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Body mass index is the most useful predictive factor for the onset of nonalcoholic fatty liver disease: a community-based retrospective longitudinal cohort study

  • Original Article—Liver, Pancreas, and Biliary Tract
  • Published:
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Abstract

Background

Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset.

Methods

In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan–Meier method.

Results

Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m2 for men and 22.2 kg/m2 for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (P < 0.001).

Conclusion

BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset.

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References

  1. Bellentani S, Saccoccio G, Masutti F, Crocè LS, Brandi G, Sasso F, et al. Prevalence of and risk factors for hepatic steatosis in Northern Italy. Ann Intern Med. 2000;132:112–7.

    PubMed  CAS  Google Scholar 

  2. Browning JD, Szczepaniak LS, Dobbins R, Nuremberg P, Horton JD, Cohen JC. Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity. Hepatology. 2004;40:1387–95.

    Article  PubMed  Google Scholar 

  3. Fan JG, Zhu J, Li XJ, Chen L, Li L, Dai F, et al. Prevalence of and risk factors for fatty liver in a general population of Shanghai, China. J Hepatol. 2005;43:508–14.

    Article  PubMed  Google Scholar 

  4. Angulo P. Nonalcoholic fatty liver disease. N Engl J Med. 2002;18:1221–31.

    Article  Google Scholar 

  5. Marchesini G, Bugianesi E, Forlani G, Cerrelli F, Lenzi M, Manini R, et al. Nonalcoholic fatty liver, steatohepatitis, and the metabolic syndrome. Hepatology. 2003;37:917–23.

    Article  PubMed  Google Scholar 

  6. Shimada M, Hashimoto E, Taniai M, Hasegawa K, Okuda H, Hayashi N, et al. Hepatocellular carcinoma in patients with non-alcoholic steatohepatitis. J Hepatol. 2002;37:154–60.

    Article  PubMed  Google Scholar 

  7. Hamaguchi M, Kojima T, Takeda N, Nakagawa T, Taniguchi H, Fujii K, et al. The metabolic syndrome as a predictor of nonalcoholic fatty liver disease. Ann Intern Med. 2005;143:722–8.

    PubMed  CAS  Google Scholar 

  8. Akbar DH, Kawther AH. Nonalcoholic fatty liver disease in Saudi type 2 diabetic subjects attending a medical outpatient clinic: prevalence and general characteristics. Diabetes Care. 2003;26:3351–2.

    Article  PubMed  Google Scholar 

  9. Gupte P, Amarapurkar D, Agal S, Baijal R, Kulshrestha P, Pramanik S, et al. Non-alcoholic steatohepatitis in type 2 diabetes mellitus. J Gastroenterol Hepatol. 2004;19:854–8.

    Article  PubMed  Google Scholar 

  10. Assy N, Kaita K, Mymin D, Levy C, Rosser B, Minuk G. Fatty infiltration of liver in hyperlipidemic patients. Dig Dis Sci. 2000;45:1929–34.

    Article  PubMed  CAS  Google Scholar 

  11. Donati G, Stagni B, Piscaglia F, Venturoli N, Morselli-Labate AM, Rasciti L, et al. Increased prevalence of fatty liver in arterial hypertensive patients with normal liver enzymes: role of insulin resistance. Gut. 2004;53:1020–3.

    Article  PubMed  CAS  Google Scholar 

  12. Hamaguchi M, Kojima T, Takeda N, Nagata C, Takeda J, Sarui H, et al. Nonalcoholic fatty liver disease is a novel predictor of cardiovascular disease. World J Gastroenterol. 2007;13:1579–84.

    PubMed  CAS  Google Scholar 

  13. Bae JC, Rhee EJ, Lee WY, Park SE, Park CY, Oh KW, et al. Combined effect of nonalcoholic fatty liver disease and impaired fasting glucose on the development of type 2 diabetes: a 4-year retrospective longitudinal study. Diabetes Care. 2011;34:727–9.

    Article  PubMed  Google Scholar 

  14. Miyake T, Kumagi T, Hirooka M, Koizumi M, Furukawa S, Ueda T, et al. Metabolic markers and ALT cutoff level for diagnosing nonalcoholic fatty liver disease: a community-based cross-sectional study. J Gastroenterol. 2012;47:696–703.

    Article  PubMed  CAS  Google Scholar 

  15. Yu C, Xu C, Xu L, Yu J, Miao M, Li Y. Serum proteomic analysis revealed diagnostic value of hemoglobin for nonalcoholic fatty liver disease. J Hepatol. 2011;56:241–7.

