Income Inequality and Population Health: A Global Gradient?

Social transition, socioeconomic status and self-rated health in China: evidence from a national cross-sectional survey (CGSS)

Background

Social transition is one of the multi-level mechanisms that influence health disparities. However, it has received less attention as one of the non-traditional social determinants of health. A few studies have examined China's social transition and its impact on health inequality in self-rated health (SRH). Therefore, this study explores the impact of China's market-oriented reforms-social transition and socioeconomic status (SES)-on residents' SRH.

Methods

Using the cross-sectional data from the Chinese General Social Survey (CGSS) in 2017, we analyzed the effects of social transition and SES on the SRH of Chinese residents using the RIF (Recentered influence function) method. The RIF decomposition method investigated health differences among different populations and their determinants.

Results

Social transition and SES have significant positive effects on the SRH of Chinese residents. The correlation between SES and the SRH of Chinese residents is moderated by social transition, implying that social transition can weaken the correlation between SES and the SRH of Chinese residents. The impacts of SES and social transition on SRH vary across populations.

Conclusion

Promoting social transition and favoring disadvantaged groups with more resources are urgently needed to promote equitable health outcomes.

Cumulative Unionization and Physical Health Disparities among Older Adults

Whereas previous research shows that union membership is associated with improved health, static measurements have been used to test dynamic theories linking the two. We construct a novel measure of cumulative unionization, tracking individuals across their entire careers, to examine health consequences in older adulthood. We use data from the Panel Study of Income Dynamics (1970-2019) and predict self-rated health, functional limitations, and chronic health conditions in ages 60 to 79 using cumulative unionization measured during respondents' careers. Results from growth models show that unionized careers are associated with .25 SD to .30 SD improvements in health among older adults across all measures. Analyses of life course mechanisms reveal heterogeneous effects across unionization timing, age in older adulthood, and birth cohort. Moreover, subgroup analyses reveal unionization to partially, but not fully, ameliorate disparities based on privileged social positions. Our findings reveal a substantial and novel mechanism driving older adulthood health disparities.

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.

Distribution of the compression and expansion of morbidity in 194 countries and territories, 1990-2016: The role of income inequality

Studies on detailed types of health changes and the associations between the types and income inequality are inadequate. This study analyses the global distribution of the compression and expansion of morbidity in 194 countries and territories between 1990 and 2016, and investigates the role of income inequality in the distribution. This study shows that all seven types of health changes coexist, despite being distributed unevenly. The relative expansion of morbidity with increased or constant life expectancy (Type 6, 54.48%) is the most popular type, followed by the relative compression of morbidity with increased or constant life expectancy (Type 3, 30.71%). Income distribution within a society matters for health changes. Societies with greater income inequality tend to have Type 6, a worse scenario of health changes. Measures to reduce income inequality or mitigate its adverse effects will contribute to the relative compression of morbidity with increased or constant life expectancy.

Digitalization, income inequality, and public health: Evidence from developing countries

The COVID-19 pandemic has amplified the awareness and demand of public health worldwide. Based on the panel data of 81 developing countries from 2002 to 2019, this study probes into the effect of digitalization on public health and explores the mechanism through which digitalization affects public health from the perspective of income inequality. The results show that digitalization significantly enhances public health in developing countries, and this conclusion still holds after the robustness test. The heterogeneity analysis based on geographic location and income level indicates that the enhancing effect of digitalization on public health is most evident in Africa and middle-income countries. A further mechanism analysis suggests that digitalization can positively impact public health through the intermediary channel of suppressing income inequality. This study enriches the research on digitalization and public health and provides insights for comprehending public health needs and the powerful empowering effects of digitalization.

Socioeconomic Positions and Midlife Health Trajectories in a Changing Social Context: Evidence from China, 1991-2006

Cumulative (dis)advantage theory posits that socioeconomic disparities in health may increase with age. This study examines individuals' midlife health trajectories, taking account of how their life courses are embedded within changing social contexts. Using the China Health and Nutrition Survey (1991-2006), it examines the health gap between Chinese rural peasants and urban nonpeasants in three adjacent time periods, during which a rapid process of social change increased the inequalities between rural and urban areas. Findings show that the health gap increases more rapidly in the more recent time periods, with higher levels of inequality, indicating that health inequalities between the two groups are contingent upon the social contexts in which individuals' lives unfold. To better understand the differences observed over these time periods, further analysis will examine the roles of two structural factors: income inequality and differential access to medical care.

