Unpacking income inequality and population health: the peculiar absence of geography

Income inequality and population health: a political-economic research agenda

There is more than 30 years of research on relationships between income inequality and population health. In this article, we propose a research agenda with five recommendations for future research to refine existing knowledge and examine new questions. First, we recommend that future research prioritise analyses with broader time horizons, exploring multiple temporal aspects of the relationship. Second, we recommend expanding research on the effect of public expenditures on the inequality-health relationship. Third, we introduce a new area of inquiry focused on interactions between social mobility, income inequality and population health. Fourth, we argue the need to examine new perspectives on 21st century capitalism, specifically the population health impacts of inequality in income from capital (especially housing), in contrast to inequality in income from labour. Finally, we propose that this research broaden beyond all-cause mortality, to cause-specific mortality, avoidable mortality and subcategories thereof. We believe that such a research agenda is important for policy to respond to the changes following the COVID-19 pandemic.

Geospatial cluster analyses of pneumonia-associated hospitalisations among adults in New York City, 2010-2014

Pneumonia is a leading cause of death in New York City (NYC). We identified spatial clusters of pneumonia-associated hospitalisation for persons residing in NYC, aged ⩾18 years during 2010-2014. We detected pneumonia-associated hospitalisations using an all-payer inpatient dataset. Using geostatistical semivariogram modelling, local Moran's I cluster analyses and χ2 tests, we characterised differences between 'hot spots' and 'cold spots' for pneumonia-associated hospitalisations. During 2010-2014, there were 141 730 pneumonia-associated hospitalisations across 188 NYC neighbourhoods, of which 43.5% (N = 61 712) were sub-classified as severe. Hot spots of pneumonia-associated hospitalisation spanned 26 neighbourhoods in the Bronx, Manhattan and Staten Island, whereas cold spots were found in lower Manhattan and northeastern Queens. We identified hot spots of severe pneumonia-associated hospitalisation in the northern Bronx and the northern tip of Staten Island. For severe pneumonia-associated hospitalisations, hot-spot patients were of lower mean age and a greater proportion identified as non-Hispanic Black compared with cold spot patients; additionally, hot-spot patients had a longer hospital stay and a greater proportion experienced in-hospital death compared with cold-spot patients. Pneumonia prevention efforts within NYC should consider examining the reasons for higher rates in hot-spot neighbourhoods, and focus interventions towards the Bronx, northern Manhattan and Staten Island.

Does Social Context Matter? Income Inequality, Racialized Identity, and Health Among Canada's Aboriginal Peoples Using a Multilevel Approach

OBJECTIVES

Debates surrounding the importance of social context versus individual level processes have a long history in public health. Aboriginal peoples in Canada are very diverse, and the reserve communities in which they reside are complex mixes of various cultural and socioeconomic circumstances. The social forces of these communities are believed to affect health, in addition to individual level determinants, but no large scale work has ever probed their relative effects. One aspect of social context, relative deprivation, as indicated by income inequality, has greatly influenced the social determinants of health landscape. An investigation of relative deprivation in Canada's Aboriginal population has never been conducted. This paper proposes a new model of Aboriginal health, using a multidisciplinary theoretical approach that is multilevel.

METHODS

This study explored the self-rated health of respondents using two levels of determinants, contextual and individual. Data were from the 2001 Aboriginal Peoples Survey. There were 18,890 Registered First Nations (subgroup of Aboriginal peoples) on reserve nested within 134 communities. The model was assessed using a hierarchical generalized linear model.

RESULTS

There was no significant variation at the contextual level. Subsequently, a sequential logistic regression analysis was run. With the sole exception culture, demographics, lifestyle factors, formal health services, and social support were significant in explaining self-rated health.

CONCLUSIONS

The non-significant effect of social context, and by extension relative deprivation, as indicated by income inequality, is noteworthy, and the primary role of individual level processes, including the material conditions, social support, and lifestyle behaviors, on health outcomes is illustrated. It is proposed that social structure is best conceptualized as a dynamic determinant of health inequality and more multilevel theoretical models of Aboriginal health should be developed and tested.

The role of geographic scale in testing the income inequality hypothesis as an explanation of health disparities

This study re-examined the role of geographic scale in measuring income inequality and testing the income inequality hypothesis (IIH) as an explanation of health disparities. We merged Behavioral Risk Factor Surveillance System (BRFSS) 2000 data with income inequality indices constructed at different geographic scales to test the association between income inequality and four different health indicators, i.e., self-assessed health status as a morbidity measure, vaccination against influenza as a measure of use of preventive healthcare, having any kind of health insurance as a measure of access, and obesity as a modifiable health risk factor measure. Multilevel models are used in our regression of the health indicators on measures of income inequalities and control variables. Our analysis suggests that because income inequality is a contextual variable, income inequalities measured at different geographic scales have different interpretations and relate to societal characteristics at different levels. Therefore, a rejection of the IIH at one level does not necessarily negate the possibility that income inequality affects health at another level. Assessment across a variety of scales is needed to have a comprehensive picture of the IIH in any given study. Empirical results also show that whether the IIH holds could depend on the sex group examined and the health indicator used, which implies different mechanisms of IIH exist for different sex groups and health indicators, in addition to the geographic scale. The role of geographic scale should be more rigorously considered in social determinants of health research.