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.

Evidence of economic development revealed in centennial scale sedimentary records of organic pollutants in Huguangyan Marr Lake.

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

Early-life air pollution and green space exposures as determinants of stunting among children under age five in Sub-Saharan Africa.

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

Higher depression risks in medium- than in high-density urban form across Denmark.

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.

Multilevel interactions between family and neighbourhood socioeconomic indices in childhood and later risks of self-harm and violent criminality in Denmark: a national cohort study.

BACKGROUND: A socioeconomically disadvantaged childhood has been associated with elevated self-harm and violent criminality risks during adolescence and young adulthood. However, whether these risks are modified by a neighbourhood's socioeconomic profile is unclear. The aim of our study was to compare risks among disadvantaged young people residing in deprived areas versus risks among similarly disadvantaged individuals residing in affluent areas. METHODS: We did a national cohort study, using Danish interlinked national registers, from which we delineated a longitudinal cohort of people born in Denmark between Jan 1, 1981, and Dec 31, 2001, with two Danish-born parents, who were alive and residing in the country when they were aged 15 years, who were followed up for a hospital-treated self-harm episode or violent crime conviction. A neighbourhood affluence indicator was derived based on nationwide income quartiles, with parental income and educational attainment indicating the socioeconomic position of each cohort member's family. Bayesian multilevel survival analyses were done to examine the moderating influences of neighbourhood affluence on associations between family socioeconomic position and sex-specific risks for the two adverse outcomes. FINDINGS: 1 084 047 cohort members were followed up for 12·8 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. INTERPRETATION: Even in a high-income European country with comprehensive social welfare and low levels of poverty and inequality, individuals residing in affluent neighbourhoods have lower risks of self-harm and violent criminality compared with individuals residing in deprived neighbourhoods. More research is needed to explore the potential of neighbourhood policies and interventions to reduce the harmful effects of growing up in socioeconomically deprived circumstances on later risk of self-harm and violent crime convictions. FUNDING: European Research Council, Lundbeck Foundation Initiative for Integrative Psychiatric Research, and BERTHA, the Danish Big Data Centre for Environment and Health funded by the Novo Nordisk Foundation Challenge Programme.

Multilevel and spatial analyses of childhood malnutrition in Uganda: examining individual and contextual factors.

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

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.

Residential mobility: Towards progress in mobility health research.

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.

How do moving and other major life events impact mental health? A longitudinal analysis of UK children.

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.

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.

Open-Source web-based Geographical Information System for health exposure assessment.

This paper presents the design and development of an open source web-based Geographical Information System allowing users to visualise, customise and interact with spatial data within their web browser. The developed application shows that by using solely Open Source software it was possible to develop a customisable web based GIS application that provides functions necessary to convey health and environmental data to experts and non-experts alike without the requirement of proprietary software.

Uncertainty in epidemiology and health risk and impact assessment.

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

The influence of road curvature on fatal crashes in New Zealand.

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

Neighbourhood effects on health: does it matter where you draw the boundaries?

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