Advanced Search

Publications > Journals > Journal of Clinical and Translational Hepatology > Article Full Text


HbA1C as a Biomarker of Non-alcoholic Fatty Liver Disease: Comparison with Anthropometric Parameters

  • Muhammad Masroor*  and
  • Zeba Haque 
 Author information
Journal of Clinical and Translational Hepatology   2021;9(1):15-21

doi: 10.14218/JCTH.2019.00046


Background and Aims

Multiple non-invasive methods including radiological, anthropometric and biochemical markers have been reported with variable performance. The present study assessed glycosylated hemoglobin (HbA1C) as a biomarker to predict non-alcoholic fatty liver disease (NAFLD) and its severity, compared with body mass index (BMI), waist to hip ratio (WHR) and waist circumference (WC)


This case control study included 450 individuals, including 150 cases and 300 age- and gender-matched controls recruited from the Dow Radiology Institute on the basis of radiological findings of fatty infiltration on abdominal ultrasound through convenient sampling. BMI, WHR and WC were measured according to standard protocols. HbA1C was determined by turbidimetric inhibition immunoassay


Among the cases and controls, 66% and 32% had HbA1C levels higher than 5.7% respectively. HbA1C and BMI were significantly associated with NAFLD [crude odds ratio (cOR)=4.12, 2.88, 2.25 (overweight) and 4.32 (obese)]. WC was found to be significantly associated with NAFLD for both genders (cOR in males=5.50 and females=5.79, p<0.01). After adjustment for other parameters, HbA1C and WC were found to be significantly associated with NAFLD (aOR=3.40, p<0.001) along with WC in males (aOR=2.91, p<0.05) and in females (aOR=4.28, p<0.05). A significant rise in severity of hepatic steatosis was noted with increases in HbA1C, BMI and WC. HbA1C possessed a positive predictive value of 76% for the study population [0.76, confidence interval (CI): 0.715-0.809], 70.6% for males (0.706, CI: 0.629-0.783) and 80% for females (0.80, CI: 0.741-0.858).


Higher than normal HbA1C and WC measurements possess a more than 70% potential to predict NAFLD. It is the single risk factor that is strongly associated with NAFLD after adjustment for indices of body measurements. HbA1C may be presented as a potential biomarker for NAFLD in examination with other anthropometric measures in the adult population.


NAFLD, HbA1C, Biomarker, Non-diabetic population, Body weight measurements, Body mass index (BMI), Waist circumference (WC)


Non-alcoholic fatty liver disease (NAFLD) refers to a condition wherein excess fat accumulates in the liver of people with no history of significant alcohol consumption.1 Fat molecules are deposited in the form of triacylglycerols (TAGs) in hepatocytes. Hepatic steatosis refers to fatty change in hepatocytes and is largely a benign condition, while, not in a small number of patients, it may trigger an immune response and lead to non-alcoholic steatohepatitis (NASH) followed by cirrhosis and cancer.2 NAFLD is alarmingly increasing around the globe. The estimated global prevalence of NAFLD ranges from 6.3-33% among the general population, varying among and within populations.3 The prevalence is highest among obese (57%) and diabetic (90%) populations.4 A rising trend of prevalence of NAFLD has been observed in line with obesity, at a rate of 25%.5 Sedentary lifestyle, dyslipidemia and metabolic syndrome are also well documented risk factors for NAFLD,4 along with other risk factors, such as hepatitis B and C virus infection, Wilson’s disease, and chronic blood and kidney diseases.

High blood glucose levels non-enzymatically form glycosylated hemoglobin (HbA1C) as an irreversible reaction. Once formed, HbA1C remains in circulation for 2-3 months; hence, it has been identified as the marker for diabetes diagnosis and control. According to the American Association of Clinical Endocrinologists, an acceptable level of HbA1C in diabetics is <6.5% and reflects good metabolic control;6 although, tight control is recommended to avoid increased risk of hypoglycemia, but the level of <6.5% is considered as acceptable in this study. Obesity and diabetes have been reported as strong predictors of NAFLD.7 Therefore, it may be assumed that patients with NAFLD have increased levels of HbA1C as well.

