, 37:75 | Cite as

Aging and low-grade inflammation reduce renal function in middle-aged and older adults in Japan and the USA

  • Reagan Costello-White
  • Carol D. Ryff
  • Christopher L. Coe


The objective of this study was to investigate the effects of low-grade inflammation on age-related changes in glomerular filtration rate (GFR) in middle-aged and older white Americans, African-Americans, and Japanese adults. Serum creatinine, C-reactive protein (CRP), and interleukin-6 (IL-6) levels were determined for 1570 adult participants in two surveys of aging in the USA and Japan (N = 1188 and 382, respectively). Kidney function declined with age in both countries and was associated with IL-6 and CRP. IL-6 and CRP also influenced the extent of the arithmetic bias when calculating the GFR using the chronic kidney disease epidemiology (CKD-EPI) formula with just serum creatinine. Younger African-Americans initially had the highest GFR but showed a steep age-related decrement that was associated with elevated inflammation. Japanese adults had the lowest average GFR but evinced a large effect of increased inflammatory activity when over 70 years of age. Importantly, our results also indicate that low-grade inflammation is important to consider when evaluating kidney function solely from serum creatinine.


Inflammation Interleukin-6 C-reactive protein Kidney Glomerular filtration rate Race Aging Gender Japanese African-American 



This research was supported by grants from the National Institute on Aging (5R37 AG027343, P01 AG020166) to conduct the Midlife in Japan (MIDJA) and Midlife in the US (MIDUS) studies. The specimen collection was facilitated by the General Clinical Research Centers program (M01-RR023942 [Georgetown], M01-RR00865 [UCLA]), and at UW from the Clinical and Translational Science Award (CTSA) program of the National Center for Research Resources (1UL1RR025011). The contributions of Drs. G Love, M. Karasawa, and N. Kawakami and Ms. D. Brar in specimen collection and processing are gratefully acknowledged.


