Trends in socioeconomic health inequalities in Korea: use of mortality and morbidity measures

STUDY OBJECTIVE: To examine trends in educational mortality and morbidity inequalities in Korea. DESIGN: Census data (1990, 1995, 2000) and death certificate data (1990-91, 1995-96, 2000-01) were used for mortality. For morbidity, four waves (1989, 1992, 1995, and 1999) of Social Statistics Survey from Korea's National Statistical Office were used. Morbidity indicators were self rated health and self reported illness in the past two weeks. Trends were studied using indices for both the relative and absolute size of socioeconomic inequalities in health. SETTING: South Korea. Patients (or Participants): Representative annual samples of the adult population aged 30-59 in Korea. Main results: Based on trends in relative index of inequalities, the relative level of socioeconomic mortality inequality remained virtually unchanged in men and women in the past 10 years. Meanwhile, inequalities in self rated health have increased over time in both sexes. Most of the total increase in health inequalities happened between 1995 and 1999. Inequalities in self reported acute illness increased in the past 10 years. CONCLUSIONS: The rise in inequalities in morbidity requires increased social discourse and policy discussions about health inequalities in Korean society.     

Trends in socioeconomic inequalities in self-assessed health in 10 European countries

BACKGROUND: Changes over time in inequalities in self-reported health are studied for increasingly more countries, but a comprehensive overview encompassing several countries is still lacking. The general aim of this article is to determine whether inequalities in self-assessed health in 10 European countries showed a general tendency either to increase or to decrease between the 1980s and the 1990s and whether trends varied among countries. METHODS: Data were obtained from nationally representative interview surveys held in Finland, Sweden, Norway, Denmark, England, The Netherlands, West Germany, Austria, Italy, and Spain. The proportion of respondents with self-assessed health less than 'good' was measured in relation to educational level and income level. Inequalities were measured by means of age-standardized prevalence rates and odds ratios (ORs). RESULTS: Socioeconomic inequalities in self-assessed health showed a high degree of stability in European countries. For all countries together, the ORs comparing low with high educational levels remained stable for men (2.61 in the 1980s and 2.54 in the 1990s) but increased slightly for women (from 2.48 to 2.70). The ORs comparing extreme income quintiles increased from 3.13 to 3.37 for men and from 2.43 to 2.86 for women. Increases could be demonstrated most clearly for Italian and Spanish men and women, and for Dutch women, whereas inequalities in health in the Nordic countries showed no tendency to increase. CONCLUSIONS: The results underscore the persistent nature of socioeconomic inequalities in health in modern societies. The relatively favourable trends in the Nordic countries suggest that these countries' welfare states were able to buffer many of the adverse effects of economic crises on the health of disadvantaged groups.     

Pathways between socioeconomic determinants of health

STUDY OBJECTIVE: Many previous studies on socioeconomic inequalities in health have neglected the causal interdependencies between different socioeconomic indicators. This study examines the pathways between three socioeconomic determinants of ill health. DESIGN, SETTING, AND PARTICIPANTS: Cross sectional survey data from the Helsinki health study in 2000 and 2001 were used. Each year employees of the City of Helsinki, reaching 40, 45, 50, 55, and 60 years received a mailed questionnaire. Altogether 6243 employees responded (80% women, response rate 68%). Socioeconomic indicators were education, occupational class, and household income. Health indicators were limiting longstanding illness and self rated health. Inequality indices were calculated based on logistic regression analysis. MAIN RESULTS: Each socioeconomic indicator showed a clear gradient with health. Among women half of inequalities in limiting longstanding illness by education were mediated through occupational class and household income. Inequalities by occupational class were largely explained by education. A small part of inequalities for income were explained by education and occupational class. For self rated health the pathways were broadly similar. Among men most of the inequalities in limiting longstanding illness by education were mediated through occupational class and income. Part of occupational class inequalities were explained by education. Two thirds of inequalities by income were explained by education and occupational class. CONCLUSIONS: Parts of the effects of each socioeconomic indicator on health are either explained by or mediated through other socioeconomic indicators. Analyses of the predictive power of socioeconomic indicators on health run the risk of being fruitless, if interrelations between various indicators are neglected.     

