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

BackgroundA socioeconomically disadvantaged childhood has been associated with elevated self-harm and violent criminality risks during adolescence and young adulthood. However, whether these risks are modified by a neighbourhood's socioeconomic profile is unclear. The aim of our study was to compare risks among disadvantaged young people residing in deprived areas versus risks among similarly disadvantaged individuals residing in affluent areas.MethodsWe did a national cohort study, using Danish interlinked national registers, from which we delineated a longitudinal cohort of people born in Denmark between Jan 1, 1981, and Dec 31, 2001, with two Danish-born parents, who were alive and residing in the country when they were aged 15 years, who were followed up for a hospital-treated self-harm episode or violent crime conviction. A neighbourhood affluence indicator was derived based on nationwide income quartiles, with parental income and educational attainment indicating the socioeconomic position of each cohort member's family. Bayesian multilevel survival analyses were done to examine the moderating influences of neighbourhood affluence on associations between family socioeconomic position and sex-specific risks for the two adverse outcomes.Findings1 084 047 cohort members were followed up for 12·8 million person-years in aggregate. Individuals of a low socioeconomic position residing in deprived neighbourhoods had a higher incidence of both self-harm and violent criminality compared with equivalently disadvantaged peers residing in affluent areas. Women from a low-income background residing in affluent areas had, on average, 95 (highest density interval 76–118) fewer self-harm episodes and 25 (15–41) fewer violent crime convictions per 10 000 person-years compared with women of an equally low income residing in deprived areas, whereas men of a low income residing in affluent areas had 61 (39–81) fewer self-harm episodes and 88 (56–191) fewer violent crime convictions per 10 000 person-years than men of a low income residing in deprived areas.InterpretationEven in a high-income European country with comprehensive social welfare and low levels of poverty and inequality, individuals residing in affluent neighbourhoods have lower risks of self-harm and violent criminality compared with individuals residing in deprived neighbourhoods. More research is needed to explore the potential of neighbourhood policies and interventions to reduce the harmful effects of growing up in socioeconomically deprived circumstances on later risk of self-harm and violent crime convictions.FundingEuropean Research Council, Lundbeck Foundation Initiative for Integrative Psychiatric Research, and BERTHA, the Danish Big Data Centre for Environment and Health funded by the Novo Nordisk Foundation Challenge Programme.

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.

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.

The distance between home and school considerably influences the probability of children’s walking or biking to school (termed Active School Travel) which is a significant opportunity to promote their daily physical activity. This study investigated the shortest routes from home to school of primary school students and how the route distance can be shortened at the household level in Nanjing, China. We found that gated urban form results in significantly roundabout routes to school. In 2016, China issued the Opening and Prohibiting Gated Communities policy, subsequently the Healthy Cities Initiative, etc. which may leverage cities towards more healthy and sustainable transformations. In the light of these policies, we hypothesised that providing through access as management option, and opening new entries as reengineering option, would shorten school travel distance with minor costs. The scenario analysis shows that such management and reengineering adaptions would provide shorter and potentially less exposed routes for students. This study identifies how the existent urban form works against active school travel, and proposes how salutogenic pathways may be created in the gated urban form. The study, with transferability to other cities, can assist urban designers and policy makers in piloting urban (re)form incrementally and pragmatically to prompt active travel to schools.

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.

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.

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.

