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Association between neutrophil-to-high-density lipoprotein cholesterol ratio and metabolic dysfunction-associated steatotic liver disease and liver fibrosis in the US population: a nationally representative cross-sectional study using NHANES data from 2017 to 2020

BMC Gastroenterology volume 24, Article number: 300 (2024) Cite this article

Abstract

Background

The neutrophil-to-high-density lipoprotein cholesterol ratio (NHR) has emerged as a promising biomarker for assessing inflammation and lipid dysregulation. Increasing evidence indicates that these metabolic disturbances play a crucial role in the development of metabolic dysfunction-associated steatotic liver disease(MASLD). This study aims to investigate the association between NHR, MASLD, and liver fibrosis.

Methods

This cross-sectional study analyzed data from the 2017–2020 National Health and Nutrition Examination Survey (NHANES). Weighted multivariate logistic regression models were used to investigate the association between NHR and both MASLD and liver fibrosis. Smoothed curve fitting and threshold effect analysis were performed to detect potential nonlinear relationships. Subgroup analyses were conducted to assess the consistency of these associations across different groups.

Results

The study involved 4,761 participants. We observed a significant positive association between NHR and MASLD (OR = 1.20, 95% CI: 1.09–1.31). However, there was no significant association between NHR and liver fibrosis (OR = 1.01; 95% CI: 0.94–1.09). The analysis of smoothed curve fitting and threshold effect revealed an inverted U-shaped relationship between NHR and MASLD, with a turning point at 5.63.

Conclusion

Our findings indicate a positive correlation between elevated NHR levels and MASLD prevalence. However, we did not observe a significant association between NHR and liver fibrosis prevalence. Further prospective research is needed to validate these findings in a longitudinal setting.

Peer Review reports

Introduction

Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent chronic liver diseases worldwide [1]. This intricate disease is a metabolic-related disease influenced by a range of factors, including genetic, lifestyle, and socioeconomic aspects [2]. The worldwide prevalence of MASLD ranges approximately between 13% and 42%, with increasing incidence attributed to high-energy diets and lack of physical activity [3, 4]. MASLD is characterized by the accumulation of extra fat in the liver, no history of heavy drinking, or only a small amount of alcohol, and is often associated with metabolic disorders such as insulin resistance, type 2 diabetes, and obesity [5,6,7]. Disease-destructive evolution includes stages of steatosis, metabolic dysfunction-associated steatohepatitis (MASH), severe liver fibrosis, and cirrhosis [8]. The latter stages, particularly liver fibrosis and cirrhosis, may lead to permanent structural alterations and potentially hepatocellular carcinoma (HCC) [9,10,11]. Due to its increasing incidence, MASLD has become a leading cause of hepatocellular cancer, cirrhosis, fibrosis, and even liver transplantation [12], imposing a heavy financial burden on individuals and society. Therefore, identifying effective, rapid, and affordable biomarkers is crucial for the early identification of individuals at high risk of MASLD.

Neutrophils, as early participants in the inflammatory response, can initiate and regulate inflammation and cellular damage during the progression of MASLD by engulfing lipids and producing inflammatory cytokines and oxygen radicals [13]. High-density lipoprotein cholesterol (HDL-C) possesses anti-inflammatory and antioxidative properties. Additionally, it helps the body eliminate dietary cholesterol through the reverse cholesterol transport mechanism [14]. Lower HDL-C levels are associated with MASLD incidence and severity [15]. The neutrophil-to-HDL-C ratio (NHR) serves as one of the biomarkers for assessing the state of inflammation and lipid metabolism, determined by calculating the ratio between neutrophil count and levels of high-density lipoprotein cholesterol [16]. Elevated NHR value is generally considered as an indicator of chronic inflammation and lipid metabolism disorder [17]. Previous studies have linked NHR with several disorders, such as coronary heart disease [18], diabetes [19], mental illness [20], and Parkinson’s disease [21]. Moreover, it has been demonstrated that NHR may be a useful predictive factor of mortality for liver cancer patients [22]. Despite these associations, research on the correlation between NHR and MASLD remains limited.

