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.

Trends in inequalities in childhood overweight and obesity prevalence: a repeat cross-sectional analysis of the Health Survey for England.

OBJECTIVE: To examine trends in socio-economic and ethnic inequalities in childhood overweight and obesity in the England between 1995 and 2019 in survey data and to compare these to administrative data. DESIGN: Observational repeated cross-sectional study using the Health Survey for England (HSE) and National Child Measurement Programme (NCMP). OUTCOME: Age and sex standardised overweight, obesity and overweight including obesity. ANALYSIS: Inequalities assessed by parental education, family structure, ethnicity (binary non-white vs white) and area-level Index of Multiple Deprivation. Estimates stratified by age and sex. Trends compared against NCMP data (age 4-5 and 10-11 years). RESULTS: Prevalence of childhood overweight including obesity increased from 26.0% in 1995 to 31.7% in 2019, with the highest and fastest growing levels in those aged 11-15 years, rising from 29.7% to 38.0%. Despite a plateau in overall childhood obesity since 2004, differences between groups demonstrated widening inequalities over time. Inequalities widened by area-level deprivation, household educational attainment, household structure and ethnicity driven primarily by increased prevalence among socioeconomically disadvantaged children. For example, the gap between children from households with no qualifications versus degree-level qualifications increased from -1.1% to 13.2%, and the gap between single-parent households and couple households increased from 0.5% to 5.3%. HSE trends in prevalence of childhood overweight and obesity by deprivation quintile were consistent with those in NCMP. CONCLUSION: Overall levels of child overweight and obesity increased between 1995 and 2004. Since then, increases in prevalence among less advantaged groups have driven widening of inequalities.

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'.