On the contrary, recently emerging data suggest that HbA1C may be raised in the absence of diabetes. Chen et al.,8 in 2020, reported that after multiple adjustments HbA1C serves as a risk factor for NAFLD, with a significant odds ratio of 1.58 in metabolically-intact patients. The South Asian countries have reported a prevalence of 13.9% of NAFLD in the adult healthy population that excludes obesity and diabetes.9 It is suggested that inter-individual biological differences may also contribute to the elevation of HbA1C, apart from high blood sugar.10,11

Similarly, various indices of body measurements, such as body mass index (BMI), waist to hip ratio (WHR), and obesity status, have been linked with insulin resistance, type II diabetes mellitus (Type II DM),12 and NAFLD. About 20–35% of lean NAFLD cases have been reported from rural areas of some Asian countries.13 Waist circumference (WC), on the other hand, has emerged as the physical measure associated significantly with NAFLD.14 The debate on the relevance of various body weight measurements, including BMI, WHR and WC, has generated much data with conflicting observations regarding their significance as the risk factor for NAFLD.15,16

Although liver biopsy is the gold standard for the diagnosis and grading of severity of hepatic steatosis and NASH, due to its invasive nature and cost/risks, alternate non-invasive and cost-effective methods have been widely searched and reported.17 Radiological diagnoses and grading is widely recommended by nearly all associations for study of liver diseases, such as the European Association for the Study of the Liver, the Italian Association for the Study of the Liver, and the American Association for the Study of Liver Diseases.18 The non-invasive protocols to diagnose NAFLD cannot equate to the gold standard liver biopsy, but they may help in detecting early steatosis in hepatocytes.

NAFLD is among the most common cause of chronic liver disease.17 The diagnosis protocol of NAFLD basically addresses pathological/radiological evidence of fatty infiltration, liver biochemistry, and history of alcohol consumption and other chronic diseases. There is dire need of identifying biochemical markers with significant discriminatory performance for NAFLD diagnosis. The present study was, therefore, designed to measure and find the association of HbA1C as a novel biomarker for the diagnosis of NAFLD patients identified through abdominal ultrasound.


This case control study was conducted at the Dow University of Health Sciences (DUHS). Diagnosis of fatty liver disease (referred to here as FLD) was based on ultrasonographic evidence of fatty infiltration of hepoatocytes.18 Individuals of both genders in the adult age group, undergoing upper abdominal ultrasonography at the Department of Radiology at the DUHS, were recruited for the study. Those having FLD on ultrasound were identified as cases, while people showing no fatty infiltration were included as controls. Informed consent was obtained after explaining the study procedures and outcomes; those who refused to be included were dropped out. Considering the prevalence of the condition in Pakistan,6 sample size was calculated by OpenEpi as 104 (52 each in the case and control groups). However, to improve the strength of our study, the total sample size was increased to 450, with case-to-control ratio of 1:2. The participants were recruited through convenient sampling (150 cases and 300 age- and gender-matched controls). The severity of steatosis was graded on the basis of fatty infiltration found on ultrasonography, from grades (1-3) as follows: grade 1 had minimal infiltration, with echogenicity slightly increased; grade 2 had moderate infiltration, with echogenically obscured portal vessel walls; and grade 3 had heavy fatty infiltration.19

For the purpose of standardization, subjects undergoing ultrasonography (by two trained sonologists) were included in the study. Patients with chronic liver disease, tumors, acute hepatitis, Wilson’s and kidney diseases, known NAFLD, and those having history of alcohol consumption were excluded. History regarding presenting complaints, comorbidities, lifestyle, dietary intake, and medication were recorded on structured proforma. Detailed physical examination was carried out. Height in meters and weight in Kg was recorded for BMI (reported as Kg/m2). WC and WHR were measured by standard methods.20 Blood samples were collected in the fasting state, with samples in appropriate bar-coded containers, for estimation of HbA1C by turbidimetric inhibition immunoassay and expressed as percentage (%). The value of 5.7% or below was taken as normal.21 The study was approved by the institutional review board of DUHS (IRB-447/DUHS/-14) and funded by the Higher Education Commission of Pakistan.

