Ecological analysis of the health effects of income inequality in Argentina

Intraurban socioeconomic inequalities in life expectancy: a population-based cross-sectional analysis in the city of Córdoba, Argentina (2015-2018)

OBJECTIVES

To evaluate variability in life expectancy at birth in small areas, describe the spatial pattern of life expectancy, and examine associations between small-area socioeconomic characteristics and life expectancy in a mid-sized city of a middle-income country.

DESIGN

Cross-sectional, using data from death registries (2015-2018) and socioeconomic characteristics data from the 2010 national population census.

PARTICIPANTS/SETTING

40 898 death records in 99 small areas of the city of Córdoba, Argentina. We summarised variability in life expectancy at birth by using the difference between the 90th and 10th percentile of the distribution of life expectancy across small areas (P90-P10 gap) and evaluated associations with small-area socioeconomic characteristics by calculating a Slope Index of Inequality in linear regression.

PRIMARY OUTCOME

Life expectancy at birth.

RESULTS

The median life expectancy at birth was 80.3 years in women (P90-P10 gap=3.2 years) and 75.1 years in men (P90-P10 gap=4.6 years). We found higher life expectancies in the core and northwest parts of the city, especially among women. We found positive associations between life expectancy and better small-area socioeconomic characteristics, especially among men. Mean differences in life expectancy between the highest versus the lowest decile of area characteristics in men (women) were 3.03 (2.58), 3.52 (2.56) and 2.97 (2.31) years for % adults with high school education or above, % persons aged 15-17 attending school, and % households with water inside the dwelling, respectively. Lower values of % overcrowded households and unemployment rate were associated with longer life expectancy: mean differences comparing the lowest versus the highest decile were 3.03 and 2.73 in men and 2.57 and 2.34 years in women, respectively.

CONCLUSION

Life expectancy is substantially heterogeneous and patterned by socioeconomic characteristics in a mid-sized city of a middle-income country, suggesting that small-area inequities in life expectancy are not limited to large cities or high-income countries.

SOCIOECONOMIC INEQUALITIES IN SELF-REPORTED HEALTH AND PHYSICAL FUNCTIONING IN ARGENTINA: FINDINGS FROM THE NATIONAL SURVEY ON QUALITY OF LIFE OF OLDER ADULTS 2012 (ENCaViAM)

This study aimed to evaluate educational and income inequalities in self-reported health (SRH), and physical functioning (limitations in Activities of Daily Living (ADL)/Instrumental Activities of Daily Living (IADL)), among 60-year-old and older adults in Argentina. Using cross-sectional data from the Argentinian National Survey on Quality of Life of Older Adults 2012 (Encuesta Nacional sobre Calidad de Vida de Adultos Mayores, ENCaViAM), gender-specific socioeconomic inequalities in SRH and ADL and IADL limitations were studied in relation to educational level and household per capita income. The Relative Index of Inequality (RII) - an index of the relative size of socioeconomic inequalities in health - was used. Socioeconomic inequalities in the studied health indicators were found - except for limitations in ADL among women - favouring socially advantaged groups. The results remained largely significant after full adjustment, suggesting that educational and income inequalities, mainly in SRH and IADL, were robust and somehow independent of age, marital status, physical activity, the use of several medications, depression and the occurrence of falls. The findings add to the existing knowledge on the relative size of the socioeconomic inequalities in subjective health indicators among Argentinian older adults, which are to the detriment of lower socioeconomic groups. The results could be used to inform planning interventions aimed at decreasing socioeconomic inequalities in health, to the benefit of socially disadvantaged adults.

Poverty and inequality - but of what - as social determinants of health in Africa?

BACKGROUND

Many African economies have achieved substantial economic growth over the past recent years, yet several of the Millennium Development Goals (MDGs) including those concerned with health, remain considerably behind target. This paper examines whether progress towards these goals is being hampered by existing levels of poverty and income inequality. It also considers whether the inequality hypothesis of Wilkinson and Pickett1 applies to population health outcomes in African states.

METHODS

Correlation analysis and scatter plots were used to assess graphically the link between variations in health outcomes, level of poverty and income inequality in different countries. Health status outcomes were measured by using four indicators: infant and under-five (child) mortality rates; maternal mortality ratios; and life expectancy at birth. In each of the 52 African nations, the proportion of the population living below the poverty line is used as an indicator of the level of poverty and Gini coefficient as a measure of income inequality. The study used a comprehensive review of secondary and relevant literature that are pertinent in the subject area. The data datasets obtained online from UNICEF2 and UNDP3 (2009) used to test the research questions. World Health Organization the three broad dimensions to consider when moving towards better population health outcome through Universal Health Coverage and the Social Determinants of Health framework reviewed to establish the poverty and income inequality link in African countries population health outcomes.

RESULTS

The study shows that poverty is strongly associated with all health outcome differences in Africa (IMR, cc = 0.63; U5MR, cc = 0.64; MMR, cc = 0.49; life expectancy at birth, cc = -0.67); income inequality with only one of the four indicators (IMR, cc = 0.14; U5MR, cc = 0.07; MMR, cc = 0.22; life expectancy at birth, cc = -0.49), whereas income inequality is associated with one of the four indicators.

CONCLUSION

The study shows that tackling poverty should be the immediate concern in Africaas a means of promoting better health for all. There is a question mark over whether the findings of Wilkinson and Pickett1 on the relationship between income inequality and health apply to Africa. The reasons for this question mark are discussed. More research is needed to investigate whether the inequality results found in this study are replicated in other studies of African health.

