Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Body composition, energy expenditure and physical activity

Impact of body composition on estimated glomerular filtration rate in relatively healthy adults in Taiwan

Abstract

Background/Objectives:

Chronic kidney diseases are associated with changes in cardiometabolic risk (CMR) factors in which body composition parameters have been used as sensitive predictors. This study aimed to explore the associations of anthropometric indicators, body fat (BF), body mass index (BMI) and waist circumference (WC) with estimated glomerular filtration rate (eGFR) in an adult healthy Chinese population.

Subjects/Methods:

A cross-sectional study was conducted for the subjects undergoing annual health examinations. The associations of subjects with body composition parameters were analyzed using the cutoff values of BMI, BF and WC in accordance with the criteria for Asian or Taiwanese population by gender.

Results:

A total of 3473 subjects, aged 30–45 years, who received physical examinations in 2007 were analyzed. The levels of CMR factors were significantly higher in males than in females. eGFR was negatively associated with BMI but positively related to BF. The additional roles of BMI and WC were observed in the subjects who were categorized according to BF. Females with normal weight obese were associated with increased eGFR, whereas a higher eGFR was found in males with low/normal BF and BMI or normal WC.

Conclusions:

Our data provided evidence that anthropometric parameters were associated with changes of eGFR in relatively healthy adults. Higher eGFR was observed in females with normal weight obese in whom hyperfiltration may be suspected, and this finding deserves further studies.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY . Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004; 351: 1296–1305.

    Article  CAS  Google Scholar 

  2. Fox CS, Larson MG, Leip EP, Culleton B, Wilson PW, Levy D . Predictors of new-onset kidney disease in a community-based population. JAMA 2004; 291: 844–850.

    Article  CAS  Google Scholar 

  3. Whaley-Connell AT, Sowers JR, Stevens LA, McFarlane SI, Shlipak MG, Norris KC et al. CKD in the United States: Kidney Early Evaluation Program (KEEP) and National Health and Nutrition Examination Survey (NHANES) 1999-2004. Am J Kidney Dis 2008; 51 (Suppl 2): S13–S20.

    Article  CAS  Google Scholar 

  4. Hsu CY, McCulloch CE, Iribarren C, Darbinian J, Go AS . Body mass index and risk for end-stage renal disease. Ann Int Med 2006; 144: 21–28.

    Article  Google Scholar 

  5. Foster MC, Hwang SJ, Larson MG, Lichtman JH, Parikh NI, Vasan RS et al. Overweight, obesity, and the development of stage 3 CKD: the Framingham Heart Study. Am J Kidney Dis 2008; 52: 39–48.

    Article  Google Scholar 

  6. Ritz E . Metabolic syndrome and kidney disease. Blood Purif 2008; 26: 59–62.

    Article  CAS  Google Scholar 

  7. Poirier P, Despres JP . Waist circumference, visceral obesity, and cardiovascular risk. J Cardiopulm Rehabil 2003; 23: 161–169.

    Article  Google Scholar 

  8. Klein S . The case of visceral fat: argument for the defense. J Clin Invest 2004; 113: 1530–1532.

    Article  CAS  Google Scholar 

  9. Kanaya AM, Harris T, Goodpaster BH, Tylavsky F, Cummings SR, Health A et al. Adipocytokines attenuate the association between visceral adiposity and diabetes in older adults. Diabetes Care 2004; 27: 1375–1380.

    Article  CAS  Google Scholar 

  10. Katzmarzyk PT, Leon AS, Wilmore JH, Skinner JS, Rao DC, Rankinen T et al. Targeting the metabolic syndrome with exercise: evidence from the HERITAGE Family Study. Med Sci Sports Exerc 2003; 35: 1703–1709.

    Article  CAS  Google Scholar 

  11. Pollex RL, Hegele RA . Genetic determinants of the metabolic syndrome. Nat Clin Pract Cardiovasc Med 2006; 3: 482–489.

    Article  CAS  Google Scholar 

  12. WHO/IASO/IOTF The Asia-Pacific perspective: redefining obesity and its treatment: Health Communications Australia Pty Ltd, 2000.

  13. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000; 894: i–xii. 1-253.

  14. Ashwell M, Gibson S . Waist to height ratio is a simple and effective obesity screening tool for cardiovascular risk factors: analysis of data from the British National Diet And Nutrition Survey of adults aged 19-64 years. Obes Facts 2009; 2: 97–103.

    Article  Google Scholar 

  15. Browning LM, Hsieh SD, Ashwell M . A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0.5 could be a suitable global boundary value. Nutr Res Rev 2010; 23: 247–269.

    Article  Google Scholar 

  16. Deurenberg-Yap M, Chew SK, Deurenberg P . Elevated body fat percentage and cardiovascular risks at low body mass index levels among Singaporean Chinese, Malays and Indians. Obes Rev 2002; 3: 209–215.

    Article  CAS  Google Scholar 

  17. Ruderman N, Chisholm D, Pi-Sunyer X, Schneider S . The metabolically obese, normal-weight individual revisited. Diabetes 1998; 47: 699–713.

    Article  CAS  Google Scholar 

  18. Pinto-Sietsma SJ, Navis G, Janssen WM, de Zeeuw D, Gans RO, de Jong PE et al. A central body fat distribution is related to renal function impairment, even in lean subjects. Am J Kidney Dis 2003; 41: 733–741.