Ambient PM2.5 (fine particulate matter) pollution in China has been greatly reduced in recent years, especially since the implementation of the Clean Air Action in 2013. The analysis of variations in the pollution-related health burden and its driving factors has important implications for policy makers in terms of further improving the health benefits associated with air pollution control. Here, the Global Estimates Mortality Model was adopted to newly estimate the annual mortality attributable to PM2.5 in China from 2004 to 2017. Then, the effects of the changed ambient PM2.5 concentrations, population size and migration, aging and baseline mortality rate on the total variation of the PM2.5 health burden were quantified, and insights were provided into the factors impeding the achievement of health benefits as air pollution is mitigated. Our modelling results showed that the national PM2.5 health burden generally increased from 2.22 million (95% confidence interval: 1.39–2.98) in 2004 to 2.45 million (1.72–3.13) in 2017 with a tendency to rise first and then decline, and peaking at 2.65 million (1.60–3.60) in 2013. The average exposure to ambient PM2.5 in China has dropped since 2011, two years earlier than the overall PM2.5-attributable mortality turning point. Compared to 2013, the mitigation of PM2.5 pollution would have prevented 0.85 million deaths in 2017, at the same time, the effect of the population aging determined the addition of 0.51 million deaths from air pollution, which partly masked the effect of the mitigation. For future air pollution control policies to alleviate the public health burdens in the fast-growing Chinese cities, attention should be focused on old age care, especially in areas where PM2.5-attributable mortality may increase.

There is limited knowledge on the effect of contextual and environmental factors on the risk of anaemia, as well as the spatial distribution of anaemia in the Sub-Saharan Africa region. In this study, we used multi-country data from the Demographic & Health survey (DHS) with 270,011 observations and PM2.5 data from NASA, applied to the spatial risk pattern of anaemia in the SSA region. The prevalence of anaemia among women (41%) was almost twice that of men (22%). A Bayesian hierarchical model showed that individual household, neighbourhood and regional socioeconomic factors were significantly associated with the likelihood of being anaemic. One μg/m3 increase in cumulative lifetime PM2.5 exposure accounted for 1% (β=0.011, CI = 0.008 – 0.015) increase in the likelihood of being anaemic. The results suggest the need for a multidimensional approach to tackle anaemia in the Sub-Saharan African region and identify high-risk areas for target intervention policies or programs.

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.

Research has found that sexual minority individuals are more likely to experience health inequalities and have higher rates of substance use compared with their heterosexual counterparts. This association between sexuality and health outcomes is increasingly being explored using quantitative methodologies within the context of public health, psychology and health geography. Much of this research, however, has relied on primary data, despite the wide availability of secondary sources, mainly survey data, collecting information on sexuality and different types of health outcomes and health risk behaviours, such as substance use. This study reviewed recent surveys in the UK that are appropriate for exploring topics related to LGB populations and substance use behaviours. We carried out a narrative review of secondary data sources in the UK to assess the accessibility and suitability of secondary sources for sexuality and substance use research. We identified eight cross-sectional and two longitudinal surveys that contained both sexuality and substance use data. We summarised the possible applications of each survey and the scope of questions within sexuality and substance use research that could be addressed by each survey. The identification of appropriate surveys in this review can allow researchers to extend the use of secondary data sources in the UK to examine substance use inequalities between sexuality groups, further advancing this key topic.

BackgroundThe COVID-19 pandemic has asked unprecedented questions of governments around the world. Policy responses have disrupted usual patterns of movement in society, locally and globally, with resultant impacts on national economies and human well-being. These interventions have primarily centred on enforcing lockdowns and introducing social distancing recommendations, leading to questions of trust and competency around the role of institutions and the administrative apparatus of state. This study demonstrates the unequal societal impacts in population movement during a national ‘lockdown’.MethodsWe use nationwide mobile phone movement data to quantify the effect of an enforced lockdown on population mobility by neighbourhood deprivation using an ecological study design. We then derive a mobility index using anonymised aggregated population counts for each neighbourhood (2253 Census Statistical Areas; mean population n=2086) of national hourly mobile phone location data (7.45 million records, 1 March 2020–20 July 2020) for New Zealand (NZ).ResultsCurtailing movement has highlighted and exacerbated underlying social and spatial inequalities. Our analysis reveals the unequal movements during ‘lockdown’ by neighbourhood socioeconomic status in NZ.ConclusionIn understanding inequalities in neighbourhood movements, we are contributing critical new evidence to the policy debate about the impact(s) and efficacy of national, regional or local lockdowns which have sparked such controversy.