Statistical analysis

Data was analyzed using SPSS version 21.0 and STATA 14. Chi-square, ANOVA and binary logistic regression were used for analysis. Frequencies and proportions were generated for all categorical variables, study participants’ characteristics and body weight measurements with NAFLD. These were compared using the chi-square (χ2) test, while mean differences for anthropometric measures with steatosis severity grades were assessed using ANOVA. Binary logistic regression analyses (univariate and multivariate) were used to assess the factors associated with NAFLD occurrence. Results of regression were reported as crude odds ratio (cOR) and adjusted odds ratio (aOR) with 95% confidence interval (CI). Receiver operating characteristic (ROC) curve was plotted to compare each variable with NAFLD and to find the valid predictive value of HbA1C to diagnose NAFLD. A p value <0.05 was taken as significant.


Baseline characteristics are given in Table 1. Females dominated the sample, with 56% among cases and 60.3% among controls. The mean age of the study sample was 43.96 ± 11.06 years.

Table 1

Baseline characteristics among cases and controls, n=450

Age, yearsMean ± SD44.68 ± 10.6243.61 ± 11.270.333
Gender, n (%)0.378
Male66 (44.0)119 (39.7)
Female84 (56.0)181 (60.3)
HbA1C, n (%)<0.001
≤5.7%51 (34.0)204 (68.0)
>5.7%99 (66.0)96 (32.0)
Diabetes status, n (%)<0.001
Yes29 (19.3)23 (7.7)
No121 (80.7)277 (92.3)
BMI, n (%)<0.001
Underweight/Normal18 (12.0)93 (31.0)
Overweight45 (30.0)103 (34.3)
Obese87 (58.0)104 (34.7)
WHR, n (%)
  Male<0.99 (13.6)47 (39.5)<0.001
≥0.957 (86.4)72 (60.5)
  Female<0.8516 (19.0)43 (23.8)0.391
≥0.8568 (81.0)138 (76.2)
Waist circumference, n (%)
  Male<90 cm7 (10.6)47 (39.5)<0.001
≥90 cm59 (89.4)72 (60.5)
  Female<80 cm3 (3.6)32 (17.7)0.002
≥80 cm81 (96.4)149 (82.3)

Table 2 shows the variations of HbA1C, BMI, WHR, WC and frequency of known diabetics (type II DM) among the various grades of NAFLD. We found that 40% of individuals with type II DM had grade III steatosis, while 23.7% and 10.9% were among grades II and I respectively. Only 7.7% of diabetic people within the study sample did not have FLD.

Table 2

Variations in HbA1C and indices of body measurements with severity of steatosis

No fatty liverFatty liver
Grade IGrade IIGrade III
HbA1C (Mean ± SD)5.54 ± 0.896.21 ± 1.256.90 ± 1.857.49 ± 2.22<0.001
BMI (Mean ± SD)28.38 ± 6.1529.86 ± 5.9232.19 ± 5.2932.36 ± 3.63<0.001
WHR-Male (Mean ± SD)0.91 ± 0.110.94 ± 0.040.96 ± 0.060.98 ± 0.090.038
WHR-Female (Mean ± SD)0.90 ± 0.100.91 ± 0.070.92 ± 0.070.95 ± 0.100.772
WC-Male (Mean ± SD)94.16 ± 16.4101.10 ± 11.0105.63 ± 14.2111.2 ± 8.9<0.001
WC-Female (Mean ± SD)95.12 ± 14.3100.38 ± 11.2101.61 ± 12.2108.3 ± 6.40.003
Diabetes, n (%)<0.001
  Yes23 (7.7)7 (10.9)18 (23.7)4 (40.0)
  No277 (92.3)57 (89.1)58 (76.3)6 (60.0)