Do social and economic reforms change socioeconomic inequalities in child mortality? A case study: New Zealand 1981–1999

BACKGROUND: Socioeconomic inequalities in child mortality are known to exist; however the trends in these inequalities have not been well examined. This study examines the trends in child mortality inequality between 1981 and 1999 against the background of the rapid and dramatic social and economic restructuring in New Zealand during this time period. METHODS: Record linkage studies of census and mortality records of all New Zealand children aged 0-14 years on census night 1981, 1986, 1991, 1996, each followed up for three years for mortality between ages 1-14 years. Socioeconomic position was measured using maternal education, household income, and highest occupational class in the household. Standardised mortality rates, rate ratios, and rates differences as well as regression based measures of inequality were calculated. RESULTS: Mortality in all socioeconomic groups fell between 1981 and 1999. Socioeconomic inequality in child mortality existed by all measures of socioeconomic position, however only trends by income suggested a change over time: the relative index of inequality increased from 1.5 in 1981-84 to 1.8 in 1996-99 (p trend 0.06), but absolute inequality remained stable (slope index of inequality 15/100 000 in 1981-84 and 14/100 000 in 1996-99. CONCLUSIONS: Dramatic changes in income in New Zealand possibly translated into increasing relative inequality in child mortality by income, but not by education or occupational class. The a priori hypothesis that socioeconomic inequalities in child mortality would have increased in New Zealand during a period of rapid structural reform and widening income inequalities was only partly supported.     

Changes in social inequalities in health in the Basque Country

STUDY OBJECTIVE: To determine the extent of the inequalities in self reported health between socioeconomic groups and its changes over time in the Basque Country (Spain). DESIGN: Cross sectional data on the association between occupation, education and income and three health indicators was obtained from the Basque Health Surveys of 1986 and 1992. Representative population samples were analysed. In 1986 the number of respondents was 24 657 and in 1992, 13 277. SETTING: Basque Country, Spain. MAIN OUTCOME MEASURES: The effect of socioeconomic position on health and the magnitude of social inequalities in health were quantified using the odds ratios based on logistic regression analysis, and the Relative Index of Inequality. RESULTS: As was expected, social inequalities in self reported health existed in both surveys, but the social gradient was greater in 1992. Social differences varied according to gender and health indicator. According to education an increase in social inequalities was observed consistently in all the health indicators except long term conditions in women. A consistent increase in inequalities in limiting longstanding illness was also observed according to all socioeconomic indicators. CONCLUSIONS: These results agree to a large extent with those of previous studies in other countries. In this context the unequal distribution of material circumstances and working conditions between socioeconomic groups seem to play a major part in health inequalities. The worsening of the labour market during this period and the onset of a new economic recession may explain the increase in social inequalities over time.     

Health inequalities in Panama

OBJECTIVES: To document socioeconomic inequalities in health and health services in Panama and thus create a baseline for the prospective monitoring of the impact of health policies on equity. METHODS: Analysis of data from the 1997 Living Standards Measurement Survey, the 1990 National Population Census and birth registration data for 1996. The relative index of inequality and concentration coefficient were calculated for a wide range of indicators of out-of-pocket health expenditure, access, utilization and quality of health services and of health outcomes. RESULTS: Large and statistically significant socioeconomic differences in many of the variables examined were detected, almost all of which favored the rich. The inequalities identified included qualitative factors such as the type of care received as well as quantitative factors such as travelling times and utilization rates. Some of the inequalities were concentrated among a small, very poor segment of the population whilst others were the result of gradually increasing advantage with increased levels of outcome. CONCLUSIONS: The results obtained provide a valuable starting point for the Panamanian government from which it can identify the most serious inequalities in health and health service provision and develop policies to eliminate or reduce them. They also offer a baseline to monitor changes in the magnitude of these inequalities over time.     

