What is the relationship between changes in the size of economies and mortality derived population health measures in high income countries: A causal systematic review.

CONTEXT: The economy has been long recognised as an important determinant of population health and a healthy population is considered important for economic prosperity. AIM: To systematically review the evidence for a causal bidirectional relationship between aggregate economic activity (AEA) at national level for High Income Countries, and 1) population health (using mortality and life expectancy rates as indicators) and 2) inequalities in population health. METHODS: We undertook a systematic review of quantitative studies considering the relationship between AEA (GDP, GNI, GNP or recession) and population health (mortality or life expectancy) and inequalities for High Income Countries. We searched eight databases and grey literature. Study quality was assessed using an adapted version of the Effective Public Health Practice Project's Quality Assessment tool. We used Gordis' adaptation of the Bradford-Hill framework to assess causality. The studies were synthesised using Cochrane recommended alternative methods to meta-analysis and reported following the Synthesis without Meta-analysis (SWiM) guidelines. We assessed the certainty of the evidence base in line with GRADE principles. FINDINGS: Of 21,099 records screened, 51 articles were included in our analysis. There was no evidence for a consistent causal relationship (either beneficial or harmful) of changes in AEA leading to changes in population health (as indicated by mortality or life expectancy). There was evidence suggesting that better population health is causally related to greater AEA, but with low certainty. There was insufficient evidence to consider the causal impact of AEA on health inequalities or vice versa. CONCLUSIONS: Changes in AEA in High Income Countries did not have a consistently beneficial or harmful causal relationship with health, suggesting that impacts observed may be contextually contingent. We tentatively suggest that improving population health might be important for economic prosperity. Whether or not AEA and health inequalities are causally linked is yet to be established.

The changing shape of general practice in Scotland: the rise of the 'megapractice'.

OBJECTIVES: To describe the trends in the nature of general practices in Scotland between 2014/15 and 2023. STUDY DESIGN: Descriptive ecological study. METHODS: We obtained data from Public Health Scotland and used general practitioner (GP) practice codes, practice names, and the General Medical Council (GMC) numbers of their listed GPs to describe trends in practice characteristics and to identify individual practices that were likely to be operating as a single entity. RESULTS: Defining practice entities is difficult because different GP practice codes are often retained when GPs are performing across multiple practices. If GP practice codes alone are used, the median practice list size increased from 5094 to 5881, and the mean from 5588 to 6289, between 2013/14 and 2020/21. There was one outlier practice that grew to have over 45,000 patients registered by 2020/21. However, this underestimates the extent of this new mega-practice phenomenon. Using the GMC numbers of GPs listed as performers to identify where the same GPs are working across multiple GP practice codes, we identified a series of mega-practices that span across health board areas and which have experienced a dramatic increase in their list size (with the two largest having list sizes of over 101,000 and 77,000 patients, respectively). CONCLUSIONS: Further research is needed to better understand: how mega-practices provide services and whether this differs from other practices; where financial rewards accumulate within mega-practices; differences in staffing between mega-practices and other models; and the impacts mega-practices have on the quality and continuity of care and on health and inequality outcomes.

Is Austerity Responsible for the Stalled Mortality Trends Across Many High-Income Countries? A Systematic Review.

This article systematically reviews evidence evaluating whether macroeconomic austerity policies impact mortality, reviewing high-income country data compiled through systematic searches of nine databases and gray literature using pre-specified methods (PROSPERO registration: CRD42020226609). Eligible studies were quantitatively assessed to determine austerity's impact on mortality. Two reviewers independently assessed eligibility and risk of bias using ROBINS-I. Synthesis without meta-analysis was conducted due to heterogeneity. Certainty of evidence was assessed using the GRADE framework. Of 5,720 studies screened, seven were included, with harmful effects of austerity policies demonstrated in six, and no effect in one. Consistent harmful impacts of austerity were demonstrated for all-cause mortality, life expectancy, and cause-specific mortality across studies and different austerity measures. Excess mortality was higher in countries with greater exposure to austerity. Certainty of evidence was low. Risk of bias was moderate to critical. A typical austerity dose was associated with 74,090 [-40,632, 188,792] and 115,385 [26,324, 204,446] additional deaths per year. Austerity policies are consistently associated with adverse mortality outcomes, but the magnitude of this effect remains uncertain and may depend on how austerity is implemented (e.g., balance between public spending reductions or tax rises, and distributional consequences). Policymakers should be aware of potential harmful health effects of austerity policies.