To establish a clinically available monitoring index for predicting MASLD risk, we, conducted a representative cross-sectional study using data from the National Health and Nutrition Survey (NHANES) 2017–2020. This study aimed to investigate the correlation between NHR and MASLD as well as liver fibrosis in the general population of the United States.

Patients and methods

Data and sample source

NHANES is a population-representative survey conducted in the United States, employing sophisticated multi-stage and probabilistic sampling to provide comprehensive data on the dietary habits and overall health of the US populace [23]. This analysis utilized continuous NHANES data from the 2017 to 2020 cycles, involving 15,560 participants. Participants were excluded based on the following criteria: lack of necessary data to calculate NHR (n = 4742), missing data on median stiffness/CAP or incomplete elastography (n = 2455), information on heavy drinking data (defined as male average daily drinking > 30 g, female average daily drinking > 20 g) [24] or missing data on drinking (n = 1304), missing data on other underlying liver disease causes (n = 159), including autoimmune hepatitis, viral hepatitis infection (defined as HCV-RNA, HCV antibody, or HBsAg test positive), liver cancer, and missing data on covariates (n = 2258). Ultimately, 4,761 individuals were included in the study (Fig. 1).

Fig. 1
figure 1

Flowchart of the sample selection. NHANES, National Health and Nutrition Examination Survey. NHR, Ratio of neutrophils to high-density lipoprotein cholesterol. CAP, Controlled Attenuation Parameter

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Evaluation of hepatic steatosis and hepatic fibrosis

During the 2017–2020 cycle, NHANES technicians performed vibration-controlled transient elastography (VCTE) using FibroScan ® model 502 V2 Touch (Echosens) with medium (M) and super large (XL) probes. An influential study has identified that the CAP value (also known as CAP) ≥ 274dB/m, ≥ 290dB/m, and ≥ 302dB/m correspond to hepatic steatosis grades S1, S2, and S3, respectively, with a 90% sensitivity in identifying these conditions [25]. Liver fibrosis stages are determined based on liver stiffness, with threshold values for fibrosis stages ≥ F2, ≥F3, and F4 being 8.2, 9.7, and 13.6 kPa, respectively [25, 26].

Definition of MASLD and liver fibrosis

The definition of MASLD is based on hepatic steatosis(≥ S1), the absence of heavy alcohol consumption, and no viral hepatitis, along with meeting at least one of the following conditions [24, 27]: (1) Individuals with a BMI ≥ 25 kg/m2 or a waist circumference ≥ 94 cm for men and ≥ 80 cm for women; (2) Fasting glucose levels ≥ 100 mg/dL or hemoglobin A1c levels ≥ 5.7%, or a history of type 2 diabetes diagnosis or current treatment for type 2 diabetes; (3) Blood pressure levels ≥ 130/85 mmHg or current treatment for hypertension; (4) Triglyceride levels ≥ 1.70 mmol/L or individuals on lipid-lowering therapy; (5) Low high-density lipoprotein cholesterol levels, with < 1.0 mmol/L for men or those on lipid-lowering therapy, and < 1.3 mmol/L for women. Clinically significant fibrosis is defined by LSM thresholds ≥ 8.2 kPa. MASLD and liver fibrosis are the primary outcomes of this study.

Calculation of NHR

Neutrophil counts were determined by total blood count using an automated blood analysis system (Coulter DxH 800 analyzer) and displayed as 10 ^ 3 cells / µ l. HDL-C levels were assessed using an automatic device with venous blood samples obtained after 8-hour fasting. The Neutrophil to High-Density Lipoprotein Cholesterol Ratio (NHR) is calculated as the neutrophil count (10^3 cells/µL) divided by the HDL-C level (mmol/L) [28, 29]. The standard reference range for HDL-C is 1.3–1.5 mmol/L for females and 1.0–1.5 mmol/L for males. Similarly, the range for neutrophil counts is 1.5–8.0 × 10^3 cells /uL.