Agricultural plastic greenhouse (PG) production can extend the growing season of crops to satisfy domestic consumption in countries such as China. Workers in PGs have potential higher phthalate exposure risks than the general population as phthalate accumulation has been observed in greenhouse soil, air, and crops. To date, biomonitoring tests of phthalates for the working population have not been carried out. To address this shortage, we conducted a pilot study in Shaanxi Province, China, among 35 healthy PG workers by follow-up recording their seasonal dietary habits and work activities and urine sample collection and measurement between 2018 and 2019. The objectives were to uncover the association between phthalate metabolites and the population characteristics, seasonal and diurnal variations and causes, and to estimate exposure risks and contributions of exposure pathways from PG production systems. A total of 13 phthalate metabolite concentrations (Σ13 phthalate metabolites) ranged from 102 to 781 (5th-95th) ng/mL (median: 300 ng/mL). Mono-n-butyl phthalate (MNBP) made up 51.3% of Σ13 phthalate metabolites, followed by the sum of four di-2-ethylhexyl phthalate (DEHP) metabolites (24.2%), mono-2-isobutyl phthalate (MIBP) (13.4%), and mono-ethyl phthalate (MEP) (9.8%). The concentrations of MNBP and MIBP in summer were significantly higher than the levels in winter (p < 0.0001). A total of 62.3% of the PG worker population was shown to have exposure risks, and the proportion was as high as 79.4% in summer. Phthalate exposure of the workers from PG production systems constituted over 20% of the total creatinine-based daily intake, and consuming vegetables and fruit planted in PGs and inhalation in PGs were the two largest exposure pathways. Our findings demonstrate that it is important to protect workers in PGs from phthalate exposure risks, and phasing out the use of plastic materials containing phthalates in PGs is imperative, to guarantee food safety in PGs.

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.

The ever-growing development of sensor technology brings new opportunities to investigate impacts of the outdoor environment on human health at the individual level. However, there is limited literature on the use of multiple personalized sensors in urban environments. This review paper focuses on examining how multiple personalized sensors have been integrated to enhance the monitoring of co-exposures and health effects in the city. Following PRISMA guidelines, two reviewers screened 4898 studies from Scopus, Web of Science, ProQuest, Embase, and PubMed databases published from January 2010 to April 2021. In this case, 39 articles met the eligibility criteria. The review begins by examining the characteristics of the reviewed papers to assess the current situation of integrating multiple sensors for health and environment monitoring. Two main challenges were identified from the quality assessment: choosing sensors and integrating data. Lastly, we propose a checklist with feasible measures to improve the integration of multiple sensors for future studies.

There is limited knowledge on the effect of contextual and environmental factors on the risk of anaemia, as well as the spatial distribution of anaemia in the Sub-Saharan Africa region. In this study, we used multi-country data from the DemographicHealth survey (DHS) with 270,011 observations and PM

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.

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 30m 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

Childhood exposure to green space has previously been associated with lower risk of developing schizophrenia later in life. It is unclear whether this association is mediated by genetic liability or whether the 2 risk factors work additively. Here, we investigate possible gene–environment associations with the hazard ratio (HR) of schizophrenia by combining (1) an estimate of childhood exposure to residential-level green space based on the normalized difference vegetation index (NDVI) from Landsat satellite images, with (2) genetic liability estimates based on polygenic risk scores for 19 746 genotyped individuals from the Danish iPSYCH sample. We used information from the Danish registers of health, residential address, and socioeconomic status to adjust HR estimates for established confounders, ie, parents’ socioeconomic status, and family history of mental illness. The adjusted HRs show that growing up surrounded by the highest compared to the lowest decile of NDVI was associated with a 0.52-fold (95% confidence interval [CI]: 0.40 to 0.66) lower schizophrenia risk, and children with the highest polygenic risk score had a 1.24-fold (95% CI: 1.18 to 1.30) higher schizophrenia risk. We found that NDVI explained 1.45% (95% CI: 1.07 to 1.90) of the variance on the liability scale, while polygenic risk score for schizophrenia explained 1.01% (95% CI: 0.77 to 1.46). Together they explained 2.40% (95% CI: 1.99 to 3.07) with no indication of a gene–environment interaction (P = .29). Our results suggest that risk of schizophrenia is associated additively with green space exposure and genetic liability, and provide no support for an environment-gene interaction between NDVI and schizophrenia.

