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      The value of neck circumference (NC) as a predictor of non-alcoholic fatty liver disease (NAFLD) *

      research-article
      Author(s): a , b , 1 , a , c , 1 , a , a , d , e , e , a , a , f , a , g , h , ** , a , *
      Publication date (Electronic):
      Journal: Journal of Clinical & Translational Endocrinology
      Publisher: Elsevier
      Keywords: Neck circumference, Waist circumference, Non-alcoholic fatty liver disease, Insulin resistance, NC, Neck circumference, NAFLD, Nonalcoholic fatty liver disease, NHtR, Neck circumference-height ratio, T2DM, Type 2 diabetes mellitus, IR, Insulin resistance, MS, Metabolic syndrome, CVD, Cardiovascular diseases, TG, Triglyceride, HOMA-IR, Homeostasis model assessment-insulin resistance, VAT, Visceral adipose tissue, BMI, Body mass index, NWtR, Neck circumference-weight ratio, WC, Waist circumference, HC, Hip circumference, HUA, Hyperuricemia, TC, Total cholesterol, HDL-C, High-density lipoprotein cholesterol, LDL-C, Low-density lipoprotein cholesterol, FBG, Fasting blood glucose, ALT, Alanine aminotransferase, AST, Aspartate aminotransferase, γ-GT, gamma-glutamyltransferase, SUA, Serum uric acid, BUN, Blood urea nitrogen, Scr, Serum creatinine, HbA1c, Hemoglobin A1c, FINS, Fasting insulin, FT3, Free triiodothyronine 3, FT4, Free thyroxine, TSH, Thyroid stimulating hormone, QUICKI, Quantitative insulin-sensitivity check index, AUC, Area under the curve, OR, Odd ratio

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          Abstract

          Aims

          To analyze the correlation between neck circumference (NC) and non-alcoholic fatty liver disease (NAFLD) and compare the predictive value of NC for NAFLD with that of other simple anthropometric measures and other biochemical profiles.

          Methods

          2761 subjects, undergoing a medical check-up at the Changhai Hospital between October 01, 2012 and November 30, 2012, were recruited to the study. NC, other simple anthropometric measures, and biochemical profiles were analyzed.

          Results

          NC in NAFLD subjects with or without elevated ALT were 38.94 ± 2.62 cm and 37.21 ± 3.06 cm respectively, which was significantly higher than that in subjects with other metabolic disorders (NC: 35.33 ± 3.03 cm) and in normal controls (NC: 32.60 ± 2.37) (both P < 0.001). NC in women with NAFLD increased by 1 cm and fasting insulin (FINS) and homeostasis model assessment-insulin resistance (HOMA-IR) increased by 1.87 mIU/L and 1.43, respectively. Compared with other anthropometric measures, neck circumference-height ratio (NHtR) had a significant impact both on the incidence of NAFLD. After adjustment for sex, abdominal obesity and other influencing factors, the incidence of NAFLD still tended to positively correlate with NC. Optimal cut-off points of NC and NHtR for predicting NAFLD in males were 37.25 cm and 0.224, respectively, and such points in females were 32.90 cm and 0.208, respectively.

          Conclusion

          NC was wider in NAFLD patients than in healthy subjects and other metabolic disorder sufferers. NC and NHtR could be used as simple predictive tools for NAFLD.

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          Most cited references29

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          Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

          S Nambi, K Mather, A. Katz … (2000)
          Insulin resistance plays an important role in the pathophysiology of diabetes and is associated with obesity and other cardiovascular risk factors. The "gold standard" glucose clamp and minimal model analysis are two established methods for determining insulin sensitivity in vivo, but neither is easily implemented in large studies. Thus, it is of interest to develop a simple, accurate method for assessing insulin sensitivity that is useful for clinical investigations. We performed both hyperinsulinemic isoglycemic glucose clamp and insulin-modified frequently sampled iv glucose tolerance tests on 28 nonobese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SI(Clamp)) and minimal model analysis (SI(MM)) that were comparable to previous reports (r = 0.57). We performed a sensitivity analysis on our data and discovered that physiological steady state values [i.e. fasting insulin (I(0)) and glucose (G(0))] contain critical information about insulin sensitivity. We defined a quantitative insulin sensitivity check index (QUICKI = 1/[log(I(0)) + log(G(0))]) that has substantially better correlation with SI(Clamp) (r = 0.78) than the correlation we observed between SI(MM) and SI(Clamp). Moreover, we observed a comparable overall correlation between QUICKI and SI(Clamp) in a totally independent group of 21 obese and 14 nonobese subjects from another institution. We conclude that QUICKI is an index of insulin sensitivity obtained from a fasting blood sample that may be useful for clinical research.
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            Neck circumference as a novel measure of cardiometabolic risk: the Framingham Heart study.