Covariates

These covariates considered in this study included age (years), sex (male/female), ethnicity (Mexican American/other Hispanic/non-Hispanic White/non-Hispanic Black/other race), education (below grade 9/grades 9–11 (including grade 12), no diploma)/high school graduation or GED or equivalent/some college or AA degrees and college degree or above), and Income-to-Poverty Ratio (PIR). Additionally, smoking status (never/before/now), body mass index (BMI, kg/m2), sedentary behavior (hour/day), Hypertension (yes/no), Diabetes Grade (Normal/Diabetes/Prediabetes), Alanine aminotransferase (ALT, IU/L), HbA1c (HbA1c, %), serum albumin (ALB, g/dL), serum creatinine (SCr, umol/L), total cholesterol (mmol/L), and serum uric acid (µmol/L) were considered. PIR categories were defined as < 1, 1-3.9, and 4, representing low, middle, and high-income groups, respectively. In this research, BMI categories of < 25, 25–29.9, and 30 kg/m2 corresponded to normal weight, overweight, and obese populations, respectively. For comprehensive measurement instructions on these variables, please visit the NHANES website at www.cdc.gov/nchs/nhanes/.

Statistical analysis

Versions 4.2 and 4.1 of Empowerstats and R were used for all the analyses. Weighting was done following NCHS analytical criteria, and then all data were statistically examined. Continuous variables were presented as means ± standard error, and categorical variables were expressed as values and percentages. Weighted chi-square tests and t-tests were used for categorical and continuous variables, respectively. Utilizing weighted logistics regression analysis, we examined the association between independent and dependent variables. Based on covariate adjustments, three models were developed. Model 1: Unadjusted covariates. Model 2: Adjusted for PIR, age, sex, race, and education. Model 3: Building upon Model 2, further adjusted for uric acid, albumin, creatinine, ALT, hemoglobin A1c, BMI, sedentary behavior, hypertension, diabetes, and cholesterol. The linear and nonlinear relations between NHR and NAFLD are studied by fit-smoothed curves. Subgroup analyses were conducted based on gender, ethnicity, BMI, hypertension, and diabetes status. Statistical significance was set at a two-sided P < 0.05.

Results

Baseline characteristics

A total of 4,761 participants were included in this study, with 2,123 (44.08%) being found with MASLD and 453 (8.82%) exhibiting liver fibrosis. All participants were aged over 20, with a mean age of 48.22 ± 17.15 years. The sample consisted of 48.45% male and 51.55%female. The ranges of NHR across quartiles 1–4 were as follows: Q1(0.191–2.065), Q2(2.067–2.993), Q3(3.000-4.207) and Q4(4.211–19.028). In the NHR quartile(Q1 to Q4), significant differences were observed in age, gender, race, education level, PIR, smoking, sedentary, BMI, hypertension, diabetes grade, hemoglobin A1c, ALT, serum albumin, serum creatinine, total cholesterol, and serum uric acid (all P < 0.05). Male, non-Hispanic White, below college degree, moderately income, longer periods of sedentary behavior, elevated BMI, hypertension, diabetes, elevated HbA1c levels, elevated levels of creatinine, uric acid, and ALT in the blood serum, and a history of smoking were all associated with higher levels of NHR. Conversely, lower levels of albumin and cholesterol in the blood serum were linked to higher levels of NHR (Table 1).

Table 1 Clinical characteristics of the study participants
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Association between NHR and MASLD

The outcomes of the logistic regression models for the three models are presented in Table 2. NHR and MASLD showed a significant positive correlation in both the unadjusted model (Model 1: OR = 1.48, 95% CI: 1.38–1.56) and the model adjusted for age, sex, race, education level, and PIR (Model 2: OR = 1.49, 95% CI: 1.37–1.62). The positive association between NHR and NAFLD remained significant (Model 3:OR = 1.20, 95% CI: 1.09–1.31) even after adjusting for all variables. Upon stratifying the data by NHR quartiles, we found that Q4 continued to exhibit a significantly positive correlation with MASLD, even after accounting for all other factors (Model 3: OR = 3.00, 95%CI: 2.10–4.30). Using Q1 as a reference, each unit increase in the NHR ratio was associated with a 3-fold increase in the odds of MASLD prevalence.

