This Environment and Human Health project aims to develop a health-based summary measure of multiple physical environmental deprivation for the UK, akin to the measures of multiple socioeconomic deprivation that are widely used in epidemiology. Here we describe the first stage of the project, in which we aimed to identify health-relevant dimensions of physical environmental deprivation and acquire suitable environmental datasets to represent population exposure to these dimensions at the small-area level. We present the results of this process: an evidence-based list of environmental dimensions with population health relevance for the UK, and the spatial datasets we obtained and processed to represent these dimensions. This stage laid the foundations for the rest of the project, which will be reported elsewhere.
Recent work has identified growing geographical inequalities in health between deprived and nondeprived areas in a number of countries. Despite the plethora of studies monitoring these trends, the explanations for this growing spatial divide remain unclear. This lack of clarity has been a hindrance to the implementation of strategies by policymakers to reduce health inequalities. One explanation for the noted spatial differences in health is that geographical access to a range of community resources, such as health care facilities, supermarkets, and recreational amenities, is lower in deprived areas. However, the evidence base for this explanation is low. In our previous work we noted a strong relationship at the national level between community resource accessibility and social deprivation, with access tending to be better in more deprived neighbourhoods. Other research suggests that the relationship between community resources varies at a subnational scale. Here, we consider whether the relationship of better access to community resources in more deprived areas persists for all regions of New Zealand, urban and rural. Using geographical information systems, we calculate levels of geographical access to sixteen types of community resources in 38350 small census areas across the country and, using an index of deprivation, examine whether access varies between deprived and nondeprived areas of the country. The results suggest that access to community resources in New Zealand is to some extent context specific. In urban areas, access is better in more deprived neighbourhoods, and the same is true of intermediate urban/rural areas although the gradient is considerably more pronounced. However, for rural areas, the relationship between com- munity resource access and deprivation is more mixed, with access to the majority of resources being worse in more deprived areas. Similarly, there are regional variations in the relationship between deprivation and community resource access. These results challenge some aspects of neomaterial interpretations of geographical inequalities in health.
Exposure to air pollution is associated with a range of diseases. Biomarkers derived from DNA methylation (DNAm) offer potential mechanistic insights into human health differences, connecting disease pathogenesis and biological ageing. However, little is known about sensitive periods during the life course where air pollution might have a stronger impact on DNAm, or whether effects accumulate over time. We examined associations between air pollution exposure across the life course and DNAm-based markers of biological ageing.Data were derived from the Scotland-based Lothian Birth Cohort 1936. Participants' residential history was linked to annual levels of fine particle (PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) around 1935, 1950, 1970, 1980, 1990, and 2001; pollutant concentrations were estimated using the EMEP4UK atmospheric chemistry transport model. Blood samples were obtained between ages of 70 and 80 years, and Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, DNAmGrimAge, and DNAm telomere length (DNAmTL) were computed. We applied the structured life-course modelling approach: least angle regression identified best-fit life-course models for a composite measure of air pollution (air quality index [AQI]), and mixed-effects regression estimated selected models for AQI and single pollutants.We included 525 individuals with 1782 observations. In the total sample, increased air pollution around 1970 was associated with higher epigenetic age (AQI: b = 0.322 year, 95 %CI: 0.088, 0.555) measured with Horvath DNAmAge in late adulthood. We found shorter DNAmTL among males with higher air pollution around 1980 (AQI: b = -0.015 kilobase, 95 %CI: -0.027, -0.004) and among females with higher exposure around 1935 (AQI: b = -0.017 kilobase, 95 %CI: -0.028, -0.006). Findings were more consistent for the pollutants PM2.5, SO2 and NO2.We tested the life-course relationship between air pollution and DNAm-based biomarkers. Air pollution around birth and in young-to-middle adulthood is linked to accelerated epigenetic ageing and telomere-associated ageing in later life.
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A multitude of studies have demonstrated that individual circumstances throughout life influence subsequent health and well‐being outcomes. The life‐course perspective emphasises that health is affected by the accumulation of social and economic (dis)advantages over an individual's life but, importantly, also that there can be critical periods where the effects of exposure can be greater. Yet few researchers have applied a life‐course perspective to the study of health and place, which has resulted in a partial understanding of the dynamics of person–health–place relations. By explicitly recognising that places are spatial‐temporal products, and applying a novel longitudinal life‐course approach, this study examines the opportunities for incorporating aspects of place into a life‐course framework. The focus is the influence of neighbourhood social deprivation and provision of local green space on mental health (particularly anxiety and depression). Historical and contemporary place‐based information from the Lothian region of Scotland is combined with data from a cohort of individuals born in 1936 (the Lothian Birth Cohort 1936) to consider the influence of these environmental factors over the life course on mental health outcomes later in life. The results establish the utility of the life course of place approach, and demonstrate how this concept can be operationalised using historical data sources. The findings suggest that, after adjustment, residing in the most socially disadvantaged neighbourhoods in childhood was detrimental to mental health outcomes at age 70. Further, green space provision in early life environments is related to mental health outcomes in later life, but any effect may be restricted to those residing in socially disadvantaged places, and dependent on the specific mental health outcome being considered. The findings emphasise the potential of the life course of place approach for enhancing the evidence base considering the relationships between health and place.
