Clinical and Experimental Nephrology

, Volume 22, Issue 4, pp 850–859 | Cite as

Glucosuria and all-cause mortality among general screening participants

  • Kunitoshi IsekiEmail author
  • Tsuneo Konta
  • Koichi Asahi
  • Kunihiro Yamagata
  • Shouichi Fujimoto
  • Kazuhiko Tsuruya
  • Ichiei Narita
  • Masato Kasahara
  • Yugo Shibagaki
  • Toshiki Moriyama
  • Masahide Kondo
  • Chiho Iseki
  • Tsuyoshi Watanabe
  • For the “Design of the Comprehensive Health Care System for Chronic Kidney Disease (CKD) Based on the Individual Risk Assessment by Specific Health Check”
Original article



Dipstick urine tests are used for general health screening in Japan, but how the test results (e.g., glucosuria) relate to mortality is unknown.


Subjects participated in a nationwide screening in 2008 in six districts in Japan. We identified those who might have died using the national database of death certificates from 2008 to 2012 (total registered ~ 6 million) and verified candidates with the regional National Health Insurance Agency and public health nurses. Diabetes mellitus (DM) was defined as HbA1c ≥ 6.5%, fasting blood glucose ≥ 126 mg/dl, or medicated for DM. Hazard ratio (HR) and 95% confidence interval (CI) were calculated by Cox proportional hazard analysis. Glucosuria was defined as dipstick ≥ 1 +.


Among 209,060 subjects, we identified 2714 fatalities (median follow-up 3.57 years). Crude mortality rates were 1.2% for those without glucosuria and 3.4% for those with glucosuria. After adjusting for sex, age, body mass index, comorbidity (DM, hypertension, and dyslipidemia), history (stroke, heart disease, and kidney disease), and lifestyle (smoking, drinking, walking, and exercise), the HR (95% CI) for dipstick glucosuria was 1.475 (1.166–1.849, P < 0.001). DM subjects with glucosuria (N = 4655) had a higher HR [1.302 (1.044–1.613, P = 0.020)] than DM subjects without glucosuria (N = 20,245), and non-DM subjects with glucosuria (N = 470) had a higher HR [2.511 (1.539–3.833, P < 0.001)] than non-DM subjects without glucosuria (N = 183,690).


Dipstick glucosuria significantly affected mortality in Japanese community-based screening participants.


Glucosuria Proteinuria Chronic kidney disease (CKD) Mortality rate Obesity 



This study was not possible without the generous support of the public health nurses, the Kokuho Agency in each district. This work was supported by a Health and Labor Sciences Research Grants for “Study on the design of the comprehensive health care system for chronic kidney disease (CKD) based on the individual risk assessment by Specific Health Checkup” from the Ministry of Health, Labor and Welfare of Japan, and a Grant-in-Aid for “Research on Advanced Chronic Kidney Disease (REACH-J), Practical Research Project for Renal Disease” from the Japan Agency for Medical Research and Development, AMED.

Compliance with ethical standards

Conflict of interest

All authors have declared that no conflict of interest exists.

Ethics approval

All procedures performed in studies involving human participants were performed in accordance with the ethical standards of the institutional and/or national research committee at which the studies were conducted (Fukushima Medical University; IRB Approval Number #1485, #2771) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

This study was performed according to Ethical Guidelines for Medical and Health Research Involving Human Subjects enacted by MHLW of Japan [ and]. In the context of the guideline, the investigators shall not necessarily be required to obtain informed consent, but we made public information concerning this study on the web [] and ensured the opportunities for the research subjects to refuse use of their personal information.