Income Inequality and Population Health: Examining the Role of Social Policy

Studies of the relationship between income inequality and life expectancy often speculate about the role of policy, but direct empirical research is limited. Drawing on the neo-materialist perspective, we examine whether the longitudinal association between income inequality and life expectancy is mediated and moderated by policy liberalism in U.S. states (2000-2014). More liberal policy contexts are characterized by greater efforts to regulate the economy, redistribute income, and protect vulnerable groups and lesser efforts to penalize deviant social behavior. We find that state-level income inequality is inversely associated with policy liberalism and life expectancy. The association between income inequality and life expectancy was not mediated by policy liberalism but was moderated by it. The association is attenuated in states with more liberal policy contexts, supporting the neo-materialist perspective. This finding illustrates how states like New York and California (with liberal policy contexts) can exhibit high income inequality and high life expectancy.

Is Economic Growth Good for Population Health? A Critical Review

A large multidisciplinary literature discusses the relationship between economic growth and population health. The idea that economic growth is good for societies has inspired extensive academic debate, but conclusions have been mixed. To help shed light on the subject, this paper focuses on opportunities for consensus in this large literature. Much scholarship finds that the health-growth relationship varies according to (1) which aspect of "health" is under consideration, (2) shape (e.g., positive linear or logarithmic), (3) issues of timing (e.g., growth over the short or long term), (4) a focus on health inequalities as opposed to population averages, and (5) multivariable relationships with additional factors. After reflecting upon these findings, I propose that economic growth promotes health in some respects, for some countries, and in conjunction with other life-supporting priorities, but does not by itself improve population health generally speaking. I then argue there is already wide, interdisciplinary consensus to support this stance. Moreover, policies focusing exclusively on economic growth threaten harm to both population health and growth, which is to say that political dynamics are also implicated. Yet multivariable approaches can help clarify the bigger picture of how growth relates to health. For moving this literature forward, the best opportunities may involve the simultaneous analysis of multiple factors. The recognition of consensus around these issues would be welcome, and timely.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42650-023-00072-y.

A test of the predictive validity of relative versus absolute income for self-reported health and well-being in the United States

BACKGROUND

A classic debate concerns whether absolute or relative income is more salient. Absolute values resources as constant across time and place while relative contextualizes one's hierarchical location in the distribution of a time and place.

OBJECTIVE

This study investigates specifically whether absolute income or relative income matters more for health and well-being.

METHODS

We exploit within-person, within-age, and within-time variation with higher-quality income measures and multiple health and well-being outcomes in the United States. Using the Panel Study of Income Dynamics and the Cross-National Equivalent File, we estimate three-way fixed effects models of self-rated health, poor health, psychological distress, and life satisfaction.

RESULTS

For all four outcomes, relative income has much larger standardized coefficients than absolute income. Robustly, the confidence intervals for relative income do not overlap with zero. By contrast, absolute income mostly has confidence intervals that overlap with zero, and its coefficient is occasionally signed in the wrong direction. A variety of robustness checks support these results.

CONCLUSIONS

Relative income has far greater predictive validity than absolute income for self-reported health and well-being.

CONTRIBUTION

Compared to earlier studies, this study provides a more rigorous comparison and test of the predictive validity of absolute and relative income that is uniquely conducted with data on the United States. This informs debates on income measurement, the sources of health and well-being, and inequalities generally. Plausibly, these results can guide any analysis that includes income in models.

