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At least 19 recordsLinked to original sources
PubMed2003

Modelling health, income and income inequality: the impact of income inequality on health and health inequality.

A framework is developed to analyse the impact of the distribution of income on individual health and health inequality, with individual health modelled as a function of income and the distribution of income. It is demonstrated that the impact of income inequality can generate non-concave health production functions resulting in a non-concave health production possibility frontier. In this context, the impact of different health policies are considered and it is argued that if the distribution of income affects individual health, any policy aimed at equalising health, which does not account for income inequality, will lead to unequal distributions of health. This is an important development given current UK government attention to reducing health inequality.

Health Policy↗
PubMed2005

Whose health is affected by income inequality? A multilevel interaction analysis of contemporaneous and lagged effects of state income inequality on individual self-rated health in the United States.

The empirical relationship between income inequality and health has been much debated and discussed. Recent reviews suggest that the current evidence is mixed, with the relationship between state income inequality and health in the United States (US) being perhaps the most robust. In this paper, we examine the multilevel interactions between state income inequality, individual poor self-rated health, and a range of individual demographic and socioeconomic markers in the US. We use the pooled data from the 1995 and 1997 Current Population Surveys, and the data on state income inequality (represented using Gini coefficient) from the 1990, 1980, and 1970 US Censuses. Utilizing a cross-sectional multilevel design of 201,221 adults nested within 50 US states we calibrated two-level binomial hierarchical mixed models (with states specified as a random effect). Our analyses suggest that for a 0.05 change in the state income inequality, the odds ratio (OR) of reporting poor health was 1.30 (95% CI: 1.17-1.45) in a conditional model that included individual age, sex, race, marital status, education, income, and health insurance coverage as well as state median income. With few exceptions, we did not find strong statistical support for differential effects of state income inequality across different population groups. For instance, the relationship between state income inequality and poor health was steeper for whites compared to blacks (OR=1.34; 95% CI: 1.20-1.48) and for individuals with incomes greater than $75,000 compared to less affluent individuals (OR=1.65; 95% CI: 1.26-2.15). Our findings, however, primarily suggests an overall (as opposed to differential) contextual effect of state income inequality on individual self-rated poor health. To the extent that contemporaneous state income inequality differentially affects population sub-groups, our analyses suggest that the adverse impact of inequality is somewhat stronger for the relatively advantaged socioeconomic groups. This pattern was found to be consistent regardless of whether we consider contemporaneous or lagged effects of state income inequality on health. At the same time, the contemporaneous main effect of state income inequality remained statistically significant even when conditioned for past levels of income inequality and median income of states.

Adult↗
PubMedDate not supplied

[Social inequities of health in Spain. Report of the Scientific Commission for the Study of Social Inequities in Health in Spain].

In 1993 the Ministry of Health of the Spanish Government appointed a Scientific Commission to analyze social inequalities in health in Spain, as well as to make recommendations for improving Spanish health, through the practical implementation of public policies to reduce existing inequalities. The present report is the result of the work carried out by the said Commission. It has the following aims: first, to present a general introduction to the topic of social inequalities in health; second, to offer a global vision of the topic in Spain based upon the editing of available information: finally, to encourage the need for an in-depth analysis of the study and the reduction in social inequalities in health in the scientific and social fields, offering illustrative examples. The first chapter points out the importance of the topic, and Spain is located in the international historical and geographical context. The second chapter presents the most important concepts regarding the definition and measurement of health and inequality. The third and fourth chapters review various international and national studies of particular importance, and the Spanish case includes the current limitations to research. The fifth chapter presents two original investigations on the four perspectives of social inequalities in health in Spain: death rate, noticeable health, conducts related to health and the use and access to health services. Chapter six comments on some examples of policies aimed at reducing inequalities in health. Finally, the seventh chapter summarises the main conclusions of the report and makes some recommendations both for the improvement of current information systems as well as for obtaining the main conclusions for the health policies. Amongst the report's main conclusions the following may be pointed out: 1) an ecological study on the social inequalities in the death rate of small areas between 1990-1992 has revealed the existence of inequalities at a small area level. Autonomous Communities and regions. Inequality is confirmed between North-Northwestern Spain (with a high level) and South-Southwestern Spain (with a low level). Likewise, a positive relationship may be observed between various social indicators and the death rate; 2) the analysis of health surveys for 1987 and 1993 according to social class has revealed the existence of inequalities in health. Thus, in most of the health variables studied regarding the state of health-the conducts related to health or health services-the most disadvantaged social classes present greater health problems; 3) the political social and health experiences carried out in the Basque Country and Barcelona respectively, aimed at improving living standards, social welfare and the health of the most vulnerable sectors of the population have been positive and should be expanded and studied in depth; 4) the study and decrease of social inequalities in health by putting into practice social and health public policies should be a main objective of all political and social forces.

