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The newly proposed plasma-glycosylated hemoglobin A1c/High-Density lipoprotein cholesterol ratio serves as a simple and practical indicator for screening metabolic associated fatty liver disease: an observational study based on a physical examination population

BMC Gastroenterology volume 24, Article number: 274 (2024) Cite this article

Abstract

Background

Glycotoxicity and lipotoxicity are key pathophysiological mechanisms underlying the development of metabolic associated fatty liver disease (MAFLD). The primary objective of this study is to investigate the association between the newly proposed Plasma-Glycosylated Hemoglobin A1c/High-Density Lipoprotein Cholesterol Ratio (HbA1c/HDL-C ratio) and the risk of MAFLD.

Methods

A study population of 14,251 individuals undergoing health examinations was included. The association between the HbA1c/HDL-C ratio and MAFLD was analyzed using multivariable logistic regression and restricted cubic spline (RCS) analysis. Exploratory analyses were conducted to assess variations in this association across subgroups stratified by gender, age, body mass index (BMI), exercise habits, drinking status, and smoking status. The discriminatory value of the HbA1c/HDL-C ratio and its components for screening MAFLD was evaluated using receiver operating characteristic (ROC) curves.

Results

A total of 1,982 (13.91%) subjects were diagnosed with MAFLD. After adjusting for confounding factors, we found a significant positive association between the HbA1c/HDL-C ratio and MAFLD [odds ratio (OR) 1.34, 95% confidence interval (CI): 1.25, 1.44]. No significant differences in this association were observed across all subgroups (All P for interaction > 0.05). Furthermore, through RCS analysis, we observed a nonlinear positive correlation between the HbA1c/HDL-C ratio and MAFLD (P for non-linearity < 0.001), with a potential threshold effect point (approximately 3 for the HbA1c/HDL-C ratio). Beyond this threshold point, the slope of the MAFLD prevalence curve increased rapidly. Additionally, in further ROC analysis, we found that for the identification of MAFLD, the HbA1c/HDL-C ratio was significantly superior to HbA1c and HDL-C, with an area under the curve (AUC) and optimal threshold of 0.81 and 4.08, respectively.

Conclusions

Our findings suggest that the newly proposed HbA1c/HDL-C ratio serves as a simple and practical indicator for assessing MAFLD, exhibiting well-discriminatory performance in screening for MAFLD.

Peer Review reports

Background

Metabolic associated fatty liver disease (MAFLD) is the most common chronic liver disease globally, encompassing a spectrum of liver conditions ranging from hepatic steatosis to inflammation, necrosis, fibrosis, and cirrhosis [1, 2]. In recent years, with improvements in living conditions and the epidemic of obesity, the incidence of MAFLD has been steadily increasing [3, 4], becoming one of the leading causes of liver disease in adults and children worldwide [5]. According to the latest epidemiological data, the global prevalence of MAFLD is estimated to be around 30% [6], and it appears to be on the rise. It is noteworthy that a high prevalence often implies higher health risks and economic burdens [7]. Studies have shown that besides damaging the liver itself, MAFLD also increases the risk of cardiovascular diseases [8, 9], diabetes [10], metabolic syndrome [11], and cancer mortality [12], posing a serious threat to people’s health and significantly reducing the quality of life in populations. Therefore, early identification of individuals at high risk of MAFLD is crucial.

As it is well known, various risk factors contribute to MAFLD, with insulin resistance (IR) and obesity being key factors, while glycotoxicity and lipotoxicity are considered the most important pathophysiological mechanisms underlying MAFLD development [2, 13]. HbA1c serves as a critical indicator for measuring blood glucose levels [14, 15]. Elevated levels of HbA1c often indicate potential abnormalities in glucose metabolism, which can lead to increased hepatic fat accumulation by activating IR, enhancing liver fat synthesis, and inhibiting fat breakdown. Additionally, high blood glucose levels directly induce oxidative stress and inflammatory responses in the liver, further exacerbating liver damage [16,17,18]. HDL-C is a unique component of the lipid family [19]. Unlike other lipids, HDL-C aids in the reverse transport of cholesterol to the liver for metabolism and excretion, thereby alleviating hepatic lipid burden [20, 21]. Considering the significant roles of glucose and lipid metabolism in MAFLD development, evaluating both HbA1c and HDL-C may provide important assistance in stratifying MAFLD risk. Moreover, we noted a recent study by Hu et al., which reported that combining HbA1c and HDL-C in a ratio could be used to assess the risk of carotid atherosclerosis [22]. To further explore whether the combination of HbA1c and HDL-C is helpful in stratifying the risk of MAFLD, the present study aims to investigate the association between the HbA1c/HDL-C ratio and MAFLD based on data from the NAGALA project’s health examination population and to evaluate the application value of the HbA1c/HDL-C ratio in MAFLD screening.

