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World J Gastroenterol. Jul 14, 2026; 32(26): 118957
Published online Jul 14, 2026. doi: 10.3748/wjg.v32.i26.118957
Clinical assessment of malnutrition among patients with alcoholic liver cirrhosis: A single-center study in Southern China
Xiao-Qin Wu, Yi-Yan Liu, Hong-Sheng Yu, Kodjo-Kunale Abassa, Li-Li Pan, Bi-Lun Ke, Yun-Wei Guo, Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong Province, China
Xiao-Qin Wu, Yi-Yan Liu, Hong-Sheng Yu, Kodjo-Kunale Abassa, Li-Li Pan, Bi-Lun Ke, Yun-Wei Guo, Alcoholic Liver Disease Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong Province, China
ORCID number: Xiao-Qin Wu (0000-0001-6983-4618); Hong-Sheng Yu (0000-0003-2548-7882); Yun-Wei Guo (0000-0003-1008-3228).
Co-first authors: Xiao-Qin Wu and Yi-Yan Liu.
Author contributions: Wu XQ and Liu YY contributed equally to this work, as they are co-first authors; Guo YW designed the research study; Wu XQ, Liu YY, Yu HS, Abassa KK, Pan LL, Ke BL and Guo YW performed the research; Liu YY, Pan LL and Ke BL collected the data; Wu XQ, Yu HS and Abassa KK analyzed the data; Wu XQ, Yu HS and Guo YW wrote the manuscript; all authors contributed to the interpretation of the study and have read and approve the final manuscript.
Supported by the National Natural Science Foundation of China, No. 82370599.
Institutional review board statement: The study was reviewed and approved by the Institutional Review Board of the Third Affiliated Hospital of Sun Yat-sen University, approval No. [2020]02-032-01.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
STROBE statement: The authors have read the STROBE Statement—a checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-a checklist of items.
Data sharing statement: The dataset used during the current study is available from the corresponding author upon reasonable request.
Corresponding author: Yun-Wei Guo, MD, Chief Physician, Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-sen University, No. 600 Tianhe Road, Tianhe District, Guangzhou 510630, Guangdong Province, China. guoyw@mail.sysu.edu.cn
Received: January 16, 2026
Revised: March 3, 2026
Accepted: April 1, 2026
Published online: July 14, 2026
Processing time: 165 Days and 22.2 Hours

Abstract
BACKGROUND

The burden of alcohol-related liver disease in China is becoming increasingly significant, and malnutrition in Chinese patients with alcoholic liver cirrhosis (ALC) is inadequately characterized.

AIM

To evaluate nutritional assessment tools, detail anthropometric and micronutrient alterations, and their associations with disease severity and prognosis in ALC.

METHODS

This case-control study included hospitalized male ALC patients, age-matched patients with hepatitis B virus-related cirrhosis (HBV-C), and relatively healthy controls (HCs). Nutritional status was assessed using subjective global assessment (SGA) and nutritional risk screening 2002 (NRS-2002) scores, anthropometric measurements, and serum levels of trace elements and vitamins. Kaplan-Meier analysis and Cox regression were employed to determine survival outcomes.

RESULTS

We enrolled 249 male ALC patients, 103 HBV-C patients, and 83 HCs. ALC patients demonstrated significantly lower hemoglobin, magnesium (Mg), vitamin D (VD), vitamin B (VB) 1, and VB2 levels than the HBV-C group (P < 0.001). Notably, ALC patients exhibited a unique nutritional phenotype: Increased central adiposity (higher waist circumference, hip circumference, and abdominal fat thickness) despite higher mid-arm circumference (AC) and arm muscle circumference values than HBV-C patients. Malnutrition progressed with disease severity; serum zinc (Zn), Mg, corrected calcium and VD were significantly lower in Child-Pugh B/C than in class A patients. Low albumin levels, Child-Pugh B/C, reduced AC, and high SGA/NRS-2002 scores were associated with decreased survival. Multivariate analysis identified low Zn [hazard ratio (HR) = 0.51], low VD (HR = 0.92), and reduced AC (HR = 0.85) as independent predictors of liver-related mortality.

CONCLUSION

ALC patients exhibit unique malnutrition phenotypes and micronutrient deficiencies. Low Zn, VD, and AC are independent prognostic predictors, necessitating etiology-specific nutritional interventions to improve clinical outcomes.