Health Status↗
PubMed1997

Socioeconomic inequalities in morbidity and mortality in western Europe. The EU Working Group on Socioeconomic Inequalities in Health.

BACKGROUND: Previous studies of variation in the magnitude of socioeconomic inequalities in health between countries have methodological drawbacks. We tried to overcome these difficulties in a large study that compared inequalities in morbidity and mortality between different countries in western Europe. METHODS: Data on four indicators of self-reported morbidity by level of education, occupational class, and/or level of income were obtained for 11 countries, and years ranging from 1985 to 1992. Data on total mortality by level of education and/or occupational class were obtained for nine countries for about 1980 to about 1990. We calculated odds ratios or rate ratios to compare a broad lower with a broad upper socioeconomic group. We also calculated an absolute measure for inequalities in mortality, a risk difference, which takes into account differences between countries in average rates of illhealth. FINDINGS: Inequalities in health were found in all countries. Odds ratios for morbidity ranged between about 1.5 and 2.5, and rate ratios for mortality between about 1.3 and 1.7. For men's perceived general health, for instance, inequalities by level of education in Norway were larger than in Switzerland or Spain (odds ratios [95% CI]: 2.57 [2.07-3.18], 1.60 [1.30-1.96], 1.65 [1.44-1.88], respectively). For mortality by occupational class, in men aged 30-44, the rate ratio was highest in Finland (1.76 [1.69-1.83]), although there was no large difference in the size of the inequality in those countries with data. For men aged 45-59, for whom France did have data, this country had the largest inequality (1.71 [1.66-1.77]). In the age-group 45-64, the absolute risk difference ranked Finland second after France (9.8% [9.1-10.4], 11.5% [10.7-12.4]), with Sweden and Norway coming out more favourably than on the basis of rate ratios. In a scatter-plot of average rank scores for morbidity versus mortality. Sweden and Norway had larger relative inequalities in health than most other countries for both measures; France fared badly for mortality but was average for morbidity. INTERPRETATION: Our results challenge conventional views on the between-country pattern of inequalities in health in western European countries.

Adult↗
PubMed2006

Peripherality, income inequality, and life expectancy: revisiting the income inequality hypothesis.

BACKGROUND: Recent criticisms of the income inequality and health hypothesis have stressed the lack of consistent significant evidence for the stronger effects of income inequality among rich countries. Despite such criticisms, little attention has been devoted to the income-based criteria underlying the stratification of countries into rich/poor groups and whether trade patterns and world-system role provide an alternative means of stratifying groups. METHODS: To compare income-based and trade-based criteria, 107 countries were grouped into four typologies: (I) high/low income, (II) OECD membership/non-membership, (III) core/non-core, and (IV) non-periphery/periphery. Each typology was tested separately for significant differences in the effects of income inequality between groups. Separate group comparison tests and regression analyses were conducted for each typology using Rodgers (1979) specification of income, income inequality, and life expectancy. Interaction terms were introduced into Rodgers specification to test whether group classification moderated the effects of income inequality on health. RESULTS: Results show that the effects of income inequality are stronger in the periphery than non-periphery (IV) (-0.76 vs -0.23; P < 0.05). An incremental F-test confirmed significant differences in the coefficient subsets between the two groups (F(2,101) = 6.31; P < 0.01). CONCLUSIONS: Cross-national analyses of income inequality and population health have assumed (i) income differences between countries best capture global stratification and (ii) the negative effects of income inequality are stronger in high-income countries. However, present findings emphasize (i) the importance of measuring global stratification according to trading patterns and (ii) the strong, negative effects of income inequality on life expectancy among peripheral populations.