Table 2 Association between NHR and MASLD
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Association between NHR and liver fibrosis

Table 3 presents the results of logistic regression models, showing that in Model 1 (OR = 1.24, 95% CI: 1.16–1.32) and Model 2 (OR = 1.22, 95% CI: 1.14–1.30), there is a significant positive association between NHR and liver fibrosis. However, the positive association between NHR and liver fibrosis becomes non-significant after adjusting for all variables (Model 3:OR = 1.01; 95% CI: 0.94–1.09). When examining NHR quartiles, Q3 and Q4 exhibit a significantly positive correlation with liver fibrosis in Models 1 (Q3: OR = 2.29, 95% CI: 1.64–3.19; Q4: OR = 3.41, 95% CI: 2.46–4.73)and 2(Q3:OR = 2.06, 95% CI: 1.39–3.06; Q4: OR = 2.96, 95% CI: 1.97–4.46). However, in Model 3, there is no statistically significant association between Q3 (OR = 0.98, 95% CI: 0.64–1.52) and Q4 (OR = 0.97, 95% CI: 0.60–1.55) and hepatic fibrosis.

Table 3 Association between NHR and liver fibrosis
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Smoothing curve fitting and threshold effect analysis

After adjusting for each variable, an inverted U-shaped relationship between NHR and MASLD was observed (Fig. 2A). However, there was a positive correlation between NHR and liver fibrosis (Fig. 2B). The inflection point of the inverted U-shaped relationship between NHR and MASLD was determined to be 5.63. For NHR > 5.63, there was a negative correlation with MASLD (OR = 0.86,95% CI: 0.76–0.97), whereas for NHR < 5.63, a positive correlation was observed (OR = 1.35,95% CI: 1.27–1.45). However, there was no significant positive correlation between NHR and liver fibrosis (OR = 1.01,95% CI: 0.94–1.09) (Table 4).

Fig. 2
figure 2

Smooth-curve fitting of NHR, MASLD, and liver fibrosis. (A) The association between NHR and MASLD. (B) The association between NHR and liver fibrosis. The solid red line represents the smooth curve fit between variables. Blue bands represent the 95% confidence interval from the fit. All the covariates in Table 1 are adjusted

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Table 4 Threshold effect of the relationship between NHR, MASLD, and liver fibrosis
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Subgroup analysis

Subgroup analysis revealed inconsistent correlations between the NHR level, MASLD, and hepatic fibrosis. Across subgroups stratified by sex, BMI, and hypertension, a substantial positive association between NHR and MASLD was observed (all P < 0.05), as shown in Table 5. Similarly, significant positive correlations (P < 0.05) were found among Mexican Americans, non-Hispanic Whites, non-Hispanic Blacks, and other racial groups in ethnic stratification. However, no significant correlation between NHR and MASLD was observed among individuals with prediabetes. The correlation between NHR and MASLD did not change significantly throughout subgroups, according to the interaction test (P for interaction > 0.05). The subgroup analysis of the correlation between NHR and liver fibrosis shows that in each subgroup based on sex and hypertension, there is a positive correlation between NHR and liver fibrosis, although it is not statistically significant (P > 0.05). Notably, in subgroups based on race, BMI, and diabetes, Only Mexican Americans, other races, BMI > 30(kg/m²) and Diabetes show a statistically significant positive correlation between NHR and liver fibrosis (P < 0.05). According to interaction testing, there is no significant difference in the correlation between NHR and liver fibrosis across these subgroups (P for interaction > 0.05) (Table 6).

Table 5 Subgroup of the relationship between NHR and MASLD
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Table 6 Subgroup of the relationship between NHR and liver fibrosis
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Discussion

In this cross-sectional study involving 4,761 participants, we identified a positive correlation between NHR levels and MASLD. However, no significant positive association was observed between liver fibrosis and NHR levels. Subgroup analyses and interaction tests indicated that this relationship is consistent across various populations. It is noteworthy that the association between NHR and MASLD exhibits an inverted U-shaped pattern, with an inflection point at 5.63. Below this threshold, NHR was identified as an independent risk factor for MASLD.

