Frank Popham

Effect of exposure to natural environment on health inequalities: an observational population study

BACKGROUND Studies have shown that exposure to the natural environment, or so-called green space, has an independent effect on health and health-related behaviours. We postulated that income-related inequality in health would be less pronounced in populations with greater exposure to green space, since access to such areas can modify pathways through which low socioeconomic position can lead to disease. METHODS We classified the population of England at younger than retirement age (n=40 813 236) into groups on the basis of income deprivation and exposure to green space. We obtained individual mortality records (n=366 348) to establish whether the association between income deprivation, all-cause mortality, and cause-specific mortality (circulatory disease, lung cancer, and intentional self-harm) in 2001-05, varied by exposure to green space measured in 2001, with control for potential confounding factors. We used stratified models to identify the nature of this variation. FINDINGS The association between income deprivation and mortality differed significantly across the groups of exposure to green space for mortality from all causes (p<0.0001) and circulatory disease (p=0.0212), but not from lung cancer or intentional self-harm. Health inequalities related to income deprivation in all-cause mortality and mortality from circulatory diseases were lower in populations living in the greenest areas. The incidence rate ratio (IRR) for all-cause mortality for the most income deprived quartile compared with the least deprived was 1.93 (95% CI 1.86-2.01) in the least green areas, whereas it was 1.43 (1.34-1.53) in the most green. For circulatory diseases, the IRR was 2.19 (2.04-2.34) in the least green areas and 1.54 (1.38-1.73) in the most green. There was no effect for causes of death unlikely to be affected by green space, such as lung cancer and intentional self-harm. INTERPRETATION Populations that are exposed to the greenest environments also have lowest levels of health inequality related to income deprivation. Physical environments that promote good health might be important to reduce socioeconomic health inequalities.

Greenspace, urbanity and health: relationships in England

Objectives: To determine the association between the percentage of greenspace in an area and the standardised rate of self-reported “not good” health, and to explore whether this association holds for areas exhibiting different combinations of urbanity and income deprivation. Design and setting: Cross-sectional, ecological study in England. Participants: All residents of England as at the 2001 Census. Main outcome measures: Age and sex standardised rate of reporting “not good” health status. Results: A higher proportion of greenspace in an area was generally associated with better population health. However, this association varied according to the combination of area income deprivation and urbanity. There was no significant association between greenspace and health in higher income suburban and higher income rural areas. In suburban lower income areas, a higher proportion of greenspace was associated with worse health. Conclusions: Although, in general, higher proportion of greenspace in an area is associated with better health, the association depends on the degree of urbanity and level of income deprivation in an area. One interpretation of these analyses is that quality as well as quantity of greenspace may be significant in determining health benefits.

Trends in population mental health before and after the 2008 recession: a repeat cross-sectional analysis of the 1991–2010 Health Surveys of England

Objective To assess short-term differences in population mental health before and after the 2008 recession and explore how and why these changes differ by gender, age and socio-economic position. Design Repeat cross-sectional analysis of survey data. Setting England. Participants Representative samples of the working age (25–64 years) general population participating in the Health Survey for England between 1991 and 2010 inclusive. Main outcome measures Prevalence of poor mental health (caseness) as measured by the general health questionnaire-12 (GHQ). Results Age–sex standardised prevalence of GHQ caseness increased from 13.7% (95% CI 12.9% to 14.5%) in 2008 to 16.4% (95% CI 14.9% to 17.9%) in 2009 and 15.5% (95% CI 14.4% to 16.7%) in 2010. Women had a consistently greater prevalence since 1991 until the current recession. However, compared to 2008, men experienced an increase in age-adjusted caseness of 5.1% (95% CI 2.6% to 7.6%, p<0.001) in 2009 and 3% (95% CI 1.2% to 4.9%, p=0.001) in 2010, while no statistically significant changes were seen in women. Adjustment for differences in employment status and education level did not account for the observed increase in men nor did they explain the differential gender patterning. Over the last decade, socio-economic inequalities showed a tendency to increase but no clear evidence for an increase in inequalities associated with the recession was found. Similarly, no evidence was found for a differential effect between age groups. Conclusions Population mental health in men has deteriorated within 2 years of the onset of the current recession. These changes, and their patterning by gender, could not be accounted for by differences in employment status. Further work is needed to monitor recessionary impacts on health inequalities in response to ongoing labour market and social policy changes.

Leisure time exercise and personal circumstances in the working age population: longitudinal analysis of the British household panel survey

Objectives: Investigate the impact of social, economic, and family circumstances on participation in weekly leisure time exercise. Design: Longitudinal regression analysis of the British household panel survey. Participants: 9473 people (4521 men and 4952 women) giving 27 881 person years of responses across eight years and four survey waves. Main results: There was considerable variation among people in regular exercise participation over time. Having children was associated with a reduced likelihood of exercise for both men and women, although there were sex differences in this association according to the age of the youngest child. For both men and women working long hours was associated with a reduced likelihood of exercise, as was having a lower grade job. Retired men and women were more likely to exercise, as were those who attended a fee paying school. There was no strong independent association between household income and exercise. Conclusions: For most people, participation in leisure time exercise “comes and goes” rather than being something they always or never do. Those with time pressures from work or domestic life are less likely to participate in leisure time physical activity. There are important sex differences in the impact of having children, with women experiencing longer term detrimental effects. Working long hours reduces leisure time exercise participation. Opportunities for physical activity as part of our daily working routines should be increased.