Commerce↗
PubMed2006

Incorporating concepts of inequality and inequity into health benefits analysis.

BACKGROUND: Although environmental policy decisions are often based in part on both risk assessment information and environmental justice concerns, formalized approaches for addressing inequality or inequity when estimating the health benefits of pollution control have been lacking. Inequality indicators that fulfill basic axioms and agree with relevant definitions and concepts in health benefits analysis and environmental justice analysis can allow for quantitative examination of efficiency-equality tradeoffs in pollution control policies. METHODS: To develop appropriate inequality indicators for health benefits analysis, we provide relevant definitions from the fields of risk assessment and environmental justice and consider the implications. We evaluate axioms proposed in past studies of inequality indicators and develop additional axioms relevant to this context. We survey the literature on previous applications of inequality indicators and evaluate five candidate indicators in reference to our proposed axioms. We present an illustrative pollution control example to determine whether our selected indicators provide interpretable information. RESULTS AND CONCLUSIONS: We conclude that an inequality indicator for health benefits analysis should not decrease when risk is transferred from a low-risk to high-risk person, and that it should decrease when risk is transferred from a high-risk to low-risk person (Pigou-Dalton transfer principle), and that it should be able to have total inequality divided into its constituent parts (subgroup decomposability). We additionally propose that an ideal indicator should avoid value judgments about the relative importance of transfers at different percentiles of the risk distribution, incorporate health risk with evidence about differential susceptibility, include baseline distributions of risk, use appropriate geographic resolution and scope, and consider multiple competing policy alternatives. Given these criteria, we select the Atkinson index as the single indicator most appropriate for health benefits analysis, with other indicators useful for sensitivity analysis. Our illustrative pollution control example demonstrates how these indices can help a policy maker determine control strategies that are dominated from an efficiency and equality standpoint, those that are dominated for some but not all societal viewpoints on inequality averseness, and those that are on the optimal efficiency-equality frontier, allowing for more informed pollution control policies.

Journal Article↗
PubMed2003

Does inequality in self-assessed health predict inequality in survival by income? Evidence from Swedish data.

This paper empirically addresses two questions using a large, individual-level Swedish data set which links mortality data to health survey data. The first question is whether there is an effect of an individual's self-assessed health (SAH) on his subsequent survival probability and if this effect differs by socioeconomic factors. Our results indicate that the effect of SAH on mortality risk declines with age-probably because of adjustment towards 'milder' overall health evaluations at higher ages-but does not seem to differ by indicators of socioeconomic status (SES) like income or education. This finding suggests that there is no systematic adjustment of SAH by SES and therefore that any measured income-related inequality in SAH is unlikely to be biased by reporting error. The second question is: how much of the income-related inequality in mortality can be explained by income-related inequality in SAH? Using a decomposition method, we find that inequality in SAH accounts for only about 10% of mortality inequality if interactions are not allowed for, but its contribution is increased to about 28% if account is taken of the reporting tendencies by age. In other words, omitting the interaction between age and SAH leads to a substantial underestimation of the partial contribution of SAH inequality by income. These results suggest that the often observed inequalities in SAH by income do have predictive power for the-less often observed-inequalities in survival by income.

