Glomerular hyperfiltration may be a novel risk factor of restrictive spirometry pattern: Analysis of the Korea National Health and Nutrition Examination Survey (KNHANES) 2009-2015

Autoři: Hong Il Lim aff001;  Sang Jin Jun aff001;  Sung Woo Lee aff001
Působiště autorů: Department of Internal Medicine, Nowon Eulji Medical Center, Eulji University, Seoul, Korea aff001
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0223050


Background and objectives

There have been limited studies regarding the association between glomerular hyperfiltration (GHF) and restrictive spirometry pattern (RSP) in Korean adults.


We used data of 23,189 adults from the Korea National Health and Nutritional Examination Survey 2009–2015 with a complete data set including spirometry, serum creatinine, and anthropometric measurements. Spirometry data included the forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). We defined GHF as the >90th percentile of age & sex adjusted estimated glomerular filtration rate (eGFR), and RSP was defined as an FVC <80%-predicted value and an FEV1/FVC ratio ≥0.7.


Participants with RSP showed higher blood pressure, fasting glucose, and triglyceride, reduced high density lipoprotein cholesterol, and central obesity, which resulted in a higher prevalence of metabolic syndrome (MetS) compared to those without RSP. Multivariate logistic regression revealed that the odds for RSP were significantly increased with an increased number of MetS components. In addition, increased eGFR was associated with decreased FVC, showing an inverted J-shaped relationship in a multivariate generalized additive model analysis. In the multivariate logistic regression analysis, the adjusted odds ratio and 95% confidence interval of GHF for RSP was 1.184 (1.026–1.368, P = 0.021), which was evident in groups without metabolic disorders.


We concluded that GHF was associated with increased odds for RSP, particularly in groups without metabolic disorders. Further prospective studies are needed to confirm our study results.

Klíčová slova:

Creatinine – Glomerular filtration rate – Kidneys – Metabolic disorders – Obesity – Regression analysis – Spirometry – Tuberculosis


1. Pellegrino R, Viegi G, Brusasco V, Crapo RO, Burgos F, Casaburi R, et al. Interpretative strategies for lung function tests. Eur Respir J. 2005;26(5):948–68. doi: 10.1183/09031936.05.00035205 16264058

2. Vogelmeier CF, Criner GJ, Martinez FJ, Anzueto A, Barnes PJ, Bourbeau J, et al. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease 2017 Report. GOLD Executive Summary. Am J Respir Crit Care Med. 2017;195(5):557–82. doi: 10.1164/rccm.201701-0218PP 28128970

3. Aaron SD, Dales RE, Cardinal P. How Accurate Is Spirometry at Predicting Restrictive Pulmonary Impairment? Chest. 1999;115(3):869–73. doi: 10.1378/chest.115.3.869 10084506

4. Venkateshiah SB, Ioachimescu OC, McCarthy K, Stoller JK. The utility of spirometry in diagnosing pulmonary restriction. Lung. 2008;186(1):19–25. doi: 10.1007/s00408-007-9052-8 17990034

5. Godfrey MS, Jankowich MD. The Vital Capacity Is Vital: Epidemiology and Clinical Significance of the Restrictive Spirometry Pattern. Chest. 2016;149(1):238–51. doi: 10.1378/chest.15-1045 26356330

6. Engstrom G, Hedblad B, Nilsson P, Wollmer P, Berglund G, Janzon L. Lung function, insulin resistance and incidence of cardiovascular disease: a longitudinal cohort study. J Intern Med. 2003;253(5):574–81. doi: 10.1046/j.1365-2796.2003.01138.x 12702035

7. Lazarus R, Sparrow D, Weiss ST. Baseline ventilatory function predicts the development of higher levels of fasting insulin and fasting insulin resistance index: the Normative Aging Study. Eur Respir J. 1998;12(3):641–5. doi: 10.1183/09031936.98.12030641 9762793

8. Lee HM, Chung SJ, Lopez VA, Wong ND. Association of FVC and total mortality in US adults with metabolic syndrome and diabetes. Chest. 2009;136(1):171–6. doi: 10.1378/chest.08-1901 19429724

9. Nakajima K, Kubouchi Y, Muneyuki T, Ebata M, Eguchi S, Munakata H. A possible association between suspected restrictive pattern as assessed by ordinary pulmonary function test and the metabolic syndrome. Chest. 2008;134(4):712–8. doi: 10.1378/chest.07-3003 18625672

10. Leone N, Courbon D, Thomas F, Bean K, Jego B, Leynaert B et al. Lung function impairment and metabolic syndrome: the critical role of abdominal obesity. Am J Respir Crit Care Med 2009; 179(6):509–16. doi: 10.1164/rccm.200807-1195OC 19136371

11. Vaz Fragoso CA, Gill TM, McAvay G, Yaggi HK, Van Ness PH, Concato J. Respiratory impairment and mortality in older persons: a novel spirometric approach. J Investing Med. 2011;59(7):1089–95.