Comprehensive metrological and content analysis of the income inequality research in health field: A bibliometric analysis

The association between income inequality in a society and the poor health status of its people has attracted the attention of researchers from multiple disciplines. Based on the ISI Web of Science database, bibliometric methods were used to analyze 546 articles related to income inequality research in health field published between 1997 and 2021. We found that the USA contributed most articles, the Harvard Univ was the most influential institution, Social Science & Medicine was the most influential journal, and Kawachi I was the most influential author; the main hotspots included the income inequality, income, health inequality, mortality, socioeconomic factors, concentration index, social capital, self-rated health, income distribution, infant mortality, and population health in 1997-2021; the cardiovascular disease risk factor, social capital income inequality, individual mortality risk, income-related inequalities, understanding income inequalities, income inequality household income, and state income inequality had been the hot research topics in 1997-2003; the self-assessed health, achieving equity, income-related inequalities, oral health, mental health, European panel, occupational class, and cardiovascular diseases had been the hot research topics in 2004-2011; the adolescent emotional problem, South Africa, avoidable mortality, rising inequalities, results from world health survey, working-age adult, spatial aggregation change, prospective study, and mental health-empirical evidence had been the hot research topics in 2012-2021; there were 11 articles with strong transformation potential during 2012-2021. The research results of this paper are helpful to the scientific understanding of the current status of income inequality research in health field.

The Impact of Information and Communication Technologies (ICTs) on Health Outcomes: A Mediating Effect Analysis Based on Cross-National Panel Data

When ICTs (Information and Communications Technologies) are combined with healthcare, they can make a key contribution to gradually improve national health outcomes. The global outbreak of COVID-19 in 2020 further highlighted the important role of e-Health and m-Health service modes. This research structures a mediated effect model to explore dynamic relationships between ICT factors, ICT impacts, and national health outcomes, among which ICT factors are independent variables; ICT impacts are mediating variables, and national health outcome indicators selected from United Nations Millennium Development Goals (MDGs) and World Development Indicators are dependent variables. The fixed effect model is used to process a set of 141 countries’ panel data from 2012 to 2016 from World Bank and World Economic Forum, while the classical three-step test method and Sobel test combined with fixed effects are used to test the mediated effects of the panel data. The results show that there are significant associations between ICT factors and national health outcome indicators, while only some of the partial mediated effects are proved. ICT environment and ICT usage can influence both the under-five mortality rate and adolescent fertility rate via ICT social impact. However, the mediated effect of ICT social impact on maternal mortality ratio and life expectancy at birth has not been confirmed. Meanwhile, the mediated effect of ICT economic impact has not been proven. This research is an interdisciplinary research in the field of information and communication technology and public health and reveals the path and mechanism whereby ICT factors improve national health outcomes, which can help global policymakers drive the next phase of the implementation of the Sustainable Development Goals (SDGs) and continue to improve the overall health at the national level.

Are stress-related pathways of social status differentiation more important determinants of health inequities in countries with higher levels of income inequality?

We explored socioeconomic gradients in self-rated overall health (SROH) using indicators of materialist (educational attainment and perceived income adequacy) and psychosocial perspectives (subjective social status (SSS)) among adults living in countries with varying levels of income inequality, and the importance of psychosocial stress in mediating these associations. If psychosocial processes at the individual and societal levels correspond, associations between SSS and SROH should be higher among adults in countries with higher income inequality, and psychosocial stress should be a more important mediator of these associations. We used multigroup structural equation models to analyse cross-sectional data from the International Food Policy Study of adults (n = 22,824) in Australia, Canada, Mexico, the UK and the United States. Associations between SSS and SROH were not higher in more unequal countries, nor was psychosocial stress a more important mediator of these associations. Inequities in SROH in more unequal countries may not predominantly reflect stress-related pathways of social status differentiation.

Assessing the causal relationship between income inequality and mortality and self-rated health: protocol for systematic review and meta-analysis

BACKGROUND

Income inequality has been linked to health and mortality. While there has been extensive research exploring the relationship, the evidence for whether the relationship is causal remains disputed. We describe the methods for a systematic review that will transparently assess whether a causal relationship exists between income inequality and mortality and self-rated health.

METHODS

We will identify relevant studies using search terms relating to income inequality, mortality, and self-rated health (SRH). Four databases will be searched: MEDLINE, ISI Web of Science, EMBASE, and the National Bureau of Economic Research. The inclusion criteria have been developed to identify the study designs best suited to assess causality: multilevel studies that have conditioned upon individual income (or a comparable measure, such as socioeconomic position) and natural experiment studies. Risk of bias assessment of included studies will be conducted using ROBINS-I. Where possible, we will convert all measures of income inequality into Gini coefficients and standardize the effect estimate of income inequality on mortality/SRH. We will conduct random-effects meta-analysis to estimate pooled effect estimates when possible. We will assess causality using modified Bradford Hill viewpoints and assess certainty using GRADE.