Methods

Data source and study design

The data for this study were derived from the health examination population recruited by the NAGALA project, aimed at exploring the association between the HbA1c/HDL-C ratio and MAFLD. Detailed information regarding the study design, subject recruitment, eligibility criteria, and data collection for the NAGALA project has been previously described [23]. In brief, the NAGALA project is a population-based survey initiated by the Murakami Memorial Hospital in 1994, aimed at conducting epidemiological investigations of common chronic diseases to promote public health development. The NAGALA cohort data analyzed in this study have been deposited by Okamura et al. into the DRYAD database (https://datadryad.org/stash/dataset/doi:https://doi.org/10.5061/dryad.8q0p192). Based on the terms of service of the DRYAD database and the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, we are permitted to reuse this dataset for secondary analysis with proper attribution of the data source. For the current study purposes, we extracted health examination data from 14,251 adult subjects enrolled in the NAGALA dataset from 1994 to 2016 and conducted secondary analysis of these data based on the new research hypotheses. In this study, we excluded subjects with the following characteristics: (1) individuals with a baseline diagnosis of viral hepatitis or diabetes; (2) subjects with excessive alcohol consumption: ≥210 g per week for men and ≥ 140 g per week for women [24]; (3) subjects taking medication at baseline; (4) subjects lacking covariate data or those who withdrew from the survey without cause. Finally, a total of 14,251 subjects were included in this study (Fig. 1). The implementation of the NAGALA project was authorized by the Institutional Review Board of the Murakami Memorial Hospital, and the use of research data obtained informed consent from the subjects [23]. This study involved secondary analysis of the NAGALA cohort data, and the research protocol was approved by the Ethics Committee of Jiangxi Provincial People’s Hospital. Additionally, due to the de-identification of the current dataset regarding subject identifiers, the Ethics Committee of Jiangxi Provincial People’s Hospital waived the requirement for informed consent from the subjects (IRB2021-066). The entire research process followed the principles of the Declaration of Helsinki.

Fig. 1
figure 1

Flow chart of study participants

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Health examination and laboratory screening

As previously described, standardized questionnaires were utilized to record general clinical data and lifestyle factors of the subjects, including exercise habits, gender, waist circumference (WC), height, weight, smoking/drinking status, and diastolic/systolic blood pressure (D/SBP). Blood samples of subjects were collected after fasting for at least 8 h, and hematological samples were analyzed and determined using automated analyzers according to standard methods to measure γ-glutamyl transferase (GGT), triglycerides (TG), fasting plasma glucose (FPG), HDL-C, alanine aminotransferase (ALT), HbA1c, total cholesterol (TC), and aspartate aminotransferase (AST). Low-density lipoprotein cholesterol (LDL-C) was calculated using the Friedewald equation [25].

Definitions and calculations

Smoking status of subjects were categorized into Non, Past, and Current based on their smoking history.

Drinking status was classified based on the subject’s weekly alcohol intake in the past month into non or samll (< 40 g/week), light (40–139 g/week) and moderate (140–209 g/week).

Exercise Habits defined as subjects engaging in any type of regular physical activity at least once a week.

HbA1c/HDL-C Ratio: Calculated as the ratio of HbA1c (%) to HDL-C (mmol/L) [22].

