Association between air pollution exposure and mental health service use among individuals with first presentations of psychotic and mood disorders: retrospective cohort study.

BACKGROUND: Growing evidence suggests that air pollution exposure may adversely affect the brain and increase risk for psychiatric disorders such as schizophrenia and depression. However, little is known about the potential role of air pollution in severity and relapse following illness onset. AIMS: To examine the longitudinal association between residential air pollution exposure and mental health service use (an indicator of illness severity and relapse) among individuals with first presentations of psychotic and mood disorders. METHOD: We identified individuals aged ≥15 years who had first contact with the South London and Maudsley NHS Foundation Trust for psychotic and mood disorders in 2008-2012 (n = 13 887). High-resolution (20 × 20 m) estimates of nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM2.5 and PM10) levels in ambient air were linked to residential addresses. In-patient days and community mental health service (CMHS) events were recorded over 1-year and 7-year follow-up periods. RESULTS: Following covariate adjustment, interquartile range increases in NO2, NOx and PM2.5 were associated with 18% (95% CI 5-34%), 18% (95% CI 5-34%) and 11% (95% CI 3-19%) increased risk for in-patient days after 1 year. Similarly, interquartile range increases in NO2, NOx, PM2.5 and PM10 were associated with 32% (95% CI 25-38%), 31% (95% CI 24-37%), 7% (95% CI 4-11%) and 9% (95% CI 5-14%) increased risk for CMHS events after 1 year. Associations persisted after 7 years. CONCLUSIONS: Residential air pollution exposure is associated with increased mental health service use among people recently diagnosed with psychotic and mood disorders. Assuming causality, interventions to reduce air pollution exposure could improve mental health prognoses and reduce healthcare costs.

Mental health consequences of urban air pollution: prospective population-based longitudinal survey.

PURPOSE: The World Health Organisation (WHO) recently ranked air pollution as the major environmental cause of premature death. However, the significant potential health and societal costs of poor mental health in relation to air quality are not represented in the WHO report due to limited evidence. We aimed to test the hypothesis that long-term exposure to air pollution is associated with poor mental health. METHODS: A prospective longitudinal population-based mental health survey was conducted of 1698 adults living in 1075 households in South East London, from 2008 to 2013. High-resolution quarterly average air pollution concentrations of nitrogen dioxide (NO2) and oxides (NOx), ozone (O3), particulate matter with an aerodynamic diameter < 10 µm (PM10) and < 2.5 µm (PM2.5) were linked to the home addresses of the study participants. Associations with mental health were analysed with the use of multilevel generalised linear models, after adjusting for large number of confounders, including the individuals' socioeconomic position and exposure to road-traffic noise. RESULTS: We found robust evidence for interquartile range increases in PM2.5, NOx and NO2 to be associated with 18-39% increased odds of common mental disorders, 19-30% increased odds of poor physical symptoms and 33% of psychotic experiences only for PM10. These longitudinal associations were more pronounced in the subset of non-movers for NO2 and NOx. CONCLUSIONS: The findings suggest that traffic-related air pollution is adversely affecting mental health. Whilst causation cannot be proved, this work suggests substantial morbidity from mental disorders could be avoided with improved air quality.

The mortality rates and the space-time patterns of John Snow's cholera epidemic map.