    Article  PubMed  Google Scholar 

  16. Xu C, Yu C, Xu L, Miao M, Li Y. High serum uric acid increases the risk for nonalcoholic fatty liver disease: a prospective observational study. PLoS ONE. 2010;5:e11578.

    Article  PubMed  Google Scholar 

  17. Chang Y, Ryu S, Sung E, Jang Y. Higher concentrations of alanine aminotransferase within the reference interval predict nonalcoholic fatty liver disease. Clin Chem. 2007;53:686–92.

    Article  PubMed  CAS  Google Scholar 

  18. Omagari K, Morikawa S, Nagaoka S, Sadakane Y, Sato M, Hamasaki M, et al. Predictive factors for the development or regression of fatty liver in Japanese adults. J Clin Biochem Nutr. 2009;45:56–67.

    Article  PubMed  Google Scholar 

  19. Examination Committee of Criteria for ‘Obesity Disease’ in Japan, Japan Society for the Study of Obesity. New criteria for ‘obesity disease’ in Japan. Circ J. 2002;66:987–92.

    Google Scholar 

  20. Kojima S, Watanabe N, Numata M, Ogawa T, Matsuzaki S. Increase in the prevalence of fatty liver in Japan over the past 12 years: analysis of clinical background. J Gastroenterol. 2003;38:954–61.

    Article  PubMed  Google Scholar 

  21. Prati D, Taioli E, Zanella A, Torre ED, Butelli S, Del Vecchio E, et al. Updated definitions of healthy ranges for serum alanine aminotransferase levels. Ann Intern Med. 2002;137:1–9.

    PubMed  CAS  Google Scholar 

  22. Lee JK, Shim JH, Lee HC, Lee SH, Kim KM, Lim YS, et al. Estimation of the healthy upper limits for serum alanine aminotransferase in Asian populations with normal liver histology. Hepatology. 2010;51:1577–83.

    Article  PubMed  CAS  Google Scholar 

  23. Kim HC, Nam CM, Jee SH, Han KH, Oh DK, Suh I. Normal serum aminotransferase concentration and risk of mortality from liver diseases: prospective cohort study. BMJ. 2004;328:983.

    Article  PubMed  CAS  Google Scholar 

  24. Nugent C, Younossi ZM. Evaluation and management of obesity-related nonalcoholic fatty liver disease. Nat Clin Pract Gastroenterol Hepatol. 2007;4:432–41.

    Article  PubMed  Google Scholar 

  25. Fujikawa K, Ohata K, Honda T, Miyazoe S, Ichikawa T, Ishikawa H, et al. Nonalcoholic steatohepatitis with improved hepatic fibrosis after weight reduction. Intern Med. 2004;43:289–94.

    Article  PubMed  Google Scholar 

  26. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and investigation strategies. Lancet. 2004;363:157–63.

    Article  Google Scholar 

  27. Shiwaku K, Anuurad E, Enkhmaa B, Nogi A, Kitajima K, Shimono K, et al. Overweight Japanese with body mass indexes of 23.0–24.9 have higher risks for obesity-associated disorders: a comparison of Japanese and Mongolians. Int J Obes Relat Metab Disord. 2004;28:152–8.

    Article  PubMed  CAS  Google Scholar 

  28. Misra A, Misra R, Wijesuriya M, Banerjee D. The metabolic syndrome in South Asians: continuing escalation & possible solutions. Indian J Med Res. 2007;125:345–54.

    PubMed  Google Scholar 

  29. Deurenberg P, Deurenberg-Yap M, Guricci S. Asians are different from Caucasians and from each other in their body mass index/body fat percent relationship. Obes Rev. 2002;3:141–6.

    Article  PubMed  CAS  Google Scholar 

  30. Misra A, Wasir JS, Vikram NK. Action and research are needed for evaluation of optimal definitions of anthropometric parameters and metabolic syndrome for Asians. Diabetes Res Clin Pract. 2005;68:178–9.

    Article  PubMed  Google Scholar 

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Acknowledgments

This work was supported in part by a Grant-in-Aid for Scientific Research from the Japanese Ministry of Education, Culture, Sports, Science, and Technology (KAKENHI No. 23700907), and a research grant from Ehime University.

Conflict of interest

The authors declare that we have no conflict of interest.

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Correspondence to Morikazu Onji.

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Miyake, T., Kumagi, T., Hirooka, M. et al. Body mass index is the most useful predictive factor for the onset of nonalcoholic fatty liver disease: a community-based retrospective longitudinal cohort study. J Gastroenterol 48, 413–422 (2013). https://doi.org/10.1007/s00535-012-0650-8

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  • DOI: https://doi.org/10.1007/s00535-012-0650-8

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