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

Abstract

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.

Keywords: causality; income inequality; systematic review.

Figure 1

Forest Plot for a Meta‐Analysis of Studies Considering Income Inequality and Poor SRH, Stratified by RoB for a 0.05‐Unit Increase in the Gini Coefficient. The number of people were 2,916,576, and the number of studies were 38. AGES, Aichi Gerontological Evaluation Study Project; BHPS, British Household Panel Survey; BRFSS, Behavioral Risk Factor Surveillance System; CASEN, National Socioeconomic Characterization Survey; CHNS, China Health and Nutrition Survey; CI, confidence interval; CLHLS, Chinese Longitudinal Healthy Longevity Survey; CNPHS, Canadian National Population Health Survey; CPS, Current Population Survey; CSLCPHW, Comprehensive Survey of Living Conditions of People on Health and Welfare; DANE, Departamento Administrativo Nacional de Estadística; ECHP, European Community Household Panel survey; EQLS, European Quality of Life Surveys; ESS, European Social Survey; GHS, British General Household Survey; GSS, General Social Survey; HILDA, Household Income and Labour Dynamics in Australia; HRS, Health and Retirement Study; HWBA, Health, Well‐Being, and Aging study; LA FANS, Los Angeles Family and Neighborhood Survey; LCS, Life Conditions Survey; MCIC‐MS, Metropolitan Chicago Information Center Metro Survey; NDB, New Democracies Barometer; NEB, New European Barometer; NHANES, National Health and Nutrition Examination Survey; NHIS, National Health Interview Survey; NMIHS, National Maternal Infant Health Survey; OHS, Ontario Health Survey; PHQ. Stockholm County Council's Public Health Questionnaire; PNS, National Health Survey; RoB, risk of bias; SHARE, Survey of Health, Ageing and Retirement in Europe; SHS, Scottish household survey; THS, Thematic Household Surveys; WVS, World Values Survey.

Figure 2

Forest Plot for a Meta‐Analysis of Studies Considering Income Inequality and All‐Cause Mortality, Stratified by RoB for a 0.05‐Unit Increase in the Gini Coefficient. The number of people were 10,727,470, and the number of studies were 14. Canada, census, Canadian Census Mortality Follow‐up Study; CCHS/GPS, Copenhagen City Heart Study; CI, confidence interval; CR‐LMS, Costa Rican Longitudinal Mortality Study; LISA, Linnaeus Database; NHANES I/NHEFS, National Health and Nutrition Examination Survey; NHIS, National Health Interview Survey; NLMS, US National Longitudinal Mortality Study; PSID, Panel Study of Income Dynamics; RoB, risk of bias; SABE, Health, Well‐Being, and Aging; SLC, Statistic Sweden's Survey of Living Conditions; USRDS: US Renal Data System.