Health haves, health have nots, and heterogeneity in population health
Authors: Sandro Galea
Journal: The Lancet Public Health (2017)

There is approximately an 18-year difference in male life expectancy between Japan (80·5 years) and Sudan (62·4 years).1WHOWorld Health Statistics 2016: monitoring health for the Sustainable Development Goals. World Health Organization, Geneva2016Google Scholar The study by Laura Dwyer-Lindgren and colleagues2Dwyer-Lindgren L Stubbs RW Bertozzi-Villa A et al.Variation in life expectancy and mortality by cause among neighborhoods in King County, WA, USA, 1990–2014: a census tract-level analysis for the Global Burden of Disease Study 2015.Lancet Public Health. 2017; 2: e400-e410Summary Full Text Full Text PDF Scopus (34) Google Scholar in this issue of The Lancet Public Health shows that there is also an approximately 18-year difference in male life expectancy between the census tracts with the highest and the lowest life expectancy in King County, WA, USA. There is approximately a 14-year difference in female life expectancy between the UK (83·0 years) and Senegal (68·6 years),1WHOWorld Health Statistics 2016: monitoring health for the Sustainable Development Goals. World Health Organization, Geneva2016Google Scholar which is similar to the gap in the female life expectancy between the census tracts with the highest and lowest female life expectancy in King County.2Dwyer-Lindgren L Stubbs RW Bertozzi-Villa A et al.Variation in life expectancy and mortality by cause among neighborhoods in King County, WA, USA, 1990–2014: a census tract-level analysis for the Global Burden of Disease Study 2015.Lancet Public Health. 2017; 2: e400-e410Summary Full Text Full Text PDF Scopus (34) Google Scholar These data are perhaps more remarkable since overall health in King County is among the best in the USA, ranking in the 95th percentile among county health nationwide. Although public health writing often comments on the overall poor health indicators in the USA by comparison with peer high-income countries,3Institute of Medicine and National Research CouncilU.S. Health in international perspective: shorter lives, poorer health. The National Academies Press, Washington, DC2013Google Scholar and although recent publications have shown some of the deep health divides across counties in the USA,4Egan O Beatty K Blackley DJ Brown K Wykoff R Health and social conditions of the poorest versus wealthiest counties in the US.Am J Public Health. 2017; 107: 130-135Crossref PubMed Scopus (30) Google Scholar this paper is the first to show these enormous differences by census tracts within one, overall high performing county. These data are an important reminder of the health divides within the USA and occasion a revisit of three key principles that inform population health. First, these data highlight the health divides within one high-income country, casting a harsh light on the growing problem of health haves and health have nots in the USA. Health inequities have long characterised the US health landscape, tightly linked to both socioeconomic position and race or ethnicity. Although overall racial and ethnic health gaps are narrowing,5Harper S MacLehose RF Kaufman JS Trends in the black-white life expectancy gap among US states, 1990–2009.Health Aff. 2014; 33: 1375-1382Crossref Scopus (48) Google Scholar the gap between health indicators among the poorest 50% of Americans and the richest 50% is now wider than it has been in the past,6Bor J Cohen G Galea S Population health in an era of rising income inequality: USA, 1980–2015.Lancet. 2017; 389: 1475-1490Summary Full Text Full Text PDF PubMed Scopus (237) Google Scholar as it is between the richest and poorest quintiles.7National Academy of MedicineThe growing gap in life expectancy by income: implications for federal programs and policy responses. The National Academies Press, Washington, DC2015Google Scholar Simply put, a substantial proportion of the US population is gradually being left behind on health achievement. Apart from the moral challenge presented by such health inequities, these health gaps have broader national implications. For example, areas in the USA where wellbeing has deteriorated during the past decades overwhelmingly voted for Donald Trump—a protest candidate—in the last US election.8Bor J Diverging life expectancies and voting patterns in the 2016 US Presidential election.Am J Public Health. 2017; (published online Aug 17.)DOI:10.2105/AJPH.2017.303945PubMed Google Scholar The health implications of the actions of the Trump administration are pervasive, and, sadly, likely to further deepen these same health inequities that in part propelled his candidacy to the presidency.9Galea S How the Trump administration's health policies may harm the public's health.Milbank Q. 2017; 95: 229-232Crossref PubMed Scopus (4) Google Scholar The data from Dwyer-Lindgren and colleagues2Dwyer-Lindgren L Stubbs RW Bertozzi-Villa A et al.Variation in life expectancy and mortality by cause among neighborhoods in King County, WA, USA, 1990–2014: a census tract-level analysis for the Global Burden of Disease Study 2015.Lancet Public Health. 