Odds for HbA1C were significantly high [cOR=4.12 (CI: 2.72-6.25)] and were consistently high after adjusting with history of type II DM and the indices of body measurements [BMI, WHR and WC of 3.40 (CI: 2.19-5.26); in males, 2.08 (CI: 1.06- 4.11) and in females, 5.20 (CI: 2.79-9.68)] (Table 3). BMI was significantly associated with NAFLD; however, after adjustment with type II DM and HbA1C, the odds of BMI were found to retain significance in obese individuals only. Further, after stratification of data on the basis of gender, it became insignificant in males. In both genders, WHR was found to be not significant. Odds for HbA1C and WC were found to consistently be significant in the total study sample as well as in both genders (Table 3).

Table 3

Associations of HbA1C, BMI, history of type II DM, WHR and WC with NAFLD

VariablescOR (95% CI)p-valueNAFLD
aOR (95% CI)p-valueaOR (95% CI)p-valueaOR (95% CI)p-value
  ≤ 5.7%1111
  > 5.7%4.12 (2.72-6.25)<0.0013.40 (2.19-5.26)<0.0012.08 (1.06-4.11)0.0335.20 (2.79-9.68)<0.001
Diabetes status
  Yes2.88 (1.60-5.19)<0.0011.64 (0.86-3.0900.1271.08 (0.40-2.86)0.8772.21 (0.88-5.52)0.089
  Overweight2.25 (1.22-4.17)0.0091.79 (0.94-3.40)0.0741.65 (0.66-4.07)0.2781.02 (0.36-2.89)0.962
  Obese4.32 (2.42-7.71)<0.0013.30 (1.80-6.050<0.0011.73 (0.70-4.26)0.2302.90 (1.11-7.58)0.029
    WHR <0.91--1--
    WHR ≥0.94.13 (1.87-9.13)<0.001--2.03 (0.81-5.09)0.128--
    WHR <0.851----1
    WHR ≥0.851.32 (0.69-2.52)0.392----0.72 (0.32-1.61)0.432
    WC <90 cm1---1---
    WC ≥90 cm5.50 (2.31-13.07)<0.001--2.91 (1.06-7.94)0.037--
    WC <80 cm1-----1
    WC ≥80 cm5.79 (1.72-19.52)0.005----4.28 (1.10-16.61)0.035

ROC curve analysis demonstrated a valid positive prediction value for HbA1C in comparison with WC, and HbA1C for a binary outcome (NAFLD) (Fig. 1A, 1B) in both genders. The area under the curve (AUC) was 76% for HbA1C in the overall study population (0.76, CI: 0.715-0.809), being 70.6% for males (0.706, CI: 0.629-0.783) and 80% for females (0.80, CI: 0.741-0.858).

ROC curve of HbA<sub>1C</sub> and WC in males (A) and females (B) in relation to NAFLD.
Fig. 1  ROC curve of HbA1C and WC in males (A) and females (B) in relation to NAFLD.


Baseline characteristics of the study population are given in Table 1. Age- and gender-matched controls exhibited more than 5.7% HbA1C in 66% and 32% of controls and cases respectively. The other significant presentation was a higher BMI in more than 80% and 70% of controls and cases respectively, which is consistent with others reports.22,23 Generally, BMI and central obesity are higher in Asian populations.24 We also confirmed a female preponderance (89.4 vs. 96.4), with higher WC presenting with NAFLD. Attempts are in progress to develop non-invasive methods to predict NAFLD, one being the assessment of HbA1C to detect hepatic steatosis. A cross-sectional study found a significant association of HbA1C with NAFLD in an elderly Chinese population.25 Similarly, a significant correlation was found between HbA1C and NAFLD in an adult Korean population, again in a cross- sectional setting.26 However, the cross-sectional design only identifies the prevalence of a factor at a certain point of time. A longitudinal study, on the other hand, suggested that HbA1C may contribute to the development of NAFLD.8 Chen et al.8 further expressed the need for more studies to test the impact of HbA1C on development of NAFLD.

