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Association Between Income Disparities and Risk of Chronic Kidney Disease

A Nationwide Cohort Study of Seven Million Adults in Korea



      To examine the association between income level and incident chronic kidney disease (CKD) in adults with normal baseline kidney function.

      Patient and Methods

      We studied the association between income level categorized into deciles and incident CKD in a national cohort comprised of 7,405,715 adults who underwent National Health Insurance Service health examinations during January 1, 2009, to December 31, 2015, with baseline estimated glomerular filtration rates (eGFRs) ≥60 mL/min/1.73 m2. Incident CKD was defined as de novo development of eGFR <60 mL/min/1.73 m2 (model 1) or ≥25% decline in eGFR from baseline values accompanied by eGFR <60 mL/min/1.73 m2 (model 2).


      During a median follow-up of 4.8 years, there were 122,032 of 7,405,715 (1.65%) and 55,779 of 7,405,715 (0.75%) incident CKD events based on model 1 and 2 definitions, respectively. Compared with income levels in the sixth decile, there was an inverse association between lower income level and higher risk for CKD up to the fourth decile, above which no additional reduction (model 1) or slightly higher risk for CKD (model 2) was observed at higher income levels. The multivariable-adjusted hazard ratios from the lowest to fourth deciles were 1.30 (95% CI, 1.26-1.33), 1.16 (95% CI, 1.13-1.19), 1.07 (95% CI, 1.05-1.10), and 1.06 (95% CI, 1.03-1.09) in model 1 and 1.32 (95% CI, 1.27-1.37), 1.18 (95% CI, 1.14-1.22), 1.08 (95% CI, 1.04-1.13), and 1.05 (95% CI, 1.01-1.09) in model 2, respectively. These associations persisted across various subgroups of age, sex, and comorbidity status.


      In this large nationwide cohort, lower income levels were associated with higher risk for incident CKD.

      Abbreviations and Acronyms:

