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The ‘inclusion health’ agenda aims to draw attention to health disadvantages accompanying experiences putatively characterised by social exclusion, such as homelessness, problem substance use, or imprisonment. However, its increasing prominence has surfaced conceptual uncertainties and potential tensions with other understandings of health inequalities.\ud \ud We undertook a discourse analysis of how recent health inequalities policy documents describe, explain, and make recommendations relating to inclusion health. Using the UK as a case study, and with reference to public health accounts of multi-level governance theory, we selected five recent health inequalities policy reviews covering Scotland, UK, European Union, and the World Health Organisation.\ud \ud All documents referred to some inclusion health concerns, though their relative emphasis differed between documents. Terms like inclusion, exclusion, and vulnerability were commonly used, but ill-defined and often ambiguous. Explanatory discourses were diverse, with a particular focus on intergenerational cycles and disproportionate exposure to risk, with a varying emphasis on individual versus structural factors. Few documents provided coherent explanatory accounts for the relationship between the issues of interest to inclusion health, their associations with poor health, and other axes of inequality.\ud \ud Our results suggest that health inequalities policymaking in a multi-level context may benefit from comprehensive conceptual frameworks which encompass diverse forms of social stratification, advantage, and disadvantage, and acknowledge potential tensions and trade-offs between different understandings. This may necessitate further theoretical and empirical work for inclusion health on its definitions, bounds, and how its scope of interest interacts with other forms of social and health inequality.

In this project we are testing the effect of the school system (selective versus comprehensive) on inequalities in health using two birth cohorts. Full details in the attached protocol and code for baseline attached.

Rates of teenage pregnancy have fallen in several high-income countries across the last 20-30 years. Several interventions have been suggested as contributing to this change, alongside other culture, policy and environmental change. This review aims to assess the evidence for what could have contributed to these falling rates.

Evaluating the Teenage Pregnancy Strategy using natural experiments. Interrupted time series methods were used to compare England with other UK countries, and synthetic control methods were used to compare with a wider pool of high-income countries.

Background: \ud 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.\ud \ud Methods: \ud 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.\ud \ud Results: \ud 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.\ud \ud Interpretation: \ud 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.

Supplemental Material, sj-docx-1-smr-10.1177_0049124121995548 for Marginal and Conditional Confounding Using Logits by Kristian Bernt Karlson, Frank Popham and Anders Holm in Sociological Methods & Research

Additional file 1: Appendix.

In the context of worldwide ageing, increasing numbers of older people are lonely, isolated and excluded, with serious implications for health, and cognitive and physical functioning. Access to good public transport can improve mobility and social participation among older adults, and policies that improve access and promote use, such as concessionary travel schemes, are potentially important in promoting healthy and successful ageing. Concessionary travel schemes for older people are in place in many countries but are under threat following the global financial crisis. Evidence regarding their success in encouraging activity and social participation is generally positive but based largely on qualitative or observational associations and, in particular, is often limited by the lack of appropriate comparison groups. We use changes in the English statutory scheme, in particular the rising eligibility age from 2010 onwards, as a natural experiment to explore its impact on older people's travel. A difference-in-difference-in-difference analysis of National Travel Surveys (2002–2016) compares three age groups differentially affected by eligibility criteria: 50–59 years (consistently ineligible), 60–64 years (decreasing eligibility from 2010) and 65–74 years (consistently eligible). Compared with 50–59-year-olds, bus travel by 60–74-year-olds increased year-on-year from 2002 to 2010 then fell following rises in eligibility age (annual change in weekly bus travel: −2.9 per cent (−4.1%, −1.7%) in 60–74- versus 50–59-year-olds). Results were consistent across gender, occupation and rurality. Our results indicate that access to, specifically, free travel increases bus use and access to services among older people, potentially improving mobility, social participation and health. However, the rising eligibility age in England has led to a reduction in bus travel in older people, including those not directly affected by the change, demonstrating that the positive impact of the concession goes beyond those who are eligible. Future work should explore the cost–benefit trade-off of this and similar schemes worldwide.