Key Words: Alcoholic liver cirrhosis; Malnutrition; Micronutrients; Body composition; Anthropometric evaluation; Nutritional assessment tools; Prognosis

Core Tip: This study identifies a unique malnutrition phenotype in Chinese male patients with alcoholic liver cirrhosis (ALC), featuring pronounced anemia, hypoproteinemia, and central adiposity despite relatively higher muscle circumferences. Severe zinc, magnesium, and vitamin D depletion correlates with disease severity. Notably, mid-arm circumference remains a robust bedside survival predictor despite the potential confounding effects of fluid retention. Furthermore, the independent prognostic value of serum zinc and vitamin D levels highlights their potential as therapeutic targets. These findings advocate for etiology-specific nutritional assessment and early intervention to optimize clinical outcomes in ALC.



INTRODUCTION

Excessive ethanol intake remains a primary driver of global liver-related mortality, with pathological states evolving from simple steatosis to end-stage cirrhosis[1-3]. The burden of alcohol-related liver disease (ALD) in China is becoming increasingly significant, driven by complex socioeconomic factors and a prevalent harmful drinking culture[4]. Data from our institution revealed an increase in ALD-related hospitalizations, with alcoholic liver cirrhosis (ALC) patients exhibiting significantly higher risks of upper gastrointestinal bleeding than patients with hepatitis B virus-induced cirrhosis (HBV-C) do[5]. Furthermore, concomitant excessive alcohol consumption significantly worsens hepatic impairment and elevates the likelihood of developing hepatocellular carcinoma or esophagogastric variceal hemorrhage among individuals already suffering from viral-induced cirrhosis[6].

A significant proportion of cirrhotic patients, ranging from 20% to 50%, suffer from the co-occurrence of malnutrition and sarcopenia. Malnutrition, manifested as an imbalance in body composition, frequently leads to functional decline and unfavorable clinical prognoses[7-9]. Sarcopenia, which involves the progressive depletion of muscle mass and strength, is considered a critical stage of malnutrition that directly elevates the risk of mortality and complications[10]. The development of these conditions is multifactorial, driven by a synergistic interplay of inadequate nutrient intake, impaired absorption, metabolic dysregulation, endocrine shifts, chronic inflammation, and intestinal dysbiosis[7]. Despite the established importance of aggressive nutritional support, reversing muscle loss remains clinically demanding, necessitating prompt screening and precise diagnostic approaches.

Several practice guidelines, including the 2021 Practice Guidance by the American Association for the Study of Liver Diseases and the 2019 European Association for the Study of the Liver (EASL), provide frameworks for managing malnutrition and sarcopenia in cirrhosis[11,12]. However, the direct application of Western criteria to Chinese patients remains problematic because of different etiologies and ethnic-specific characteristics. Evidence also highlights deficiencies in vitamins, particularly involving vitamins A and D alongside essential minerals like zinc (Zn) and magnesium (Mg), in chronic liver disease populations[7-9,13]. Nevertheless, detailed data specifically linking micronutrient profiles to the prognosis of ALC patients in China remain sparse. Most importantly, the distinct nutritional phenotype of ALC which may differ substantially from the well-studied HBV-C has not been fully elucidated using multidimensional assessment tools.

Therefore, this study aimed to compare the performance of different nutritional assessment techniques in detecting malnutrition and to characterize alterations in anthropometry, vitamins, and trace elements in male ALC patients. By comparing these parameters across cirrhosis severities and against HBV-C and healthy controls (HCs), we sought to evaluate their impact on patient prognosis and identify etiology-specific nutritional biomarkers.

MATERIALS AND METHODS
Methods

Subjects and study design: In this case-control study, adult male inpatients (≥ 18 years) with confirmed ALC were recruited from the Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-sen University (Guangzhou, Guangdong Province, China) between June 2020 and June 2024. Given the epidemiological characteristics of ALC in Southern China and the social stigma associated with female alcohol consumption, only male patients were enrolled. Age-matched male controls included patients with HBV-C and HCs (the latter being patients with colon polyps and no underlying liver disease or significant history of alcohol use). The diagnosis of ALC was established through a comprehensive review of patients’ long-term alcohol intake history, with other potential etiologies strictly ruled out, supplemented by corroborating biochemical, imaging, or pathological findings. Criteria for exclusion comprised: (1) Other chronic liver diseases; (2) Serious infection; (3) Specific endocrinopathies (e.g., Graves’ disease or Cushing syndrome); (4) Malignancy; (5) Advanced multi-organ failure involving the cardiovascular, respiratory, renal, or hematopoietic systems; and (6) Corticosteroid use. This investigation was performed in strict accordance with the Declaration of Helsinki. Ethical clearance was granted by the Institutional Review Board of the Third Affiliated Hospital of Sun Yat-sen University, approval No. [2020]02-032-01, and every subject signed an informed consent form prior to participation.

