution, as well as the density of vulnerable groups varies within cities. The objective was to investigate the extent of neighbourhood differences in mortality risk due to heat and air pollution in a city with a temperate maritime climate. Methods A case-crossover design was used to study associations between heat, air pollution and mortality. Different thermal indicators and air pollutants (PM 10 , NO 2 , O 3 ) were reconstructed at high spatial resolution to improve exposure classification. Daily exposures were linked to individual mortality cases over a 15 year period. Results Significant interaction between maximum air temperature (Ta max ) and PM 10 was observed. During “summer smog” days (Ta max > 25 °C and PM 10 > 50 μg/m 3 ), the mortality risk at lag 2 was 7% higher compared to the reference (Ta max 15 °C and PM 10 15 μg/m 3 ). Persons above age 85 living alone were at highest risk. Conclusion We found significant synergistic effects of high temperatures and air pollution on mortality. Single living elderly were the most vulnerable group. Due to spatial differences in temperature and air pollution, mortality risks varied substantially between neighbourhoods, with a difference up to 7%. [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]

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]

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.

Natural environments have been associated with mental health benefits, but globally access to these benefits is threatened by urban development and densification. However, it remains unclear how natural environments relate to mental health and how consistent the association is across populations. Here we use a life-course approach with a population consisting of 66 194 individuals from the Danish Blood Donor Study (DBDS) to investigate the association between green and blue space (e.g. parks and lakes) and self-evaluated mental well-being. Green and blue space was identified from remotely-sensed images from the Landsat program, while mental well-being was based on the mental component score (MCS) calculated using the 12-item short form health survey. We use multivariate linear regression models and logistic regression models to quantify the associations. We adjust for additional environmental (urbanization, and air pollution) and lifestyle factors (smoking, body mass index, socioeconomic status, and physical activity) and specifically evaluate the role of physical activity and air pollution as possible mediating factors. We found a positive association between the MCS and current and childhood green space, and a non-significant association for current and childhood blue space. Adjusting for environmental and the other factors attenuated the effect sizes indicating that a broad range of factors determine mental well-being. Physical activity and air pollution were both associated with the MCS as possible mediators of green space associations. In addition, the odds for successfully completing tasks', seeing others, and feeling less downhearted increased with higher levels of green space, and the odds of feeling calm increased with higher levels of blue space. In conclusion, we found support for an association between green and, to less degree, blue space and mental well-being throughout different life stages. In addition, we found a positive association with individual indicators of mental well-being such as being productive, feeling less downhearted and calmer, and being social. The healthy blood donor effect and the bias towards urban residency may explain why we found smaller effect sizes between green and blue space and mental well-being for this generally healthy and resourceful cohort compared to previous studies. [ABSTRACT FROM AUTHOR]

Abstract: Bends in roads can cause crashes but a recent study in the UK found that areas with mostly curved roads had lower crash rates than areas with straighter roads. This present study aimed to replicate the previous research in a different country. Variations in the number of fatal road crashes occurring between 1996 and 2005 in 73 territorial local authorities across New Zealand were modelled against possible predictors. The predictors were traffic flow, population counts and characteristics, car use, socio-economic deprivation, climate, altitude and road characteristics including four measures of average road curvature. The best predictors of the number of fatal crashes on urban roads, rural state highways and other rural roads were traffic flow, speed limitation and socio-economic deprivation. Holding significant factors constant, there was no evidence that TLAs with the most curved roads had more crashes than elsewhere. Fatal crashes on urban roads were significantly and negatively related to two measures of road curvature: the ratio of road length to straight distance and the cumulative angle turned per kilometre. Weaker negative associations on rural state highways could have occurred by chance. These results offer limited support to the suggestion that frequently occurring road bends might be protective. [Copyright &y& Elsevier]