Objective To re-evaluate the impact of England’s Teenage Pregnancy Strategy (1999 to 2010) on pregnancy and birth rates. Hailed as a unique, nation-wide, comprehensive, evidence-based intervention, the strategy has been promoted as a reproducible model for other countries with high teenage pregnancy rates. Design Controlled interrupted time series and synthetic control analyses using routinely collected data on births and abortions in 16 countries. Setting The Strategy was published in July 1999 and implemented from 2000-2010, with increased investment in areas with higher rates of under-18 pregnancies from 2006 onwards. Participants Women aged under 20 living in England during the intervention period were considered to be the target population. Women in Scotland and Wales were the control population in our interrupted time series analyses. Women from European and English-speaking high-income countries were the control population in our synthetic control analyses. Main outcome measures The pregnancy rate among women aged under-18 was our primary outcome, as this was the target of the Strategy. We used under-18 births and under-20 pregnancies as secondary outcomes. Results In the controlled interrupted time series analyses, trends in rates of teenage pregnancy in England were similar to Scotland (0.08 fewer pregnancies per 1,000 women per year in England; −0.74 to 0.59) and Wales (0.14 more pregnancies per 1,000 women per year in England; −0.48 to 0.76). In synthetic control analyses, under-18 birth rates were very similar in England and the synthetic control. Under-20 pregnancy rates were marginally higher in England than in the synthetic control. Placebo testing and other sensitivity analyses supported the finding of little observable effect. Conclusion Although teenage pregnancies and births in England fell following implementation of the Teenage Pregnancy Strategy, comparisons with other countries suggest the strategy had little, if any, effect. This raises doubts about whether the strategy should be used as a model for future public health interventions in England or in other countries aiming to reduce teenage pregnancy. The protocol for the analysis was published online at https://osf.io/tdbr8/ SUMMARY BOX What is already known on this topic: Teenage pregnancy is associated with numerous health risks, and efforts to reduce rates of pregnancy may lead to improved health outcomes The Teenage Pregnancy Strategy was launched in 1999 with the goal of reducing teenage pregnancies in England Initial observations showed a drop in rate across the strategy period; this has been interpreted as demonstrating the success of the intervention. What this study adds: Our study suggests there was little or no effect of the strategy, and that the rapid decline in rates would have occurred without the intervention, in line with similar countries.

Additional file 3: Figure S1. Assessment of the smoothness of the confounding variables across the selective schooling cut-point. Population is the study sample (n = 5039) and points are means of 50 people. Figures A, D and G in first column show the 11+ exam score vs the confounder. Figures B, E and H in the second column show the same data with the population separated by selective (open orange triangles) and non-selective (open blue circles) secondary school attendance. The line shows the estimated effect size of secondary school attendance at the cut-point extrapolated across the optimal bandwidth. Figures C, F and I in the third column show re-estimates of the effect size of secondary school attendance for a range of population sizes around the cut-point (bandwidth sizes). The effect size estimate at the predicted optimal bandwidth (reported in Table 3) is shown as a dashed line.

Many interventions that may have large impacts on health and health inequalities, such as social and public health policies and health system reforms, are not amenable to evaluation using randomised controlled trials. The United Kingdom Medical Research Council's guidance on the evaluation of natural experiments draws attention to the need for ingenuity to identify interventions which can be robustly studied as they occur, and without experimental manipulation. Studies of intervention withdrawal may usefully widen the range of interventions that can be evaluated, allowing some interventions and policies, such as those that have developed piecemeal over a long period, to be evaluated for the first time. In particular, sudden removal may allow a more robust assessment of an intervention's long-term impact by minimising ‘learning effects’. Interpreting changes that follow withdrawal as evidence of the impact of an intervention assumes that the effect is reversible and this assumption must be carefully justified. Otherwise, withdrawal-based studies suffer similar threats to validity as intervention studies. These threats should be addressed using recognised approaches, including appropriate choice of comparators, detailed understanding of the change processes at work, careful specification of research questions, and the use of falsification tests and other methods for strengthening causal attribution.\ud \ud Evaluating intervention withdrawal provides opportunities to answer important questions about effectiveness of population health interventions, and to study the social determinants of health. Researchers, policymakers and practitioners should be alert to the opportunities provided by the withdrawal of interventions, but also aware of the pitfalls.

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.

No abstract available.