      aHR (adjusted hazard ratio), CKD (chronic kidney disease), eGFR (estimated glomerular filtration rate), ESRD (end-stage renal disease), HR (hazard ratio), NHIS (National Health Insurance Service), SES (socioeconomic status)
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        • Hill N.R.
        • Fatoba S.T.
        • Oke J.L.
        • et al.
        Global prevalence of chronic kidney disease - a systematic review and meta-analysis.
        PLoS One. 2016; 11: e0158765
        • Thomas B.
        • Matsushita K.
        • Abate K.H.
        • et al.
        Global Burden of Disease 2013 GFR Collaborators; CKD Prognosis Consortium; Global Burden of Disease Genitourinary Expert Group. Global cardiovascular and renal outcomes of reduced GFR.
        J Am Soc Nephrol. 2017; 28: 2167-2179
        • Matsushita K.
        • van der Velde M.
        • Astor B.C.
        • et al.
        • Chronic Kidney Disease Prognosis Consortium
        Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis.
        Lancet. 2010; 375: 2073-2081
        • van der Velde M.
        • Matsushita K.
        • Coresh J.
        • et al.
        Lower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality. A collaborative meta-analysis of high-risk population cohorts.
        Kidney Int. 2011; 79: 1341-1352
        • Webster A.C.
        • Nagler E.V.
        • Morton R.L.
        • Masson P.
        Chronic kidney disease.
        Lancet. 2017; 389: 1238-1252
        • Jha V.
        • Garcia-Garcia G.
        • Iseki K.
        • et al.
        Chronic kidney disease: global dimension and perspectives.
        Lancet. 2013; 382: 260-272
        • World Kidney Day
        Chronic kidney disease.
        • Allen L.
        • Williams J.
        • Townsend N.
        • et al.
        Socioeconomic status and non-communicable disease behavioural risk factors in low-income and lower-middle-income countries: a systematic review.
        Lancet Glob Health. 2017; 5: e277-e289
        • Lago S.
        • Cantarero D.
        • Rivera B.
        • et al.
        Socioeconomic status, health inequalities and non-communicable diseases: a systematic review.
        Z Gesundh Wiss. 2018; 26: 1-14
        • Biswas T.
        • Islam M.S.
        • Linton N.
        • Rawal L.B.
        Socio-economic inequality of chronic non-communicable diseases in Bangladesh.
        PLoS One. 2016; 11: e0167140
        • Bauman A.
        • Phongsavan P.
        • Schoeppe S.
        • Chey T.
        Noncommunicable disease risk factors and socioeconomic inequalities – what are the links? A multicountry analysis of noncommunicable disease surveillance data. Report to the WHO Regional Office for the Western Pacific.
        • Nicholas S.B.
        • Kalantar-Zadeh K.
        • Norris K.C.
        Socioeconomic disparities in chronic kidney disease.
        Adv Chronic Kidney Dis. 2015; 22: 6-15
        • Ward M.M.
        Socioeconomic status and the incidence of ESRD.
        Am J Kidney Dis. 2008; 51: 563-572
        • Dodd R.
        • Palagyi A.
        • Guild L.
        • Jha V.
        • Jan S.
        The impact of out-of-pocket costs on treatment commencement and adherence in chronic kidney disease: a systematic review.
        Health Policy Plan. 2018; 33: 1047-1054
        • Kwon S.
        Thirty years of national health insurance in South Korea: lessons for achieving universal health care coverage.
        Health Policy Plan. 2009; 24: 63-71
        • Song S.O.
        • Jung C.H.
        • Song Y.D.
        • et al.
        Background and data configuration process of a nationwide population-based study using the Korean National Health Insurance System.
        Diabetes Metab J. 2014; 38: 395-403
        • Levey A.S.
        • Stevens L.A.
        • Schmid C.H.
        • et al.
        CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate.
        Ann Intern Med. 2009; 150: 604-612
      1. National Health Insurance Statistical Year Book 2015. Seoul: National Health Insurance Service, Health Insurance Review & Assessment Service.
        Date accessed: November 28, 2019
        • Levin A.
        • Stevens P.E.
        Summary of KDIGO 2012 CKD Guideline: behind the scenes, need for guidance, and a framework for moving forward.
        Kidney Int. 2014; 85: 49-61
        • Inker L.A.
        • Astor B.C.
        • Fox C.H.
        • et al.
        KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD.
        Am J Kidney Dis. 2014; 63: 713-735
        • Grams M.E.
        • Rebholz C.M.
        • McMahon B.
        • et al.
        Identification of incident CKD stage 3 in research studies.
        Am J Kidney Dis. 2014; 64: 214-221
        • Kovesdy C.P.
        • Alrifai A.
        • Gosmanova E.O.
        • et al.
        Age and outcomes associated with BP in patients with incident CKD.
        Clin J Am Soc Nephrol. 2016; 11: 821-831
        • Chetty R.
        • Stepner M.
        • Abraham S.
        • et al.
        The association between income and life expectancy in the United States, 2001-2014.
        JAMA. 2016; 315: 1750-1766
        • Stringhini S.
        • Carmeli C.
        • Jokela M.
        • et al.
        • LIFEPATH Consortium
        Socioeconomic status, non-communicable disease risk factors, and walking speed in older adults: multi-cohort population based study.
        BMJ. 2018; 360: k1046
        • Assari S.
        • Lankarani M.M.
        Income gradient in renal disease mortality in the United States.
        Front Med (Lausanne). 2017; 4: 190
        • Bruce M.A.
        • Beech B.M.
        • Crook E.D.
        • et al.
        Association of socioeconomic status and CKD among African Americans: the Jackson Heart Study.
        Am J Kidney Dis. 2010; 55: 1001-1008
        • Morton R.L.
        • Schlackow I.
        • Staplin N.
        • et al.
        • SHARP Collaborative Group
        Impact of educational attainment on health outcomes in moderate to severe CKD.
        Am J Kidney Dis. 2016; 67: 31-39
        • Vart P.