Adult↗
PubMed2004

Beyond the income inequality hypothesis: class, neo-liberalism, and health inequalities.

This paper describes and critiques the income inequality approach to health inequalities. It then presents an alternative class-based model through a focus on the causes and not only the consequences of income inequalities. In this model, the relationship between income inequality and health appears as a special case within a broader causal chain. It is argued that global and national socio-political-economic trends have increased the power of business classes and lowered that of working classes. The neo-liberal policies accompanying these trends led to increased income inequality but also poverty and unequal access to many other health-relevant resources. But international pressures towards neo-liberal doctrines and policies are differentially resisted by various nations because of historically embedded variation in class and institutional structures. Data presented indicates that neo-liberalism is associated with greater poverty and income inequalities, and greater health inequalities within nations. Furthermore, countries with Social Democratic forms of welfare regimes (i.e., those that are less neo-liberal) have better health than do those that are more neo-liberal. The paper concludes with discussion of what further steps are needed to "go beyond" the income inequality hypothesis towards consideration of a broader set of the social determinants of health.

Adolescent↗
PubMed2006

Mortality inequalities in times of economic growth: time trends in socioeconomic and regional inequalities in under 5 mortality in Indonesia, 1982-1997.

STUDY OBJECTIVE: To examine time trends in socioeconomic and regional inequalities in under 5 mortality in Indonesia during almost two decades of economic growth. DESIGN: Under 5 mortality was calculated for the total population and for subgroups by maternal education, household wealth, rural/urban residence, and island group, using the 1987, 1991, 1994, and 1997 Indonesian Demographic and Health Surveys. Inequalities were calculated using Cox proportional hazards analysis. SETTING: Indonesia, 1982-1997. Main PARTICIPANTS: 18,205, 33,907, 39,433, and 37,533 children respectively, aged under 5 years, born to women included in the above mentioned surveys. MAIN RESULTS: Under 5 mortality declined substantially during the 1980s and 1990s. Educational inequalities in under 5 mortality decreased, although not statistically significantly, from a hazard ratio of 2.00 (95%CI 1.60, 2.50) to 1.52 (95%CI 1.27, 1.82). Inequalities between urban and not electrified rural areas increased, from 1.84 (95%CI 1.48, 2.28) to 2.18 (95%CI 1.70, 2.80). Inequalities between the Outer Islands and the central islands of Java/Bali increased from 1.16 (95%CI 0.92, 1.46) to 1.43 (95%CI 1.17, 1.74). Irregular time trends were seen for inequalities by household wealth. Trends in health care use were fairly similar for the low and high educated. CONCLUSIONS: These results for education show that socioeconomic inequalities in under 5 mortality do not inevitably rise in times of rapid economic growth. Widening or narrowing of health inequalities in times of economic growth might depend on how equally this growth is distributed.

Adolescent↗
PubMed2005

Anatomic and functional leg-length inequality: a review and recommendation for clinical decision-making. Part I, anatomic leg-length inequality: prevalence, magnitude, effects and clinical significance.

BACKGROUND: Leg-length inequality is most often divided into two groups: anatomic and functional. Part I of this review analyses data collected on anatomic leg-length inequality relative to prevalence, magnitude, effects and clinical significance. Part II examines the functional "short leg" including anatomic-functional relationships, and provides an outline for clinical decision-making. METHODS: Online database--Medline, CINAHL and MANTIS--and library searches for the time frame of 1970-2005 were done using the term "leg-length inequality". RESULTS AND DISCUSSION: Using data on leg-length inequality obtained by accurate and reliable x-ray methods, the prevalence of anatomic inequality was found to be 90%, the mean magnitude of anatomic inequality was 5.2 mm (SD 4.1). The evidence suggests that, for most people, anatomic leg-length inequality does not appear to be clinically significant until the magnitude reaches approximately 20 mm (approximately 3/4"). CONCLUSION: Anatomic leg-length inequality is near universal, but the average magnitude is small and not likely to be clinically significant.