            Joseph Massaro, James Meigs, Nick Fox … (2010)
            Neck circumference, a proxy for upper-body sc fat, may be a unique fat depot that confers additional cardiovascular risk above and beyond central body fat. Participants with neck circumference measures who underwent multidetector computed tomography to assess visceral adipose tissue (VAT) were included [n=3307, 48% women; mean age=51 yr; mean body mass index (BMI)=27.8 kg/m2; mean neck circumference=40.5 cm (men) and 34.2 cm (women)]. Sex-specific linear regression models were used to assess the association between sd increase in neck circumference and cardiovascular disease (CVD) risk factors (systolic and diastolic blood pressure; total, low-density lipoprotein, and high-density lipoprotein cholesterol and triglycerides; and fasting plasma glucose, insulin, proinsulin, and homeostasis model assessment of insulin resistance). Neck circumference was correlated with VAT [r=0.63 (men); r=0.74 (women); P<0.001] and BMI [r=0.79 (men); r=0.80 (women); P<0.001]. After further adjustment for VAT, neck circumference was positively associated with systolic blood pressure, diastolic blood pressure in men only, triglycerides, fasting plasma glucose in women only, insulin, proinsulin, and homeostasis model assessment of insulin resistance and was inversely associated with high-density lipoprotein (all P values<0.01). Similar results were observed in models that adjusted for both VAT and BMI. In a secondary analysis of incident CVD as an outcome, there was no statistically significant association observed for neck circumference in multivariable-adjusted models. Neck circumference is associated with CVD risk factors even after adjustment for VAT and BMI. These findings suggest that upper-body sc fat may be a unique, pathogenic fat depot.
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              Simple noninvasive systems predict long-term outcomes of patients with nonalcoholic fatty liver disease.

              Jon P. Day, Svanhildur Haflidadottir, Kevin Mills … (2013)
              Some patients with nonalcoholic fatty liver disease (NAFLD) develop liver-related complications and have higher mortality than other patients with NAFLD. We determined the accuracy of simple, noninvasive scoring systems in identification of patients at increased risk for liver-related complications or death. We performed a retrospective, international, multicenter cohort study of 320 patients diagnosed with NAFLD, based on liver biopsy analysis through 2002 and followed through 2011. Patients were assigned to mild-, intermediate-, or high-risk groups based on cutoff values for 2 of the following: NAFLD fibrosis score, aspartate aminotransferase/platelet ratio index, FIB-4 score, and BARD score. Outcomes included liver-related complications and death or liver transplantation. We used multivariate Cox proportional hazard regression analysis to adjust for relevant variables and calculate adjusted hazard ratios (aHRs). During a median follow-up period of 104.8 months (range, 3-317 months), 14% of patients developed liver-related events and 13% died or underwent liver transplantation. The aHRs for liver-related events in the intermediate-risk and high-risk groups, compared with the low-risk group, were 7.7 (95% confidence interval [CI]: 1.4-42.7) and 34.2 (95% CI: 6.5-180.1), respectively, based on NAFLD fibrosis score; 8.8 (95% CI: 1.1-67.3) and 20.9 (95% CI: 2.6-165.3) based on the aspartate aminotransferase/platelet ratio index; and 6.2 (95% CI: 1.4-27.2) and 6.6 (95% CI: 1.4-31.1) based on the BARD score. The aHRs for death or liver transplantation in the intermediate-risk and high-risk groups compared with the low-risk group were 4.2 (95% CI: 1.3-13.8) and 9.8 (95% CI: 2.7-35.3), respectively, based on the NAFLD fibrosis scores. Based on aspartate aminotransferase/platelet ratio index and FIB-4 score, only the high-risk group had a greater risk of death or liver transplantation (aHR = 3.1; 95% CI: 1.1-8.4 and aHR = 6.6; 95% CI: 2.3-20.4, respectively). Simple noninvasive scoring systems help identify patients with NAFLD who are at increased risk for liver-related complications or death. NAFLD fibrosis score appears to be the best indicator of patients at risk, based on HRs. The results of this study require external validation. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Shizhong Bu
                Qin Huang
                Journal
                Journal ID (nlm-ta): J Clin Transl Endocrinol
                Journal ID (iso-abbrev): J Clin Transl Endocrinol
                Title: Journal of Clinical & Translational Endocrinology
                Publisher: Elsevier
                ISSN (Electronic): 2214-6237
                Publication date PMC-release: 23 July 2014
                Publication date Collection: December 2014
                Publication date (Electronic): 23 July 2014
                Volume: 1
                Issue: 4
                Pages: 133-139
                Affiliations
                [a ]Department of Endocrinology, Changhai Hospital, Shanghai 200433, PR China
                [b ]Tenth People's Hospital, Tongji University, Shanghai 200072, PR China
                [c ]Fujian Provincial Corps Hospital, Chinese People's Armed Police Forces, Fuzhou 350003, PR China
                [d ]Department of Endocrinology, Fuzhou General Hospital of Nanjing Military Command, Fuzhou 350025, PR China
                [e ]Medical Center, Changhai Hospital, Shanghai 200433, PR China
                [f ]Xiang'an Cadre Sanatorium, Second Military Medical University, Shanghai 200433, PR China
                [g ]Diabetes Center, School of Medicine, Ningbo University, Ningbo 315211, PR China
                [h ]The Affiliated Hospital, Ningbo University, Ningbo 315211, PR China
                Author notes
                [* ]Corresponding author. Department of Endocrinology, Changhai Hospital, No. 168 Changhai Road, Shanghai 200433, PR China. Tel.: +86 21 31161392; fax: +86 21 65385289Corresponding author. Department of EndocrinologyChanghai HospitalNo. 168 Changhai RoadTel.: +86 21 31161392; fax: +86 21 65385289Shanghai200433PR China qxinyi1220@ 123456163.com
                [** ]Corresponding author. 411 Wang Changlai Building, No. 818 Fenghua Road, Ningbo 315211, PR China. Tel.: +86 574 87609607Corresponding author.411 Wang Changlai Building, No. 818 Fenghua RoadTel.: +86 574 87609607Ningbo315211PR China bushizhong@ 123456nbu.edu.cn
                [1]