MAFLD diagnosis

The diagnosis of MAFLD was based on hepatic steatosis detected by ultrasound and also requires at least one of the following two criteria [26]: clinical evidence of overweight or obesity, metabolic dysfunction. Metabolic dysfunction was determined by the presence of at least two of the following metabolic risk factors: (1) SBP/DBP ≥ 130/85mmHg; (2) HDL-C < 40/50 mg/dL for men and women, respectively; (3) WC ≥ 90/80 centimeters for Asian men and women, respectively; (4) TG ≥ 150 mg/dL; (5) Prediabetes (i.e., FPG 5.6–6.9 mmol/L, or HbA1c of 5.7-6.4%).

Statistical analysis

All analyses for this study were conducted using R version 4.2.1 and Empower (R) version 2.0, with a significance level set at P < 0.05. In order to clearly display the study population corresponding to different levels of HbA1c/HDL-C ratio, we grouped them by the quartiles of the HbA1c/HDL-C ratio (that is, the values ​​at the 25%, 50%, and 75% positions of the HbA1c/HDL-C ratio) to describe the baseline characteristics of the study population. The differences between quartiles were examined using chi-square tests, one-way analysis of variance, and Kruskal-Wallis H tests.

The relationship of the HbA1c/HDL-C ratio with MAFLD was analyzed using logistic regression models, with results reported as ORs and 95% CIs per unit increment. Model 1 focused on the influence of gender, age, weight, and BMI in the association. Model 2 further adjusted for SBP, smoking/drinking status, and exercise habits. Model 3, as the final model, included all non-collinear variables for consideration (collinearity among variables was assessed using variance inflation factors, detailed in Supplementary Table 1) [27]. Similar analysis steps were also performed in different subgroups based on gender, age, BMI, exercise habits, and smoking/drinking status, with thresholds for age and BMI groups referring to World Health Organization standards [28]. Differences between strata were further examined by likelihood ratio tests and used to determine whether the association of the HbA1c/HDL-C ratio with MAFLD interacted with subgroup variables. Additionally, the discriminatory value of the HbA1c/HDL-C ratio and its components, simple measurement parameters WC, TG, SBP, DBP and non-invasive detection methods fatty liver index (FLI), hepatic steatosis index (HSI) for identifying MAFLD were evaluated through ROC analysis, calculating the corresponding AUC values (optimal thresholds), and statistically comparing differences using the DeLong test [29]. In addition, we further evaluated whether adding the HbA1c/HDL-C ratio to a separate WC, TG, SBP, DBP, FLI or HSI model would improve the identification value of the model. Finally, to further intuitively present the association between the HbA1c/HDL-C ratio and MAFLD prevalence, RCS was used to fit and visualize the relationship between the two.

Results

Baseline characteristics

A total of 14,251 subjects were included, with a mean age of 43 years, including 7,411 males and 6,840 females. Table 1 shows the baseline characteristics of the subjects grouped according to quartiles of the HbA1c/HDL-C ratio (Q1: 2.41–2.84, Q2 3.16–3.48, Q3 3.83–4.21, Q4 4.75–5.68). It can be observed that the proportion of male subjects gradually increased across the four quartiles, while the proportion of female subjects decreased. Additionally, we found that parameters such as height, weight, BMI, WC, ALT, AST, GGT, LDL-C, TG, FPG, HbA1c, SBP, DBP, etc., all increased with increasing quartiles of the HbA1c/HDL-C ratio, while the number of individuals engaging in regular exercise decreased with increasing quartiles of the HbA1c/HDL-C ratio. Furthermore, among the quartiles of the HbA1c/HDL-C ratio, the number of individuals with MAFLD showed a substantial increase in a multiplicative manner (Q1: 1.43%, Q2: 5.09%, Q3: 13.90%, Q4: 35.16%).

Table 1 Baseline information according to quartiles of the HbA1c/HDL-C ratio
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Association of HbA1c/HDL-C ratio with MAFLD

Table 2 summarizes the association between the HbA1c/HDL-C ratio and MAFLD in logistic regression analysis. Four multivariable-adjusted models were established. In both unadjusted and adjusted models 1, 2, and 3, we observed that the HbA1c/HDL-C ratio was consistently positively associated with MAFLD [OR: Unadjusted model 2.63(2.50–2.75), Model 1 1.76(1.66–1.86), Model 2 1.80(1.69–1.91), Model 3 1.34(1.25–1.44)].