12. Engstrom G, Janzon L. Risk of developing diabetes is inversely related to lung function: a population-based cohort study. Diabet Med. 2002;19(2):167–70. doi: 10.1046/j.1464-5491.2002.00652.x 11874435

13. Litonjua AA, Lazarus R, Sparrow D, Demolles D, Weiss ST. Lung function in type 2 diabetes: the Normative Aging Study. Respir Med. 2005;99(12):1583–90. doi: 10.1016/j.rmed.2005.03.023 16291079

14. Yeh HC, Punjabi NM, Wang NY, Pankow JS, Duncan BB, Brancati FL. Vital capacity as a predictor of incident type 2 diabetes: the Atherosclerosis Risk in Communities study. Diabetes Care. 2005;28(6):1472–9. doi: 10.2337/diacare.28.6.1472 15920070

15. Wannamethee SG, Shaper AG, Rumley A, Sattar N, Whincup PH, Thomas MC, et al. Lung function and risk of type 2 diabetes and fatal and nonfatal major coronary heart disease events: possible associations with inflammation. Diabetes Care. 2010;33(9):1990–6. doi: 10.2337/dc10-0324 20519659

16. Ford ES, Mannino DM, National H, Nutrition Examination Survey Epidemiologic Follow-up S. Prospective association between lung function and the incidence of diabetes: findings from the National Health and Nutrition Examination Survey Epidemiologic Follow-up Study. Diabetes Care. 2004;27(12):2966–70. doi: 10.2337/diacare.27.12.2966 15562215

17. Jankowich M, Elston B, Liu Q, Abbasi S, Wu WC, Blackshear C, et al. Restrictive Spirometry Pattern, Cardiac Structure and Function, and Incident Heart Failure in African Americans. The Jackson Heart Study. Ann Am Thorac Soc. 2018;15(10):1186–96. doi: 10.1513/AnnalsATS.201803-184OC 30011374

18. Wu IH, Sun ZJ, Lu FH, Yang YC, Chou CY, Chang CJ, et al. Restrictive Spirometry Pattern Is Associated With Increased Arterial Stiffness in Men and Women. Chest. 2017;152(2):394–401. doi: 10.1016/j.chest.2017.03.039 28411113

19. Mukai H, Ming P, Lindholm B, Heimburger O, Barany P, Anderstam B, et al. Restrictive lung disorder is common in patients with kidney failure and associates with protein-energy wasting, inflammation and cardiovascular disease. PloS One. 2018;13(4):e0195585. doi: 10.1371/journal.pone.0195585 29702682

20. Yilmaz S, Yildirim Y, Yilmaz Z, Kara AV, Taylan M, Demir M, et al. Pulmonary Function in Patients with End-Stage Renal Disease: Effects of Hemodialysis and Fluid Overload. Med Sci Monit. 2016;22:2779–84. doi: 10.12659/MSM.897480 27497672

21. Navaneethan SD, Mandayam S, Arrigain S, Rahman M, Winkelmayer WC, Schold JD. Obstructive and Restrictive Lung Function Measures and CKD: National Health and Nutrition Examination Survey (NHANES) 2007–2012. Am J Kidney Dis. 2016;68(3):414–21. doi: 10.1053/j.ajkd.2016.03.415 27130720

22. De Cosmo S, Menzaghi C, Prudente S, Trischitta V. Role of insulin resistance in kidney dysfunction: insights into the mechanism and epidemiological evidence. Nephrol Dial Transplant. 2013;28(1):29–36. doi: 10.1093/ndt/gfs290 23048172

23. Yoon JH, Won JU, Ahn YS, Roh J. Poor lung function has inverse relationship with microalbuminuria, an early surrogate marker of kidney damage and atherosclerosis: the 5th Korea National Health and Nutrition Examination Survey. PloS One. 2014;9(4):e94125. doi: 10.1371/journal.pone.0094125 24718679