        • Gansevoort R.T.
        • Coresh J.
        • Reijneveld S.A.
        • Bültmann U.
        Socioeconomic measures and CKD in the United States and the Netherlands.
        Clin J Am Soc Nephrol. 2013; 8: 1685-1693
        • Krop J.S.
        • Coresh J.
        • Chambless L.E.
        • et al.
        A community-based study of explanatory factors for the excess risk for early renal function decline in blacks vs whites with diabetes: the Atherosclerosis Risk in Communities study.
        Arch Intern Med. 1999; 159: 1777-1783
        • Merkin S.S.
        • Diez Roux A.V.
        • Coresh J.
        • Fried L.F.
        • Jackson S.A.
        • Powe N.R.
        Individual and neighborhood socioeconomic status and progressive chronic kidney disease in an elderly population: the Cardiovascular Health Study.
        Soc Sci Med. 2007; 65: 809-821
        • Crews D.C.
        • McClellan W.M.
        • Shoham D.A.
        • et al.
        Low income and albuminuria among REGARDS (Reasons for Geographic and Racial Differences in Stroke) study participants.
        Am J Kidney Dis. 2012; 60: 779-786
        • Peralta C.A.
        • Ziv E.
        • Katz R.
        • et al.
        African ancestry, socioeconomic status, and kidney function in elderly African Americans: a genetic admixture analysis.
        J Am Soc Nephrol. 2006; 17: 3491-3496
        • Vart P.
        • Grams M.E.
        • Ballew S.H.
        • Woodward M.
        • Coresh J.
        • Matsushita K.
        Socioeconomic status and risk of kidney dysfunction: the Atherosclerosis Risk in Communities study [published online ahead of print June 11, 2018]. Nephrol Dial Transplant.
        • Lee J.C.
        Health care reform in South Korea: success or failure?.
        Am J Public Health. 2003; 93: 48-51
        • Gutiérrez O.M.
        • Anderson C.
        • Isakova T.
        • et al.
        • CRIC Study Group
        Low socioeconomic status associates with higher serum phosphate irrespective of race.
        J Am Soc Nephrol. 2010; 21: 1953-1960
        • Gutiérrez O.M.
        • Isakova T.
        • Enfield G.
        • Wolf M.
        Impact of poverty on serum phosphate concentrations in the Third National Health and Nutrition Examination Survey.
        J Ren Nutr. 2011; 21: 140-148
        • Gutiérrez O.M.
        • Katz R.
        • Peralta C.A.
        • et al.
        Associations of socioeconomic status and processed food intake with serum phosphorus concentration in community-living adults: the Multi-Ethnic Study of Atherosclerosis (MESA).
        J Ren Nutr. 2012; 22: 480-489
        • Gutiérrez O.M.
        Contextual poverty, nutrition, and chronic kidney disease.
        Adv Chronic Kidney Dis. 2015; 22: 31-38
        • Seligman H.K.
        • Davis T.C.
        • Schillinger D.
        • Wolf M.S.
        Food insecurity is associated with hypoglycemia and poor diabetes self-management in a low-income sample with diabetes.
        J Health Care Poor Underserved. 2010; 21: 1227-1233
        • Seligman H.K.
        • Laraia B.A.
        • Kushel M.B.
        Food insecurity is associated with chronic disease among low-income NHANES participants.
        J Nutr. 2010; 140: 304-310
        • Abate N.
        • Chandalia M.
        The impact of ethnicity on type 2 diabetes.
        J Diabetes Complications. 2003; 17: 39-58
        • Harris M.I.
        • Flegal K.M.
        • Cowie C.C.
        • et al.
        Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third National Health and Nutrition Examination Survey, 1988-1994.
        Diabetes Care. 1998; 21: 518-524
        • Sampson U.K.
        • Edwards T.L.
        • Jahangir E.
        • et al.
        Factors associated with the prevalence of hypertension in the southeastern United States: insights from 69,211 blacks and whites in the Southern Community Cohort Study.
        Circ Cardiovasc Qual Outcomes. 2014; 7: 33-54
        • Signorello L.B.
        • Schlundt D.G.
        • Cohen S.S.
        • et al.
        Comparing diabetes prevalence between African Americans and whites of similar socioeconomic status.
        Am J Public Health. 2007; 97: 2260-2267
        • Hossain M.P.
        • Goyder E.C.
        • Rigby J.E.
        • El Nahas M.
        CKD and poverty: a growing global challenge.
        Am J Kidney Dis. 2009; 53: 166-174
        • Chin H.J.
        • Ahn J.M.
        • Na K.Y.
        • et al.
        The effect of the World Kidney Day campaign on the awareness of chronic kidney disease and the status of risk factors for cardiovascular disease and renal progression.
        Nephrol Dial Transplant. 2010; 25: 413-419
        • Mahmood U.
        • Healy H.G.
        • Kark A.
        • et al.
        Spectrum (characteristics) of patients with chronic kidney disease (CKD) with increasing age in a major metropolitan renal service.
        BMC Nephrol. 2017; 18: 372
        • Neild G.H.
        Primary renal disease in young adults with renal failure.
        Nephrol Dial Transplant. 2010; 25: 1025-1032
        • Choi A.I.
        • Weekley C.C.
        • Chen S.C.
        • et al.
        Association of educational attainment with chronic disease and mortality: the Kidney Early Evaluation Program (KEEP).
        Am J Kidney Dis. 2011; 58: 228-234

      Linked Article

      • Money Matters: Income and Risk of Chronic Kidney Disease in South Korea
        Mayo Clinic ProceedingsVol. 95Issue 2
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          There is little debate that socioeconomic factors such as income, education, and employment play fundamental roles in determining health outcomes, and their inequitable distribution is a root cause of health and health care disparities. Lower income is associated with a higher risk of all-cause mortality as compared with higher income,1 and the burden of numerous health conditions has been noted in many settings to be greater in persons with low socioeconomic status (SES).
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