Table 2 Logistic regression analyses for the association between HbA1c/HDL-C ratio and MAFLD.
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Dose-response relationship between HbA1c/HDL-C ratio and MAFLD

We also used a four-knot RCS to explore the dose-response relationship between the HbA1c/HDL-C ratio and the prevalence of MAFLD, as shown in Fig. 2. After adjusting for covariates (gender, age, BMI, height, SBP, smoking status, drinking status, exercise habits, ALT, AST, GGT, TG, FPG, HbA1c), we observed a nonlinear relationship between the two (P for non-linearity < 0.001). From the fitted curves, it appears that there is a potential threshold effect point (HbA1c/HDL-C ratio approximately 3) between the HbA1c/HDL-C ratio and the prevalence of MAFLD; when the HbA1c/HDL-C ratio is below this threshold point, the prevalence of MAFLD hardly increases, whereas when the HbA1c/HDL-C ratio exceeds the threshold point, the slope of the MAFLD prevalence curve increases rapidly.

Fig. 2
figure 2

Apply the 4-knots RCS model to fit the dose-response relationship between the HbA1c/HDL-C ratio and MAFLD.

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Subgroup analysis

We conducted subgroup analysis based on age, gender, BMI, exercise habits, and smoking/drinking status to explore whether the association between the HbA1c/HDL-C ratio and MAFLD varies across common populations (Table 3). The study found that there were no significant differences in the relationship between the HbA1c/HDL-C ratio and MAFLD across different age groups, genders, BMI categories, exercise habits, and smoking/drinking status (All P for interaction > 0.05).

Table 3 Stratified associations between HbA1c/HDL-C ratio and MAFLD by age, sex and BMI.
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Evaluate the accuracy of HbA1c, HDL-C, HbA1c/HDL-C ratio, WC, TG, SBP, DBP, FLI, HSI in identifying MAFLD

As shown in Table 4, FLI, HSI and WC were significantly better than HbA1c/HDL-C ratio, and HbA1c/HDL-C ratio was significantly better than HbA1c, HDL-C, SBP and DBP in screening for NAFLD (AUC: FLI 0.92, HSI 0.90, WC 0.90, HbA1c/HDL-C ratio 0.81, HDL-C 0.78, SBP 0.76, DBP 0.76, HbA1c 0.64; All Delong P < 0.01; Fig. 3), and the best threshold of HbA1c/HDL-C ratio was calculated to be 4.08. In addition, we further added the HbA1c/HDL-C ratio to the separate WC, TG, SBP, DBP, FLI or HSI models (Table 5), and the results showed that the HbA1c/HDL-C ratio could further improve the accuracy of the above models in the identification of NAFLD (All Delong P < 0.05).

Table 4 Areas under the receiver operating characteristic curves for each evaluated parameter in identifying MAFLD.
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Fig. 3
figure 3

Area under the receiver operating characteristic curve for HbA1c, HDL-C, HbA1c/HDL-C ratio, WC, TG, SBP, DBP, HSI and FLI for identification of MAFLD.

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Table 5 ROC analysis of identifying MAFLD after adding HHR to separate WC, SBP, DBP, TG, HSI, and FLI models
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Discussion

MAFLD is a chronic disease that is becoming increasingly prevalent globally [3, 4], yet it still faces numerous challenges in diagnosis and risk stratification. Although liver biopsy is currently the most accurate method for diagnosing hepatic steatosis clinically, its invasiveness makes widespread testing difficult [30,31,32]. Therefore, finding a simple, accurate, and efficient diagnostic method is crucial for identifying MAFLD. It is currently believed that the main mechanisms of MAFLD are lipotoxicity and glucotoxicity [13]. In order to explore the impact of lipid and glucose on MAFLD, we combined two indicators, HbA1c and HDL-C, to investigate their relationship with MAFLD.