Journal Article↗
PubMedDate not supplied

[Inequities in access to information and inequities in health].

This piece presents evidence that inequities in information are an important determinant of health inequities and that eliminating these inequities in access to information, especially by using new information and communication technologies (ICTs), could represent a significant advance in terms of guaranteeing the right to health for all. The piece reviews the most important international scientific research findings on the determinants of the health of populations, emphasizing the role of socioeconomic inequities and of deteriorating social capital as factors that worsen health conditions. It is noteworthy that Latin America has both socioeconomic inequities and major sectors of the population living in poverty. Among the fundamental strategies for overcoming the inequalities and the poverty are greater participation by the poor in civic life and the strengthening of social capital. The contribution that the new ICTs could make to these strategies is analyzed, and the Virtual Health Library (VHL) is discussed. Coordinated by the Latin American and Caribbean Center on Health Sciences Information (BIREME), the VHL is a contribution by the Pan American Health Organization that takes advantage of the potential of ICTs to democratize information and knowledge and consequently promote equity in health. The "digital gap" is discussed as something that can produce inequity itself and also increase other inequities, including ones in health. Prospects are discussed for overcoming this gap, emphasizing the role that governments and international organizations should play in order to expand access to the global public good that information for social development is.

Caribbean Region↗
PubMed2002

[Data aggregation in measuring inequalities and inequities in the health of populations].

OBJECTIVES: To compare how different degrees of data aggregation influence the measurement of health inequalities and health inequities within a population, and to assess the appropriateness of those different degrees of data aggregation in performing studies on inequalities and inequities. METHODS: As an example, we used data on the infant mortality rate in Costa Rica in 1973 and in 1984 and calculated measurements that are frequently used to quantify inequalities and inequities. RESULTS: According to our results, the inequality measures presented (except for those that were derived using regression models) are not sensitive to data aggregation by socioeconomic groups. However, when geographic areas are compared, more disaggregation of the data results in the measures indicating greater inequality. CONCLUSIONS: Our results show that some measures can vary widely depending on the level of data aggregation. It is thus crucial to know how to select these measures and also how to aggregate the data in a way that is consistent with the objectives of each study.

Costa Rica↗
PubMed2006

For whom is income inequality most harmful? A multi-level analysis of income inequality and mortality in Norway.

This study investigates the degree to which contextual income inequality in economic regions in Norway affected mortality during the 1990s, above the effects of mean regional income and individual-level confounders. A further objective is to explore whether income inequality effects on mortality differed between socioeconomic groups. Data were constructed by linkages of administrative registers encompassing all Norwegian inhabitants. The outcome variable was all-cause mortality during 6 years (i.e., died 1994-1999 or alive end of 1999). Men and women aged 25-66 in 1993 were analysed. Regions' mean income and income inequality (in terms of gini coefficients) were calculated from consumption-units-adjusted family disposable income. Individual-level variables included sex, age, marital status, individual income, education, and being a recipient of health-related welfare benefits. Multilevel logistic regression models were fitted for 2,197,231 individuals nested within 88 regions. After adjusting for regional mean income and individual-level variables, the odds ratio (OR) for mortality 1994-1999 was 1.028 (95% CI 1.023-1.033) on the gini variable multiplied by 100. Analyses of cross-level interactions indicated some, albeit modest, income inequality effects on mortality in the upper income and educational categories. Among those with low individual income, low education, and among recipients of health-related welfare benefits, mortality effects of higher regional income inequality were significantly stronger than among those more advantageously placed in the social structure. The results of this study differ from previous studies which have suggested that contextual income inequality has a minor impact on population health in egalitarian countries. The results indicate that in Norway, neither a comparatively egalitarian income distribution nor generous and comprehensive welfare institutions hindered the emergence of regional-level income inequality effects on mortality, and these effects were particularly marked among socioeconomically disadvantaged groups. Explanations for the results are discussed.