Socioeconomic health inequalities in Latvia: a cross-sectional study

AIMS: Socioeconomic health differences have been studied elaborately for many Western societies. Relatively little is know about the social variations in health in the former communist states of Eastern Europe. This study investigated socioeconomic health inequalities in Latvia. METHODS: Cross-sectional analysis was undertaken of the 1999 Norbalt-II Living Conditions Survey, a random population-based sample in Latvia, and included males and females aged 25 to 70. RESULTS: Lower educated subjects had higher rates of self-assessed poor health than those with tertiary education (men OR 2.21; 1.31-3.71 95% CI, and women OR 2.48; 1.74-3.54 95% CI). After adjusting for income, educational differences were significant only for women. Income differences were larger than educational differences in self-assessed poor health for both genders (OR of highest vs. lowest quintile for men: 5.10; 2.26-11.5 95% CI, women: OR 3.26; 1.92-5.51 95% CI). For long-standing health problems socioeconomic differences were smaller. After adjusting for income no educational differences were found, but income differences were significant (men: OR 2.06; 1.15-3.69 95% CI, women: OR 1.42; 1.12-2.63 95% CI). The economically non-active were in worse health than the (self-)employed subjects (men: OR 6.12; 3.65-10.3 95% CI, women: OR 2.79; 1.66-3.39 95% CI). CONCLUSIONS: Substantial social inequalities in self-assessed poor health and longstanding health problems exist in Latvia for both sexes. Inequalities by material circumstances, as measured by income, appear to be larger than educational differences. Economic activity was also strongly associated with health. There were no inequalities with regard to urbanization and ethnic differences were found only for long-standing health problems among women.     

Trends in socioeconomic differences in sickness absence among Finnish municipal employees 1990-99

AIMS: This study examined the associations of key dimensions of socioeconomic status and long sickness absence spells as well as their changes over time from 1990 to 1999. METHODS: Municipal employees of the City of Helsinki, Finland, aged 25-59 were studied. The number of participants varied yearly from 24,029 women and 6,523 men to 27,861 women and 7,521 men. Socioeconomic status was assessed by education, occupational class, and individual income. The outcome was the number of over three days' sickness absence spells/100 person years, for which the employer requires medical certification. RESULTS: Low education, occupational class, and individual income were consistently associated with a 2-3 times higher sickness absence rates among both men and women. The age-adjusted sickness absence rates were relatively stable from 1990 to 1994 but increased from 1994 to 1999 among men and women. Socioeconomic differences in sickness absence rates tended to increase. CONCLUSIONS: The increase in the level of socioeconomic differences in sickness absence took place during a period of declining unemployment and staff increases at the City of Helsinki, which indicates that labour market conditions play a role in sickness absence.     

The generational transmission of socioeconomic inequalities in child cognitive development and emotional health

Socioeconomic inequalities in the health of adults have been largely attributed to lifestyle inequalities. The cognitive development (CD) and emotional health (EH) of the child provides a basis for many of the health-related behaviours which are observed in adulthood. There has been relatively little attention paid to the way CD and EH are transmitted in the foetal and childhood periods, even though these provide a foundation for subsequent socioeconomic inequalities in adult health. The Mater-University of Queensland Study of Pregnancy (MUSP) is a large, prospective, pre-birth cohort study which enrolled 8556 pregnant women at their first clinic visit over the period 1981-1983. These mothers (and their children) have been followed up at intervals until 14 years after the birth. The socioeconomic status of the child was measured using maternal age, family income, and marital status and the grandfathers' occupational status. Measures of child CD and child EH were obtained at 5 and 14 years of age. Child smoking at 14 years of age was also determined. Family income was related to all measures of child CD and EH and smoking, independently of all other indicators of the socioeconomic status of the child. In addition, the grandfathers' occupational status was independently related to child CD (at 5 and 14 years of age). Children from socioeconomically disadvantaged families (previous generations' socioeconomic status as well as current socioeconomic status) begin their lives with a poorer platform of health and a reduced capacity to benefit from the economic and social advances experienced by the rest of society.     

Comparison of the effects of low childhood socioeconomic position and low adulthood socioeconomic position on self rated health in four European studies

BACKGROUND: Socioeconomic inequalities in health are a persistent feature throughout Europe. Researchers and policy makers are increasingly using a lifecourse perspective to explain these inequalities and direct policy. However, there are few, if any, cross national lifecourse comparisons in this area. METHODS: Associations between socioeconomic position (SEP) in childhood and in adulthood and poor self rated health among men and women at midlife were tested in four European studies from England (n = 3615), France (n = 11 595), Germany (n = 4183), and the Netherlands (n = 3801). RESULTS: For women, mutually adjusted analyses showed significant associations between poor self rated health and low SEP in both childhood and adulthood in England and the Netherlands, only low childhood SEP in Germany and neither childhood nor adulthood SEP in France. For men, mutually adjusted analyses showed significant associations between poor self rated health and low SEP in both childhood and adulthood in France and the Netherlands, only with adult SEP in England and only with childhood SEP in Germany. CONCLUSION: In most countries adult SEP showed stronger associations with self rated health than childhood SEP. There are both gender and national differences in the associations between childhood and adulthood SEP. Policies designed to reduce inequalities in health need to incorporate a lifecourse perspective that is sensitive to different national and gender issues. Ultimately, more cross national studies are required to better understand these processes.     