Landsat imagery is an unparalleled freely available data source that allows reconstructing land-cover and land-use change, including urban form. This paper addresses the challenge of using Landsat data, particularly its 30 m spatial resolution, for monitoring three-dimensional urban densification. Unlike conventional convolutional neural networks (CNNs) for scene recognition resulting in resolution loss, the proposed semantic segmentation framework provides a pixel-wise classification and improves the accuracy of urban form mapping. We compare temporal and spatial transferability of an adapted DeepLab model with a simple fully convolutional network (FCN) and a texture-based random forest (RF) model to map urban density in the two morphological dimensions: horizontal (compact, open, sparse) and vertical (high rise, low rise). We test whether a model trained on the 2014 data can be applied to 2006 and 1995 for Denmark, and examine whether we could use the model trained on the Danish data to accurately map ten other European cities. Our results show that an implementation of deep networks and the inclusion of multi-scale contextual information greatly improve the classification and the model's ability to generalize across space and time. Between the two semantic segmentation models, DeepLab provides more accurate horizontal and vertical classifications than FCN when sufficient training data is available. By using DeepLab, the F1 score can be increased by 4 and 10 percentage points for detecting vertical urban growth compared to FCN and RF for Denmark. For mapping the ten other European cities with training data from Denmark, DeepLab also shows an advantage of 6 percentage points over RF for both horizontal and vertical dimensions. The resulting maps across the years 1985 to 2018 reveal different patterns of urban growth between Copenhagen and Aarhus, the two largest cities in Denmark, illustrating that those cities have used various planning policies in addressing population growth and housing supply challenges. In summary, we propose a transferable deep learning approach for automated, long-term mapping of urban form from Landsat images that is effective in areas experiencing a slow pace of urban growth or with small-scale changes. • A workflow capturing 30 m urban dynamics based on Landsat imagery and deep learning • CNN-based semantic segmentation models outperform random forest approaches. • Spatial and temporal transferability of 3D urban form mapping is feasible. • Urban density growth in Denmark varies between cities and through time 1985–2018. [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]

Natural environments have been associated with mental health benefits worldwide. However, how different elements and types of natural environments associate with mental health is still largely unknown. In this study, we perform a detailed analysis on a large, nation-wide data set of mental health records (908 553 individuals) for Denmark combined with remotely-sensed land cover and vegetation density data. We explore associations between growing up surrounded by different environments and rates of a spectrum of 18 psychiatric disorders. Childhood land cover exposure for urban, agricultural, near-natural green space, and blue space was determined around the residence of each individual. Vegetation density and air pollution were evaluated as potential pathways. Cox proportional hazards models were used to estimate rates as hazard ratios and then adjusted for potential confounding from other known risk factors. For 12 of 18 disorders, rates were lower for children growing up in environments with more natural elements (near-natural green space, blue space, and agriculture) compared to children growing up in urban environments. High vegetation density was associated with lower rates for most disorders within all the examined environments, whereas mitigation of air pollution by natural environments seemed a less important potential pathway. Rates were not notably changed by adjustment for urbanization, parental and municipal socioeconomic status, family history of mental illness, and parents' age. In conclusion, we found that growing up surrounded by a range of natural environments such as near-natural green space, blue space, and agriculture may lower rates of psychiatric disorders. Our results show the importance of ensuring access to natural environments from as nature-based solutions for improved public health and sustainable, livable cities. Image 1 • Psychiatric disorder rates generally increased incrementally with urban land cover. • Rates for near-natural green space decreased incrementally for most disorders. • Air pollution exposure was associated with risk for some disorders (e.g. Schizophrenia). • Land cover association strength was similar to air pollution and family history of mental illness. • Findings have implications for public health and sustainable urban development. [ABSTRACT FROM AUTHOR]

• Approximately 9% of Ghanaian older adults have depression. • There is a high sense of trust and safety among Ghanaian older adults. • Attending religious services and engaging in social outing is generally high. • Public meeting and socializing with co-workers reduces the risk of depression. • Club meetings, working with neighbors and social outing increases depression. • Neighborhood safety and networks reduces the risk of depression. Evidence from existing studies suggests social capital has mixed effects on depression and other common mental disorders. There is little knowledge of the possible association between social capital and depression among the growing older population in sub-Saharan Africa. This study investigates the effect of cognitive social capital (trust and sense of safety) and structural social capital (social participation or engagement in social activities) on depression among older adults in Ghana. Utilizing multilevel mixed-effect analysis, we investigate the effect of individual-level and neighborhood-level social capital (cognitive and structural) on depression using data from the World Health Organization Study on Global Ageing and Adult Health (WHO-SAGE) survey (Wave 1). The findings show that at an individual level, older adults who felt safe at home were less likely to have depression. We observed mixed results for elements of structural social capital at the individual level. Older adults who frequently engaged in club or group meetings, worked with neighbors and engaged in social outings were more likely to have depression; while attending public meetings and socializing with co-workers were associated with reduced likelihood of having depression. At the neighborhood level, increased trust in neighbors was associated with an increased likelihood of having depression (OR = 1.01, p < 0.05) while higher levels of neighborhood safety and structural social capital were associated with a reduced likelihood of having depression. The findings suggest that the differential associations between elements of social capital and depression may be the result of contextual factors. [ABSTRACT FROM AUTHOR]