A Swiss paradox? Higher income inequality of municipalities is associated with lower mortality in Switzerland

It has long been surmised that income inequality within a society negatively affects public health. However, more recent studies suggest there is no association, especially when analyzing small areas. This study aimed to evaluate the effect of income inequality on mortality in Switzerland using the Gini index on municipality level. The study population included all individuals >30 years at the 2000 Swiss census (N = 4,689,545) living in 2,740 municipalities with 35.5 million person-years of follow-up and 456,211 deaths over follow-up. Cox proportional hazard regression models were adjusted for age, gender, marital status, nationality, urbanization, and language region. Results were reported as hazard ratios (HR) with 95% confidence intervals. The mean Gini index across all municipalities was 0.377 (standard deviation 0.062, range 0.202-0.785). Larger cities, high-income municipalities and tourist areas had higher Gini indices. Higher income inequality was consistently associated with lower mortality risk, except for death from external causes. Adjusting for sex, marital status, nationality, urbanization and language region only slightly attenuated effects. In fully adjusted models, hazards of all-cause mortality by increasing Gini index quintile were HR = 0.99 (0.98-1.00), HR = 0.98 (0.97-0.99), HR = 0.95 (0.94-0.96), HR = 0.91 (0.90-0.92) compared to the lowest quintile. The relationship of income inequality with mortality in Switzerland is contradictory to what has been found in other developed high-income countries. Our results challenge current beliefs about the effect of income inequality on mortality on small area level. Further investigation is required to expose the underlying relationship between income inequality and population health.

Long-term exposure to income inequality: implications for physical functioning at older ages

The 'inequality hypothesis' proposes that higher levels of societal income inequality have a direct negative causal effect on health. Support for this hypothesis has been mixed; particularly among older people. However, most previous studies have not accounted for people's exposure to inequality over the long-term. We aimed to address this problem by examining the implications of long-term inequality exposure for older people's physical health. Data on individual health and covariates were drawn from three large, comparable surveys of older people, covering 16 countries: the English Longitudinal Study of Ageing, the Survey of Health and Retirement in Europe and the U.S. Health and Retirement Study. Historical inequality information was derived from the Standardised World Income Inequality Database. We used multilevel regression methods to model the association between long-term average inequality and three measures of physical functioning: grip strength, lung function and self-reported activity limitation. Exposure to higher average long-term levels of inequality was significantly negatively related to objectively measured grip strength and lung function, but unrelated to self-reported limitations (although increasing inequality over time was positively related to self-reported limitations). The grip strength and lung function associations were partially explained by between-country differences in height, and in the latter case this factor may fully account for the apparent effect of inequality. We discuss implications of these results for the inequality hypothesis.

Assessing the context of health care utilization in Ecuador: a spatial and multilevel analysis

BACKGROUND

There are few studies that have analyzed the context of health care utilization, particularly in Latin America. This study examines the context of utilization of health services in Ecuador; focusing on the relationship between provision of services and use of both preventive and curative services.

METHODS

This study is cross-sectional and analyzes data from the 2004 National Demographic and Maternal & Child Health dataset. Provider variables come from the Ecuadorian System of Social Indicators (SIISE). Global Moran's I statistic is used to assess spatial autocorrelation of the provider variables. Multilevel modeling is used for the simultaneous analysis of provision of services at the province-level with use of services at the individual level.

RESULTS

Spatial analysis indicates no significant differences in the density of health care providers among Ecuadorian provinces. After adjusting for various predisposing, enabling, need factors and interaction terms, density of public practice health personnel was positively associated with use of preventive care, particularly among rural households. On the other hand, density of private practice physicians was positively associated with use of curative care, particularly among urban households.

CONCLUSIONS

There are significant public/private, urban/rural gaps in provision of services in Ecuador; which in turn affect people's use of services. It is necessary to strengthen the public health care delivery system (which includes addressing distribution of health workers) and national health information systems. These efforts could improve access to health care, and inform the civil society and policymakers on the advances of health care reform.

An average/deprivation/inequality (ADI) analysis of chronic disease outcomes and risk factors in Argentina

Background

Recognition of the global economic and epidemiological burden of chronic non-communicable diseases has increased in recent years. However, much of the research on this issue remains focused on individual-level risk factors and neglects the underlying social patterning of risk factors and disease outcomes.

Methods

Secondary analysis of Argentina's 2005 Encuesta Nacional de Factores de Riesgo (National Risk Factor Survey, N = 41,392) using a novel analytical strategy first proposed by the United Nations Development Programme (UNDP), which we here refer to as the Average/Deprivation/Inequality (ADI) framework. The analysis focuses on two risk factors (unhealthy diet and obesity) and one related disease outcome (diabetes), a notable health concern in Latin America. Logistic regression is used to examine the interplay between socioeconomic and demographic factors. The ADI analysis then uses the results from the logistic regression to identify the most deprived, the best-off, and the difference between the two ideal types.

Results

Overall, 19.9% of the sample reported being in poor/fair health, 35.3% reported not eating any fruits or vegetables in five days of the week preceding the interview, 14.7% had a BMI of 30 or greater, and 8.5% indicated that a health professional had told them that they have diabetes or high blood pressure. However, significant variation is hidden by these summary measures. Educational attainment displayed the strongest explanatory power throughout the models, followed by household income, with both factors highlighting the social patterning of risk factors and disease outcomes. As educational attainment and household income increase, the probability of poor health, unhealthy diet, obesity, and diabetes decrease. The analyses also point toward important provincial effects and reinforce the notion that both compositional factors (i.e., characteristics of individuals) and contextual factors (i.e., characteristics of places) are important in understanding the social patterning of chronic diseases.

Conclusion

The application of the ADI framework enables identification of the regions or groups worst-off for each outcome measure under study. This can be used to highlight the variation embedded within national averages; as such, it encourages a social perspective on population health indicators that is particularly attuned to issues of inequity. The ADI framework is an important tool in the evaluation of policies aiming to prevent or control chronic non-communicable diseases.