Currently, there are limited investigations on the relationship between NHR and MASLD, and only one study reported an association [29]. Enver and his colleagues examined the connection between NHR and MASLD among 155 Turkish participants. Using one-way ANOVA for multiple comparisons, they found that NHR levels were higher in individuals with moderate and severe liver fat degeneration compared to those without liver fat degeneration [29]. However, this study was limited by its relatively small sample size and did not comprehensively assess the impact of other risk factors on the association between NHR and MASLD.

Currently, many epidemiological studies have proved that inflammatory reaction and lipid metabolism are related to the progress of MASLD [30,31,32,33]. The advanced stage of MASLD, known as MASH, is characterized by hepatocyte fibrosis and inflammation in addition to fat buildup [34]. A large multicenter cohort study involving 389 MASLD patients with significant liver fibrosis from Finland and Italy found that one-third of patients with severe fibrosis in biopsy samples did not exhibit NASH [35]. Our study revealed a lack of significant correlation between NHR and hepatic fibrosis, which may explain this phenomenon. In a cross-sectional investigation of MASLD in the US population, Xie and his colleagues similarly found no discernible relationship between liver fibrosis and the systemic immune inflammation index, consistent with our findings [36]. These results may suggest that the complex process of liver fibrosis can not be fully reflected by the assessment of the inflammatory response alone. Liver fibrosis is a multifactorial and multistep process, where inflammation is just one component. Other potential mechanisms or factors such as cellular apoptosis [37], oxidative stress [38], and changes in gene expression [39] may also contribute to liver fibrosis, although they were not addressed in our study.

Aberrant infiltration of neutrophils aggravates hepatocyte injury and inflammatory responses by generating reactive oxygen species, releasing proteases, forming neutrophil extracellular traps (NETs), and secreting inflammatory cytokines, thereby driving the MASLD [40]. Studies have shown that myeloperoxidase (MPO) produced by neutrophils can enhance the cytotoxicity of macrophages and induce neutrophil activation in mouse models of MASH [41]. In addition, activated neutrophils exacerbate liver inflammation and damage by releasing inflammatory mediators [40] and enzymes [42], advancing hepatic steatosis to more severe stages of the disease, thus playing a critical role in the pathogenesis of MASH. Another study conducted on animals found that mice treated with the neutrophil-depleting antibody 1A8 significantly reduced the expression of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1) and inflammatory cytokines after feeding C57BL/6 J mice a high-fat diet for six weeks [43]. This indicates that the depletion of neutrophils can significantly improve MASLD caused by diet in mice. These findings further validate the potential critical role neutrophils might play in developing MASLD. A negative relationship between HDL-C levels and the risk of MASLD has been demonstrated in numerous research [44, 45]. HDL-C possesses anti-inflammatory and antioxidant effects and can reduce neutrophil activity by inhibiting [46]. Reactive oxygen species and proteases produced by neutrophils can also affect HDL, diminishing its antioxidant and anti-inflammatory capacities [47]. This may partially explain the positive correlation between NHR and MASLD prevalence observed in our study.

NHR, as a novel inflammatory biomarker, integrates the dual consideration of inflammatory status and lipid metabolism. Numerous studies have confirmed that SII(Systemic Immune-Inflammation Index), WWI(weight-adjusted waist index), and CMI (cardiometabolic index) are all associated with MASLD [48,49,50]. However, NHR stands out in its comprehensiveness compared to these indicators. It not only accurately assesses the state of inflammatory response but also incorporates lipid metabolism into its assessment, a dimension that SII fails to consider. Compared to WWI and CMI, NHR features a simpler calculation process, while the latter two only reflect metabolic status. More importantly, there is a significant positive correlation between NHR and the prevalence of MASLD. Elevated levels of NHR often indicate abnormal inflammatory responses or lipid metabolism, providing an opportunity for early intervention. By timely adjusting NHR levels, we can potentially reduce the risk of MASLD, for example, through measures such as improving lifestyle, to achieve effective disease prevention and control. In other words, NHR is an ideal biomarker for large-scale screening in resource-limited settings due to its simplicity and cost-effectiveness. The laboratory data required for its calculation—neutrophil count and high-density lipoprotein levels—can be easily obtained through routine blood tests without the need for additional specialized tests. As a preliminary screening tool, NHR holds promise in identifying potential high-risk MASLD individuals in the general population, laying the groundwork for more precise diagnostic methods such as abdominal ultrasound, FibroScan, and liver biopsy to confirm hepatic steatosis and facilitate early intervention and treatment.