DataSHIELD: taking the analysis to the data, not the data to the analysis

Background: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK’s proposed ‘care.data’ initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Methods: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Results: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. Conclusions: DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property—the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis.

Rising premature mortality in the UK’s persistently deprived areas: Only a Scottish phenomenon?

In the international literature, many studies find strong relationships between area-based measures of deprivation and mortality. In the U.K., mortality rates have generally fallen in recent decades but the life expectancy gap between the most and least deprived areas has widened, with a number of Scottish studies highlighting increased mortality rates in deprived areas especially in Glasgow. However, these studies relate health outcomes at different time points against period-specific measures of deprivation which may not be comparable over time. Using longitudinal deprivation measures where levels of area deprivation are made comparable over time, a recent study demonstrated how levels of mortality change in relation to changing or persistent levels of (non-) deprivation over time. The results showed that areas which were persistently deprived in Scotland experienced a rise in premature mortality rates by 9.5% between 1981 and 2001. Here, focussing on persistently deprived areas we extended the coverage to the whole of the U.K. to assess whether, between 1991 and 2001, rising premature mortality rates in persistently deprived areas are a Scottish only phenomenon or whether similar patterns are evident elsewhere and for men and women separately. We found that male premature mortality rates rose by over 14% in Scotland over the 10-year period between the early 1990s and 2000s in persistently deprived areas. We found no significant rise in mortality elsewhere in the U.K. and that the rise among men in Scotland was driven by results for Glasgow where mortality rates rose by over 15% during the decade. Our analyses demonstrate the importance of identifying areas experiencing persistent poverty. These results justify even more of a public health focus on Glasgow and further work is needed to understand the demographic factors, such as health selective migration, immobility and population residualisation, which may contribute to these findings.

Are health inequalities really not the smallest in the Nordic welfare states? A comparison of mortality inequality in 37 countries

Background Research comparing mortality by socioeconomic status has found that inequalities are not the smallest in the Nordic countries. This is in contrast to expectations given these countries’ policy focus on equity. An alternative way of studying inequality has been little used to compare inequalities across welfare states and may yield a different conclusion. Methods We used average life expectancy lost per death as a measure of total inequality in mortality derived from death rates from the Human Mortality Database for 37 countries in 2006 that we grouped by welfare state type. We constructed a theoretical ‘lowest mortality comparator country’ to study, by age, why countries were not achieving the smallest inequality and the highest life expectancy. We also studied life expectancy as there is an important correlation between it and inequality. Results On average, Nordic countries had the highest life expectancy and smallest inequalities for men but not women. For both men and women, Nordic countries had particularly low younger age mortality contributing to smaller inequality and higher life expectancy. Although older age mortality in the Nordic countries is not the smallest. There was variation within Nordic countries with Sweden, Iceland and Norway having higher life expectancy and smaller inequalities than Denmark and Finland (for men). Conclusions Our analysis suggests that the Nordic countries do have the smallest inequalities in mortality for men and for younger age groups. However, this is not the case for women. Reducing premature mortality among older age groups would increase life expectancy and reduce inequality further in Nordic countries.

Workplace Change and Employee Mental Health: Results from a Longitudinal Study

This study is intended to improve understanding of the impact of workplace change on employee mental health and well-being. We construct and test a comprehensive measure of organizational change, which is then applied in a prospective longitudinal study of nearly 5400 employees in six UK National Health Service Trusts. Self-rated mental health was assessed using the 12-item version of the General Health Questionnaire (GHQ). Just under a quarter of the sample were at increased risk of psychiatric morbidity (‘cases’). After controlling for a wide range of personal characteristics and work variables, it was found that respondents who reported an increase in the amount of work over the previous year were more likely to be classed as GHQ cases, whereas increased training and promotion and improved job security had a beneficial effect on employee mental health (less likelihood of being GHQ cases). Quantity or degree of change showed a somewhat ambiguous relationship with GHQ status. Our findings challenge the assumption that change will necessarily have an adverse effect on health, indicating areas, such as promotion and development, where a positive impact might be anticipated.

Assessing psychological well-being: A holistic investigation of NHS employees

A substantial body of research has investigated the effects of work on the psychological well-being of employees. However, there has been little assessment of the ways in which workplace factors (such as job demands, working conditions, inter-personal relations and workplace change) interact with personal factors (such as work-life balance, family circumstances, key personality traits or demographic characteristics) to affect psychological health. This article reports findings from a study which aimed to construct and test a comprehensive model of the influences on employee well-being within the UK National Health Service (NHS). The results show that psychological well-being is influenced by a complex array of personal, environmental and work factors. A key finding is that there are clear associations between workplace change and well-being and between work-life (im)balance and well-being. These effects appear to be independent of one another and therefore require separate attention from managers and employers.

Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research

Population health interventions are essential to reduce health inequalities and tackle other public health priorities, but they are not always amenable to experimental manipulation. Natural experiment (NE) approaches are attracting growing interest as a way of providing evidence in such circumstances. One key challenge in evaluating NEs is selective exposure to the intervention. Studies should be based on a clear theoretical understanding of the processes that determine exposure. Even if the observed effects are large and rapidly follow implementation, confidence in attributing these effects to the intervention can be improved by carefully considering alternative explanations. Causal inference can be strengthened by including additional design features alongside the principal method of effect estimation. NE studies often rely on existing (including routinely collected) data. Investment in such data sources and the infrastructure for linking exposure and outcome data is essential if the potential for such studies to inform decision making is to be realized.