24. Park JY, Lee SW. A history of repetitive cesarean section is a risk factor of anemia in healthy perimenopausal women: The Korea National Health and Nutrition Examination Survey 2010–2012. PloS One. 2017;12(11):e0188903. doi: 10.1371/journal.pone.0188903 29190715

25. Melsom T, Mathisen UD, Ingebretsen OC, Jenssen TG, Njolstad I, Solbu MD, et al. Impaired fasting glucose is associated with renal hyperfiltration in the general population. Diabetes Care. 2011;34(7):1546–51. doi: 10.2337/dc11-0235 21593291

26. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome—a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet Med. 2006;23(5):469–80. doi: 10.1111/j.1464-5491.2006.01858.x 16681555

27. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16):1640–5. doi: 10.1161/CIRCULATIONAHA.109.192644 19805654

28. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–12. doi: 10.7326/0003-4819-150-9-200905050-00006 19414839

29. Cachat F, Combescure C, Cauderay M, Girardin E, Chehade H. A systematic review of glomerular hyperfiltration assessment and definition in the medical literature. Clin J Am Soc Nephrol. 2015;10(3):382–9. doi: 10.2215/CJN.03080314 25568216

30. Wood SN. Stable and efficient multiple smoothing parameter estimation for generalized additive models. J Am Stat Assoc. 2004;99:673–86.

31. Engstrom G, Lind P, Hedblad B, Wollmer P, Stavenow L, Janzon L, et al. Lung function and cardiovascular risk: relationship with inflammation-sensitive plasma proteins. Circulation. 2002;106(20):2555–60. doi: 10.1161/01.cir.0000037220.00065.0d 12427651

32. Ruggenenti P, Porrini EL, Gaspari F, Motterlini N, Cannata A, Carrara F, et al. Glomerular hyperfiltration and renal disease progression in type 2 diabetes. Diabetes Care. 2012;35(10):2061–8. doi: 10.2337/dc11-2189 22773704

33. Bjornstad P, Cherney DZ, Snell-Bergeon JK, Pyle L, Rewers M, Johnson RJ, et al. Rapid GFR decline is associated with renal hyperfiltration and impaired GFR in adults with Type 1 diabetes. Nephrol Dial Transplant. 2015;30(10):1706–11. doi: 10.1093/ndt/gfv121 26050268

34. Low S, Zhang X, Wang J, Yeoh LY, Liu YL, Ang KKL, et al. Long-term prospective observation suggests that glomerular hyperfiltration is associated with rapid decline in renal filtration function: A multiethnic study. Diab Vasc Dis Res. 2018;15(5):417–423. doi: 10.1177/1479164118776465 29807475

35. Melsom T, Nair V, Schei J, Mariani L, Stefansson VTN, Harder JL, et al. Correlation Between Baseline GFR and Subsequent Change in GFR in Norwegian Adults Without Diabetes and in Pima Indians. Am J Kidney Dis. 2019;73(6):777–85. doi: 10.1053/j.ajkd.2018.11.011 30704883

36. Park M, Yoon E, Lim YH, Kim H, Choi J, Yoon HJ. Renal hyperfiltration as a novel marker of all-cause mortality. J Am Soc Nephrol. 2015;26(6):1426–33. doi: 10.1681/ASN.2014010115 25343954

37. Helal I, Fick-Brosnahan GM, Reed-Gitomer B, Schrier RW. Glomerular hyperfiltration: definitions, mechanisms and clinical implications. Nat Rev Nephrol. 2012;8(5):293–300. doi: 10.1038/nrneph.2012.19 22349487

38. Cornelis T, Odutayo A, Keunen J, Hladunewich M. The kidney in normal pregnancy and preeclampsia. Semin Nephrol. 2011;31(1):4–14. doi: 10.1016/j.semnephrol.2010.10.002 21266261

39. Bankir L, Roussel R, Bouby N. Protein- and diabetes-induced glomerular hyperfiltration: role of glucagon, vasopressin, and urea. Am J Physiol Renal Physiol. 2015;309(1):F2–23. doi: 10.1152/ajprenal.00614.2014 25925260

40. Min HK, Sung SA, Lee SY, Lee SW. Sub-morbid dehydration-associated glomerular hyperfiltration: An emerging reality? Kidney Res Clin Pract. 2019;38(2):196–204. doi: 10.23876/j.krcp.18.0147 30991770