Health Economics in a World of Uneconomic Growth.

Multiple, accelerating and interacting ecological crises are increasingly understood as constituting a major threat to human health and well-being. Unconstrained economic growth is strongly implicated in these growing crises, and it has been argued that this growth has now become "uneconomic growth", which is a situation where the size of the economy is still expanding, but this expansion is causing more harm than benefit. This article summarises the multiple pathways by which uneconomic growth can be expected to harm human health. It describes how health care systems-especially through overuse, low value and poor quality care-can themselves drive uneconomic growth. Health economists need to understand not only the consequences of environmental impacts on health care, but also the significance of uneconomic growth, and pay closer attention to the growing body of work by heterodox economists, especially in the fields of ecological and feminist economics. This will involve paying closer heed to the existence and consequences of diminishing marginal returns to health care consumption at high levels; the central importance of inequalities and injustice in health; and the need to remedy health economists' currently limited ability to deal effectively with low value care, overdiagnosis and overtreatment.

Estimating quality-adjusted life expectancy (QALE) for local authorities in Great Britain and its association with indicators of the inclusive economy: a cross-sectional study.

OBJECTIVES: Quantifying area-level inequalities in population health can help to inform policy responses. We describe an approach for estimating quality-adjusted life expectancy (QALE), a comprehensive health expectancy measure, for local authorities (LAs) in Great Britain (GB). To identify potential factors accounting for LA-level QALE inequalities, we examined the association between inclusive economy indicators and QALE. SETTING: 361/363 LAs in GB (lower tier/district level) within the period 2018-2020. DATA AND METHODS: We estimated life tables for LAs using official statistics and utility scores from an area-level linkage of the Understanding Society survey. Using the Sullivan method, we estimated QALE at birth in years with corresponding 80% CIs. To examine the association between inclusive economy indicators and QALE, we used an open access data set operationalising the inclusive economy, created by the System Science in Public Health and Health Economics Research consortium. RESULTS: Population-weighted QALE estimates across LAs in GB were lowest in Scotland (females/males: 65.1 years/64.9 years) and Wales (65.0 years/65.2 years), while they were highest in England (67.5 years/67.6 years). The range across LAs for females was from 56.3 years (80% CI 45.6 to 67.1) in Mansfield to 77.7 years (80% CI 65.11 to 90.2) in Runnymede. QALE for males ranged from 57.5 years (80% CI 40.2 to 74.7) in Merthyr Tydfil to 77.2 years (80% CI 65.4 to 89.1) in Runnymede. Indicators of the inclusive economy accounted for more than half of the variation in QALE at the LA level (adjusted R2 females/males: 50%/57%). Although more inclusivity was generally associated with higher levels of QALE at the LA level, this association was not consistent across all 13 inclusive economy indicators. CONCLUSIONS: QALE can be estimated for LAs in GB, enabling further research into area-level health inequalities. The associations we identified between inclusive economy indicators and QALE highlight potential policy priorities for improving population health and reducing health inequalities.

Assessing the effects of population-level political, economic and social exposures, interventions and policies on inclusive economy outcomes for health equity in high-income countries: a systematic review of reviews.