The present study found a significant association of HbA1C with NAFLD in a case control design, which strengthens the results to be interpreted as a potential predictor of the disease retrospectively. This association was positive both in diabetic, non-diabetic, obese, and lean persons, indicating that those who have HbA1C higher than 5.7% are 4-times more prone to developing fatty liver disease (cOR=4.12, p<0.001). Recently, HbA1C has been reported as risk factor for NAFLD, with an odds ratio of 1.58 (p<0.004).8 Another study also showed that presence of NAFLD presents a higher risk of glycemic progression and incident diabetes.27 Therefore, existing data until now suggests that NAFLD and glycemic derangement coexist, but the conflict remains regarding the cause and effect relationship of HbA1C and NAFLD.

Ultrasonography has recently been largely discussed as a useful bedside diagnostic tool to detect hepatic steatosis.28 The need for non-invasive tools/biomarkers has also become more important, with numerous drug trials underway, some having reached phase IV. Follow-up of these cases is not feasible with multiple biopsies. The ultrasonographic fatty liver indicator is reported to be able to identify mild hepatic steatosis that correlates with histological findings of severity and metabolic parameters.29 In concordance with this, our results also identified ultrasound as a reliable tool to detect hepatic steatosis and its severity. Ballestri et al.29 also correlated ultrasonographically -detected steatosis with all parameters of glycemic control, except HbA1C.

The present study confirms that the severity grades of steatosis correlate significantly with HbA1C levels as well. Among the body measurements, BMI and WC showed stronger correlation with severity grades of steatosis than WHR in both genders (Table 2). Others have reported that ultrasonographic techniques have been improved over the last decade, but there is still a dire need to develop a combination of pre-test probability based on anthropometric variables and/or biochemical biomarkers with various ultrasonographic techniques30 which can be applied to the liver biopsy scoring system.31 Our results confirm that HbA1C and WC along with ultrasonographic evidence of steatosis can detect early fatty change in hepatocytes satisfactorily (Table 2).

HbA1C is produced in direct proportions to the duration and episodes of high blood glucose concentrations.32 HbA1C may also vary due to biological differences among individuals, apart from hyperglycemic episodes.33 Hyperglycemic episodes, in addition to the production of advanced glycation end-products also affect lipid metabolism and result in increased synthesis of TAGs that tend to deposit in various tissues of the body, including liver. TAG deposition in adipose tissue increases BMI, while in liver parenchyma it leads to fatty liver. Type II DM has been strongly linked with fatty deposition in liver and HbA1C may be causally associated with NAFLD.34 On the other hand, obesity in the absence of type II DM also relates to increased fat content in body tissues. Higher BMI has been associated with insulin resistance and increases in HbA1C.35 However, in addition to this, our study confirms increase in HbA1C levels results in more than 3-times chance of NAFLD development independent of diabetes mellitus.

Studies have demonstrated variable results when comparing effect of age, gender, BMI, and obesity. There are opinions that BMI is not a good indicator of chronic disease association, as compared to abdominal fatness36 (central obesity, represented by WC). Excess abnormal fat predisposes to obesity-related disease, regardless of total body fat. The present study found both BMI and WC to be significantly different (p<0.001) with presence of NAFLD in both genders (Table 1), while WHR was significantly different only among males. All of these indices were significantly associated with NAFLD (Table 3). However, when it was adjusted for other parameters, this association became weaker, whereas association with WC remained significant both in males and females (aOR 2.91 and 4.28 respectively, p<0.001). This indicates that abdominal obesity is more associated with presence of NAFLD. Even the patients who are lean develop fatty liver if they have central obesity.37 Both of these conditions are associated with insulin resistance and, hence, high HbA1C may be a common link between NAFLD and type II DM/central obesity.