  1. Artom M, Moss-Morris R, Caskey F, Chilcot J (2014) Fatigue in advanced kidney disease. Kidney Int 86(3):497–505CrossRefPubMedGoogle Scholar
  2. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476):307–310CrossRefPubMedGoogle Scholar
  3. Bonner A, Caltabiano M, Berlund L (2013) Quality of life, fatigue, and activity in Australians with chronic kidney disease: a longitudinal study. Nurs Health Sci 15(3):360–367CrossRefPubMedGoogle Scholar
  4. Coe CL, Love GD, Karasawa M, Kawakami N, Kitayama S, Markus HR, Tracy RP, Ryff CD (2011) Population differences in proinflammatory biology: Japanese have healthier profiles than Americans. Brain Behav Immun 25(3):494–502PubMedCentralCrossRefPubMedGoogle Scholar
  5. Coresh J, Astor BC, Greene T, Eknoyan G, Levey AS (2003) Prevalence of chronic kidney disease and decreased kidney function in the adult US population: third national health and nutrition examination survey. Am J Kidney Dis 41(1):1–12CrossRefPubMedGoogle Scholar
  6. Coresh J, Selvin E, Stevens LA, Mani J, Kusek JW, Eggers P, Van Lente F, Levey AS (2007) Prevalence of chronic kidney disease and decreased kidney function in the United States. J Am Med Assoc 298(17):2038–2047CrossRefGoogle Scholar
  7. Crews DC, Sozio SM, Liu Y, Coresh J, Powe NR (2011) Inflammation and the paradox of racial differences in dialysis survival. J Am Soc Nephrol 22(12):2279–2286PubMedCentralCrossRefPubMedGoogle Scholar
  8. Dalui A, Guha P, Chakraborty S, Chakraborty I (2014) Assessment of stress & related albuminuria in caregivers of severely mentally ill persons. Indian J Med Res 139(1):174–177PubMedCentralPubMedGoogle Scholar
  9. Gupta J, Mitra N, Kanetsky PA, Devaney J, Wing MR, Reilly M, Shah VO, Balakrishnan VS, Guzman NJ, Girndt M, Periera BG, Feldman HI, Kusek JW, Joffe MM, Raj DS (2012) Association between albuminuria, kidney function, and inflammatory biomarker profile in CKD in CRIC. Clin J Am Soc Nephrol 7(12):1938–1946PubMedCentralCrossRefPubMedGoogle Scholar
  10. Hasings C, Mosteller F, Tukey J, Winsor C (1947) Low moments for small samples: a comparative study of order statistics. Ann Math Stat 18:413–426CrossRefGoogle Scholar
  11. Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S (2010) Modification of the CKD epidemiology collaboration (CKD-EPI) equation for Japanese: accuracy and use for population estimates. Am J Kidney Dis 56(1):32–38CrossRefPubMedGoogle Scholar
  12. Imai E, Horio M, Watanabe T, Iseki K, Yamagata K, Hara S, Ura N, Kiyohara Y, Moriyama T, Ando Y, Fujimoto S, Konta T, Yokoyama H, Makino H, Hishida A, Matsuo S (2009) Prevalence of chronic kidney disease in the Japanese general population. Clin Exp Nephrol 13:621–630CrossRefPubMedGoogle Scholar
  13. Kramer H, Palmas W, Kestenbaum B, Cushman M, Allison M, Astor B, Shilpak M (2008) Chronic kidney disease prevalence estimates among racial/ethnic groups: the Multi-Ethnic Study of Atherosclerosis. Clin J Am Nephrol 3(5):1391–1397CrossRefGoogle Scholar
  14. Kshiragar AV, Bomback AS, Bang H, Gerber LM, Vupputuri S, Shoham DA, Mazumdar M, Ballantyne CM, Paparello JJ, Klemmer PJ (2008) Association of C-reactive protein and microalbuminuria (from the National Health and Nutrition Examination Surveys, 1999–2004). Am J Cardiol 101(3):401–406CrossRefGoogle Scholar
  15. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman H, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J, CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150(9):504–612CrossRefGoogle Scholar
  16. Love G, Seeman TE, Weinstein M, Ryff CD (2010) Bioindicators in the MIDUS national study: protocol, measures, sample, and well-being. J Aging Health 22:1059–1080PubMedCentralCrossRefGoogle Scholar
  17. Mallappallil M, Friedman EA, Delano BG, McFarlane SI, Slifu MO (2014) Chronic kidney disease in the elderly: evaluation and management. Clin Pract (Lond) 11(5):525–535Google Scholar
  18. Marshall Jr MC (2005) Diabetes in African Americans. Postgrad Med Ed 734-40Google Scholar
  19. Mosteller RD (1987) Simplified calculation of body-surface area. N Engl J Med 317(17):1098PubMedGoogle Scholar
  20. Nitta K, Okada K, Yanai M, Takahashi S (2013) Aging and chronic kidney disease. Kidney Blood Press Res 38(1):109–120CrossRefPubMedGoogle Scholar
  21. Noone D, Licht C (2014) Chronic kidney disease: a new look at pathogenetic mechanisms and treatment options. Pediatr Nephrol 29:771–784CrossRefGoogle Scholar
  22. Pertosa G, Grandalliano G, Gesualdo L, Schena FP (2000) Clinical relevance of cytokine production in hemodialysis. Kidney Int 58(76):S-104–S-111CrossRefGoogle Scholar
  23. Radler BT (2014) The Midlife in the United States (MIDUS) series: a national longitudinal study of health and well-being. Open Health Data 2(1):e3. doi: 10.5334/ PubMedCentralCrossRefPubMedGoogle Scholar
  24. Radler BT, Ryff CD (2010) Who participates? Accounting for longitudinal retention in the MIDUS national study of health and well-being. J Aging Health 286:327–334Google Scholar
  25. Randall OS, Retta TM, Kwagyan J, Gordeuk VR, Maqbool AR, Ketete M, Obisan TO (2004) Obese African Americans: the prevalence of dyslipidemia, hypertension, and diabetes mellitus. Ethn Dis 14(3):383–388Google Scholar
  26. Safar M, Plante GE, Mimran A (2014) Arterial stiffness, pulse pressure, and the kidney. Am J Hypertens. doi: 10.1093/ajh/hpu206 Google Scholar
  27. Silverwood R, Richards M, Pierce MP, Hardy R, Sattar N, Ferro C, Savage C, Kuh D, Nitsch D, On behalf of the NSHD scientific and data collection teams (2014) Cognitive and kidney function: results from a British birth cohort reaching retirement age. PLoS ONE 9(1):e86734CrossRefGoogle Scholar
  28. Sinha SK, Shaheen M, Rajavashisth TB, Pan D, Norris KC, Nicolas SB (2014) Association of race/ethnicity, inflammation, and albuminuria in patients with diabetes and early chronic kidney disease. Diabetes Care 37(4):1060–1068PubMedCentralCrossRefPubMedGoogle Scholar
  29. Stevens LA, Coresh J, Greene T, Levey AS (2006) Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med 354(23):2473–2483Google Scholar
  30. Sud M, Tangri N, Levin A, Pintilie M, Levey A, Naimark DM (2014) CKD stage at nephrology referral and factors influencing risks of ESRD and death. Am J Kidney Dis 63(6):928–936CrossRefPubMedGoogle Scholar
  31. Tbahriti HF, Meknassi D, Moussaoui R, Messaoudi A, Zemour L, Kaddous A, Bouchenak M, Mekki K (2013) Inflammatory status in chronic renal failure: the role of homocysteinemia and pro-inflammatory cytokines. World J Nephrol 2(2):31–37PubMedCentralCrossRefPubMedGoogle Scholar
  32. Tsuda A, Ishimura E., Ohno Y, Ichi, M., Nakatani, S., Machida, Y., Mori, K., Uchida, J., Fukumoto, S., Emoto, M., Nakatani, T., Inaba, M., (2014). Poor glycemic control is a major factor in the overestimation of glomerular filtration rate in diabetic patients. Diabetes Care 37:596-603.CrossRefPubMedGoogle Scholar
  33. Weiner JM, Tilly J (2002) Population ageing in the United States of America: implications for public programmes. Int J Epidemiol 31:776–781CrossRefGoogle Scholar
  34. Yamagata K, Yagisawa T, Nakai S, Nakayama M, Imai E, Hattori M, Iseki K, Akiba T (2014) Prevalence and incidence of chronic kidney disease stage G5 in Japan. Clin Exp Nephrol 19(1):54–64CrossRefPubMedGoogle Scholar

Copyright information

© American Aging Association 2015

Authors and Affiliations

  • Reagan Costello-White
    • 1
  • Carol D. Ryff
    • 1
  • Christopher L. Coe
    • 1
  1. 1.University of WisconsinMadisonUSA

Personalised recommendations