Data collection: Clinical and laboratory parameters were extracted from electronic medical record systems. Beyond basic demographics (age and gender), we focused on systemic inflammatory markers. Specifically, the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were derived. Advanced indices, including the systemic immune-inflammation index (SII) and the systemic inflammatory response index, were quantified using standard formulas involving neutrophil, platelet (PLT), and monocyte counts. To evaluate metabolic status, the triglyceride glucose index was determined from fasting levels of blood glucose and triglycerides as an insulin resistance proxy. Furthermore, hepatic function was staged via the Child-Pugh scoring system based on integrated clinical and biochemical data. The severity of ascites was determined according to the 2018 EASL Clinical Practice Guidelines, classified as follows: No or mild ascites (grade 1, detectable only by ultrasound) and clinically overt ascites (grades 2 or 3, moderate or gross ascites with marked abdominal distention)[14]. Importantly, only grade 1 ascites or absence of ascites was considered to have a negligible influence on anthropometric measurements. Patients were followed from the date of enrollment to death or the final follow-up (October 1, 2025).

Anthropometric evaluation: Beyond calculating body mass index (BMI) using the standard weight/height2 formula, we categorized patients into underweight (< 18.5 kg/m2), normal (18.5-25 kg/m2), and overweight (> 25 kg/m2) groups. In the absence of computed tomography (CT)-based skeletal muscle index (SMI) or dual-energy X-ray absorptiometry (DXA), mid-arm circumference (AC) and arm muscle circumference (AMC) served as indirect surrogates for muscle mass assessment. AC was measured in centimeters at the midpoint of the nondominant upper arm, using a flexible tape. Triceps skinfold thickness (TSF) was quantified using a Harpenden caliper in millimeters 2 cm above the midpoint of the nondominant upper arm. These values allowed for the derivation of AMC via the formula: AC (cm) - [TSF (mm) × 0.314]. Abdominal fat thickness (AFT) was measured 1 cm lateral to the umbilicus using a skinfold caliper. Waist circumference (WC) was recorded at the narrowest point between the inferior rib border and the iliac crest following a normal expiration. Meanwhile, hip circumference (HC) was assessed at the level of maximum gluteal protuberance. The waist-to-hip ratio was subsequently derived by dividing the WC value by the HC value. The average of three measurements was recorded. To minimize measurement bias, all anthropometric evaluations were performed by a single trained dietitian.

Serum trace elements and vitamins: Fasting peripheral venous blood (2 mL) was collected and analyzed for serum trace elements, including iron (Fe), Zn, Mg, copper (Cu), and calcium (Ca), using inductively coupled plasma mass spectrometry in the hospital laboratory. To mitigate the effects of hypoalbuminemia on Ca levels, we utilized the Payne formula[15] for correction: Adjusted Ca (mmol/L) = serum total Ca (mmol/L) + 0.02 × [normal albumin (ALB) level (g/L) - actual ALB level (g/L)]. Regarding Zn and Mg, as no internationally standardized correction formulas for hypoalbuminemia currently exist, raw measured concentrations were used for analysis. Serum vitamins, including vitamins A, vitamin B (VB) 1, VB2, VB6, VB9 (folate), vitamin C (VC), vitamin E (VE), VB12, and vitamin D (VD), were analyzed via high-performance liquid chromatography.

Nutritional assessment tools: The nutritional risk of patients was evaluated by the nutritional risk screening 2002 (NRS-2002) tool, with scores ≥ 3 indicating nutritional risk. This validated instrument incorporates nutritional status, disease severity, and age[16,17]. The subjective global assessment (SGA), a validated tool for assessing dietary intake, weight changes, gastrointestinal symptoms, functional capacity, and physical signs of malnutrition, was also administered by a single trained dietitian[18,19].

