Skip to main content

Advertisement

SpringerLink
Log in

Association of hypertriglyceridemic waist phenotype with non-alcoholic fatty liver disease: a cross-sectional study in a Chinese population

  • Original Article
  • Published:
Hormones Aims and scope Submit manuscript

Abstract

Background

The aim of this study was to determine the association between hypertriglyceridemic waist (HTGW) phenotype and non-alcoholic fatty liver disease (NAFLD) in a middle- to older-aged Chinese population.

Methods

In this cross-sectional study, a total of 9015 participants (age 40–79 years) were recruited and grouped into four phenotypes, as follows: NWNT: normal waist–normal triglyceride; NWET: normal waist–elevated triglycerides; EWNT: elevated waist–normal triglycerides; and hypertriglyceridemic waist (HTGW). Logistic regression analysis was carried out to assess the associations between HTGW phenotype and NAFLD. Receiver-operating characteristic (ROC) curves were drawn to evaluate the utility of waist circumference–triglyceride index (WTI) as a reference factor for screening for NAFLD.

Results

HTGW phenotype had a higher prevalence of NAFLD (53.3%), diabetes (19.6%), and hypertension (79.8%) than the other three subgroups. After adjusting for age, sex, and BMI, HTGW phenotype was associated with NAFLD (odds ratio (OR) 6.12; 95% confidence interval (CI) 5.11–7.32). Further adjusted for potential confounders, the HTGW phenotype was still significantly associated with NAFLD (adjusted OR 5.18; 95% CI 4.30–6.23) regardless of gender. The subgroup analyses generally revealed similar associations across all subgroups. ROC curve analysis showed that when the maximum area under the curve was 0.748, the WTI was 90.1, and the corresponding sensitivity and specificity were 90.6 and 59.5%, respectively.

Conclusions

HTGW phenotype is strongly associated with NAFLD and can be used as a reference factor for NAFLD screening.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.

Abbreviations

NAFLD:

Non-alcoholic fatty liver disease

OR:

Odds ratio

CI:

Confidence interval

CVD:

Cardiovascular disease

T2DM:

Type 2 diabetes mellitus

CKD:

Chronic kidney disease

WC:

Waist circumference

BP:

Blood pressure

BMI:

Body mass index

OGTT:

75-G oral glucose tolerance test

FPG:

Fasting plasma glucose

TC:

Total cholesterol

TG:

Triglyceride

HDL-C:

High-density lipoprotein-cholesterol

LDL-C:

Low-density lipoprotein-cholesterol

ORs:

Odds ratios

CIs:

Confidence intervals

References

  1. Zhou F, Zhou J, Wang W, Zhang XJ, Ji YX, Zhang P, She ZG, Zhu L, Cai J, Li H (2019) Unexpected rapid increase in the burden of NAFLD in China from 2008 to 2018: a systematic review and meta-analysis. Hepatol 70(4):1119–1133. https://doi.org/10.1002/hep.30702

    Article  Google Scholar 

  2. Estes C, Anstee QM, Arias-Loste MT, Bantel H, Bellentani S, Caballeria J, Colombo M, Craxi A, Crespo J, Day CP, Eguchi Y, Geier A, Kondili LA, Kroy DC, Lazarus JV, Loomba R, Manns MP, Marchesini G, Nakajima A, Negro F, Petta S, Ratziu V, Romero-Gomez M, Sanyal A, Schattenberg JM, Tacke F, Tanaka J, Trautwein C, Wei L, Zeuzem S, Razavi H (2018) Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016–2030. J Hepatol 69(4):896–904. https://doi.org/10.1016/j.jhep.2018.05.036

    Article  PubMed  Google Scholar 

  3. Huang X, Xu M, Chen Y, Peng K, Huang Y, Wang P, Ding L, Lin L, Xu Y, Chen Y, Lu J, Wang W, Bi Y, Ning G (2015) Validation of the fatty liver index for nonalcoholic fatty liver disease in middle-aged and elderly Chinese. Medicine (Baltimore) 94(40):e1682. https://doi.org/10.1097/MD.0000000000001682

