Health and income inequalities in Europe: What is the role of circumstances?

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.

Is it Time to Quit? Smoking Persistence and Self-Rated Health

This study evaluates the impact of smoking on self-rated health using a British cohort born in 1970 that was followed through adult life. Records were taken for this dataset many times; individual self-rated health was first recorded in 1996 at age 26, and afterward at ages 30, 34, and 42. The smoking rate over time determined membership in the groups of current-smokers, never-smokers, and former-smokers. Estimates showed that the current-smokers group produced an increase in the probability of being in poor health with respect to never-smokers of about 10 percentage points in the long term. This result was also consistent when we used former-smokers as the control group, or other model specifications. The baseline estimates were not contradicted by robustness checks and policy implications of these results were discussed.

Inequality among industrial workers in the late 19th century United States

This paper uses the large cross sectional survey of 8544 workers in nine industries (pig iron, bar iron, steel, coal, coke, cottons, woolens, and glass) in the United States and five European countries (Belgium, Great Britain, France, Belgium, and Switzerland) to examine inequality in the industrial working class in the late nineteenth century. The paper looks at incomes, the food budget share (estimated using the Almost Ideal Demand System), and home ownership. The results show regular gradients with the unskilled workers doing less well than semi-skilled and skilled workers. Despite the lack of proprietors, farmers, and other groups with significant income from property, such surveys can be useful in the study of the historical aspects of inequality.

The demographics and geographic distribution of laboratory-confirmed Lyme disease cases in England and Wales (2013-2016): an ecological study

OBJECTIVE

Lyme disease is a tick-borne disease of increasing incidence and public concern across the Northern Hemisphere. However, the socio-demographics and geographic distribution of the population affected in England and Wales are poorly understood. Therefore, the proposed study was designed to describe the demographics and distribution of laboratory-confirmed cases of Lyme disease from a national testing laboratory.

DESIGN

An ecological study of routinely collected laboratory surveillance data.

SETTING

Public Health England's national Lyme disease testing laboratory.

PARTICIPANTS

3986 laboratory-confirmed cases of Lyme disease between 2013 and 2016.

RESULTS

In England and Wales, the incidence of laboratory-confirmed Lyme disease rose significantly over the study period from 1.62 cases per 100 000 in 2013 to 1.95 cases per 100 000 in 2016. There was a bimodal age distribution (with peaks at 6-10 and 61-65 years age bands) with a predominance of male patients. A significant clustering of areas with high Lyme disease incidence was located in southern England. An association was found between disease incidence and socioeconomic status, based on the patient's resident postcode, with more cases found in less deprived areas. Cases were disproportionately found in rural areas compared with the national population distribution.

CONCLUSIONS

These results suggest that Lyme disease patients originate from areas with higher socioeconomic status and disproportionately in rural areas. Identification of the Lyme disease hotspots in southern England, alongside the socio-demographics described, will enable a targeted approach to public health interventions and messages.

Socioeconomic inequality in non-communicable diseases in Europe between 2004 and 2015: evidence from the SHARE survey

Background

The scope of this work was to investigate socioeconomic inequalities among European adults aged 50 or older in chronic diseases and behavioural risk factors for these diseases, namely, smoking habits, obesity and physical inactivity, between 2004 and 2015.

Methods

Data for this study were drawn from the Survey of Health, Ageing and Retirement (SHARE) in Europe, which is a panel database of microdata on health, socioeconomic status and social and family networks of people aged 50 years or older, covering most of the European Union. The predicted number of non-communicable diseases (NCDs) was used to estimate the concentration index and to find the contributions of determinants to socioeconomic inequalities in chronic diseases.

Results

The inequality disfavoured the poor in both years, but the effect was stable from 2004 (C = -0.071) to 2015 (C = -0.081). Inequality was shown to be attributed mostly to physical inactivity and obesity and this contribution increased during the study period. Among socioeconomic status (SES) determinants, education and marital status were the most concentrated in both years, while physical inactivity and obesity were the most concentrated behavioural risk factors in both years.

Conclusions

To prevent chronic diseases, health policy should aim not only to improve individual health behaviours in the population, but also to reduce socioeconomic inequality. Our study suggests promoting a healthy lifestyle in the most disadvantaged socioeconomic classes as a strategy to improve the health conditions of the whole population.