Are County Codes More Indicative of Kidney Health Than Genetic Codes?

Abstract

Related Article, p. 19 Related Article, p. 19 Within the United States, striking disparities in life expectancy exist by race, ethnicity, socioeconomic status, and geography.1Chetty R. Stepner M. Abraham S. et al.The association between income and life expectancy in the United States, 2001-2014.JAMA. 2016; 26 (315(16):1750-1766)Google Scholar, 2Dwyer-Lindgren L. Bertozzi-Villa A. Stubbs R.W. et al.Inequalities in life expectancy among US counties, 1980 to 2014: temporal trends and key drivers.JAMA Intern Med. 2017; 177: 1003-1011Crossref PubMed Scopus (253) Google Scholar As with health disparities in chronic diseases such as end-stage renal disease (ESRD), life expectancy itself reflects diverse biological, social, economic, and geographic determinants. In the United States, lower income is strongly linked to premature mortality, and the differences in life expectancy across income groups appear to be increasing over time.1Chetty R. Stepner M. Abraham S. et al.The association between income and life expectancy in the United States, 2001-2014.JAMA. 2016; 26 (315(16):1750-1766)Google Scholar Regrettably, more than 43 million Americans continue to live below the federal poverty line and many more subsist just above it.3Kneebone E. The growth and spread of concentrated poverty, 2000 to 2008-2012. Brookings: Metropolitan Opportunity Series. https://www.brookings.edu/interactives/the-growth-and-spread-of-concentrated-poverty-2000-to-2008-2012/. Accessed February 13, 2018.Google Scholar However, the distribution of low-income Americans has shifted following the economic downturn of the 2000s, and more low-income people now reside in suburbs or unincorporated areas than in large cities or rural communities. As a result, concentrated poverty has spread to more areas in the United States that often lack the service delivery infrastructure more common to large urban centers.3Kneebone E. The growth and spread of concentrated poverty, 2000 to 2008-2012. Brookings: Metropolitan Opportunity Series. https://www.brookings.edu/interactives/the-growth-and-spread-of-concentrated-poverty-2000-to-2008-2012/. Accessed February 13, 2018.Google Scholar In this issue of AJKD, Schold et al combine multiple data sources to examine the relations of life expectancy and measures of the presence and quality of nephrology care before ESRD onset (pre-ESRD nephrology care) among 606,046 adults aged 18 to 70 years who initiated ESRD treatment between 2006 and 2013.3Kneebone E. The growth and spread of concentrated poverty, 2000 to 2008-2012. Brookings: Metropolitan Opportunity Series. https://www.brookings.edu/interactives/the-growth-and-spread-of-concentrated-poverty-2000-to-2008-2012/. Accessed February 13, 2018.Google Scholar The analysis was performed at the county level (the United States comprises 3,142 counties that are uniquely identified using Federal Information Processing Standards [FIPS] codes).4Schold J.D. Flechner S.M. Poggio E.D. et al.Residential area life expectancy: Association with outcomes and processes of care for patients with ESRD in the United States.Am J Kidney Dis. 2018; 72: 19-29Abstract Full Text Full Text PDF PubMed Scopus (12) Google Scholar The investigators linked patient-level data from the US Renal Data System registry with census data, including life expectancy, from the county of residence. They observed significant inverse associations between county-level life expectancy and individual-level prevalence of pre-ESRD nephrology care, arteriovenous fistula use as initial hemodialysis access, preemptive kidney transplantation, and survival on dialysis. The findings by Schold et al align with prior reports that have linked area-level measures of health insurance coverage, socioeconomic status, and racial-ethnic composition with the presence and quality of pre-ESRD nephrology care.5Kinchen K.S. Sadler J. Fink N. et al.The timing of specialist evaluation in chronic kidney disease and mortality.Ann Intern Med. 2002; 137: 479-486Crossref PubMed Scopus (403) Google Scholar, 6McClellan W.M. Wasse H. McClellan A.C. Kipp A. Waller L.A. Rocco M.V. Treatment center and geographic variability in pre-ESRD care associate with increased mortality.J Am Soc Nephrol. 