Abstract The ability to manage ill health and care needs might be affected by who a person lives with. This study examined how the risk of unplanned hospitalisation and transition to living in a care home varied according to household size and co-resident multimorbidity. Here we show results from a cohort study using Welsh nationwide linked healthcare and census data, that employed multilevel multistate models to account for the competing risk of death and clustering within households. The highest rates of unplanned hospitalisation and care home transition were in those living alone. Event rates were lower in all shared households and lowest when co-residents did not have multimorbidity. These differences were more substantial for care home transition. Therefore, living alone or with co-residents with multimorbidity poses additional risk for unplanned hospitalisation and care home transition beyond an individual’s sociodemographic and health characteristics. Understanding the mechanisms behind these associations is necessary to inform targeted intervention strategies.
The exposure to green space in early life may support better cognitive aging in later life. However, this exposure is usually measured using the residential location alone. This disregards the exposure to green spaces in places frequented during daily activities (i.e., the ‘activity space’). Overlooking the multiple locations visited by an individual over the course of a day is likely to result in poor estimation of the environmental exposure and therefore exacerbates the contextual uncertainty. A child’s activity space is influenced by factors including age, sex, and the parental perception of the neighborhood. This paper develops indices of park availability based on individuals’ activity spaces (home, school, and the optimal route to school). These measures are used to examine whether park availability in childhood is related to cognitive change much later in life. Multi-level linear models, including random effects for schools, were used to test the association between park availability during childhood and adolescence and cognitive aging (age 70 to 76) in the Lothian Birth Cohort 1936 participants (N = 281). To test for the effect modification, these models were stratified by sex and road traffic accident (RTA) density. Park availability during adolescence was associated with better cognitive aging at a concurrently low RTA density (β = 0.98, 95% CI: 0.36 to 1.60), but not when the RTA density was higher (β = 0.22, 95% CI: −0.07 to 0.51). Green space exposure during early life may be important for optimal cognitive aging; this should be evidenced using activity space-based measures within a life-course perspective.
Research has indicated that people moving towards neighbourhoods with disadvantaged socio-economic status have poor health, in particular mental health, but the reasons for this are unclear. This study aims to assess why people moving towards more socio-economically deprived areas have poor mental health. It focuses upon the role of difficult life events that may both trigger moves and damage mental health. This study investigates how mental health and socio-spatial patterns of mobility vary between people moving following difficult life events and for other reasons.Longitudinal analysis of British Household Panel Survey data describing adults' moves between annual survey waves, pooled over ten years, 1996-2006 (N=122,892 observations). Respondents were defined as 'difficult life event movers' if they had experienced relationship breakdown, housing eviction/repossession, or job loss between waves. Respondents were categorised as moving to more or less deprived quintiles using their Census Area Statistic residential ward Carstairs score. Mental health was indicated by self-reported mental health problems. Binary logistic regression models of weighted data were adjusted for age, sex, education and social class.The migration rate over one year was 8.5%; 14.1% of movers had experienced a difficult life event during this time period. Adjusted regression model odds of mental health problems among difficult life event movers were 1.67 (95% CI 1.35-2.07) relative to other movers. Odds of difficult life events movers, compared to other movers, moving to a less deprived area, relative to an area with a similar level of deprivation, were 0.70 (95% CI 0.58-0.84). Odds of mental health problems among difficult life event movers relocating to more deprived areas were highly elevated at 2.40 (95% CI 1.63-3.53), relative to stayers.Difficult life events may influence health selective patterns of migration and socio-spatial trajectories, reducing moves to less deprived neighbourhoods among people with mental illness.
Socioeconomic deprivation accounts for much of the spatial inequality in health in the UK, but a significant proportion remains unexplained. It is highly likely that the physical environment is a key factor in this unexplained variation. The role of the socioeconomic environment in health inequalities has been studied using small-area measures of multiple socioeconomic deprivation that capture the burden of socioeconomic adversity. Although similar composite measures of the physical environment would greatly assist investigations of environmental determinants of health no such measures are available. In this study we developed two small-area measures of health-related multiple physical environmental deprivation for the UK. A thorough review and evidence appraisal process was used to identify health-relevant dimensions of physical environmental deprivation. As a result we selected both health-detrimental (air pollution, cold climate, industrial facilities) and health-beneficial (ultraviolet radiation and green space) dimensions. Datasets describing each of the selected dimensions were acquired, and rendered to UK Census Area Statistics wards ( n = 10 654, average population = 5518). We developed two summary measures: the multiple environmental deprivation index (MEDIx) and classification (MEDClass). MEDIx, on an ordinal scale, can be used to distinguish areas exposed to greater or lesser environmental deprivation. MEDClass groups areas with similar environmental characteristics and will be useful for exploring health effects of specific types of environment. Mapping these measures demonstrated a wide variation in physical environmental deprivation across the UK. MEDIx revealed greater environmental deprivation in urban and industrial areas, and at more northerly latitudes. Although created using a different methodology MEDClass also differentiated these environmental types. We concluded that it is possible to capture and characterise multiple attributes of health-related physical environmental deprivation in the UK, at a small area level. The measures we developed offer opportunities to researchers and policy makers for developing our understanding of the role of exposure to multiple dimensions of physical environmental deprivation on health outcomes.
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