Socioeconomic inequalities and mental health problems in children and adolescents: A systematic review

Socioeconomic inequalities in health are an important topic in social sciences and public health research. However, little is known about socioeconomic disparities and mental health problems in childhood and adolescence. This study systematically reviews publications on the relationships between various commonly used indicators of socioeconomic status (SES) and mental health outcomes for children and adolescents aged four to 18 years. Studies published in English or German between 1990 and 2011 were included if they reported at least one marker of socioeconomic status (an index or indicators, e.g., household income, poverty, parental education, parental occupation status, or family affluence) and identified mental health problems using validated instruments. In total, 55 published studies met the inclusion criteria, and 52 studies indicated an inverse relationship between socioeconomic status and mental health problems in children and adolescents. Socioeconomically disadvantaged children and adolescents were two to three times more likely to develop mental health problems. Low socioeconomic status that persisted over time was strongly related to higher rates of mental health problems. A decrease in socioeconomic status was associated with increasing mental health problems. The strength of the correlation varied with age and with different indicators of socioeconomic status, whereas heterogeneous findings were reported for gender and types of mental health problems. The included studies indicated that the theoretical approaches of social causation and classical selection are not mutually exclusive across generations and specific mental health problems; these processes create a cycle of deprivation and mental health problems. The review draws attention to the diversity of measures used to evaluate socioeconomic status, which might have influenced the comparability of international epidemiological studies. Furthermore, the review highlights the need for individual-level early childhood interventions as well as a reduction in socioeconomic inequalities at a societal level to improve mental health in childhood and adolescence.     

Socioeconomic inequalities and low birth weight and perinatal mortality in Rio de Janeiro, Brazil

Socioeconomic inequalities in early infant mortality have been evidenced in Brazil, with a greater mortality risk associated with the mother's socioeconomic status (SES). The aim of this paper is to identify socioeconomic inequalities in relation to low birth weight and perinatal mortality in the City of Rio de Janeiro, Brazil, discussing the appropriateness of the main health inequality indexes proposed in the international literature. As the information source, we use data collected in a survey of approximately 10,000 mothers selected for interview within 48 hours after delivery in public and private hospitals in the city. Using educational level and head of household's income as indicators of SES, as well as population attributable risk and slope index of inequality as health inequality measures, the results show a steep socioeconomic gradient in the proportion of low birth weight, and especially in the perinatal mortality rate. The persistent association between socioeconomic indicators and adverse results in pregnancy indicates (at least partially) the health system's inefficacy in diminishing perinatal health inequalities in Rio de Janeiro.     

Urban premature mortality in the U.S. between 1980 and 1990: changing roles of income inequality and social spending

Measuring the effects of policy and social inequality is complicated because inequalities and policies may have delayed or accumulative effects on health. The objective of this study is to build on the body of work on population mortality and income inequality by investigating the association between income inequality and mortality at the city level at two points in time (1980 and 1990) as well as to determine whether indicators of 1980 social policies of cities are associated with 1990 mortality rates due to delayed or accumulative effects. We found that 1980 income inequality and police spending is associated with increased premature mortality for 1990. In conclusion, there appear to be long-term consequences of city levels of income inequality on population health, although this relationship is incompletely understood. While a lack of information on how inequality operates on health should not preclude us from making policy decisions aimed at creating greater social equality, for example, through improvements in education, we would benefit from longitudinal research on specific macroeconomic and environmental factors, inequality, and health. Establishing such causal relationships is critical in creating social policies that optimally promote health and well-being.     

The impact of socioeconomic inequalities and lack of health insurance on physical functioning among middle-aged and older adults in the United States

Socioeconomic inequalities and lack of private health insurance have been viewed as significant contributors to health disparities in the United States. However, few studies have examined their impact on physical functioning over time, especially in later life. The current study investigated the impact of socioeconomic inequalities and lack of private health insurance on individuals' growth trajectories in physical functioning, as measured by activities of daily living. Data from the Health and Retirement Study (1994-2006) were used for this study, 6519 black and white adults who provided in-depth information about health, socioeconomic, financial and health insurance information were analysed. Latent growth curve modelling was used to estimate the initial level of physical functioning and its rate of change over time. Results showed that higher level of income and assets and having private health insurance significantly predicted better physical functioning. In particular, decline in physical functioning was slower among those who had private health insurance. Interestingly, changes in economic status, such as decreases in income and assets, had a greater impact on women's physical functioning than on men's. Black adults did not suffer more rapid declines in physical functioning than white adults after controlling for socioeconomic status. The current longitudinal study suggested that anti-poverty and health insurance policies should be enhanced to reduce the negative impact of socioeconomic inequalities on physical functioning throughout an individual's life course.     