  1. 1.
  2. 2.
    Iseki K, Asahi K, Moriyama T, et al. Risk factor profiles based on eGFR and dipstick proteinuria: analysis of the participants of the Specific Health Check and Guidance System in Japan 2008. Clin Exp Nephrol. 2012;16:244–9.CrossRefPubMedGoogle Scholar
  3. 3.
    Iseki K, Asahi K, Yamagata K, et al. Mortality risk among screened subjects of the Specific Health Check and Guidance Program in Japan 2008–2012. Clin Exp Nephrol. 2017. (Epub ahead of print).
  4. 4.
    Iseki K, Konta T, Asahi K, et al. Association of dipstick hematuria with all-cause mortality in the general population: results from the Specific Health Check and Guidance Program in Japan. Nephrol Dial Transpl. 2017. (Epub ahead of print).CrossRefGoogle Scholar
  5. 5.
    Calado J, Loeffler J, Sakallioglu O, et al. Familial renal glucosuria: SLC5A2 mutation analysis and evidence of salt-wasting. Kidney Int. 2006;59:852–5.CrossRefGoogle Scholar
  6. 6.
    Haque SK, Ariceta G, Batlle D. Proximal renal tubular acidosis: a not so rare disorder of multiple etiologies. Nephrol Dial Transpl. 2012;27:4273–87.CrossRefGoogle Scholar
  7. 7.
    Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med. 2015;373(22):2117–28.CrossRefPubMedGoogle Scholar
  8. 8.
    Wanner C, Inzucchi SE, Lachin JM, et al. Empagliflozin and progression of kidney disease in type 2 diabetes. N Engl J Med. 2016;375(4):323–34.CrossRefPubMedGoogle Scholar
  9. 9.
    DeFronzo RA, Norton L, Abdul-Ghani M. Renal, metabolic and cardiovascular considerations of SGLT2 inhibition. Nat Rev Nephrol. 2017;13:11–26.CrossRefPubMedGoogle Scholar
  10. 10.
    Hung CC, Lin HYH, Lee JJ, et al. Glycosuria and renal outcomes in patients with nondiabetic advanced chronic kidney disease. Sci Rep. 2016;6:39372.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Matsuo S, Imai E, Horio M, et al. Collaborators developing the Japanese equation for estimated GFR. Revised equations for estimated GFR from serum creatinine in Japan. Am J Kidney Dis. 2009;53(6):982–92.CrossRefPubMedGoogle Scholar
  12. 12.
    American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2011;34(Suppl 1):S62–S69.CrossRefPubMedCentralGoogle Scholar
  13. 13.
    Sato Y, Yano Y, Fujimoto S, et al. Glycohemoglobin not as predictive as fasting glucose as a measure of prediabetes in predicting proteinuria. Nephrol Dial Transpl. 2012;27(10):3862–8.CrossRefGoogle Scholar
  14. 14.
    Lal RA, Maahs DM. Clinical use of continuous glucose monitoring in pediatrics. Diabetes Technol Ther. 2017;19(S2):S37–S43.CrossRefPubMedGoogle Scholar
  15. 15.
    Kovatchev BP. Metrics for glycaemic control—from HbA1c to continuous glucose monitoring. Nat Rev Endocrinol. 2017;13(7):425–36.CrossRefPubMedGoogle Scholar
  16. 16.
    Andersson DK, Lundblad E, Svardsudd K. A model for early diagnosis of type 2 diabetes mellitus in primary health care. Diabetes Med. 1993;10:167–73.CrossRefGoogle Scholar
  17. 17.
    Kondo M, Yamagata K, Hoshi SL, et al. Budget impact analysis of chronic kidney disease mass screening test in Japan. Clin Exp Nephrol. 2014;18(6):885 – 91.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Nagai M, Murakami Y, Tamakoshi A, et al. Fasting but not casual blood glucose is associated with pancreatic cancer mortality in Japanese: EPOCH-JAPAN. Cancer Causes Control. 2017;28(6):625–33.CrossRefPubMedGoogle Scholar
  19. 19.
    Perkovic V, Agarwal R, Fioretto P, et al. Management of patients with diabetes and CKD: conclusions from a “Kidney Disease: improving Global Outcomes” (KDIGO) Controversies Conference. Kidney Int. 2016;90:1175–83.CrossRefPubMedGoogle Scholar
  20. 20.
    Wang JY, Yang JH, Xu J, et al. Renal tubular damage may contribute more to acute hyperglycemia induced kidney injury in non-diabetic conscious rats. J Diabetes Complicat. 2015;29:621–8.CrossRefPubMedGoogle Scholar
  21. 21.
    Slyne J, Slattery C, McMorrow T, et al. New developments concerning the proximal tubule in diabetic nephropathy: in vitro models and mechanisms. Nephrol Dial Transpl. 2015;30(Suppl 4):iv60–i67.CrossRefGoogle Scholar
  22. 22.
    Nordquist L, Friederich-Persson M, Fasching A, et al. Activation of hypoxia-inducible factors prevents diabetic nephropathy. J Am Soc Nephrol. 2015;26:328 – 38.CrossRefPubMedGoogle Scholar
  23. 23.
    Tang SC, Yiu WH, Lin M, et al. Diabetic nephropathy and proximal tubular damage. J Ren Nutr. 2015;25:230–3.CrossRefPubMedGoogle Scholar
  24. 24.
    Terami N, Ogawa D, Tachibana H, et al. Long-term treatment with the sodium glucose cotransporter 2 inhibitor, dapagliflozin, ameliorates glucose homeostasis and diabetic nephropathy in db/db mice. PLoS One. 2014;9:e100777.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Neal B, Perkovic V, Mahaffey KW, et al. Canagliflozin and cardiovascular and renal events in type 2 diabetes. N Engl J Med. 2017. (Epub ahead of print).CrossRefPubMedGoogle Scholar