2009; 20: 1078-1085Crossref PubMed Scopus (63) Google Scholar, 7Prakash S. Rodriguez R.A. Austin P.C. et al.Racial composition of residential areas associates with access to pre-ESRD nephrology care.J Am Soc Nephrol. 2010; 21: 1192-1199Crossref PubMed Scopus (48) Google Scholar, 8Kurella-Tamura M. Goldstein B.A. Hall Y.N. Mitani A.A. Winkelmayer W.C. State Medicaid coverage, ESRD incidence, and access to care.J Am Soc Nephrol. 2014; 25: 1321-1329Crossref PubMed Scopus (36) Google Scholar For years, timely nephrology care before ESRD onset has been linked not only to fewer biochemical abnormalities and increased use of permanent vascular access, but also to higher rates of kidney transplantation and lower rates of hospitalization and death following dialysis initiation.5Kinchen K.S. Sadler J. Fink N. et al.The timing of specialist evaluation in chronic kidney disease and mortality.Ann Intern Med. 2002; 137: 479-486Crossref PubMed Scopus (403) Google Scholar, 6McClellan W.M. Wasse H. McClellan A.C. Kipp A. Waller L.A. Rocco M.V. Treatment center and geographic variability in pre-ESRD care associate with increased mortality.J Am Soc Nephrol. 2009; 20: 1078-1085Crossref PubMed Scopus (63) Google Scholar, 7Prakash S. Rodriguez R.A. Austin P.C. et al.Racial composition of residential areas associates with access to pre-ESRD nephrology care.J Am Soc Nephrol. 2010; 21: 1192-1199Crossref PubMed Scopus (48) Google Scholar, 8Kurella-Tamura M. Goldstein B.A. Hall Y.N. Mitani A.A. Winkelmayer W.C. State Medicaid coverage, ESRD incidence, and access to care.J Am Soc Nephrol. 2014; 25: 1321-1329Crossref PubMed Scopus (36) Google Scholar The findings by Schold et al may help explain why US spending on health care does not favorably correlate with population health metrics such as life expectancy. Although the United States now spends more than $34 billion annually to provide care for Medicare beneficiaries with ESRD, access to timely nephrology care remains elusive for many Americans, particularly for vulnerable individuals with earlier stages of chronic kidney diseases (CKD), who often lack the health insurance benefits of the Medicare ESRD program. In using life expectancy as a latent variable, Schold et al highlight the collective and complex contextual determinants that drive disparities in health and disease.4Schold J.D. Flechner S.M. Poggio E.D. et al.Residential area life expectancy: Association with outcomes and processes of care for patients with ESRD in the United States.Am J Kidney Dis. 2018; 72: 19-29Abstract Full Text Full Text PDF PubMed Scopus (12) Google Scholar In many instances, life expectancy can be traced to behavioral risk factors such as tobacco smoking, diet, and activity patterns, which in turn are associated with wide social, economic, and educational differences.1Chetty R. Stepner M. Abraham S. et al.The association between income and life expectancy in the United States, 2001-2014.JAMA. 2016; 26 (315(16):1750-1766)Google Scholar, 2Dwyer-Lindgren L. Bertozzi-Villa A. Stubbs R.W. et al.Inequalities in life expectancy among US counties, 1980 to 2014: temporal trends and key drivers.JAMA Intern Med. 2017; 177: 1003-1011Crossref PubMed Scopus (253) Google Scholar For example, Robeson County is the poorest county in North Carolina, and it ranks last in nearly every metric of health in the state.9US Census Bureau. 2016 State & county Quickfacts: Robeson County, NC. http://quickfacts.census.gov. Accessed February 13, 2018.Google Scholar Life expectancy at birth is markedly lower than national sex-specific estimates: men and women die on average 6.3 and 4.4 years prematurely, respectively. Notably, 1 in 3 men and 1 in 4 women smoke cigarettes (as compared with 22% of men and 18% of women nationally). In addition, 41% of men and 54% of women are obese, and sex-specific mortality rates attributed to “diabetes, urogenital, blood and endocrine diseases” are double those observed nationally.10Saran R. Robinson B. Abbott K.C. et al.US Renal Data System 2016 annual data report: epidemiology of kidney disease in the United States.Am J Kidney Dis. 2017; 69: A7-A8Abstract Full Text Full Text PDF PubMed Scopus (636) Google Scholar Perhaps unsurprisingly, incidence rates of ESRD rank among the highest nationwide (Fig 111Saran R. Robinson B. Abbott K.C. et al.US Renal Data System 2017 Annual Data Report: epidemiology of kidney