Lower socioeconomic position (SEP), both accumulated across the life course and at different life-stages, has been found to be associated with higher cumulative physiological burden, as measured by allostatic load. This study aimed to identify what factors mediate the association between SEP and allostatic load, as measured through combining cardiovascular, metabolic and inflammatory markers. We explored the role of material, psychological and behavioral factors, accumulated across two periods in time, in mediating the association between SEP and allostatic load. Data are from the West of Scotland Twenty-07 Study, with respondents followed over five waves of data collection from ages 35 to 55 (n=999). Allostatic load was measured by summing nine binary biomarker scores (‘1’=in the highest-risk quartile) measured when respondents were 55years old (wave 5). SEP was measured by a person’s accumulated social class over two periods All mediators and SEP were measured at baseline in 1987 and 20years later and combined to form accumulated measures of risk. Material mediators included car and home ownership, and having low income. The General Health Questionnaire (GHQ-12) was used as the psychosocial mediator. Behavioral mediators included smoking, alcohol consumption, physical activity and diet. Path analysis using linear regressions adjusting for sex were performed for each of the potential mediators to assess evidence of attenuation in the association between lower SEP and higher allostatic load. Analyses by mediator type revealed that renting one’s home (approximately 78% attenuation) and having low income (approx. 62% attenuation) largely attenuated the SEP–allostatic load association. GHQ did not attenuate the association. Smoking had the strongest attenuating effect of all health behaviors (by 33%) with no other health behaviors attenuating the association substantially. Material factors, namely home tenure and income status, and smoking have important roles in explaining socioeconomic disparities in allostatic load, particularly when accumulated over time.

Lifespan variation adds to life expectancy by measuring the inequality surrounding age of death that a population faces. Countries that tackle premature mortality generally have decreasing lifespan variation but this is the first study to compare and statistically assess when and to what extent trends in lifespan variation have changed across Western Europe. Lifespan variation was measured using e† and joinpoint regression analysed the timing and rate of change. Trends have been mostly downward with the recent exception of men in Scotland, Northern Ireland, Ireland and Finland where trends have flattened or show slight increases. Future research aimed at identifying the ages and causes of death, driving trends in these countries, is key to preventing increasing inequalities.

Calculation of weights. Gives further technical details of the specific models used to calculate analysis weights. (DOCX 17Â kb)

Covariate balance. Includes 5 supplementary figures showing how wave-specific weights achieve covariate balance on prior measures of covariates. (DOCX 164Â kb)

No abstract available.

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 socio-economic position can lead to disease.\ud 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.\ud Findings: The association between income deprivation and mortality differed significantly across the groups of exposure to green space for mortality from all causes (p\ud 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 socio-economic health inequalities.

Life course epidemiology has used models of accumulation and critical or sensitive periods to examine the importance of exposure timing in disease aetiology. These models are usually used to describe the direct effects of exposures over the life course. In comparison with consideration of direct effects only, we show how consideration of total effects improves interpretation of these models, giving clearer notions of when it will be most effective to intervene. We show how life course variation in the total effects depends on the magnitude of the direct effects and the stability of the exposure. We discuss interpretation in terms of total, direct and indirect effects and highlight the causal assumptions required for conclusions as to the most effective timing of interventions.

Wilkinson and Pickett's1 (WP) theory has relative deprivation as a core mechanism for why income inequality impacts health in societies. A number of recent studies, including in JECH , have thus contrasted the health impact of relative to absolute deprivation.2 ,3 However, it is a false contrast I argue. This is because supposed absolute deprivation has its roots in a theory of relative deprivation.4 ,5 Further it is not only WP's theory that has relative deprivation as its core mechanism. Materialist/structural theory, as outlined in the very well-known Black report on health inequalities, does as well.6 Absolute deprivation is often defined as one's material standard of living up to some set level, for example, a subsistence level and as one's material standard of living independent of that of others.3 However, the Black report discusses in detail why materialist/structural theory sees the unequal access due to social class of economic and other resources as the key driver of health inequalities because it deprives people of contemporary standards of living.6 So there is a clear endorsement of deprivation as relative and a move away from notions of absolute deprivation and health in the report. There is nothing fixed about levels of physical well-being. They have improved in the past and there is every likelihood that they will improve in the future. But class inequalities persist in the distribution of health as in the distribution of income or wealth, and they persist as a form of relative deprivation. (ref. …