    Article  Google Scholar 

  19. Dittmann K, Hannemann A, Wallaschofski H, Rettig R, Stracke S, Volzke H et al. U-shaped association between central body fat and the urinary albumin-to-creatinine ratio and microalbuminuria. BMC Nephrol 2013; 14: 87.

    Article  CAS  Google Scholar 

  20. Watanabe H, Obata H, Watanabe T, Sasaki S, Nagai K, Aizawa Y . Metabolic syndrome and risk of development of chronic kidney disease: the Niigata preventive medicine study. Diabetes Metab Res Rev 2010; 26: 26–32.

    Article  Google Scholar 

  21. Miyatake N, Shikata K, Makino H, Numata T . Decreasing abdominal circumference is associated with improving estimated glomerular filtration rate (eGFR) with lifestyle modification in Japanese men: a pilot study. Acta Med Okayama. 2011; 65: 363–367.

    CAS  PubMed  Google Scholar 

  22. Chen W, Chen W, Wang H, Dong X, Liu Q, Mao H et al. Prevalence and risk factors associated with chronic kidney disease in an adult population from southern China. Nephrol Dial Transplant 2009; 24: 1205–1212.

    Article  Google Scholar 

  23. Sun F, Tao Q, Zhan S . Metabolic syndrome and the development of chronic kidney disease among 118 924 non-diabetic Taiwanese in a retrospective cohort. Nephrology 2010; 15: 84–92.

    Article  CAS  Google Scholar 

  24. Kitiyakara C, Yamwong S, Cheepudomwit S, Domrongkitchaiporn S, Unkurapinun N, Pakpeankitvatana V et al. The metabolic syndrome and chronic kidney disease in a Southeast Asian cohort. Kidney Int 2007; 71: 693–700.

    Article  CAS  Google Scholar 

  25. Choo V . WHO reassesses appropriate body-mass index for Asian populations. Lancet 2002; 360: 235.

    Article  Google Scholar 

  26. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care 2004; 27 (Suppl 1): S15–S35.

    Google Scholar 

  27. Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y et al. Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol 2006; 17: 2937–2944.

    Article  Google Scholar 

  28. National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002; 39 (Suppl 1): S1–S266.

    Google Scholar 

  29. National Cholesterol Education Program Expert Panel. Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002; 106: 3143-421.

  30. Chuang HH, Li WC, Sheu BF, Liao SC, Chen JY, Chang KC et al. Correlation between body composition and risk factors for cardiovascular disease and metabolic syndrome. Biofactors 2012; 38: 284–291.

    Article  CAS  Google Scholar 

  31. Helal I, Fick-Brosnahan GM, Reed-Gitomer B, Schrier RW . Glomerular hyperfiltration: definitions, mechanisms and clinical implications. Nat Rev Nephrol 2012; 8: 293–300.

    Article  CAS  Google Scholar 

  32. Levine DZ . Can rodent models of diabetic kidney disease clarify the significance of early hyperfiltration?: recognizing clinical and experimental uncertainties. Clin Sci 2008; 114: 109–118.

    Article  CAS  Google Scholar 

  33. Kim JY, Han SH, Yang BM . Implication of high-body-fat percentage on CMR in middle-aged, healthy, normal-weight adults. Obesity 2012; 21: 1571–1577.

    Article  Google Scholar 

  34. Romero-Corral A, Somers VK, Sierra-Johnson J, Korenfeld Y, Boarin S, Korinek J et al. Normal weight obesity: a risk factor for cardiometabolic dysregulation and cardiovascular mortality. Eur Heart J 2010; 31: 737–746.

    Article  Google Scholar 

  35. Prospective Studies Collaboration, Prospective Studies Collaboration Whitlock G, Prospective Studies Collaboration Lewington S, Prospective Studies Collaboration Sherliker P, Prospective Studies Collaboration Clarke R, Prospective Studies Collaboration Emberson J et al. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet 2009; 373: 1083–1096.

    Article  Google Scholar 

  36. Ashwell M, Hsieh SD . Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity. Int J Food Sci Nutr 2005; 56: 303–307.

    Article  Google Scholar 

  37. Rabe K, Lehrke M, Parhofer KG, Broedl UC . Adipokines and insulin resistance. Mol Med 2008; 14: 741–751.

    Article  CAS  Google Scholar 

  38. Tritos NA, Mantzoros CS . Leptin: its role in obesity and beyond. Diabetologia 1997; 40: 1371–1379.

    Article  CAS  Google Scholar 

  39. Yang X, Smith U . Adipose tissue distribution and risk of metabolic disease: does thiazolidinedione-induced adipose tissue redistribution provide a clue to the answer? Diabetologia 2007; 50: 1127–1139.

    Article  CAS  Google Scholar 

  40. Rosenquist KJ, Pedley A, Massaro JM, Therkelsen KE, Murabito JM, Hoffmann U et al. Visceral and subcutaneous fat quality and CMR. JACC Cardiovasc Imaging 2013; 6: 762–771.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to W-C Li.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tsai, YW., Ho, CI., Chen, JY. et al. Impact of body composition on estimated glomerular filtration rate in relatively healthy adults in Taiwan. Eur J Clin Nutr 69, 34–39 (2015). https://doi.org/10.1038/ejcn.2014.66

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ejcn.2014.66

This article is cited by

Search

Quick links