disease in the United States.Am J Kidney Dis. 2018; 71: S1-S672PubMed Google Scholar). Importantly, the study by Schold et al reinforces an ongoing need to uncover specific mechanisms underlying pervasive disparities in CKD, including persistent deficiencies in the surveillance of health care provided to nonelderly adults in earlier stages of kidney diseases. Based on their results, approximately 31% to 37% of adults initiating ESRD treatment had not received nephrology care within the 12 months preceding ESRD onset. For many low-income nonelderly Americans, the period before ESRD onset represents a void in chronic disease surveillance.12Hall Y.N. Choi A.I. Chertow G.M. Bindman A.B. Chronic kidney disease in the urban poor.Clin J Am Soc Nephrol. 2010; 5: 828-835Crossref PubMed Scopus (62) Google Scholar This gap in care is especially wide for residents of traditionally underserved communities who are more likely to receive ambulatory care from clinics that are supported by charity or municipal funds, with little capacity for structured CKD surveillance.13Rocco P. Gellad W.F. Donohue J.M. Modernizing Medicaid managed care: can states meet the data challenges?.JAMA. 2015; 314: 1559-1560Crossref PubMed Scopus (1) Google Scholar In addition, despite the central and expanding role of Medicaid in covering diverse and vulnerable populations, current and standardized data such as diagnoses, procedures, and measures of care use are not readily available for its enrollees in many states. Apart from county-level determinants, the scope of state-level health insurance coverage for vulnerable groups certainly is a platform for timely nephrology care. In addition, other area-level factors likely play important roles in accessing effective care in earlier stages of CKD. For example, the supply, training, and availability of primary and subspecialty care providers, as well as physical factors such as the location and offerings of health care facilities, have been linked with access to care and care delivery before and after the onset of ESRD.14Rodriguez R.A. Sen S. Mehta K. Moody-Ayers S. Bacchetti P. O'Hare A.M. Geography matters: relationships among urban residential segregation, dialysis facilities, and patient outcomes.Ann Intern Med. 2007; 146: 493-501Crossref PubMed Scopus (155) Google Scholar, 15Tonelli M. Klarenbach S. Rose C. Wiebe N. Gill J. Access to kidney transplantation among remote- and rural-dwelling patients with kidney failure in the United States.JAMA. 2009; 301: 1681-1690Crossref PubMed Scopus (67) Google Scholar Among geographic attributes, adjustment for median income attenuated the associations between life expectancy and most clinical outcomes, whereas adjustment for population size and urban-rurality did not. Building on the initial work of Schold et al, additional analyses into proxies of health care resources (eg, per-capita supply of primary care or subspecialty providers within each county) may provide further insight into whether differences in specific resources influence variations in life expectancy and nephrology care. Additional analyses that examine digital, spatial, or physical barriers to health care and health education (eg, internet use, smart phone penetration, and availability of public transportation) may also lead to enhanced insight into the study’s findings. It is also important to note that the study by Schold et al used estimates of nephrology care based only on patients who lived long enough to start treatment for ESRD. Because most patients with CKD die before reaching ESRD, use of life expectancy as a primary exposure likely underestimates the magnitude of disparities in primary and nephrology care. Globally, the burden of CKD has continued to grow for almost every country in the world, and most of it occurs disproportionately in people living in low- or middle-income countries, where an estimated 80% of the 500 million people living with CKD reside.16Stanifer J.W. Muiru A. Jafar T. Patel U.D. Chronic kidney disease in low-income countries.Nephrol Dial Transplant. 2016; 31: 868-874Crossref PubMed Scopus (133) Google Scholar Worldwide, the attributed causes of CKD are diverse and range from communicable diseases (human immunodeficiency virus [HIV], hepatitis B and C, and parasitic diseases) to toxic exposures (nonsteroidal analgesics, pesticides, and contaminated products) to noncommunicable diseases (diabetes mellitus, hypertension, and immunoglobulin A nephropathy).16Stanifer J.W. Muiru A. Jafar T. Patel U.D. Chronic kidney disease in low-income countries.Nephrol Dial Transplant. 