    Article  CAS  Google Scholar 

  4. Zuo G, Xuan L, Xin Z, Xu Y, Lu J, Chen Y, Dai M, Zhang D, Wang W, Li M, Bi Y, Ning G, Xu M (2021) New nonalcoholic fatty liver disease and fibrosis progression associate with the risk of incident chronic kidney disease. J Clin Endocrinol Metab 106(10):e3957–e3968. https://doi.org/10.1210/clinem/dgab425

    Article  PubMed  Google Scholar 

  5. Panahi Y, Kianpour P, Mohtashami R, Jafari R, Simental-Mendia LE, Sahebkar A (2017) Efficacy and safety of phytosomal curcumin in non-alcoholic fatty liver disease: a randomized controlled trial. Drug Res (Stuttg) 67(4):244–251. https://doi.org/10.1055/s-0043-100019

    Article  CAS  Google Scholar 

  6. Musso G, Gambino R, Tabibian JH, Ekstedt M, Kechagias S, Hamaguchi M, Hultcrantz R, Hagstrom H, Yoon SK, Charatcharoenwitthaya P, George J, Barrera F, Hafliethadottir S, Bjornsson ES, Armstrong MJ, Hopkins LJ, Gao X, Francque S, Verrijken A, Yilmaz Y, Lindor KD, Charlton M, Haring R, Lerch MM, Rettig R, Volzke H, Ryu S, Li G, Wong LL, Machado M, Cortez-Pinto H, Yasui K, Cassader M (2014) Association of non-alcoholic fatty liver disease with chronic kidney disease: a systematic review and meta-analysis. PLoS Med 11(7):e1001680. https://doi.org/10.1371/journal.pmed.1001680

    Article  PubMed  PubMed Central  Google Scholar 

  7. Musso G, Cassader M, Olivetti C, Rosina F, Carbone G, Gambino R (2013) Association of obstructive sleep apnoea with the presence and severity of non-alcoholic fatty liver disease. A systematic review and meta-analysis. Obes Rev 14(5):417–31. https://doi.org/10.1111/obr.12020

    Article  CAS  PubMed  Google Scholar 

  8. Deprince A, Haas JT, Staels B (2020) Dysregulated lipid metabolism links NAFLD to cardiovascular disease. Mol Metab 42:101092. https://doi.org/10.1016/j.molmet.2020.101092

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Lee H, Ahn J, Shin SS, Yoon M (2019) Ascorbic acid inhibits visceral obesity and nonalcoholic fatty liver disease by activating peroxisome proliferator-activated receptor alpha in high-fat-diet-fed C57BL/6J mice. Int J Obes (Lond) 43(8):1620–1630. https://doi.org/10.1038/s41366-018-0212-0

    Article  CAS  Google Scholar 

  10. Fuchs CD, Claudel T, Kumari P, Haemmerle G, Pollheimer MJ, Stojakovic T, Scharnagl H, Halilbasic E, Gumhold J, Silbert D, Koefeler H, Trauner M (2012) Absence of adipose triglyceride lipase protects from hepatic endoplasmic reticulum stress in mice. Hepatol 56(1):270–280. https://doi.org/10.1002/hep.25601

    Article  CAS  Google Scholar 

  11. Yamaguchi K, Yang L, McCall S, Huang J, Yu XX, Pandey SK, Bhanot S, Monia BP, Li YX, Diehl AM (2007) Inhibiting triglyceride synthesis improves hepatic steatosis but exacerbates liver damage and fibrosis in obese mice with nonalcoholic steatohepatitis. Hepatol 45(6):1366–1374. https://doi.org/10.1002/hep.21655

    Article  CAS  Google Scholar 

  12. Alkhouri N, Dixon LJ, Feldstein AE (2009) Lipotoxicity in nonalcoholic fatty liver disease: not all lipids are created equal. Expert Rev Gastroenterol Hepatol 3(4):445–451. https://doi.org/10.1586/egh.09.32

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Eguchi Y, Eguchi T, Mizuta T, Ide Y, Yasutake T, Iwakiri R, Hisatomi A, Ozaki I, Yamamoto K, Kitajima Y, Kawaguchi Y, Kuroki S, Ono N (2006) Visceral fat accumulation and insulin resistance are important factors in nonalcoholic fatty liver disease. J Gastroenterol 41(5):462–469. https://doi.org/10.1007/s00535-006-1790-5