  26. 26.
    Wanner C. EMPA-REG outcome: the nephrologist’s point of view. Am J Cardiol. 2017;120(suppl):S59-S67.PubMedGoogle Scholar
  27. 27.
    Wakisaka M, Nagao T. Sodium glucose cotransporter 2 in mesangial cells and retinal pericytes and its implications for diabetic nephropathy and retinopathy. Glycobiology. 2017. (Epub ahead of print).PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Selph S, Dana T, Blazina I, et al. Screening for type 2 diabetes mellitus: a systematic review for the US Preventive Services Task Force. Ann Intern Med. 2015;162:765–76.CrossRefPubMedGoogle Scholar
  29. 29.
    Zhang L, Long J, Jiang W, et al. Trends in chronic kidney disease in China. N Engl J Med. 2016;375(9):905–6.CrossRefPubMedGoogle Scholar
  30. 30.
    Barzilai N, Crandall JP, Kritchevsky SB, Espeland MA. Metformin as a tool to target aging. Cell Matb. 2016;23:1060–5.CrossRefGoogle Scholar
  31. 31.
    Griffin SJ, Leaver JK, Irving GJ. Impact of metformin on cardiovascular disease: a meta-analysis of randomized trials among people with type 2 diabetes. Diabetologia. 2017;60:1620–9.CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Kocogullari CU, Kunt AT, Aksoy R, et al. Hemoglobin A1c predicts acute kidney injury after coronary artery bypass surgery in non-diabetic patients. Braz J Cardiovasc Surg. 2017;32(2):83 – 9.PubMedPubMedCentralGoogle Scholar
  33. 33.
    Krolewski AS, Skupien J, Rossing P, et al. Fast renal decline to end-stage renal disease: an unrecognized feature of nephropathy in diabetes. Kidney Int. 2017;91(6):1300–11.CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Yokoyama H, Kanno S, Takahashi S, et al. Determinants of decline in glomerular filtration rate in nonproteinuric subjects with or without diabetes and hypertension. Clin J Am Soc Nephrol. 2009;4:1432–40.CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Furuichi K, Yuzawa Y, Shimizu M, et al. Nationwide multicenter kidney biopsy study of Japanese patients with type 2 diabetes. Nephrol Dial Transpl. 2017. (Epub ahead of print).CrossRefGoogle Scholar
  36. 36.
    Usui T, Kanda E, Iseki C, et al. Observation period for changes in proteinuria and risk prediction of end-stage renal disease in general population. Nephrology. 2017. (Epub ahead of print).CrossRefPubMedGoogle Scholar
  37. 37.
    Wada T, Haneda M, Furuichi K, et al. Clinical impact of albuminuria and glomerular filtration rate on renal and cardiovascular events, and all-cause mortality in Japanese patients with type 2 diabetes. Clin Exp Nephrol. 2014;18:613–20.CrossRefPubMedGoogle Scholar
  38. 38.
    Yamagata K, Makino H, Iseki K, et al. Effect of behavior modification on outcome in early- to moderate-stage chronic kidney disease: a cluster-randomized trial. PLoS One. 2016;11(3):e0151422.CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Sekikawa A, Tominaga M, Takahashi K, et al. Prevalence of diabetes and impaired glucose tolerance in Funagata area, Japan. Diabetes Care. 1993;16(4):570–4.CrossRefPubMedGoogle Scholar
  40. 40.
    Tominaga M, Eguchi H, Manaka H, et al. Impaired glucose tolerance is a risk factor for cardiovascular disease, but not impaired fasting glucose. The Funagata Diabetes Study. Diabetes Care. 1999;22(6):920–4.CrossRefPubMedGoogle Scholar
  41. 41.
    de Jong PE, Curhan GC. Screening, monitoring, and treatment of albuminuria: public health perspectives. J Am Soc Nephrol. 2006;17:2120–6.CrossRefPubMedGoogle Scholar

Copyright information

© Japanese Society of Nephrology 2018

Authors and Affiliations

  • Kunitoshi Iseki
    • 1
    • 2
    • 3
    Email author
  • Tsuneo Konta
    • 2
  • Koichi Asahi
    • 2
  • Kunihiro Yamagata
    • 2
  • Shouichi Fujimoto
    • 2
  • Kazuhiko Tsuruya
    • 2
  • Ichiei Narita
    • 2
  • Masato Kasahara
    • 2
  • Yugo Shibagaki
    • 2
  • Toshiki Moriyama
    • 2
  • Masahide Kondo
    • 2
  • Chiho Iseki
    • 3
  • Tsuyoshi Watanabe
    • 2
  • For the “Design of the Comprehensive Health Care System for Chronic Kidney Disease (CKD) Based on the Individual Risk Assessment by Specific Health Check”
  1. 1.Clinical Research Support CenterTomishiro Central HospitalTomigusukuJapan
  2. 2.Steering Committee of Research on Design of the Comprehensive Health Care System for Chronic Kidney Disease (CKD) Based on the Individual Risk Assessment by Specific Health CheckFukushimaJapan
  3. 3.Okinawa Heart and Renal Association (OHRA)OkinawaJapan

Personalised recommendations