The results of this study also depicted that, as compared to male patients, females had higher central obesity (Table 1) and NAFLD in concordance to results reported by Dai et al.,38 who also found increased measures of BMI and WC in NAFLD patients. The present study demonstrates that NAFLD can be predicted by a combination of HbA1C and WC both in males (AUC=0.706 and 0.681 respectively) and in females (AUC=0.800 and 0.632 respectively). This is in concordance to others who claimed that a combination of age, sex, WC, alanine aminotransferase, HbA1C, and HOMA-IR with an AUC of 0.87 can best predict NAFLD.39 With these data, it is tempting to suggest that investigation of HbA1C and central obesity may predict the presence of NAFLD in otherwise healthy individuals.


HbA1C level is significantly associated with presence of NAFLD. Higher than normal HbA1C levels possess greater than 70% potential to predict NAFLD. WC is the second most associated factor with NAFLD. HbA1C is the single risk factor that is strongly associated with NAFLD after adjustment for BMI, WHR and WC. HbA1C may be presented as a novel potential biomarker for NAFLD examined with WC in the adult population.


Liver biopsy was not performed owing to its invasive nature, with no justification for the test in controls. Secondly, ultrasonography of liver may not identify cases of NAFLD with early changes; therefore, some of the potential cases may have been grouped as controls.



adjusted odds ratio


area under the ROC curve


body mass index


confidence interval


crude odds ratio


Dow University of Health Sciences


fatty liver disease


glycosylated hemoglobin


non-alcoholic fatty liver disease


non-alcoholic steatohepatitis


receiver operating characteristic



Type II DM: 

type II diabetes mellitus


waist circumference


waist to hip ratio



The authors are grateful to the sonologists at the Institute of Radiology and Ms. Sidra Zaheer in the Department of Research at the Dow University of Health Sciences for their cooperation to sample recruitment and analysis of data respectively.


The study was supported by the Higher Education Commission (HEC) of Pakistan by a financial grant (No. 20-4231/NRPU/R&d/HEC/14). The role of the HEC is to support the research study only.

Conflict of interest

The authors have no conflict of interests related to this publication.

Authors’ contributions

Conception and design of the study (MM, ZH), recruitment and examination of the patients (MM), collection of the data (MM), performance of the assays (MM), analysis of the data (MM, ZH), and writing of the paper (MM, ZH).