DISCUSSION

This systematic review protocol lays out the complexity of the relationship between income inequality and individual health, as well as our approach for assessing causality. Understanding whether income inequality impacts the health of individuals within a population has major policy implications. By setting out our methods and approach as transparently as we can, we hope this systematic review can provide clarity to an important topic for public policy and public health, as well as acting as an exemplar for other "causal reviews".

Health Outcomes, Income and Income Inequality: Revisiting the Empirical Relationship

In this paper we revisit the relationship between health outcomes, income, and income inequality by applying alternative panel methodologies to a dataset of high-income countries spanning the time period 1980-2017. In this direction, we adopt alternative methodological frameworks in order to provide a) meaningful results by taking into account standard errors that alleviate problems of cross-sectional (spatial) and temporal dependence, and b) insights into the underlying relationships at several points of the conditional distribution of the health outcomes dependent variables. The evidence strongly supports the significant role that income plays in determining health outcomes. The findings relating to income inequality and nonlinear terms are more fragmented in that their significance and sign-direction depend on the functional form and the respective quantiles of the distribution the relationships are evaluated.

How democracy alters our view of inequality - and what it means for our health

BACKGROUND

Income inequality is associated with poor health when economic disparities are especially salient. Yet, political institutions may alter this relationship because democracies (as opposed to autocracies) may be more inclined to frame inequalities in negative rather than positive ways. Living in a particular political system potentially alters the messages individuals receive about whether inequality is large or small, good or bad, and this, in turn, might affect whether beliefs about inequality influence health. Further, media coverage of economic inequality may negatively affect health if it contributes toward the general perception that the gap between rich and poor has gone up, even if there has been no change in income differentials.

METHODS

In this study, we explore the relationship between democracy, perceptions of inequality, and self-rated health across 28 post-communist countries using survey and macro-level data, multilevel regression models, and inverse probability weighting to estimate the average treatment effect on the treated.

RESULTS

We find that self-rated health is higher in more democratic countries and lower among people who believe that inequality has risen in the last few years. Moreover, we observe that people in democracies are more likely to learn about rising inequality through watching television and that when they do it has a more harmful effect on their health than when people in autocracies learn about rising inequality through the same channel, suggesting that in countries where there is less trust in the television media learning about rising inequality is not as harmful for health.

CONCLUSIONS

Our results indicate that while democracies are generally good for well-being, they may not be unambiguously positive for health. This does not mean, of course, that inequality is good for health nor that, on average, autocracies have better health than democracies; but rather that being more aware of inequality can negatively affect self-rated health.

Inequality amplifies the negative association between life expectancy and air pollution: A cross-national longitudinal study

Ambient air pollution, in the form of fine particulate matter (PM_2.5), poses serious population health risks. We estimate cross-national longitudinal models to test whether the negative relationship between life expectancy and PM_2.5 concentration is larger in nations with higher levels of income inequality. The dependent variable is average life expectancy at birth, and the focal predictor variables include PM_2.5 concentration, income inequality, and the two-way interaction between them. We also estimate the average marginal effects of PM_2.5 concentration from low to high values of income inequality, and the predicted values of life expectancy from low to high values of PM_2.5 concentration and income inequality. Results indicate that the negative relationship between life expectancy and PM_2.5 concentration is larger in nations with higher levels of income inequality, and the reductions in predicted life expectancy are substantial when both PM_2.5 concentration and income inequality are high. We suggest that the theoretical principles of Power, Proximity, and Physiology help explain our findings. This study underscores the importance in considering the multiplicative impacts of environmental conditions and socioeconomic factors in the modeling of population health.