Ambient PM2.5 (fine particulate matter) pollution in China has been greatly reduced in recent years, especially since the implementation of Clean Air Action in 2013. Analysis of variations in the pollution related health burden and the driving factors has important implications for the policymakers to further improve the health benefit of air pollution controls. Here we adopted an annual population distribution estimate, disaggregated by age structure, together with PM2.5 concentration and incidence data, to better estimate total PM2.5 attributable mortality considering the effect of changing population size and age structure. We then quantified the contribution of each factor to the total variation of PM2.5 attributable mortality both nationally and regionally. Our analysis showed that national PM2.5 attributable mortality generally increased from 861,140 (95% confidence interval: 525,860~1,161,550) in 2004 to 932,500 (546,590~1,300,160) in 2017. In most 2nd- and higher-tier cities in China, which stand for highly developed cities like Beijing, Shanghai, Guangzhou, etc., the PM2.5 health burden increased. Meanwhile, the decrease in city-level PM2.5 health burden mainly happened in 3rd- and lower-tier cities, where local developments were relatively smaller. The effect of exposure to PM2.5 on air pollution-related mortality has altered from aggravating to mitigating since 2012, and the abated PM2.5 exposure resulted in a reduction of 19.7% of PM2.5 attributable mortality between 2012 and 2017. However, such benefit was almost masked by the effect of the population aging, which brought an increase of 18.4% to the health burden. Our results implied that the increasing trend in China’s PM2.5 health burden since 2006 was halted after 2012 due to the pollution control policies, and population aging impeded it from declining further. For future air pollution control and public health affairs, growing cities in China should focus attention on old-age care, where the growth of attributable mortality might occur.

Landsat imagery is an unparalleled freely available data source that allows reconstructing horizontal and vertical urban form. This paper addresses the challenge of using Landsat data, particularly its 30m spatial resolution, for monitoring three-dimensional urban densification. 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 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. 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 other European cities with training data from Denmark, DeepLab also shows an advantage of 6 percentage points over RF for both the 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., Comment: Accepted manuscript including appendix (supplementary file)

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.

Assessments of the development of geography as a discipline, and studies of sub-disciplinary development within geography, have generally focused on the subject matter under study. Consideration has concentrated on topics, theories, methods, and paradigm shifts identified by analyses of published literature. There has been rather less interest in the spatialisation of the practice and performance of the discipline by people and institutions (though there have been exceptions) and equally little attention to the evidence provided by geographical conferences. We address these lacunae in current knowledge through a quantitative study of changing disciplinary endeavour in health geography as evidenced by participation in the International Medical Geography Symposia. For 35 years this biennial meeting has been the flagship conference for health and medical geographers. We have obtained, reviewed, and coded the proceedings of all 17 symposia, analysing the submitted papers by location of symposia, lead authorship, affiliation, and country of authorship. We investigate the globalisation of the sub-discipline and changes in key institutional involvement. Novel network analysis methods are used to identify changing linkages between research centres. What emerges is a complex sub-discipline driven by the changing neoliberal context of higher education and marked by both continuities and discontinuities in its practitioner networks.