  1. Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association. Hepatology 2012;55:2005-2023 View Article
  2. Zhang XJ, She ZG, Li H. Time to step-up the fight against NAFLD. Hepatology 2018;67:2068-2071 View Article
  3. Vernon G, Baranova A, Younossi ZM. Systematic review: the epidemiology and natural history of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in adults. Aliment Pharmacol Ther 2011;34:274-285 View Article
  4. Lam B, Younossi ZM. Treatment options for nonalcoholic fatty liver disease. Therap Adv Gastroenterol 2010;3:121-137 View Article
  5. Younossi ZM. Non-alcoholic fatty liver disease - A global public health perspective. J Hepatol 2019;70:531-544 View Article
  6. Garber AJ, Handelsman Y, Grunberger G, Einhorn D, Abrahamson MJ, Barzilay JI, et al. Consensus statement by the American association of clinical endocrinologists and American college of endocrinology on the comprehensive type 2 diabetes management algorithm - 2020 executive summary. Endocr Pract 2020;26:107-139 View Article
  7. Byrne CD, Targher G. NAFLD: a multisystem disease. J Hepatol 2015;62:S47-S64 View Article
  8. Chen C, Zhu Z, Mao Y, Xu Y, Du J, Tang X, et al. HbA1c may contribute to the development of non-alcoholic fatty liver disease even at normal-range levels. Biosci Rep 2020;40:BSR20193996 View Article
  9. Niaz A, Ali Z, Nayyar S, Fatima N. Prevalence of NAFLD in healthy and young male individuals. ISRN Gastroenterol 2011;2011:363546 View Article
  10. Chalew SA, McCarter RJ, Hempe JM. Biological variation and hemoglobin A1c: relevance to diabetes management and complications. Pediatr Diabetes 2013;14:391-398 View Article
  11. Li K, Song WJ, Wu X, Gu DY, Zang P, Gu P, et al. Associations of serum glucagon levels with glycemic variability in type 1 diabetes with different disease durations. Endocrine 2018;61:473-481 View Article
  12. Ostovaneh MR, Zamani F, Ansari-Moghaddam A, Sharafkhah M, Saeedian FS, Rohani Z, et al. Nonalcoholic fatty liver: The association with metabolic abnormalities, body mass index and central obesity—A population-based study. Metab Syndr Relat Disord 2015;13:304-311 View Article
  13. Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol 2018;15:11-20 View Article
  14. Lee J, Cho YK, Kang YM, Kim HS, Jung CH, Kim HK, et al. The impact of NAFLD and waist circumference changes on diabetes development in prediabetes subjects. Sci Rep 2019;9:17258 View Article
  15. VanWagner LB, Khan SS, Ning H, Siddique J, Lewis CE, Carr JJ, et al. Body mass index trajectories in young adulthood predict non-alcoholic fatty liver disease in middle age: The CARDIA cohort study. Liver Int 2018;38:706-714 View Article
  16. Niriella MA, Kasturiratne A, Pathmeswaran A, De Silva ST, Perera KR, Subasinghe SKCE, et al. Lean non-alcoholic fatty liver disease (lean NAFLD): characteristics, metabolic outcomes and risk factors from a 7-year prospective, community cohort study from Sri Lanka. Hepatol Int 2019;13:314-322 View Article
  17. Yoneda M, Imajo K, Nakajima A. Non-invasive diagnosis of nonalcoholic fatty liver disease. Am J Gastroenterol 2018;113:1409-1411 View Article
  18. Leoni S, Tovoli F, Napoli L, Serio I, Ferri S, Bolondi L. Current guidelines for the management of non-alcoholic fatty liver disease: A systematic review with comparative analysis. World J Gastroenterol 2018;24:3361-3373 View Article
  19. Onyekwere CA, Ogbera AO, Samaila AA, Balogun BO, Abdulkareem FB. Nonalcoholic fatty liver disease: Synopsis of current developments. Niger J Clin Pract 2015;18:703-712 View Article
  20. Pimenta NM, Santa-Clara H, Melo X, Cortez-Pinto H, Silva-Nunes J, Sardinha LB. Waist-to-hip ratio is related to body fat content and distribution regardless of the waist circumference measurement protocol in nonalcoholic fatty liver disease patients. Int J Sport Nutr Exerc Metab 2016;26:307-314 View Article
  21. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes-2019. Diabetes Care 2019;42:S13-S28 View Article
  22. Bae JC, Cho YK, Lee WY, Seo HI, Rhee EJ, Park SE, et al. Impact of nonalcoholic fatty liver disease on insulin resistance in relation to HbA1c levels in nondiabetic subjects. Am J Gastroenterol 2010;105:2389-2395 View Article
