Centennial Records of Microplastics in Lake Cores in Huguangyan Maar Lake, China.

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

The complexities of suicide: a multilevel survival analysis examining individual, familial and neighbourhood determinants of suicide risk using Danish register-based data.

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.

Sediment core records and impact factors of polycyclic aromatic hydrocarbons in Chinese lakes.

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.

Assessing the association between overcrowding and human physiological stress response in different urban contexts: a case study in Salzburg, Austria.

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.

Perspectives on environment and health research in Denmark.

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

The latitude gradient for multiple sclerosis prevalence is established in the early life course.

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.

Associations between growing up in natural environments and subsequent psychiatric disorders in Denmark.

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.

Influence of residential land cover on childhood allergic and respiratory symptoms and diseases: Evidence from 9 European cohorts.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Examining the Effect of Geographic Region of Residence on Childhood Malnutrition in Uganda.

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.

Earth Observation: Investigating Noncommunicable Diseases from Space.

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.

Lifelong exposure to multiple stressors through different environmental pathways for European populations.

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.

Health burdens of ambient PM2.5 pollution across Chinese cities during 2006-2015.

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 (PM2.5) 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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 pollution levels due to rapid development. Significant differences in PM2.5-induced premature deaths indicated the need for specific policies to mitigate the health burden of air pollution in different types of Chinese cities.

Developing a data-driven spatial approach to assessment of neighbourhood influences on the spatial distribution of myocardial infarction.

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.

Public health impacts of city policies to reduce climate change: findings from the URGENCHE EU-China project.

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.

Building-related health impacts in European and Chinese cities: a scalable assessment method.

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.

Beyond greenspace: an ecological study of population general health and indicators of natural environment type and quality.

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.

Modelling the spatial risk pattern of dementia in Denmark using residential location data: A registry-based national cohort.

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

Changing Neighborhood Income Deprivation Over Time, Moving in Childhood, and Adult Risk of Depression.

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

The impact of area-level socioeconomic status in childhood on mental health in adolescence and adulthood: A prospective birth cohort study in Aotearoa New Zealand.

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.

Exposure to air pollution and risk of respiratory tract infections in the adult Danish population-a nationwide study.

OBJECTIVES: The association between air pollution and risk of respiratory tract infection (RTI) in adults needs to be clarified in settings with low to moderate levels of air pollution. We investigated this in the Danish population between 2004 and 2016. METHODS: We included 3 653 490 persons aged 18-64 years in a nested case-control study. Exposure was defined as the average daily concentration at the individual's residential address of CO, NOX, NO2, O3, SO2, NH3, PPM2.5, black carbon, organic carbon, mineral dust, sea salt, secondary inorganic aerosols, SO42-, NO3-, NH4+, secondary organic aerosols, PM2.5, and PM10 during a 3-month exposure window. RTIs were defined by hospitalization for RTIs. Incidence rate ratios (IRRs) and 95% CIs were estimated comparing highest with lowest decile of exposure using conditional logistic regression models. RESULTS: In total, 188 439 incident cases of RTI were identified. Exposure to most air pollutants was positively associated with risk of RTI. For example, NO2 showed an IRR of 1.52 (CI: 1.48-1.55), and PM2.5 showed an IRR of 1.45 (CI: 1.40-1.50). In contrast, exposure to sea salt, PM10, NH3, and O3 was negatively associated with a risk of RTIs. DISCUSSION: In this nationwide study comprising adults, exposure to air pollution was associated with risk of RTIs and subgroups hereof. Sea salt, PM10, NH3, and O3 may be proxies for rural areas, as the levels of these species in Denmark are higher near the western coastlines and/or in rural areas with fewer combustion sources.