    Article  CAS  PubMed  Google Scholar 

  14. Liu PJ, Lou HP, Zhu YN (2021) Identification of hepatic steatosis in premenopausal and postmenopausal women based on phenotypes combining triglyceride levels and anthropometric indices: a cross-sectional study. Diabetes Metab Syndr Obes 14:1339–1347. https://doi.org/10.2147/DMSO.S302297

    Article  PubMed  PubMed Central  Google Scholar 

  15. Clemente AP, Netto BD, de Carvalho-Ferreira JP, da Silveira Campos RM, de Piano Ganen A, Tock L, de Mello MT, Damaso AR (2016) Waist circumference as a marker for screening nonalcoholic fatty liver disease in obese adolescents. Rev Paul Pediatr 34(1):47–55. https://doi.org/10.1016/j.rpped.2015.05.007

    Article  PubMed  PubMed Central  Google Scholar 

  16. Sam S, Haffner S, Davidson MH, D’Agostino RB Sr, Feinstein S, Kondos G, Perez A, Mazzone T (2009) Hypertriglyceridemic waist phenotype predicts increased visceral fat in subjects with type 2 diabetes. Diabetes Care 32(10):1916–1920. https://doi.org/10.2337/dc09-0412

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Lemieux I, Pascot A, Couillard C, Lamarche B, Tchernof A, Almeras N, Bergeron J, Gaudet D, Tremblay G, Prud’homme D, Nadeau A, Despres JP (2000) Hypertriglyceridemic waist: a marker of the atherogenic metabolic triad (hyperinsulinemia; hyperapolipoprotein B; small, dense LDL) in men? Circulation 102(2):179–184. https://doi.org/10.1161/01.cir.102.2.179

    Article  CAS  PubMed  Google Scholar 

  18. Lemieux I, Poirier P, Bergeron J, Almeras N, Lamarche B, Cantin B, Dagenais GR, Despres JP (2007) Hypertriglyceridemic waist: a useful screening phenotype in preventive cardiology? Can J Cardiol 23(Suppl B):23B-31B. https://doi.org/10.1016/s0828-282x(07)71007-3

    Article  PubMed  PubMed Central  Google Scholar 

  19. Gomez-Huelgas R, Bernal-Lopez MR, Villalobos A, Mancera-Romero J, Baca-Osorio AJ, Jansen S, Guijarro R, Salgado F, Tinahones FJ, Serrano-Rios M (2011) Hypertriglyceridemic waist: an alternative to the metabolic syndrome? Results of the IMAP Study (multidisciplinary intervention in primary care). Int J Obes (Lond) 35(2):292–299. https://doi.org/10.1038/ijo.2010.127

    Article  CAS  Google Scholar 

  20. Janghorbani M, Salamat MR, Aminorroaya A, Amini M (2017) Utility of the visceral adiposity index and hypertriglyceridemic waist phenotype for predicting incident hypertension. Endocrinol Metab (Seoul) 32(2):221–229. https://doi.org/10.3803/EnM.2017.32.2.221

    Article  CAS  Google Scholar 

  21. Zhao K, Yang SS, Wang HB, Chen K, Lu ZH, Mu YM (2018) Association between the hypertriglyceridemic waist phenotype and prediabetes in Chinese adults aged 40 years and older. J Diabetes Res 2018:1031939. https://doi.org/10.1155/2018/1031939

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ren Y, Zhang M, Zhao J, Wang C, Luo X, Zhang J, Zhu T, Li X, Yin L, Pang C, Feng T, Wang B, Zhang L, Li L, Yang X, Zhang H, Hu D (2016) Association of the hypertriglyceridemic waist phenotype and type 2 diabetes mellitus among adults in China. J Diabetes Investig 7(5):689–694. https://doi.org/10.1111/jdi.12489

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Qiu Y, Zhao Q, Wang N, Yu Y, Wang R, Zhang Y, Cui S, Zhu M, Liu X, Jiang Y, Zhao G (2020) Association of hypertriglyceridemic waist phenotype with renal function impairment: a cross-sectional study in a population of Chinese adults. Nutr Metab (Lond) 17:63. https://doi.org/10.1186/s12986-020-00483-7