How should interventions to reduce inequalities in health be evaluated?

OBJECTIVE: The effectiveness of interventions which have been proposed or are currently in progress to reduce socioeconomic inequalities in health is largely unknown. This paper aims to develop guidelines for evaluating these interventions. APPROACH: Starting from a set of general guidelines which was recently proposed by a group of experts reporting to the national Programme Committee on Socioeconomic Inequalities in Health in The Netherlands, an analysis was made of the appropriateness of different study designs which could be used to assess the effectiveness of interventions to reduce inequalities in health. RESULTS: A "full" study design requires the measurement, in one or more experimental populations and one or more control populations, of changes over time in the magnitude of socioeconomic inequalities in health. This will usually imply a community intervention trial. Five alternative study designs are distinguished which require less complex measurements but also require more assumptions to be made. Several examples are given. CONCLUSIONS: Building up a systematic knowledge base on the effectiveness of interventions to reduce socioeconomic inequalities in health will be a major enterprise. Elements of a strategy to increase learning speed are discussed. Although the guidelines and design recommendations developed in this paper apply to the evaluation of specific interventions where rigorous evaluation methods can often be used, they may also be useful for the interpretation of the results of less rigorous evaluation studies, for example of broader policies to reduce socioeconomic inequalities in health.     

Nimmt die gesundheitliche Ungleichheit zu?

The analyses focused on time trends in health inequalities in the 25 to 64-year-old population of Augsburg. The analyses are based on four independent cross-sectional surveys from the MONICA/KORA study covering 15 years: 1984/1985 (n?=?4,022), 1989/1990 (n?=?3,966), 1994/1995 (n?=?3,916) and 1999/2000 (n?=?3,492). Socioeconomic status (SES) was assessed by educational level and per capita household income with separate analyses for each of these two variables. Both absolute and relative health inequalities were calculated. The results showed that inequalities in self-rated health did not change very much (with some indications for increasing inequalities). However, concerning smoking the results clearly pointed towards increasing health inequalities (for example concerning relative inequalities among women by educational level: significant increase from survey to survey of about 20?%). The prevalence of obesity was increased in all SES groups but the inequalities did not change very much. These time trends show that the efforts aimed at reducing health inequalities should be intensified.     

Neighbourhoods and self rated health: a comparison of public sector employees in London and Helsinki

STUDY OBJECTIVE: Mortality and morbidity vary across neighbourhoods and larger residential areas. Effects of area deprivation on health may vary across countries, because of greater spatial separation of people occupying high and low socioeconomic positions and differences in the provision of local services and facilities. Neighbourhood variations in health and the contribution of residents' characteristics and neighbourhood indicators were compared in London and Helsinki, two settings where inequality and welfare policies differ. DESIGN: Data from two cohorts were used to investigate associations between self rated health and neighbourhood indicators using a multilevel approach. SETTING: London and Helsinki. PARTICIPANTS: From the Whitehall II study (London, aged 39-63) and the Helsinki health study (aged 40-60). MAIN RESULTS: Socioeconomic segregation was higher in London than in Helsinki. Age and sex adjusted differences in self rated health between neighbourhoods were also greater in London. Independent of individual socioeconomic position, neighbourhood unemployment, proportion of residents in manual occupations, and proportion of single households were associated with health. In pooled data, residence in a neighbourhood with highest unemployment was associated with an odds ratio of less than good self rated health of 1.51 (95% CI 1.30 to 1.75). High rates of single parenthood were associated with health in London but not in Helsinki. CONCLUSIONS: Neighbourhood socioeconomic context was associated with health in both countries, with some evidence of greater neighbourhood effects in London. Greater socioeconomic segregation in London may have emergent effects at the neighbourhood level. Local and national social policies may reduce, or restrict, inequality and segregation between areas.     