Traditional exposure studies provide valuable insights for epidemiology, toxicology, and risk assessment. Throughout their lives, individuals are exposed to thousands of stressors in the environment which are not static, but influenced by environmental, temporal, spatial, and even socio-demographic factors. Existing exposure studies have usually focused on specific stressors for a constrained period of time. In response, the concept of the exposome has been raised, which is defined as the totality of exposure experienced from conception until death. The EU FP7-ENVIRONMENT research project HEALS was launched with the aim of incorporating a series of novel technologies, data analysis, and modelling tools to efficiently support exposome studies in Europe. The authors have developed a framework of modelling tools for estimating the long-term external exposure of selected population groups to multiple stressors through different pathways. As the starting point, the stressors, including electromagnetic fields (EMF) and ultraviolet light (UV) through dermal uptake, phthalates (DEHP, DIDP, and DINP) through inhalation, as well as chromium, mercury, and lead through food intake, have been selected. The simulation for multiple stressors has been realised by developing a probabilistic model that integrates the micro-environment approach, time-activity patterns, and a life course trajectory model. The methodology has been applied to a selected sample of subjects enrolled in the Italian Twin Registry (ITR). The results show that long-term exposures to multiple stressors are affected by factors including age, gender, geographical location, and education level. The methods developed in this paper extended the temporal and spatial scales of exposure modelling in Europe. Moreover, the application of our methods provided a novel approach and crucial input data for future work on environment-wide association studies.

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 PM2.5 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. Keywords: Air pollution, Public health, Trade, China

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 ...

Climate change mitigation policies aim to reduce climate change through reducing greenhouse gas (GHG) emissions whereas adaption policies seek to enable humans to live in a world with increasingly variable and more extreme climatic conditions. It is increasingly realised that enacting such policies will have unintended implications for public health, but there has been less focus on their implications for wellbeing. Wellbeing can be defined as a positive mental state which is influenced by living conditions. As part of URGENCHE, an EU funded project to identify health and wellbeing outcomes of city greenhouse gas emission reduction policies, a survey designed to measure these living conditions and levels of wellbeing in Kuopio, Finland was collected in December 2013. Kuopio was the northmost among seven cities in Europe and China studied. Generalised estimating equation modelling was used to determine which living conditions were associated with subjective wellbeing (measured through the WHO-5 Scale). Local greenspace and spending time in nature were associated with higher levels of wellbeing whereas cold housing and poor quality indoor air were associated with lower levels of wellbeing. Thus adaption policies to increase greenspace might, in addition to reducing heat island effects, have the co-benefit of increasing wellbeing and improving housing insulation., Highlights • Climate change policies may change wellbeing-associated living conditions in a city. • Local greenspace and nature immersion associated with higher levels of wellbeing. • Climate change adaption policy to increase greenspace may increase wellbeing. • Housing which is cold or has low quality indoor air associated with lower wellbeing. • A housing insulation policy may increase wellbeing if ventilation is adequate.

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 (PM2.5) 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 PM2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM2.5 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 PM2.5 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. Keywords: Air pollution, Fine particulate matter, Urbanization, Public health, China

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

Climate change vulnerabilities are key environmental and social determinants of health, particularly in sub-Saharan Africa where public health and other infrastructure are not yet geared towards counteracting the potential impacts of changing climates. Health-related climate change adaptation research for sub-Saharan Africa is limited and existing research is not effectively translated into practical advice for decision makers. A World University Network (WUN) collaboration project was started in 2016 to investigate climate change impacts on non-communicable diseases (NCDs). This interdisciplinary collaboration, established through the Healthy-Polis International Consortium for Urban Environmental Health and Sustainability focuses on the intersection of health, climate and sustainability within urban environments through innovative research methods, co-production of knowledge, capacity building and intervention. NCDs like cancers, asthma, diabetes, cardiovascular disease and mental health are on the increase in sub-Saharan African urban areas and can be further aggravated by climate change. If NCDs and the climate nexus are unaddressed, they will undermine achieving several of the Sustainable Development Goals (SDGs). Principally, we highlight climate-sensitive NCDs impacts on vulnerable populations, i.e. women, children, elderly, immune compromised and people with low socio-economic status, throughout their life course. We argue that interventions need to target disciplinary and sector ‘intersections’ for effective adaptation strategies. These interventions should be specifically linked to four SDGs, namely, SDG 3 (Good Health and Well-Being), SDG 7 (Affordable and Clean Energy), SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action). We conclude with capacity development and policy guidance to strengthen sub-Saharan African countries ability to address climate-sensitive NCDs.