  23. Loomis AK, Kabadi S, Preiss D, Hyde C, Bonato V, St Louis M, et al. Body mass index and risk of nonalcoholic fatty liver disease: Two electronic health record prospective studies. J Clin Endocrinol Metab 2016;101:945-952 View Article
  24. Bodicoat DH, Gray LJ, Henson J, Webb D, Guru A, Misra A, et al. Body mass index and waist circumference cut-points in multi-ethnic populations from the UK and India: the ADDITION-Leicester, Jaipur heart watch and New Delhi cross-sectional studies. PLoS One 2014;9:e90813 View Article
  25. Ma H, Xu C, Xu L, Yu C, Miao M, Li Y. Independent association of HbA1c and nonalcoholic fatty liver disease in an elderly Chinese population. BMC Gastroenterol 2013;13:3 View Article
  26. Lin TC, Lee HM, Seo HN, Oh JS, Kong HR, Cho SA, et al. Correlation between non-alcoholic fatty liver disease and hemoglobin A1c level in adult males without diabetes. Korean J Fam Pract 2018;8:131-135 View Article
  27. Hung CS, Tseng PH, Tu CH, Chen CC, Liao WC, Lee YC, et al. Increased pancreatic echogenicity with US: Relationship to glycemic progression and incident diabetes. Radiology 2018;287:853-863 View Article
  28. Khov N, Sharma A, Riley TR. Bedside ultrasound in the diagnosis of nonalcoholic fatty liver disease. World J Gastroenterol 2014;20:6821-6825 View Article
  29. Ballestri S, Nascimbeni F, Baldelli E, Marrazzo A, Romagnoli D, Targher G, et al. Ultrasonographic fatty liver indicator detects mild steatosis and correlates with metabolic/histological parameters in various liver diseases. Metabolism 2017;72:57-65 View Article
  30. Ballestri S, Nascimbeni F, Lugari S, Lonardo A, Francica G. A critical appraisal of the use of ultrasound in hepatic steatosis. Expert Rev Gastroenterol Hepatol 2019;13:667-681 View Article
  31. Nascimbeni F, Ballestri S, Machado MV, Mantovani A, Cortez-Pinto H, Targher G, et al. Clinical relevance of liver histopathology and different histological classifications of NASH in adults. Expert Rev Gastroenterol Hepatol 2018;12:351-367 View Article
  32. Sherwani SI, Khan HA, Ekhzaimy A, Masood A, Sakharkar MK. Significance of HbA1c test in diagnosis and prognosis of diabetic patients. Biomark Insights 2016;11:95-104 View Article
  33. Hu DS, Zhu SH, Li X, Chen QF, Lin CJ, Fang DH, et al. Association between hemoglobin glycation index and NAFLD in Chinese nondiabetic individuals. Can J Gastroenterol Hepatol 2019;2019:8748459 View Article
  34. Dongiovanni P, Stender S, Pietrelli A, Mancina RM, Cespiati A, Petta S, et al. Causal relationship of hepatic fat with liver damage and insulin resistance in nonalcoholic fatty liver. J Intern Med 2018;283:356-370 View Article
  35. Polsky S, Ellis SL. Obesity, insulin resistance, and type 1 diabetes mellitus. Curr Opin Endocrinol Diabetes Obes 2015;22:277-282 View Article
  36. Kelishadi R, Mirmoghtadaee P, Najafi H, Keikha M. Systematic review on the association of abdominal obesity in children and adolescents with cardio-metabolic risk factors. J Res Med Sci 2015;20:294-307
  37. Sookoian S, Pirola CJ. Systematic review with meta-analysis: risk factors for non-alcoholic fatty liver disease suggest a shared altered metabolic and cardiovascular profile between lean and obese patients. Aliment Pharmacol Ther 2017;46:85-95 View Article
  38. Dai YN, Zhu JZ, Fang ZY, Zhao DJ, Wan XY, Zhu HT, et al. A case-control study: Association between serum neuregulin 4 level and non-alcoholic fatty liver disease. Metabolism 2015;64:1667-1673 View Article
  39. Kühn T, Nonnenmacher T, Sookthai D, Schübel R, Quintana Pacheco DA, von Stackelberg O, et al. Anthropometric and blood parameters for the prediction of NAFLD among overweight and obese adults. BMC Gastroenterol 2018;18:113 View Article
  • Journal of Clinical and Translational Hepatology
  • pISSN 2225-0719
  • eISSN 2310-8819
Back to Top

HbA1C as a Biomarker of Non-alcoholic Fatty Liver Disease: Comparison with Anthropometric Parameters

Muhammad Masroor, Zeba Haque
  • Reset Zoom
  • Download TIFF