                Y.H. and J.C. contributed equally to this work.

                Article
                Publisher ID: S2214-6237(14)00022-2
                DOI: 10.1016/j.jcte.2014.07.001
                PMC ID: 5685024
                PubMed ID: 29159094
                SO-VID: 3a177fbf-50f2-4e1f-bb95-08c2434c0159
                Copyright © © 2014 The Authors
                License:

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

                History
                Date received : 4 May 2014
                Date revision received : 19 June 2014
                Date accepted : 1 July 2014
                Categories
                Subject: Research Paper

                Keywords: neck circumference,waist circumference,non-alcoholic fatty liver disease,insulin resistance,nc, neck circumference,nafld, nonalcoholic fatty liver disease,nhtr, neck circumference-height ratio,t2dm, type 2 diabetes mellitus,ir, insulin resistance,ms, metabolic syndrome,cvd, cardiovascular diseases,tg, triglyceride,homa-ir, homeostasis model assessment-insulin resistance,vat, visceral adipose tissue,bmi, body mass index,nwtr, neck circumference-weight ratio,wc, waist circumference,hc, hip circumference,hua, hyperuricemia,tc, total cholesterol,hdl-c, high-density lipoprotein cholesterol,ldl-c, low-density lipoprotein cholesterol,fbg, fasting blood glucose,alt, alanine aminotransferase,ast, aspartate aminotransferase,γ-gt, gamma-glutamyltransferase,sua, serum uric acid,bun, blood urea nitrogen,scr, serum creatinine,hba1c, hemoglobin a1c,fins, fasting insulin,ft3, free triiodothyronine 3,ft4, free thyroxine,tsh, thyroid stimulating hormone,quicki, quantitative insulin-sensitivity check index,auc, area under the curve,or, odd ratio
                Data availability:
                Keywords: neck circumference, waist circumference, non-alcoholic fatty liver disease, insulin resistance, nc, neck circumference, nafld, nonalcoholic fatty liver disease, nhtr, neck circumference-height ratio, t2dm, type 2 diabetes mellitus, ir, insulin resistance, ms, metabolic syndrome, cvd, cardiovascular diseases, tg, triglyceride, homa-ir, homeostasis model assessment-insulin resistance, vat, visceral adipose tissue, bmi, body mass index, nwtr, neck circumference-weight ratio, wc, waist circumference, hc, hip circumference, hua, hyperuricemia, tc, total cholesterol, hdl-c, high-density lipoprotein cholesterol, ldl-c, low-density lipoprotein cholesterol, fbg, fasting blood glucose, alt, alanine aminotransferase, ast, aspartate aminotransferase, γ-gt, gamma-glutamyltransferase, sua, serum uric acid, bun, blood urea nitrogen, scr, serum creatinine, hba1c, hemoglobin a1c, fins, fasting insulin, ft3, free triiodothyronine 3, ft4, free thyroxine, tsh, thyroid stimulating hormone, quicki, quantitative insulin-sensitivity check index, auc, area under the curve, or, odd ratio

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