HbA1c, as a compound formed by the combination of hemoglobin and glucose in serum [33], is closely related to the lifespan of red blood cells and the concentration of glucose in the blood [34], mainly reflecting the level of glycemic control over the past 2–3 months [35]. In recent years, increasing evidence suggests a close association between HbA1c and liver diseases. Studies have found that elevated levels of HbA1c increase IR, inhibit lipoprotein lipase activity, leading to impaired TG clearance, thereby increasing the hepatic lipid burden [16,17,18]. Additionally, elevated levels of HbA1c can also increase the release of inflammatory factors, such as CRP, IL-1β, IL-6, and IL-17, through chronic inflammatory responses [36]. Moreover, elevated levels of HbA1c can lead to increased production of reactive oxygen species, causing hepatic damage at the cellular level, such as membrane lipid peroxidation, cellular degeneration and necrosis, apoptosis, increased expression of pro-inflammatory cytokines, activation of hepatic stellate cells, and fibrosis [37,38,39,40,41,42]. Evidence from observational studies shows that HbA1c is positively correlated with the degree of liver cirrhosis in patients with FLD, and some scholars believe that the reason for this result may be related to metabolic disorders of blood glucose [43, 44]. HDL-C, as a beneficial cholesterol in the body, primarily functions by transporting cholesterol from peripheral tissues back to the liver for metabolism, thereby reducing the burden on the liver [22, 23]. Additionally, HDL also acts as an endogenous inhibitor of inflammatory reactions [45], exerting anti-inflammatory properties through its HDL3 particles, thereby attenuating the inflammatory response [46]. A large number of completed clinical research evidence has further confirmed that HDL-C has a significant risk warning effect on MAFLD and its poor prognosis [47,48,49]. Overall, both an increase in HbA1c and a decrease in HDL-C levels increase the risk of liver disease.

As a novel composite index, the HbA1c/HDL-C ratio reflects both the metabolic status of glucose and lipids in the body. In a recent retrospective study by Hu et al. [22], they analyzed 1,654 patients with various cardiovascular risk factors or symptoms of suspected coronary artery disease and found that an increase in the HbA1c/HDL-C ratio significantly increased the risk of carotid artery atherosclerosis (OR = 1.13, 95% CI 1.05–1.21). In the current analysis for MAFLD, we also report similar findings to Hu et al. Furthermore, through additional ROC curve analysis, we found that the HbA1c/HDL-C ratio had better diagnostic value for MAFLD compared to HbA1c and HDL-C alone. These findings further suggested the promising potential of the HbA1c/HDL-C ratio in metabolic diseases. The mechanisms underlying the association between the HbA1c/HDL-C ratio and MAFLD are currently unclear. However, considering the pathological pathways of high blood sugar or low HDL-C levels in MAFLD [16,17,18, 36,37,38,39,40,41,42], the HbA1c/HDL-C ratio may combine the characteristics of both and promote IR, thereby facilitating the development of MAFLD, by regulating lipid metabolism, exerting oxidative stress, and modulating inflammatory responses.

In the current study, we also made an interesting discovery. After fitting the dose-response relationship curve of the HbA1c/HDL-C ratio and the prevalence of MAFLD using RCS, we found a potential threshold effect point between them (approximately HbA1c/HDL-C ratio of 3). It appeared that when the HbA1c/HDL-C ratio was below this threshold point, the prevalence of MAFLD hardly increased, whereas when the HbA1c/HDL-C ratio exceeded this threshold, the prevalence of MAFLD sharply rose. Additionally, through further ROC analysis, we calculated the optimal threshold of HbA1c/HDL-C ratio for identifying MAFLD to be 4.04. These findings hold significant value for the screening of MAFLD.

Study strengths and limitations

Strengths: (1) This is a large-scale retrospective cohort study involving 14,251 participants, indicating a substantial sample size. (2) The study elucidates, for the first time, the positive correlation between HbA1c/HDL-C ratio and MAFLD. Additionally, the identification of potential threshold points through RCS and ROC analyses offers a new perspective for the screening of MAFLD.