BACKGROUND: A fairer economy is increasingly recognised as crucial for tackling widening social, economic and health inequalities within society. However, which actions have been evaluated for their impact on inclusive economy outcomes is yet unknown. OBJECTIVE: Identify the effects of political, economic and social exposures, interventions and policies on inclusive economy (IE) outcomes in high-income countries, by systematically reviewing the review-level evidence. METHODS: We conducted a review of reviews; searching databases (May 2020) EconLit, Web of Science, Sociological Abstracts, ASSIA, International Bibliography of the Social Sciences, Public Health Database, Embase and MEDLINE; and registries PROSPERO, Campbell Collaboration and EPPI Centre (February 2021) and grey literature (August/September 2020). We aimed to identify reviews which examined social, political and/or economic exposures, interventions and policies in relation to two IE outcome domains: (i) equitable distribution of the benefits of the economy and (ii) equitable access to the resources needed to participate in the economy. Reviews had to include primary studies which compared IE outcomes within or between groups. Quality was assessed using a modified version of AMSTAR-2 and data synthesised informed by SWiM principles. RESULTS: We identified 19 reviews for inclusion, most of which were low quality, as was the underlying primary evidence. Most reviews (n = 14) had outcomes relating to the benefits of the economy (rather than access to resources) and examined a limited set of interventions, primarily active labour market programmes and social security. There was limited high-quality review evidence to draw upon to identify effects on IE outcomes. Most reviews focused on disadvantaged groups and did not consider equity impacts. CONCLUSIONS: Review-level evidence is sparse and focuses on 'corrective' approaches. Future reviews should examine a diverse set of 'upstream' actions intended to be inclusive 'by design' and consider a wider range of outcomes, with particular attention to socioeconomic inequalities.

Causal Assessment of Income Inequality on Self-Rated Health and All-Cause Mortality: A Systematic Review and Meta-Analysis.

Policy Points Income is thought to impact a broad range of health outcomes. However, whether income inequality (how unequal the distribution of income is in a population) has an additional impact on health is extensively debated. Studies that use multilevel data, which have recently increased in popularity, are necessary to separate the contextual effects of income inequality on health from the effects of individual income on health. Our systematic review found only small associations between income inequality and poor self-rated health and all-cause mortality. The available evidence does not suggest causality, although it remains methodologically flawed and limited, with very few studies using natural experimental approaches or examining income inequality at the national level. CONTEXT: Whether income inequality has a direct effect on health or is only associated because of the effect of individual income has long been debated. We aimed to understand the association between income inequality and self-rated health (SRH) and all-cause mortality (mortality) and assess if these relationships are likely to be causal. METHODS: We searched Medline, ISI Web of Science, Embase, and EconLit (PROSPERO: CRD42021252791) for studies considering income inequality and SRH or mortality using multilevel data and adjusting for individual-level socioeconomic position. We calculated pooled odds ratios (ORs) for poor SRH and relative risk ratios (RRs) for mortality from random-effects meta-analyses. We critically appraised included studies using the Risk of Bias in Nonrandomized Studies - of Interventions tool. We assessed certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework and causality using Bradford Hill (BH) viewpoints. FINDINGS: The primary meta-analyses included 2,916,576 participants in 38 cross-sectional studies assessing SRH and 10,727,470 participants in 14 cohort studies of mortality. Per 0.05-unit increase in the Gini coefficient, a measure of income inequality, the ORs and RRs (95% confidence intervals) for SRH and mortality were 1.06 (1.03-1.08) and 1.02 (1.00-1.04), respectively. A total of 63.2% of SRH and 50.0% of mortality studies were at serious risk of bias (RoB), resulting in very low and low certainty ratings, respectively. For SRH and mortality, we did not identify relevant evidence to assess the specificity or, for SRH only, the experiment BH viewpoints; evidence for strength of association and dose-response gradient was inconclusive because of the high RoB; we found evidence in support of temporality and plausibility. CONCLUSIONS: Increased income inequality is only marginally associated with SRH and mortality, but the current evidence base is too methodologically limited to support a causal relationship. To address the gaps we identified, future research should focus on income inequality measured at the national level and addressing confounding with natural experiment approaches.

Social security cuts and life expectancy: a longitudinal analysis of local authorities in England, Scotland and Wales.