Statistical analysis

All statistical computations were executed using R, version 4.3.2. Continuous data are presented as means ± SD or as medians and interquartile ranges (IQRs), based on normality tests (Shapiro-Wilk). Categorical data are presented as n (%). For group comparisons, either analysis of variance (with post hoc Tukey) or the Kruskal-Wallis test (with Dunn’s test) was used for continuous variables, and the χ2 or Fisher’s exact test was used for categorical variables. Dunn’s post hoc test was conducted to identify specific group differences following significant Kruskal-Wallis results. To maximize data integrity, missing values (all < 5% for nutritional variables) were addressed using multiple imputation by chained equations with five imputations. To explore etiology-specific nutritional profiles, principal component analysis (PCA) was conducted in an exploratory manner on the imputed dataset. Standardized continuous variables including minerals and trace elements (Zn, Mg, Fe, Cu, and Ca) and vitamins (VA, VB1, VB2, VB6, folate, VC, VE, VB12, and VD) were included in the PCA model. All data were Z-score standardized prior to analysis to mitigate measurement unit bias, and the first two principal components (PC) (PC1 and PC2) were retained for visualization.

Regarding variable processing, continuous variables were dichotomized based on established clinical cut-offs solely for the purpose of prevalence estimation and visualization, for example, a BMI < 18.5 kg/m2 was reclassified as malnutrition and a BMI > 18.5 kg/m2 was reclassified as no malnutrition (no)[11]; the same was done for AC, AMC, TSF, SGA scores, and NRS-2002 scores, according to the criteria established by Blackburn et al[20] and Frisancho[21]. However, in all Cox proportional hazards regression models and prognostic analyses, these nutritional indicators were treated as continuous variables to preserve statistical power and accurately identify dose-response relationships. Kaplan-Meier survival curves were constructed to visualize cumulative survival probabilities over time. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) for mortality risk factors. A two-tailed P value < 0.05 was considered to indicate statistical significance.

RESULTS
Characteristics of all the patients with ALC or HBV-C and the HCs

A total of 435 male participants were included: 249 with ALC, 103 with HBV-C, and 83 HCs (Figure 1). No significant differences in age, height, weight, or BMI were detected among the three groups. The detailed clinical and laboratory characteristics are shown in Table 1.