    Article  CAS  Google Scholar 

  24. Chen S, Guo X, Dong S, Yu S, Chen Y, Zhang N, Sun Y (2017) Association between the hypertriglyceridemic waist phenotype and hyperuricemia: a cross-sectional study. Clin Rheumatol 36(5):1111–1119. https://doi.org/10.1007/s10067-017-3559-z

    Article  PubMed  Google Scholar 

  25. Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, Monauni T, Muggeo M (2000) Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care 23(1):57–63. https://doi.org/10.2337/diacare.23.1.57

    Article  CAS  PubMed  Google Scholar 

  26. Lee SB, Ahn CW, Lee BK, Kang S, Nam JS, You JH, Kim MJ, Kim MK, Park JS (2018) Association between triglyceride glucose index and arterial stiffness in Korean adults. Cardiovasc Diabetol 17(1):41. https://doi.org/10.1186/s12933-018-0692-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Li M, Xu Y, Xu M, Ma L, Wang T, Liu Y, Dai M, Chen Y, Lu J, Liu J, Bi Y, Ning G (2012) Association between nonalcoholic fatty liver disease (NAFLD) and osteoporotic fracture in middle-aged and elderly Chinese. J Clin Endocrinol Metab 97(6):2033–2038. https://doi.org/10.1210/jc.2011-3010

    Article  CAS  PubMed  Google Scholar 

  28. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O’Brien WL, Bassett DR Jr, Schmitz KH, Emplaincourt PO, Jacobs DR Jr, Leon AS (2000) Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 32(9 Suppl):S498-504. https://doi.org/10.1097/00005768-200009001-00009

    Article  CAS  PubMed  Google Scholar 

  29. Won KB, Park GM, Lee SE, Cho IJ, Kim HC, Lee BK, Chang HJ (2018) Relationship of insulin resistance estimated by triglyceride glucose index to arterial stiffness. Lipids Health Dis 17(1):268. https://doi.org/10.1186/s12944-018-0914-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Hashimoto Y, Tanaka M, Okada H, Senmaru T, Hamaguchi M, Asano M, Yamazaki M, Oda Y, Hasegawa G, Toda H, Nakamura N, Fukui M (2015) Metabolically healthy obesity and risk of incident CKD. Clin J Am Soc Nephrol 10(4):578–583. https://doi.org/10.2215/CJN.08980914

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Farrell GC, Chitturi S, Lau GK, Sollano JD, N Asia-Pacific Working Party on (2007) Guidelines for the assessment and management of non-alcoholic fatty liver disease in the Asia-Pacific region: executive summary. J Gastroenterol Hepatol 22(6):775–7. https://doi.org/10.1111/j.1440-1746.2007.05002.x

    Article  PubMed  Google Scholar 

  32. Chen S, Guo X, Yu S, Sun G, Li Z, Sun Y (2016) Association between the hypertriglyceridemic waist phenotype, prediabetes, and diabetes mellitus in rural Chinese population: a cross-sectional study. Int J Environ Res Public Health 13(4):368. https://doi.org/10.3390/ijerph13040368

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zhou BF, C Cooperative Meta-Analysis Group of the Working Group on Obesity in (2002) Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults–study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci 15(1):83–96

    PubMed  Google Scholar 

  34. Huang TD, Behary J, Zekry A (2020) Non-alcoholic fatty liver disease: a review of epidemiology, risk factors, diagnosis and management. Intern Med J 50(9):1038–1047. https://doi.org/10.1111/imj.14709

    Article  PubMed  Google Scholar 

  35. Piscaglia F, Svegliati-Baroni G, Barchetti A, Pecorelli A, Marinelli S, Tiribelli C, Bellentani S, H -N I S Group (2016) Clinical patterns of hepatocellular carcinoma in nonalcoholic fatty liver disease: a multicenter prospective study. Hepatol 63(3):827–838. https://doi.org/10.1002/hep.28368