BACKGROUND: The UK Government's 'welfare reform' programme included reductions to social security payments, phased in over the financial years 2011/2012-2015/2016. Previous studies of social security cuts and health outcomes have been restricted to analysing single UK countries or single payment types (eg, housing benefit). We examined the association between all social security cuts fully implemented by 2016 and life expectancy, for local authorities in England, Scotland and Wales. METHODS: Our unit of analysis was 201 upper tier local authorities (unitary authorities and county councils: 147 in England, 32 in Scotland, 22 in Wales). Our exposure was estimated social security loss per head of the working age population per year for each local authority, calculated against the baseline in 2010/2011. The primary outcome was annual life expectancy at birth between the calendar years 2012 and 2016 (year lagged following exposure). We used a panel regression approach with fixed effects. RESULTS: Social security cuts implemented by 2016 were estimated to be £475 per head of the working age population in England, £390 in Scotland and £490 in Wales since 2010/2011. During the study period, there was either no improvement or only marginal increases in national life expectancy. Social security loss and life expectancy were significantly associated: an estimated £100 decrease in social security per head of working age population was associated with a 1-month reduction in life expectancy. CONCLUSIONS: Social security cuts, at the UK local authority level, were associated with lower life expectancy. Further research should examine causality.

What is missing from how we measure and understand the experience of poverty and deprivation in population health analyses?

BACKGROUND: Explaining why some populations are healthier than others is a core task of epidemiology. Socioeconomic position (SEP), encompassing a broad range of exposures relating to economic circumstances, social class and deprivation, is an important explanation, but lacks a comprehensive framework for understanding the range of relevant exposures it encompasses. METHODS: We reviewed existing literature on experiential accounts of poverty through database searching and the identification of relevant material by experts. We mapped relevant concepts into a complex systems diagram. We developed this diagram through a process of consultation with academic experts and experts with direct experience of poverty. Finally, we categorized concepts on the basis of whether they have previously been measured, their importance to the causal flow of the diagram, and their importance to those consulted, creating a list of priorities for future measurement. RESULTS: There are a great many aspects of SEP which are not frequently measured or used in epidemiological research and, for some of these, work is needed to better conceptualize and develop measures. Potentially important missing aspects include stigma, social class processes, access to education, sense of lost potential, neighbourhoods, fairness and justice, emotional labour, masking poverty, being (in)visible, costs, and experiences of power. CONCLUSIONS: Analyses seeking to understand the extent to which SEP exposures explain differences in the health of populations are likely to benefit from a comprehensive understanding of the range and inter-relationships between different aspects of SEP. More research to better conceptualize and measure these aspects is now needed.

How to measure progress towards a wellbeing economy: distinguishing genuine advances from 'window dressing'.

The world is experiencing multiple intersecting urgent and existential crises, which have profound and inequitable implications for population health. Arguably, the design of the current, dominant economic system and its antecedents is the root cause of these crises, as it externalises impacts on nature, climate and population health, exacerbates inequalities, and rewards extraction, rent-seeking and social hierarchy. A 'wellbeing economy', which aims to achieve social justice within planetary boundaries, has been proposed as an alternative approach to economic design. Many governments, businesses and organisations have expressed interest or commitment to this, but not at the required scale or with the required urgency. Indeed, there is the risk now that the radicalism of a wellbeing economy approach is undermined in its delivery thus far as it has either only been adopted in rhetoric or nascent form; or implemented only as isolated components rather than as part of a comprehensive shift. We, therefore, propose a series of criteria by which judgement can be made on whether progress towards a wellbeing economy is occurring: 1) Is the economy explicitly viewed by relevant actors as serving social, health, cultural, equity and nature outcomes, rather than the reverse?; 2) Is there a comprehensive and plausible pathway to design the economy in a way that achieves these outcomes?; 3) Is there a clear commitment to transitioning away from socially and ecologically damaging economic activities and doing so in a just way?; 4) Are there clear mechanisms that extend democracy over all sectors of the economy, including economic strategy and policy design, and in ownership of economic assets?; 5) Are negative externalities between policy areas or populations assessed and avoided, and positive externalities identified and promoted?; and 6) Are all the measures of economic success focused on social, health, cultural, equity and nature outcomes? We then apply these criteria using a series of examples to show contrasts between genuine wellbeing approaches and wellbeing economy 'window dressing'.

Trends in psychological distress in Great Britain, 1991-2019: evidence from three representative surveys.

