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It is well known that social, cultural and economic factors cause substantial inequalities in health. Should we strive to achieve a more even share of good health, beyond improving the average health status of the population? We examine four arguments for the reduction of health inequalities. 1 Inequalities are unfair. Inequalities in health are undesirable to the extent that they are unfair, or unjust. Distinguishing between health inequalities and health inequities can be contentious. Our view is that inequalities become "unfair" when poor health is itself the consequence of an unjust distribution of the underlying social determinants of health (for example, unequal opportunities in education or employment). 2 Inequalities affect everyone. Conditions that lead to marked health disparities are detrimental to all members of society. Some types of health inequalities have obvious spillover effects on the rest of society, for example, the spread of infectious diseases, the consequences of alcohol and drug misuse, or the occurrence of violence and crime. 3 Inequalities are avoidable. Disparities in health are avoidable to the extent that they stem from identifiable policy options exercised by governments, such as tax policy, regulation of business and labour, welfare benefits and health care funding. It follows that health inequalities are, in principle, amenable to policy interventions. A government that cares about improving the health of the population ought therefore to incorporate considerations of the health impact of alternative options in its policy setting process. 3 Interventions to reduce health inequalities are cost effective. Public health programmes that reduce health inequalities can also be cost effective. The case can be made to give priority to such programmes (for example, improving access to cervical cancer screening in low income women) on efficiency grounds. On the other hand, few programmes designed to reduce health inequalities have been formally evaluated using cost effectiveness analysis. ...

Throughout the world, wealth and income are becoming more concentrated. Growing evidence suggests that the distribution of income-in addition to the absolute standard of living enjoyed by the poor-is a key determinant of population health. A large gap between rich people and poor people leads to higher mortality through the breakdown of social cohesion. The recent surge in income inequality in many countries has been accompanied by a marked increase in the residential concentration of poverty and affluence. Residential segregation diminishes the opportunities for social cohesion. Income inequality has spillover effects on society at large, including increased rates of crime and violence, impeded productivity and economic growth, and the impaired functioning of representative democracy. The extent of inequality in society is often a consequence of explicit policies and public choice. Reducing income inequality offers the prospect of greater social cohesiveness and better population health.

OBJECTIVES: This study tested the hypothesis that disparities in political participation across socioeconomic status affect health. Specifically, the association of voting inequality at the state level with individual self-rated health was examined. METHODS: A multilevel study of 279,066 respondents to the Current Population Survey (CPS) was conducted. State-level inequality in voting turnout by socioeconomic status (family income and educational attainment) was derived from November CPS data for 1990, 1992, 1994, and 1996. RESULTS: Individuals living in the states with the highest voting inequality had an odds ratio of fair/poor self-rated health of 1.43 (95% confidence interval [CI] = 1.22, 1.68) compared with individuals living in the states with the lowest voting inequality. This odds ratio decreased to 1.34 (95% CI = 1.14, 1.56) when state income inequality was added and to 1.27 (95% CI = 1.10, 1.45) when state median income was included. The deleterious effect of low individual household income on self-rated health was most pronounced among states with the greatest voting and income inequality. CONCLUSIONS: Socioeconomic inequality in political participation (as measured by voter turnout) is associated with poor self-rated health, independently of both income inequality and state median household income.

Background Previous research has highlighted the impact of economic conditions and uncertainty on physical and mental health. The unexpected result of the Brexit referendum in 2016 triggered high levels of economic uncertainty. Objective To examine whether prescriptions for antidepressants increased after the referendum result, benchmarking them against other drug classes. Methods We used GP practice prescribing data to compile the number of defined daily doses per capita every month in each of the 326 voting areas in England over the period 2011-2016. We used a difference-in-differences (DID) approach to identify the effects of Brexit on antidepressant prescriptions, compared with trends in a control group (antigout and iron preparations) that were unlikely to be associated with uncertainty and depression. Results Antidepressant prescribing continued to increase after the referendum but at a slower pace. Therapeutic classes used as controls showed a decrease. The DID approach shows that there was a relative increase of 13.4% in antidepressants compared with other therapeutic classes (DID coeff: 0.134; 95% CI 0.093 to 0.174). Conclusion Our results are open to different interpretations and should be treated with caution. This relative increase in antidepressant prescribing after the referendum may be attributed to increased uncertainty for certain parts of the population, but does not rule out an improvement in mood for others. Alternatively, some other factor - for example, distraction, might have contributed to a decrease in the control therapeutic classes. A possible policy implication is that programmes for the promotion of mental health may need to be intensified during periods of uncertainty.

Objective To evaluate the association between physical distancing interventions and incidence of coronavirus disease 2019 (covid-19) globally. Design Natural experiment using interrupted time series analysis, with results synthesised using meta-analysis. Setting 149 countries or regions, with data on daily reported cases of covid-19 from the European Centre for Disease Prevention and Control and data on the physical distancing policies from the Oxford covid-19 Government Response Tracker. Participants Individual countries or regions that implemented one of the five physical distancing interventions (closures of schools, workplaces, and public transport, restrictions on mass gatherings and public events, and restrictions on movement (lockdowns)) between 1 January and 30 May 2020. Main outcome measure Incidence rate ratios (IRRs) of covid-19 before and after implementation of physical distancing interventions, estimated using data to 30 May 2020 or 30 days post-intervention, whichever occurred first. IRRs were synthesised across countries using random effects meta-analysis. Results On average, implementation of any physical distancing intervention was associated with an overall reduction in covid-19 incidence of 13% (IRR 0.87, 95% confidence interval 0.85 to 0.89; n=149 countries). Closure of public transport was not associated with any additional reduction in covid-19 incidence when the other four physical distancing interventions were in place (pooled IRR with and without public transport closure was 0.85, 0.82 to 0.88; n=72, and 0.87, 0.84 to 0.91; n=32, respectively). Data from 11 countries also suggested similar overall effectiveness (pooled IRR 0.85, 0.81 to 0.89) when school closures, workplace closures, and restrictions on mass gatherings were in place. In terms of sequence of interventions, earlier implementation of lockdown was associated with a larger reduction in covid-19 incidence (pooled IRR 0.86, 0.84 to 0.89; n=105) compared with a delayed implementation of lockdown after other physical distancing ...