Figure 1
Figure 1 Flow chart showing study participant selection. ALD: Alcohol-related liver disease; ALC: Alcoholic liver cirrhosis; HBV: Hepatitis B virus; HCs: Healthy controls.
Table 1 Patients’ overall characteristics, n (%)/median (interquartile range).
Variables
HCs (n = 83)
HBV-C (n = 103)
ALC (n = 249)
P value
Age (year)50.00 (35.00-62.50)53.00 (47.00-58.50)53.00 (46.00-60.00)0.122
Height (m)1.68 (1.63-1.73)1.68 (1.62-1.71)1.68 (1.64-1.71)0.769
Weight (kg)65.00 (54.15-75.25)64.00 (59.60-70.65)64.00 (57.90-71.00)0.910
BMI (kg/m2)23.24 (19.74-25.88)23.32 (20.99-25.84)23.03 (20.98-25.06)0.835
WBC (× 109/L)5.89 (5.12-7.29)3.98 (2.96-4.99)a4.85 (3.54-6.40)a,b< 0.001
RBC (× 1012/L)4.72 (3.89-5.08)3.72 (3.08-4.22)a3.44 (2.84-4.04)a,b< 0.001
Hb (g/L)137.00 (118.50-150.00)109.00 (83.50-131.00)a101.00 (76.00-119.00)a,b< 0.001
MCV (fL)89.80 (85.05-92.35)89.30 (79.25-94.15)88.70 (77.70-96.10)0.987
PLT (× 109/L)231.00 (189.00-288.00)77.00 (51.50-120.00)a104.00 (72.00-155.00)a,b< 0.001
NEUT0.56 (0.51-0.65)0.60 (0.51-0.69)0.60 (0.49-0.68)0.383
LYMPH0.32 (0.25-0.37)0.25 (0.18-0.33)a0.27 (0.17-0.34)a0.002
MONO0.08 (0.06-0.09)0.10 (0.08-0.12)a0.11 (0.09-0.13)a< 0.001
NLR1.79 (1.39-2.54)2.42 (1.52-3.89)a2.18 (1.38-3.88)0.031
PLR118.60 (97.19-164.77)88.31 (65.12-128.85)a86.37 (67.07-117.62)a< 0.001
SII419.67 (299.52-635.94)220.73 (113.15-350.83)a256.81 (133.52-387.29)a< 0.001
SIRI0.91 (0.60-1.24)0.87 (0.47-1.84)0.99 (0.64-2.06)0.185
AST (U/L)20.00 (16.50-27.00)35.00 (26.00-56.50)a42.00 (29.00-65.00)a< 0.001
ALT (U/L)18.00 (12.50-30.00)28.00 (18.00-38.50)a25.00 (17.00-37.00)a0.002
AST/ALT1.06 (0.76-1.52)1.43 (1.09-1.79)a1.74 (1.21-2.44)a,b< 0.001
GGT (U/L)22.00 (16.00-42.00)50.00 (22.50-91.50)a85.00 (45.00-196.25)a,b< 0.001
ALP (U/L)67.00 (56.50-81.00)97.00 (77.50-136.50)a120.00 (85.75-174.75)a,b< 0.001
ALB (g/L)41.85 (39.00-45.50)35.30 (31.90-39.70)a34.10 (29.40-38.40)a< 0.001
TBIL (μmol/L)9.45 (6.53-13.65)15.20 (11.15-20.20)a20.80 (12.20-40.80)a,b< 0.001
DBILI (μmol/L)2.20 (1.50-3.10)4.80 (3.50-9.35)a6.90 (3.60-17.50)a< 0.001
IBILI (μmol/L)6.80 (3.45-10.05)9.60 (7.00-12.95)a10.40 (7.20-17.60)a< 0.001
BUN (mmol/L)5.07 (4.28-5.97)5.09 (3.97-6.67)4.69 (3.40-6.36)0.074
Cr (μmol/L)67.00 (57.50-83.00)71.00 (58.50-81.00)65.00 (55.00-81.00)0.215
GLU (mmol/L)5.16 (4.66-6.29)5.85 (4.83-8.18)a5.84 (4.71-7.98)a0.010
CHOL (mmol/L)4.68 (4.08-5.54)3.85 (3.34-4.60)a3.79 (2.84-4.67)a< 0.001
TG (mmol/L)1.26 (0.83-1.92)0.91 (0.68-1.40)a1.03 (0.75-1.44)0.002
HDL (mmol/L)1.02 (0.87-1.18)0.93 (0.68-1.14)a0.89 (0.68-1.14)a0.008
LDL (mmol/L)2.83 (2.20-3.54)2.15 (1.61-2.71)a2.06 (1.45-2.73)a< 0.001
UA (μmol/L)349.00 (277.00-426.00)311.00 (240.50-388.00)360.50 (291.75-452.25)b0.001
TyG8.59 (8.11-9.20)8.48 (8.01-8.97)8.50 (8.09-9.06)0.323
PT (second)13.10 (12.78-13.80)15.50 (14.75-17.00)a16.00 (14.80-18.05)a< 0.001
PTA (%)101.50 (94.00-111.00)73.00 (62.00-80.50)a68.00 (53.00-81.00)a< 0.001
INR0.99 (0.95-1.06)1.23 (1.14-1.37)a1.27 (1.15-1.49)a< 0.001
Ascites0.082
No or mild79 (78.22)162 (67.22)
Clinically overt ascites22 (21.78)79 (32.78)
CTP< 0.001
A51 (49.51)108 (43.37)
B/C52 (50.49)141 (56.63)

Compared with the HCs, both cirrhosis groups had significantly lower median values (with IQR) for white blood cell (WBC), red blood cell (RBC), hemoglobin (Hb), and PLT counts and lymphocyte counts. Notably, ALC patients had significantly lower RBC counts and Hb levels than those with HBV-C, despite having higher WBC and PLT counts. In terms of inflammatory indices, the NLR was significantly higher in both cirrhosis groups than in HCs, with the HBV-C group showing the greatest increase. Conversely, the PLR and the SII were significantly lower in both cirrhosis groups.

Compared with the HCs, both the ALC and the HBV-C groups had significantly elevated liver enzymes and bilirubin levels, prolonged prothrombin times and elevated international normalized ratios. The increases in aspartate aminotransferase (AST)/alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), and total bilirubin (TBIL) levels were more pronounced in the ALC group than in the HBV-C group. The serum ALB concentration was significantly lower in both patient groups than in the HCs, with the ALC group exhibiting even lower values than the HBV-C group did, although the difference was not significant. Despite differences in Child-Pugh classification, no significant difference was observed in the severity of ascites between the two cirrhosis groups (Table 1).