BACKGROUND: Previously improving UK mortality trends stalled around 2012, with evidence implicating economic policy as the cause. This paper examines whether trends in psychological distress across three population surveys show similar trends. METHODS: We report the percentages reporting psychological distress (4+ in the 12-item General Health Questionnaire) from Understanding Society (Great Britain, 1991-2019), Scottish Health Survey (SHeS, 1995-2019) and Health Survey for England (HSE, 2003-2018) for the population overall, and stratified by sex, age and area deprivation. Summary inequality indices were calculated and segmented regressions fitted to identify breakpoints after 2010. RESULTS: Psychological distress was higher in Understanding Society than in SHeS or HSE. There was slight improvement between 1992 and 2015 in Understanding Society (with prevalence declining from 20.6% to 18.6%) with some fluctuations. After 2015 there is some evidence of a worsening in psychological distress across surveys. Prevalence worsened notably among those aged 16-34 years after 2010 (all three surveys), and aged 35-64 years in Understanding Society and SHeS after 2015. In contrast, the prevalence declined in those aged 65+ years in Understanding Society after around 2008, with less clear trends in the other surveys. The prevalence was around twice as high in the most deprived compared with the least deprived areas, and higher in women, with trends by deprivation and sex similar to the populations overall. CONCLUSION: Psychological distress worsened among working-age adults after around 2015 across British population surveys, mirroring the mortality trends. This indicates a widespread mental health crisis that predates the COVID-19 pandemic.

The public health implications of the cost-of-living crisis: outlining mechanisms and modelling consequences.

The UK, and other high-income countries, are experiencing substantial increases in living costs. Several overlapping and intersecting economic crises threaten physical and mental health in the immediate and longer term. Policy responses may buffer against the worst effects (e.g. welfare support) or further undermine health (e.g. austerity). We explore fundamental causes underpinning the cost-of-living crisis, examine potential pathways by which the crisis could impact population health and use a case study to model potential impacts of one aspect of the crisis on a specific health outcome. Our modelling illustrates how policy approaches can substantially protect health and avoid exacerbating health inequalities. Targeting support at vulnerable households is likely to protect health most effectively. The current crisis is likely to be the first of many in era of political and climate uncertainty. More refined integrated economic and health modelling has the potential to inform policy integration, or 'health in all policies'.

The increasing significance of disease severity in a burden of disease framework.

Recent estimates have reiterated that non-fatal causes of disease, such as low back pain, headaches and depressive disorders, are amongst the leading causes of disability-adjusted life years (DALYs). For these causes, the contribution of years lived with disability (YLD) - put simply, ill-health - is what drives DALYs, not mortality. Being able to monitor trends in YLD closely is particularly relevant for countries that sit high on the socio-demographic spectrum of development, as it contributes more than half of all DALYs. There is a paucity of data on how the population-level occurrence of disease is distributed according to severity, and as such, the majority of global and national efforts in monitoring YLD lack the ability to differentiate changes in severity across time and location. This raises uncertainties in interpreting these findings without triangulation with other relevant data sources. Our commentary aims to bring this issue to the forefront for users of burden of disease estimates, as its impact is often easily overlooked as part of the fundamental process of generating DALY estimates. Moreover, the wider health harms of the COVID-19 pandemic have underlined the likelihood of latent and delayed demand in accessing vital health and care services that will ultimately lead to exacerbated disease severity and health outcomes. This places increased importance on attempts to be able to differentiate by both the occurrence and severity of disease.

How much of the stalled mortality trends in Scotland and England can be attributed to obesity?