BACKGROUND: Snow's work on the Broad Street map is widely known as a pioneering example of spatial epidemiology. It lacks, however, two significant attributes required in contemporary analyses of disease incidence: population at risk and the progression of the epidemic over time. Despite this has been repeatedly suggested in the literature, no systematic investigation of these two aspects was previously carried out. Using a series of historical documents, this study constructs own data to revisit Snow's study to examine the mortality rate at each street location and the space-time pattern of the cholera outbreak. METHODS: This study brings together records from a series of historical documents, and prepares own data on the estimated number of residents at each house location as well as the space-time data of the victims, and these are processed in GIS to facilitate the spatial-temporal analysis. Mortality rates and the space-time pattern in the victims' records are explored using Kernel Density Estimation and network-based Scan Statistic, a recently developed method that detects significant concentrations of records such as the date and place of victims with respect to their distance from others along the street network. The results are visualised in a map form using a GIS platform. RESULTS: Data on mortality rates and space-time distribution of the victims were collected from various sources and were successfully merged and digitised, thus allowing the production of new map outputs and new interpretation of the 1854 cholera outbreak in London, covering more cases than Snow's original report and also adding new insights into their space-time distribution. They confirmed that areas in the immediate vicinity of the Broad Street pump indeed suffered from excessively high mortality rates, which has been suspected for the past 160 years but remained unconfirmed. No distinctive pattern was found in the space-time distribution of victims' locations. CONCLUSIONS: The high mortality rates identified around the Broad Street pump are consistent with Snow's theory about cholera being transmitted through contaminated water. The absence of a clear space-time pattern also indicates the water-bourne, rather than the then popular belief of air bourne, nature of cholera. The GIS data constructed in this study has an academic value and would cater for further research on Snow's map.

Change in alcohol outlet density and alcohol-related harm to population health (CHALICE).

BACKGROUND: Excess alcohol consumption has serious adverse effects on health and violence-related harm. In the UK around 37% of men and 29% of women drink to excess and 20% and 13% report binge drinking. The potential impact on population health from a reduction in consumption is considerable. One proposed method to reduce consumption is to reduce availability through controls on alcohol outlet density. In this study we investigate the impact of a change in the density of alcohol outlets on alcohol consumption and alcohol-related harms to health in the community. METHODS/DESIGN: A natural experiment of the effect of change in outlet density between 2005-09, in Wales, UK; population 2.4 million aged 16 years and over. Data on outlets are held by the 22 local authorities in Wales under The Licensing Act 2003. The study outcomes are change in (1) alcohol consumption using data from annual Welsh Health Surveys, (2) alcohol-related hospital admissions using the Patient Episode Database for Wales, (3) Accident & Emergency department attendances between midnight-6am, and (4) alcohol-related violent crime against the person, using Police data. The data will be anonymously record-linked within the Secure Anonymised Information Linkage Databank at individual and 2001 Census Lower Super Output Area levels. New methods of network analysis will be used to estimate outlet density. Longitudinal statistical analysis will use (1) multilevel ordinal models of consumption and logistic models of admissions and Accident & Emergency attendance as a function of change in individual outlet exposure, adjusting for confounding variables, and (2) spatial models of the change in counts/rates of each outcome measure and outlet density. We will assess the impact on health inequalities and will correct for population migration. DISCUSSION: This inter-disciplinary study requires expertise in epidemiology and public health, health informatics, medical statistics, geographical information science, and research into alcohol-related violence. Information governance requirements for the use of record-linked data have been approved together with formal data access agreements for the use of the Welsh Health Survey and Police data. The dissemination strategy will include policy makers in national and local government. Public engagement will be through the Clinical Research Collaboration-Cymru "Involving People" network, which will provide input into the implementation of the research.

Community/campus partnership: tailoring geographic information systems for perinatal health planning.

BACKGROUND: Geographic information systems (GIS) are seen as potentially important additions to traditional methods of studying risk factors in maternal and child health, but little is written on actual GIS use by communities. This article describes how one community-university collaboration used GIS for perinatal planning. OBJECTIVE: The objective was to determine whether utilizing GIS could help a community to identify risk and develop potential interventions to address perinatal health problems. METHODS: We tested the use of GIS over a 9-month period, using community-based participatory research (CBPR) methods. Diffusion of innovations (DOI) theory guided this work. RESULTS: This collaboration resulted in the development of a perinatal GIS model that helped community members to decide where to focus interventions and in continued use of GIS for planning. CONCLUSION: Close collaboration early in the planning process, coupled with the incorporation of DOI theory, is necessary for communities to use GIS to plan perinatal interventions.