    Article  Google Scholar 

  36. Du P, Zhang B, Wang HJ, Qi SF, Mi YJ, Yao JC, Liu DW, Tian QB (2015) The prevalence and secular trends of abdominal obesity among Chinese adults, 1993–2011. Ann Epidemiol 25(10):797–799. https://doi.org/10.1016/j.annepidem.2015.06.082

    Article  PubMed  Google Scholar 

  37. Yang RF, Liu XY, Lin Z, Zhang G (2015) Correlation study on waist circumference-triglyceride (WT) index and coronary artery scores in patients with coronary heart disease. Eur Rev Med Pharmacol Sci 19(1):113–118

    CAS  PubMed  Google Scholar 

  38. Cunha de Oliveira C, CarneiroRoriz AK, Eickemberg M, Barreto Medeiros JM, Barbosa Ramos L (2014) Hypertriglyceridemic waist phenotype: association with metabolic disorders and visceral fat in adults. Nutr Hosp 30(1):25–31. https://doi.org/10.3305/nh.2014.30.1.7411

    Article  PubMed  Google Scholar 

  39. Kelley DE, Goodpaster BH (2001) Skeletal muscle triglyceride. An aspect of regional adiposity and insulin resistance. Diabetes Care 24(5):933–41. https://doi.org/10.2337/diacare.24.5.933

    Article  CAS  PubMed  Google Scholar 

  40. Lewis GF, Carpentier A, Adeli K, Giacca A (2002) Disordered fat storage and mobilization in the pathogenesis of insulin resistance and type 2 diabetes. Endocr Rev 23(2):201–229. https://doi.org/10.1210/edrv.23.2.0461

    Article  CAS  PubMed  Google Scholar 

  41. Ryysy L, Hakkinen AM, Goto T, Vehkavaara S, Westerbacka J, Halavaara J, Yki-Jarvinen H (2000) Hepatic fat content and insulin action on free fatty acids and glucose metabolism rather than insulin absorption are associated with insulin requirements during insulin therapy in type 2 diabetic patients. Diabetes 49(5):749–758. https://doi.org/10.2337/diabetes.49.5.749

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the invaluable assistance of the physicians of the Department of Endocrinology, Luwan Branch, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University and Ruijin Hospital, Shanghai, China. The study would not have been possible without their support.

Funding

This study was supported by Shanghai Municipal Huangpu District Commission (HLQ202004). The funder played no role in the design or conduct of the study, collection, management, analysis, or interpretation of the data, or in the preparation, review, or approval of the article.

Author information

Authors and Affiliations

  1. Institute and Department of Endocrinology, Shanghai Ruijin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Yan Xuan, Ping Gao, Ying Shen, Sujie Wang, Xi Gu, Dou Tang, Xun Wang, FanFan Zhu, Leiqun Lu & Ling Chen

Authors
  1. Yan Xuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ping Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ying Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sujie Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xi Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dou Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. FanFan Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Leiqun Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ling Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

In this study, X. Y. and G. P. are mainly responsible for the writing of the article; C. L. and L. L. Q., as guides, are mainly responsible for the research; and G. X. is mainly responsible for data input. S. Y., W. S. J., and T. D. are mainly responsible for data calculation and correction. W. X. and Z. F. F. are mainly responsible for the final results, which need additional experiments. We thank all those who participated in the preparation and writing of this article.

Corresponding authors

Correspondence to Leiqun Lu or Ling Chen.

Ethics declarations

Ethics Committee statement

The study protocol (No. LWEC2020024) was approved by the Ethics Committee of the Shanghai Ruijin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China. The subjects provided written informed consent, and the study protocol was approved by the Institute’s Committee on Human Research.

Institutional Review Board statement

The study protocol (no. LWEC2020024) was approved by the Ethics Committee of the Shanghai Ruijin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China. The subjects gave their written informed consent; the study protocol was approved by the Institute’s Committee on Human Research.

Informed consent statement

Informed consent was obtained from all the subjects involved in the study.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yan Xuan and Ping Gao contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xuan, Y., Gao, P., Shen, Y. et al. Association of hypertriglyceridemic waist phenotype with non-alcoholic fatty liver disease: a cross-sectional study in a Chinese population. Hormones 21, 437–446 (2022). https://doi.org/10.1007/s42000-022-00374-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42000-022-00374-x

Keywords

Search

Navigation