OBJECTIVES: The rate of improvement in all-cause mortality rates has slowed in the UK since around 2012. While evidence suggests that UK Government 'austerity' policies have been largely responsible, it has been proposed that rising obesity may also have contributed. The aim here was to estimate this contribution for Scotland and England. METHODS: We calculated population attributable fractions (PAFs) resulting from changes in Body Mass Index (BMI) between the mid-1990s and late 2000s for all-cause mortality among 35-89-year olds in 2017-2019. We used BMI data from national surveys (the Scottish Health Survey and the Health Survey for England), and HRs from a meta-analysis of 89 European studies. PAFs were applied to mortality data for 2017-2019 (obtained from national registries), enabling comparison of observed rates, BMI-adjusted rates and projected rates. Uncertainty in the estimates is dominated by the assumptions used and biases in the underlying data, rather than random variation. A series of sensitivity analyses and bias assessments were therefore undertaken to understand the certainty of the estimates. RESULTS: In Scotland, an estimated 10% (males) and 14% (females) of the difference between observed and predicted mortality rates in 2017-2019 may be attributable to previous changes in BMI. The equivalent figures for England were notably higher: 20% and 35%, respectively. The assessments of bias suggest these are more likely to be overestimates than underestimates. CONCLUSIONS: Some of the recent stalled mortality trends in Scotland and England may be associated with earlier increases in obesity. Policies to reduce the obesogenic environment, including its structural and commercial determinants, and reverse the impacts of austerity, are needed.

Is austerity a cause of slower improvements in mortality in high-income countries? A panel analysis.

BACKGROUND: The rate of improvement in mortality slowed across many high-income countries after 2010. Following the 2007-08 financial crisis, macroeconomic policy was dominated by austerity as countries attempted to address perceived problems of growing state debt and government budget deficits. This study estimates the impact of austerity on mortality trends for 37 high-income countries between 2000 and 2019. METHODS: We fitted a suite of fixed-effects panel regression models to mortality data (period life expectancy, age-standardised mortality rates (ASMRs), age-stratified mortality rates and lifespan variation). Austerity was measured using the Alesina-Ardagna Fiscal Index (AAFI), Cyclically-Adjusted Primary Balance (CAPB), real indexed Government Expenditure, and Public Social Spending as a % of GDP. Sensitivity analyses varied the lag times, and confined the panel to economic downturns and to non-oil-dominated economies. RESULTS: Slower improvements, or deteriorations, in life expectancy and mortality trends were seen in the majority of countries, with the worst trends in England & Wales, Estonia, Iceland, Scotland, Slovenia, and the USA, with generally worse trends for females than males. Austerity was implemented across all countries for at least some time when measured by AAFI and CAPB, and for many countries across all four measures (and particularly after 2010). Austerity adversely impacted life expectancy, ASMR, age-specific mortality and lifespan variation trends when measured with Government Expenditure, Public Social Spending and CAPB, but not with AAFI. However, when the dataset was restricted to periods of economic downturn and in economies not dominated hydrocarbon production, all measures of austerity were found to reduce the rate of mortality improvement. INTERPRETATION: Stalled mortality trends and austerity are widespread phenomena across high-income countries. Austerity is likely to be a cause of stalled mortality trends. Governments should consider alternative economic policy approaches if these harmful population health impacts are to be avoided.

Bearing the burden of austerity: how do changing mortality rates in the UK compare between men and women?

BACKGROUND: Mortality rates across the UK stopped improving in the early 2010s, largely attributable to UK Government's 'austerity' policies. Such policies are thought to disproportionately affect women in terms of greater financial impact and loss of services. The aim here was to investigate whether the mortality impact of austerity-in terms of when rates changed and the scale of excess deaths-has also been worse for women. METHODS: All-cause mortality data by sex, age, Great Britain (GB) nation and deprivation quintile were obtained from national agencies. Trends in age-standardised mortality rates were calculated, and segmented regression analyses used to identify break points between 1981 and 2019. Excess deaths were calculated for 2012-2019 based on comparison of observed deaths with numbers predicted by the linear trend for 1981-2011. RESULTS: Changes in trends were observed for both men and women, especially for those living in the 20% most deprived areas. In those areas, mortality increased between 2010/2012 and 2017/2019 among women but not men. Break points in trends occurred at similar time points. Approximately 335 000 more deaths occurred between 2012 and 2019 than was expected based on previous trends, with the excess greater among men. CONCLUSIONS: It remains unclear whether there are sex differences in UK austerity-related health effects. Nonetheless, this study provides further evidence of adverse trends in the UK and the associated scale of excess deaths. There is a clear need for such policies to be reversed, and for policies to be implemented to protect the most vulnerable in society.