The results of this study are based on a health survey of the general population, which, although providing valuable information on the prevalence of MASLD, must acknowledge the inherent limitations of the cross-sectional study design. Firstly, due to the cross-sectional design of the study, it is not possible to directly establish a causal relationship between the NHR and the severity of hepatic steatosis. Hence, longitudinal studies and intervention trials are needed to address this limitation. Despite adjusting for numerous confounding variables, it remains challenging to completely exclude all potential biases that could influence our results. Secondly, cross-sectional studies cannot differentiate between various stages of fibrosis or frank cirrhosis, as these diagnoses typically require support from imaging studies such as abdominal ultrasound. Additionally, we are unable to assess the presence or absence of portal hypertension or ascites, conditions commonly seen in cirrhotic patients and significant for disease severity and prognosis. Therefore, further prospective studies are required for further validation in the future. Finally, because a liver biopsy was not used to confirm the diagnosis of MASLD and liver fibrosis made in this study, the current conclusions need to be verified by additional research.

Conclusion

The study results show that an increase in the NHR level is positively correlated with the odds of MASLD prevalence. It is important to note that among participants with an NHR below 5.63, the odds of MASLD prevalence increase as the NHR level rises; however, there is no significant correlation between NHR and the incidence of liver fibrosis. To validate the findings of this study, larger-scale and more meticulously designed prospective studies are needed.

Data availability

The survey data are publicly available on the internet for data users and researchers throughout the world (www.cdc.gov/nchs/nhanes/).

Abbreviations

NHR:

Neutrophil-to-high-density lipoprotein cholesterol ratio

MASLD:

Metabolic dysfunction-associated steatotic liver disease

MASH:

Metabolic dysfunction-associated steatohepatitis

NHANES:

National Health and Nutrition Examination Survey

BMI:

Body mass index

PIR:

Income-to-Poverty Ratio

HDL-C:

High-density lipoprotein cholesterol

SII:

Systemic Immune-Inflammation Index

WWI:

Weight-adjusted waist index

CMI:

Cardiometabolic index

ALT:

Alanine aminotransferase

ALB:

Albumin

SCr:

Serum creatinine

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Acknowledgements

We would like to thank all members who contributed to the manuscript.

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Authors and Affiliations

  1. Department of Infectious Diseases, Wuming Hospital Affiliated to Guangxi Medical University, Nanning, Guangxi, China

    Yangni Lu, Xianli Xu, Jianlin Wu, Lei Ji & Maowei Chen

  2. Department of General Medicine, Wuming Hospital Affiliated to Guangxi Medical University, Nanning, Guangxi, China

    Huiya Huang

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Contributions

YL, XX, and HH designed the research. YL, HH, and LJ collected, analyzed the data and drafted the manuscript. MC, XX and JW revised the manuscript. All authors contributed to the article and approved the submitted version.

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Correspondence to Maowei Chen.

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Lu, Y., Xu, X., Wu, J. et al. Association between neutrophil-to-high-density lipoprotein cholesterol ratio and metabolic dysfunction-associated steatotic liver disease and liver fibrosis in the US population: a nationally representative cross-sectional study using NHANES data from 2017 to 2020. BMC Gastroenterol 24, 300 (2024). https://doi.org/10.1186/s12876-024-03394-6

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Keywords

BMC Gastroenterology

ISSN: 1471-230X

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