The 2009 pandemic influenza virus caused the majority of the influenza A virus infections in China in 2009. It arrived in several Chinese cities from imported cases and then spread as people travelled domestically by all means of transportation, among which road traffic was the most commonly used for daily commuting. Spatial variation in socioeconomic status not only accelerates migration across regions but also partly induces the differences in epidemic processes and in responses to epidemics across regions. However, the roles of both road travel and socioeconomic factors have not received the attention they deserve. Here, we constructed a national highway network for and between 333 cities in mainland China and extracted epidemiological variables and socioeconomic factors for each city. We calculated classic centrality measures for each city in the network and proposed two new measures (SumRatio and Multicenter Distance). We evaluated the correlation between the centrality measures and epidemiological features and conducted a spatial autoregression to quantify the impacts of road network and socioeconomic factors during the outbreak. The results showed that epidemics had more significant relationships with both our new measures than the classic ones. Higher population density, higher per person income, larger SumRatio and Multicenter Distance, more hospitals and college students, and lower per person GDP were associated with higher cumulative incidence. Higher population density and number of slaughtered pigs were found to advance epidemic arrival time. Higher population density, more colleges and slaughtered pigs, and lower Multicenter Distance were associated with longer epidemic duration. In conclusion, road transport and socioeconomic status had significant impacts and should be considered for the prevention and control of future pandemics.

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

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. Expected final online publication date for the Annual Review of Public Health Volume 40 is April 1, 2019. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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.

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.

Exposure to ambient ozone (O3) 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 O3, across China in 2014, by applying the Global Burden of Diseases approach and AOT40 metric (i.e., above a threshold of O3 concentration of 40 ppb). Our results show that China's total premature deaths in 2014 due to COPD attributed to O3 exposure were 89,391 (CI95: 32,225–141,649) with spatial variation across provinces. O3 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 O3 pollution also suffered severe losses in yields of winter wheat and rice. Our results provide quantitative evidence of O3 induced impacts on both the public health and crop yields across Chinese provinces, which have important policy implications for the government to alleviate O3 pollution in addition to PM2.5 pollution that is currently being addressed.

Background and Objectives We investigated the demographic, social and clinical characteristics associated with employment status and income for people with multiple sclerosis (MS) in New Zealand (NZ). Methods The NZ National MS Prevalence study included all persons resident in NZ on census day 2006 diagnosed with MS (96.7% coverage). Factors associated with employment and income status among the working age population (25-64 years) were identified by linear regression. Results Over 90% of working age people with MS (n=1727) had a work history, but 54% were not working. Work loss occurred early in the disease course, and at low disability (P

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.

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.

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 (R2 = 0.9 at a rural background site, R2 = 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 PM2.5 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.

A diffusion process can be considered as the movement of linked events through space and time. Therefore, space-time locations of events are key to identify any diffusion process. However, previous clustering analysis methods have focused only on space-time proximity characteristics, neglecting the temporal lag of the movement of events. We argue that the temporal lag between events is a key to understand the process of diffusion movement. Using the temporal lag could help to clarify the types of close relationships. This study aims to develop a data exploration algorithm, namely the TrAcking Progression In Time And Space (TaPiTaS) algorithm, for understanding diffusion processes. Based on the spatial distance and temporal interval between cases, TaPiTaS detects sub-clusters, a group of events that have high probability of having common sources, identifies progression links, the relationships between sub-clusters, and tracks progression chains, the connected components of sub-clusters. Dengue Fever cases data was used as an illustrative case study. The location and temporal range of sub-clusters are presented, along with the progression links. TaPiTaS algorithm contributes a more detailed and in-depth understanding of the development of progression chains, namely the geographic diffusion process.

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.