Organized Labor and Depression in Europe: Making Power Explicit in the Political Economy of Health

Despite engagement with the construct of power relations, research on the political economy of health has largely overlooked organized labor as a determinant of well-being. Grounded in the theory of power resources, our study aims to fill this gap by investigating the link between country-level union density and mental health while accounting for the compositional effects of individual-level union membership. We use three waves of the European Social Survey (N = 52,737) and a variation on traditional random-effects models to estimate both the contextual and change effects of labor unions on depressive symptoms. We find that country-level union density is associated with fewer depressive symptoms and that this is true irrespective of union membership. We discuss our findings vis-à-vis the literatures on the political economy of health, power resources, and fundamental causes of disease.

What Is Driving the Drug Overdose Epidemic in the United States?

The demand-side perspective argues that the drug overdose epidemic is a consequence of changes in the economy that leave behind working-class people who lack a college education. In contrast, the supply-side perspective maintains that the epidemic is primarily due to changes in the licit and illicit drug environment, whereas a third, distinct perspective argues that income inequality is likely a key driver of the epidemic. To evaluate these competing perspectives, we use a two-level random intercept model and U.S. state-level data from 2006 to 2017. Contrary to the demand-side approach, we find that educational attainment is not associated with drug-related mortality. In support of the supply-side approach, we provide evidence indicating that opioid prescription rates are positively associated with drug-related mortality. We also find that income inequality is a key driver of the epidemic, particularly the lack of resources going to the bottom 20% of earners. We conclude by arguing that considerations of income inequality are an important way to link the arguments made by the demand-side and the supply-side perspectives.

Racial and ethnic differences in individual-level and area-based socioeconomic status and 12-month DSM-IV mental disorders

The purpose of this study was to: (1) examine the associations of individual-level objective socioeconomic status (OSS), subjective socioeconomic status (SSS), and area-based indicators of socioeconomic status, with 12-month DSM-IV mood, anxiety, alcohol use, and drug use disorders; and, (2) determine the extent of racial/ethnic differences in these associations across non-Latino White, non-Latino Black, Latino, and Asian participants. Data are from the Collaborative Psychiatric Epidemiology Studies dataset, a collection of three population-based surveys of mental disorders among U.S. residents aged 18 and older (n = 13,775). Among all indicators of socioeconomic status, SSS was most consistently associated with 12-month mental disorders. Income was negatively associated with mood and anxiety disorders; education was negatively associated with alcohol use and drug use disorders. Significant interactions with race/ethnicity were found for the associations of socioeconomic indicators with anxiety, alcohol use, and drug use disorders but not with mood disorders. SSS was not associated with any of the 12-month mental disorders among Blacks. Education had stronger associations with 12-month anxiety and alcohol use disorders among Whites than among other racial/ethnic groups. Among Asians, low income compared to high income was associated with a lower risk of anxiety disorders and less than high school completion compared to college or more was associated with a lower risk of alcohol use disorders. Finally, tract-level income inequality was associated with a greater risk of drug use disorders only among Blacks. The patterns and magnitudes of the associations of individual-level and area-based socioeconomic indicators differed by type of disorder and race/ethnicity.

Air quality and life expectancy in the United States: An analysis of the moderating effect of income inequality

Although studies have shown that air pollution can be devastating to population health, little is known about the health implications of the intersection of air pollution and income inequality. We investigate if air pollution is especially detrimental to the health of US state populations characterized by more inequitable distributions of income. In other words, are the populations of states with higher levels of income inequality especially vulnerable to similar levels of air pollution? We use two-way fixed-effects panel regression techniques to analyze longitudinal data for 49 US states and the District of Columbia (2000-2010) to model state-level life expectancy as a function of fine particulate matter, income inequality, and other state-level factors. We estimate models with interaction terms to formally assess whether the association between fine particulate matter and life expectancy varies by level of state income inequality. Across multiple life expectancy outcomes and additive models, states with higher PM_2.5 levels tend to exhibit lower average life expectancy. This general pattern is observed with our specifications for raw and weighted PM_2.5 and with adjustments for income share of the top 10%, total population, GDP per capita, median household income, median age, percent college degree or higher, percent black, and percent Hispanic/Latino. We also find that the association between state PM_2.5 levels and average life expectancy intensifies in states with higher levels of income inequality. More specifically, PM_2.5 levels are more detrimental to population life expectancy in states where a higher percentage of income is concentrated in the top 10% of the state income distribution. We discuss the implications of our results for future research in social epidemiology and environmental justice.