Geographical inequalities in health in New Zealand, 1980-200: the gap widens

OBJECTIVE: To monitor geographical inequalities in health in New Zealand during the period 1980 to 2001, a time of rapid social and economic change in society. METHODS: Age-standardised mortality rates were calculated using mortality records aggregated to a consistent set of geographical areas (the 2001 District Health Boards) for the periods 1980-82, 1985-87, 1990-92, 1995-97 and 1999-2001. In addition, the Relative Index of Inequality (RII) was calculated for each period to provide a robust measure of mortality rates over time. RESULTS: Although overall mortality rates have declined through the period 1980 to 2001, the reduction has not been consistent for all areas of New Zealand. Indeed for a small number of DHBs, mortality rates have increased slightly. There has been an increase in the geographical inequalities in health as measured by the RII between each time period except for between 1986 and 1991, where there was a small reduction. CONCLUSIONS: At the start of the 21st century, geographical inequalities in health in New Zealand have reached very high levels and continue to increase. The excess mortality for the worst areas in New Zealand increased from 15% in 1981 to 25% in 2000. If policy makers are committed to reducing health inequalities then more redistributive economic policies are required.     

Neighbourhood socioeconomic inequalities in incidence of acute myocardial infarction: a cohort study quantifying age- and gender-specific differences in relative and absolute terms

ABSTRACT: BACKGROUND: Socioeconomic status has a profound effect on the risk of having a first acute myocardial infarction (AMI). Information on socioeconomic inequalities in AMI incidence across age- gender-groups is lacking. Our objective was to examine socioeconomic inequalities in the incidence of AMI considering both relative and absolute measures of risk differences, with a particular focus on age and gender. METHODS: We identified all patients with a first AMI from 1997 to 2007 through linked hospital discharge and death records covering the Dutch population. Relative risks (RR) of AMI incidence were estimated by mean equivalent household income at neighbourhood-level for strata of age and gender using Poisson regression models. Socioeconomic inequalities were also shown within the stratified age-gender groups by calculating the total number of events attributable to socioeconomic disadvantage. RESULTS: Between 1997 and 2007, 317,564 people had a first AMI. When comparing the most deprived socioeconomic quintile with the most affluent quintile, the overall RR for AMI was 1.34 (95% confidence interval (CI): 1.32 - 1.36) in men and 1.44 (95% CI: 1.42 - 1.47) in women. The socioeconomic gradient decreased with age. Relative socioeconomic inequalities were most apparent in men under 35 years and in women under 65 years. The largest number of events attributable to socioeconomic inequalities was found in men aged 45-74 years and in women aged 65-84 years. The total proportion of AMIs that was attributable to socioeconomic inequalities in the Dutch population of 1997 to 2007 was 14% in men and 18% in women. CONCLUSIONS: Neighbourhood socioeconomic inequalities were observed in AMI incidence in the Netherlands, but the magnitude across age-gender groups depended on whether inequality was expressed in relative or absolute terms. Relative socioeconomic inequalities were high in young persons and women, where the absolute burden of AMI was low. Absolute socioeconomic inequalities in AMI were highest in the age-gender groups of middle-aged men and elderly women, where the number of cases was largest.     

Income-related health inequalities in France in 2004: Decomposition and explanations

BackgroundThis analysis supplements existing work on social health inequalities at two levels: the measurement of health and the measurement of inequalities. Firstly, individual health status was measured using a subjective health indicator corrected within a promising cardinalisation method which had not yet been carried out on French data. Secondly, this study used an innovative methodology to measure income-related health inequalities, to understand the relationships between income, income inequality, various social determinants, and health.MethodsThe analysis was based on a sample of working-age adults from the 2004 Health and Health Insurance Survey. The methodology used in the study measures the total income-related health inequality using the concentration index. This index is based on a linear model explaining health according to several individual characteristics, such as age, sex, and various socioeconomic characteristics. The method thus takes into account both the causal relationships between the various explicative factors introduced in the model and their relationship with health. Furthermore, it concretely measures the contribution of the social determinants to income-related health inequalities.ResultsThe results show an income-related health inequality favouring individuals with a higher income. Moreover, income level, supplementary private health insurance, education level, and social class account for the main contributions to inequality. Therefore, the decomposition method highlights population groups that policies should target.ConclusionThe study suggests that reducing income inequality is not sufficient to lower income-related health inequalities in France in 2004 and needs to be supplemented with the reduction of the relationship between income and health and the reduction of income inequality over socioeconomic status.