2017; 2: e400-e410Summary Full Text Full Text PDF Scopus (34) Google Scholar are a sobering reminder that these divides are not simply North–South or East–West divides in the USA but rather stark, geographically adjacent health differences. Second, the demonstration of intra-county health inequalities is a powerful reminder of the heterogeneity in population health, and how a study of such variability can point to the underlying causes of population health and, by extension, suggest paths to solutions. Population health science has long been concerned with aggregate health indicators. However, the study of variability can guide us to understand the factors that confer both vulnerability and resilience.10Galea S Ahern J Karpati A A model of underlying socioeconomic variability in human populations: evidence from variability in population health and implications for public health.Soc Sci Med. 2005; 60: 2417-2430Crossref PubMed Scopus (65) Google Scholar The demonstration of geographically proximate health variability raises several questions. What are the small-scale geographical variations in the causes of health that can explain these consequences? What are the characteristics of particular neighbourhoods that still have positive health indicators despite being marked by other vulnerabilities? Dwyer-Lindgren and colleagues take a first step in this direction, showing the pathologies that explained the observed heterogeneity. This analysis goes some way towards helping us to infer the factors that might be driving differences in, for example, ischaemic heart disease. The authors are correct in noting the behavioural factors that can contribute to these differences, and stop a step short of considering the structural conditions that in turn pattern behaviour and contribute to the observed health differences. One hopes that this work can lead to more comprehensive mapping of the geography of the foundational drivers of health, pointing to local action that can lead to improvement in the health of local populations. Third, this work reminds us of one of the most important challenges faced by those charged with improving the health of populations: the balance we need to strike between promoting overall health and the imperative of tackling health inequity. Population health is typically measured at a variety of administrative levels, typically in the USA at the county or the metropolitan statistical area level. It is therefore entirely rational that regional authorities aspire to measure their health successes at these levels as illustrated, for example, by the US county health rankings. Unfortunately, the easiest way to improve overall county health is through efforts that reach those who are easiest to reach, improving overall health by targeting the so-called already health haves. This approach stands to improve overall county health while widening intra-county health divides. This is a fundamental challenge in population health science11Keyes KM Galea S Setting the agenda for a new discipline: population health science.Am J Public Health. 2016; 106: 633-634Crossref PubMed Scopus (38) Google Scholar and requires an honest engagement with the values that ultimately determine what we choose to do and why we do it. Work that highlights the unconscionable health gaps within one of the healthiest counties in the USA should jolt us into a reckoning with the centrality of health inequalities to population health, and push us to consider the trade-offs we might have to make as we aspire to improve population health. In sum, the demonstration of substantial intra-county health variability in one of the healthiest counties in the USA is an important illustration of some core concepts in population health science. This work also pushes us to confront some of the challenges we face as we aim to improve the health of populations. One hopes that the findings of this study lead to the expansion of analytical research that provides further micro-level mapping of the foundational causes of population health, guiding efforts that can grapple with these causes with the aim of improving population health. I declare no competing interests. Variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, 1990–2014: a census tract-level analysis for the Global Burden of Disease Study 2015This census tract-level analysis of life expectancy and cause-specific YLL rates highlights important differences in health among neighbourhoods in King County that are masked by county-level estimates. Efforts to improve population health in King County should focus on reducing geographical inequality, by targeting those health conditions that contribute the most to overall YLLs and to inequality. This analysis should be replicated in other locations to more fully describe fine-grained local-level variation in population health and contribute to efforts to improve health while reducing inequalities. Full-Text PDF Open AccessPublic health is local“Public health is local, and similarly local information is required to increase awareness among residents and policy makers alike of the unique challenges facing communities”, conclude Laura Dwyer-Lindgren and colleagues in an Article published in this issue of The Lancet Public Health. In their study investigating variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, between 1990 and 2014, the Global Burden of Disease Study group applies latest small area estimation methods to mortality data in King County—a county that includes the city of Seattle, 2 million individuals, and where life expectancy is among the highest in the USA. Full-Text PDF Open Access