Article

Is wealthier always healthier? The impact of national income level, inequality, and poverty on public health in Latin America

Cambridge University, St. John's College, Cambridge CB2 1TP, United Kingdom.
Social Science [?] Medicine (Impact Factor: 2.56). 07/2010; 71(2):266-73. DOI: 10.1016/j.socscimed.2010.04.002
Source: PubMed

ABSTRACT Despite findings indicating that both national income level and income inequality are each determinants of public health, few have studied how national income level, poverty and inequality interact with each other to influence public health outcomes. We analyzed the relationship between gross domestic product (GDP) per capita in purchasing power parity, extreme poverty rates, the gini coefficient for personal income and three common measures of public health: life expectancy, infant mortality rates, and tuberculosis (TB) mortality rates. Introducing poverty and inequality as modifying factors, we then assessed whether the relationship between GDP and health differed during times of increasing, decreasing, and decreasing or constant poverty and inequality. Data were taken from twenty-two Latin American countries from 1960 to 2007 from the December 2008 World Bank World Development Indicators, World Health Organization Global Tuberculosis Database 2008, and the Socio-Economic Database for Latin America and the Caribbean. Consistent with previous studies, we found increases in GDP have a sizable positive impact on population health. However, the strength of the relationship is powerfully influenced by changing levels of poverty and inequality. When poverty was increasing, greater GDP had no significant effect on life expectancy or TB mortality, and only led to a small reduction in infant mortality rates. When inequality was rising, greater GDP had only a modest effect on life expectancy and infant mortality rates, and no effect on TB mortality rates. In sharp contrast, during times of decreasing or constant poverty and inequality, there was a very strong relationship between increasing GDP and higher life expectancy and lower TB and infant mortality rates. Finally, inequality and poverty were found to exert independent, substantial effects on the relationship between national income level and health. Wealthier is indeed healthier, but how much healthier depends on how increases in wealth are distributed.

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    • "In line with the works of Blakely et al. (2000) and Avendano (2012), different lag times were tested to take into account the delay between the " cause " and the " consequence " . Taking into account a lag in the manifestation of effects linked to change in income inequality is justified by the complexity of the mechanisms mentioned in Biggs et al. (2010), Young et al. (2012) and Qi (2012) (paragraph 2.1). The values of income inequality corresponding to periods ranging from year t−1 to t−17 were introduced into the model one by one, and their effect on infant mortality was measured. "
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    ABSTRACT: Purpose This paper presents a general impact assessment relationship, intended to contribute to the development of social life cycle analysis. This relationship and the conditions of its use are called the “Wilkinson pathway”. When used for comparisons, the pathway assesses the anticipated change in the infant mortality rate caused by a change in income distribution in the population of a country, itself generated by an important change in a life cycle. Methods Since the 1980s, numerous authors have examined the relationship between income inequality and human health. Without formally proving so, these studies suggest that increases in inequality have negative consequences for health. First, this effect is re-examined using the most up-to-date time series data. Econometric modelling allowed calculating the coefficients of variation of infant mortality in relation to variations in income inequality for member and non-member Organisation for Economic Cooperation and Development (OECD) countries, taking into account the lag time. Then, a method to translate the effect of an important economic change in a life cycle on income distribution is proposed. Results and discussion The econometric estimations show that a 1 % variation in income inequality leads to an approximately equivalent variation, with a lag time of about 15 years, in infant mortality in OECD member countries. The effect is two times larger than in non-OECD member countries. Together with input-output data, labour productivity and average wages in different economic sectors, this information makes it possible to quantify the probable effects of an important change in the life cycle production stage on income inequality and then infant mortality. Due to data constraints and the many assumptions made, the tools and results presented here should be used and interpreted cautiously. Above all, what is involved is a comparative method. An isolated result must not be interpreted in absolute terms. Conclusions This work is in line with efforts to formalize general pathways allowing a comparison of socioeconomic impacts linked to various important changes in the production stage of life cycles. There are diverse prospects for improvement. A challenge for further research will be to propose methods enabling assessments of the socioeconomic impacts generated in life cycle stages other than production.
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    • "Nevertheless, critics point to ever-severe social inequalities within municipalities, and within regions, in Argentina and Brazil; such inequalities are both income-and health-related (Etienne, 2013; Biggs et al., 2010). In order to better understand the effects of WB social inequality projects, this study asks: What kind of rationality does the WB use to justify its social inequality projects? "
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    • "Evidence for the hypothesis would support redistributive policies aimed at decreasing income inequality. With some exceptions (Wagstaff and van Doorslaer 2000; Mellor and Milyo 2001; Gravelle et al. 2002; Beckfield 2004; Jen et al. 2009), most of recent research has been supportive of the hypothesis ( Shmueli 2004; De Vogli et al. 2005; Ram 2006; Dorling et al. 2007; Babones 2008; Karlsson et al. 2009; Biggs et al. 2010; Idrovo et al. 2010). "
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