Adult↗
PubMed2003

Is exposure to income inequality a public health concern? Lagged effects of income inequality on individual and population health.

OBJECTIVE: To examine the health consequences of exposure to income inequality. DATA SOURCES: Secondary analysis employing data from several publicly available sources. Measures of individual health status and other individual characteristics are obtained from the March Current Population Survey (CPS). State-level income inequality is measured by the Gini coefficient based on family income, as reported by the U.S. Census Bureau and Al-Samarrie and Miller (1967). State-level mortality rates are from the Vital Statistics of the United States, other state-level characteristics are from U.S. census data as reported in the Statistical Abstract of the United States. STUDY DESIGN: We examine the effects of state-level income inequality lagged from 5 to 29 years on individual health by estimating probit models of poor/fair health status for samples of adults aged 25-74 in the 1995 through 1999 March CPS. We control for several individual characteristics, including educational attainment and household income, as well as regional fixed effects. We use multivariate regression to estimate the effects of income inequality lagged 10 and 20 years on state-level mortality rates for 1990, 1980, 1970, and 1960. PRINCIPAL FINDINGS: Lagged income inequality is not significantly associated with individual health status after controlling for regional fixed effects. Lagged income inequality is not associated with all cause mortality, but associated with reduced mortality from cardiovascular disease and malignant neoplasms, after controlling for state fixed-effects. CONCLUSIONS: In contrast to previous studies that fail to control for regional variations in health outcomes, we find little support for the contention that exposure to income inequality is detrimental to either individual or population health.

Adult↗
PubMed2001

World Health Report 2000: inequality index and socioeconomic inequalities in mortality.

Monitoring of inequality in health has become an increasingly important task of development agencies. We compared the inequality index as published in the World Health Report 2000 with available evidence on socioeconomic inequalities in mortality in 15 industrialised and 43 less-developed countries. We found that the World Health Report index does not correspond with international variations in the size of socioeconomic inequalities in mortality. These findings indicate that the index should not be interpreted as a reflection of socioeconomic inequalities in health, nor should the index be used to replace the indices developed to monitor socioeconomic inequalities in health.

Bias↗
PubMed2005

Inequity and inequality in the use of health care in England: an empirical investigation.

Achieving equity in healthcare, in the form of equal use for equal need, is an objective of many healthcare systems. The evaluation of equity requires value judgements as well as analysis of data. Previous studies are limited in the range of health and supply variables considered but show a pro-poor distribution of general practitioner consultations and inpatient services and a pro-rich distribution of outpatient visits. We investigate inequality and inequity in the use of general practitioner consultations, outpatient visits, day cases and inpatient stays in England with a unique linked data set that combines rich information on the health of individuals and their socio-economic circumstances with information on local supply factors. The data are for the period 1998-2000, just prior to the introduction of a set of National Health Service (NHS) reforms with potential equity implications. We find inequalities in utilisation with respect to income, ethnicity, employment status and education. Low-income individuals and ethnic minorities have lower use of secondary care despite having higher use of primary care. Ward level supply factors affect utilisation and are important for investigating health care inequality. Our results show some evidence of inequity prior to the reforms and provide a baseline against which the effects of the new NHS can be assessed.

Acute Disease↗
PubMed2003

Income related inequalities in mental health in Great Britain: analysing the causes of health inequality over time.

Using regression techniques this paper estimates the level of income related health inequality in GB in 1992 and 1998. Inequality is decomposed to investigate which socio-demographic factors are important contributors to health differences. The paper includes a range of measured and subjective income variables to control for absolute income. A relative deprivation measure is included to test the impact of income inequality on health inequality. It is found that subjective financial status is a major determinant of ill-health and makes a major contribution to income related inequalities in health. Relative deprivation is an important contributor for women but not for men.

Adult↗