Limitations: (1) The study population is derived from the NAGALA project, suggesting that the research evidence may be primarily applicable to the Japanese population, necessitating further investigation in other ethnic groups. (2) This study is a non-interventional retrospective study and cannot reflect the dynamic relationship between changes in independent variables and MAFLD; In addition, due to the lack of platelet data in the current data set, we cannot further evaluate the association between HbA1c/HDL-C ratio and fibrosis-4 and the identification value of NAFLD after the combination of the two; It is hoped that this limitation can be addressed in further research in the future. (3) The exclusion criteria of the study design removed individuals with diabetes, potentially reducing the risk of MAFLD in the real world. (4) In the diagnosis of MAFLD, due to errors between evaluators, some people with mild symptoms may be missed.

Conclusions

In conclusion, the findings of this study involving a population undergoing health check-ups demonstrate a positive correlation between HbA1c/HDL-C ratio and MAFLD prevalence. Furthermore, compared to individual measures of HbA1c and HDL-C, the HbA1c/HDL-C ratio exhibits significantly higher accuracy in screening MAFLD.

Data availability

The data set supporting the results of this study has been uploaded to Dryad database (https://datadryad.org/stash/dataset/doi:10.5061/dryad.8q0p192).

Abbreviations

MAFLD:

Metabolic associated fatty liver disease

HbA1c/HDL-C ratio:

Plasma-Glycosylated Hemoglobin A1c/High-Density Lipoprotein Cholesterol Ratio

RCS:

restricted cubic splines

ROC:

receiver operating characteristic

CI:

confidence interval

OR:

odds ratio

BMI:

body mass index

GGT:

γ-glutamyl transferase

TG:

triglycerides

FPG:

fasting plasma glucose ALT: alanine aminotransferase

TC:

total cholesterol

AST:

aspartate aminotransferase (AST)

LDL-C:

Low-density lipoprotein cholesterol

AUC:

area under the curve

IR:

insulin resistance

FLI:

fatty liver index

HSI:

hepatic steatosis index

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Acknowledgements

We would like to thank Professor Okamura and his team for their efforts in collecting and organizing original data, and we would also like to thank the DRYAD database for its policy support.

Funding

This work was supported by Natural Science Foundation of Jiangxi Province [20232BAB216004].

Author information

Author notes

  1. Shiming He, Song Lu and Changhui Yu contributed equally to this work.

Authors and Affiliations

  1. Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi Province, China

    Shiming He, Song Lu, Changhui Yu, Maobin Kuang & Jiajun Qiu

  2. Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi Province, China

    Shiming He, Changhui Yu, Maobin Kuang, Jiajun Qiu & Yang Zou

  3. Jiangxi Provincial Geriatric Hospital, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi Province, China

    Shiming He, Changhui Yu, Maobin Kuang, Jiajun Qiu & Guotai Sheng

  4. Department of Cardiology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi Province, China

    Guotai Sheng

Authors
  1. Shiming He
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Contributions

Conceptualization: YZ; Supervision: GT-S; Methodology: YZ; Project administration: YZ and GT-S; Writing-original draft preparation: SM-H, SL and CH-Y; Writing-reviewing and editing: YZ, GT-S, MB-K and JJ-Q; Software: YZ, SM-H and SL; Formal analysis: SM-H, MB-K and JJ-Q; data curation and validation: SL, JJ-Q, CH-Y, SM-H and MB-K; All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Guotai Sheng or Yang Zou.

Ethics declarations

Ethics approval and consent to participate

This study involved secondary analysis of the NAGALA cohort data, and the research protocol was approved by the Ethics Committee of Jiangxi Provincial People’s Hospital. Additionally, due to the de-identification of the current dataset regarding subject identifiers, the Ethics Committee of Jiangxi Provincial People’s Hospital waived the requirement for informed consent from the subjects (IRB2021-066). The entire research process followed the principles of the Declaration of Helsinki.

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Not applicable.

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The authors declare no competing interests.

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He, S., Lu, S., Yu, C. et al. The newly proposed plasma-glycosylated hemoglobin A1c/High-Density lipoprotein cholesterol ratio serves as a simple and practical indicator for screening metabolic associated fatty liver disease: an observational study based on a physical examination population. BMC Gastroenterol 24, 274 (2024). https://doi.org/10.1186/s12876-024-03362-0

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Keywords

BMC Gastroenterology

ISSN: 1471-230X

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