41. Tonneijck L, Muskiet MH, Smits MM, van Bommel EJ, Heerspink HJ, van Raalte DH, et al. Glomerular Hyperfiltration in Diabetes: Mechanisms, Clinical Significance, and Treatment. J Am Soc Nephrol. 2017;28(4):1023–39. doi: 10.1681/ASN.2016060666 28143897

42. D'Agati VD, Chagnac A, de Vries AP, Levi M, Porrini E, Herman-Edelstein M, et al. Obesity-related glomerulopathy: clinical and pathologic characteristics and pathogenesis. Nat Rev Nephrol. 2016;12(8):453–71. doi: 10.1038/nrneph.2016.75 27263398

43. Tomaszewski M, Charchar FJ, Maric C, McClure J, Crawford L, Grzeszczak W, et al. Glomerular hyperfiltration: a new marker of metabolic risk. Kidney Int. 2007;71(8):816–21. doi: 10.1038/ 17332732

44. Sasaki M, Shikata K, Okada S, Miyamoto S, Nishishita S, Kataoka HU et al. The macrophage is a key factor in renal injuries caused by glomerular hyperfiltration. Acta Med Okayama. 2011;65(2):81–9. doi: 10.18926/AMO/45266 21519365

45. Har R, Scholey JW, Daneman D, Mathmud FH, Dekker R, Lai V, et al. The effect of renal hyperfiltration on urinary inflammatory cytokines/chemokines in patients with uncomplicated type 1 diabetes mellitus. Diabetologia 2013;56(5):1166–73. doi: 10.1007/s00125-013-2857-5 23412605

46. Hwang HJ, Kim SH. The association among three aspects of physical fitness and metabolic syndrome in Korean elderly population. Diabetol Metab Syndr. 2015;12;7:112. doi: 10.1186/s13098-015-0106-4 26692906

47. Senechal M, McGavock JM, Church TS, Lee DC, Earnest CP, Sui X et al. Cut points of muscle strength associated with metabolic syndrome in men. Med Sci Sports Exerc. 2014;46(8):1475–81. doi: 10.1249/MSS.0000000000000266 25029165

48. Kleiven Ø, Bjørkavoll-Bergseth M, Melberg T, Skadberg Ø, Bergseth R, Selvag J et al. High physical fitness is associated with reduction in basal- and exercise-induced inflammation. Scand J Med Sci Sports 2018;28(1):172–179. doi: 10.1111/sms.12878 28314078

49. Silva B, Camoes M, Simoes M, Bezerra P. Obesity, Physical fitness and inflammation in the elderly. Geriatrics. 2017;21(4):30.

50. Sperandio EF, Arantes RL, Matheus AC, Silva RP, Lauria VT, Romiti M et al. Restrictive pattern on spirometry: association with cardiovascular risk and level of physical activity in asymptomatic adults. J Bras Pneumol. 2016;42(1):22–8. doi: 10.1590/S1806-37562016000000030 26982037

51. Baxmann AC, Ahmed MS, Marques NC, Menon VB, Pereira AB, Kirsztain GM et al. Influence of muscle mass and physical activity on serum and urinary creatinine and serum cystatin C. Clin J Am Soc Nephrol. 2008;3(2):348–54. doi: 10.2215/CJN.02870707 18235143

52. Moualla M, Qualls C, Arynchyn A, Thyagarajan B, Kalhan R, Smith LJ, et al. Rapid decline in lung function is temporally associated with greater metabolically active adiposity in a longitudinal study of healthy adults. Thorax. 2017;72(12):1113–20. doi: 10.1136/thoraxjnl-2016-209125 28729298

53. Sumida K, Kwak L, Grams ME, Yamagata K, Punjabi NM, Kovesdy CP, et al. Lung Function and Incident Kidney Disease: The Atherosclerosis Risk in Communities (ARIC) Study. Am J Kidney Dis. 2017;70(5):675–85. doi: 10.1053/j.ajkd.2017.05.021 28754455

Článok vyšiel v časopise


2019 Číslo 9

Najčítanejšie v tomto čísle

Tejto téme sa ďalej venujú…


Zvýšte si kvalifikáciu online z pohodlia domova

Faktory ovlivňující léčbu levotyroxinem
nový kurz

Kurz originály vs. generika

Autori: MUDr. Petr Výborný, CSc., FEBO

Autori: MUDr. Jiří Horažďovský, Ph.D

Klinická farmakokinetika betablokátorů

Všetky kurzy
Zabudnuté heslo

Nemáte účet?  Registrujte sa

Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.


Nemáte účet?  Registrujte sa