2016; 31: 868-874Crossref PubMed Scopus (133) Google Scholar However, considering variability in the quality and reporting consistency of methods for assessing kidney function, the approach taken by Schold et al may have salience beyond the United States. In low- and middle-income counties, where demographic transitions and lifestyle changes parallel rapid urbanization and increasingly crowded cities (where unplanned infrastructure, poor sanitation, haphazard waste disposal, and heavy environmental pollution abound), innovative studies that incorporate readily available health metrics; for example, using life expectancy as a lens into social determinants of health, may provide better understanding of the dimensions and causes of CKD, as well as insight into population-based approaches to address important risk factors. To better understand and address racial-ethnic and geographic disparities in kidney diseases in Robeson County, we have used a systems science approach that leverages an extensive network of collaborators and stakeholders. This network extends far beyond nephrologists and includes local medical providers, nonprofit organizations, and community leaders. We are also building research capacity and developing broader research themes by optimizing electronic data sources and increasing transdisciplinary training that incorporates multilevel social determinants. Unfortunately, the broader nephrology community remains slow in recognizing and addressing the complex and stark disparities that persist within our patient populations, and Schold et al provide compelling evidence that we need to do much more. Because most of the variation in life expectancy across areas likely stems from differences in health behaviors rather than access to subspecialty care, we need to embrace broader population health initiatives that are supported by timely dependable data and systematic health promotion.1Chetty R. Stepner M. Abraham S. et al.The association between income and life expectancy in the United States, 2001-2014.JAMA. 2016; 26 (315(16):1750-1766)Google Scholar, 2Dwyer-Lindgren L. Bertozzi-Villa A. Stubbs R.W. et al.Inequalities in life expectancy among US counties, 1980 to 2014: temporal trends and key drivers.JAMA Intern Med. 2017; 177: 1003-1011Crossref PubMed Scopus (253) Google Scholar Because many states and municipal governments persist with policies that undermine our ability to achieve health equity, we should continue to push for reforms that aim to reduce marked inequities in social determinants such as income, housing, education, and health insurance coverage.17Marks J.S. Why your zip code may be more important than your genetic code.The Huffington Post. May 25, 2011; (Accessed January 4, 2018)https://www.huffingtonpost.com/james-s-marks/why-your-zip-code-may-be_b_190650.htmlGoogle Scholar, 18Ludwig J. Duncan G.J. Gennetian L.A. et al.Neighborhood effects on the long-term well-being of low-income adults.Science. 2012; 337: 1505-1510Crossref PubMed Scopus (440) Google Scholar, 19Schroeder S.A. Shattuck Lecture. We can do better–improving the health of the American people.N Engl J Med. 2007; 357: 1221-1228Crossref PubMed Scopus (724) Google Scholar, 20Herd P. Goesling B. House J.S. Socioeconomic position and health: the differential effects of education versus income on the onset versus progression of health problems.J Health Soc Behav. 2007; 48: 223-238Crossref PubMed Scopus (260) Google Scholar These keys to better longevity hold the greatest long-term potential to promote health equity in nephrology, particularly for society’s most vulnerable constituents. Residential Area Life Expectancy: Association With Outcomes and Processes of Care for Patients With ESRD in the United StatesAmerican Journal of Kidney DiseasesVol. 72Issue 1PreviewThe effects of underlying noncodified risks are unclear on the prognosis of patients with end-stage renal disease (ESRD). We aimed to evaluate the association of residential area life expectancy with outcomes and processes of care for patients with ESRD in the United States. Full-Text PDF