Nutritional status analysis in ALC patients, HBV-C patients, and HCs

Normal reference ranges for trace elements and vitamins were provided (Supplementary Table 1). ALC patients exhibited distinct micronutrient deficiencies. Specifically, serum levels of Mg, VD, VB1, and VB2 were significantly lower in ALC patients than in those with HBV-C and HCs (Table 2). The proportion of variance explained by each PC was calculated and reported in the corresponding figures (Figures 2 and 3) and legends. Exploratory PCA of serum trace elements (including Zn, Mg, Fe, Cu, and corrected Ca) revealed significant separation between ALC and HBV-C patients, highlighting etiology-specific micronutrient profiles (Figure 2). Specifically, the PC1 explained approximately 29.5% of the total variance of the original data, while the PC2 explained approximately 20.9%. Collectively, PC1 and PC2 accounted for 50.4% of the total variance of the original micronutrient, indicating that the first two PCs effectively retained the majority of information from the original variables, which is sufficient to reflect the overall differences in trace elements among the three groups. Similarly, PCA of serum vitamin levels revealed that alterations in serum vitamin levels are more prominent in ALC patients (Figure 3).

Figure 2
Figure 2 Principal component analysis and serum trace element profiles distinguish cirrhosis etiologies. A-C: Principal component analysis of serum trace elements showing metabolic separation between groups. Hepatitis B virus-related cirrhosis (HBV-C) vs healthy controls (HCs) (A). Alcoholic liver cirrhosis (ALC) vs HCs (B). Among ALC, HBV-C, and HCs (C). Individual samples are shown as points with 95% confidence ellipses; principal components and explained variance (%) are labeled; D-H: Violin plots of serum trace elements. Iron (D); zinc (E); magnesium (F); copper (G); calcium (H). Horizontal lines indicate medians and interquartile ranges. aP < 0.05. NS: Not significant; ALC: Alcoholic liver cirrhosis; HBV-C: Hepatitis B virus-related cirrhosis; HCs: Healthy controls; PC: Principal component; Fe: Iron; Zn: Zinc; Mg: Magnesium; Cu: Copper; Ca: Calcium.
Figure 3
Figure 3 Principal component analysis and serum vitamin profiles in healthy controls, hepatitis B virus-related cirrhosis, and alcoholic liver cirrhosis groups. A-C: Principal component analysis of serum vitamins showing distribution between groups. Hepatitis B virus-related cirrhosis (HBV-C) vs healthy controls (HCs) (A); alcoholic liver cirrhosis (ALC) vs HCs (B); among ALC, HBV-C, and HCs (C). Individual samples are shown as points with 95% confidence ellipses; principal components and explained variance (%) are labeled; D-L: Violin plots of serum vitamins. Vitamin A (D); vitamin B (VB) 1 (E); VB2 (F); VB6 (G); VB9 (H); vitamin C (I); vitamin E (J); VB12 (K); vitamin D (L). Horizontal lines indicate medians and interquartile ranges. aP < 0.05. NS: Not significant; ALC: Alcoholic liver cirrhosis; HBV-C: Hepatitis B virus-related cirrhosis; HCs: Healthy controls; PC: Principal component; Vit: Vitamin.
Table 2 Nutritional status analysis with hepatitis B virus-related cirrhosis, and alcoholic liver cirrhosis and healthy controls, n (%)/median (interquartile range).
Variables
HCs (n = 83)
HBV-C (n = 103)
ALC (n = 249)
P value
Anthropometric
WC (cm)76.50 (74.00-86.00)80.50 (76.00-86.00)85.00 (80.00-89.00)a,b0.002
HC (cm)88.00 (80.00-91.00)82.00 (80.00-87.00)90.00 (84.00-93.00)b< 0.001
WHR0.92 (0.89-0.97)0.97 (0.95-1.01)a0.95 (0.92-1.01)a,b0.002
AC (cm)26.00 (24.00-28.00)24.00 (22.00-25.00)a25.00 (23.00-28.00)b< 0.001
AMC (cm)21.00 (19.20-22.30)20.20 (18.20-21.50)21.90 (20.10-24.50)b< 0.001
TSF (mm)12.00 (10.00-18.00)10.00 (8.00-12.00)10.00 (8.00-13.00)0.142
AFT (mm)18.00 (12.00-28.00)10.00 (10.00-16.00)a18.50 (10.25-30.00)b< 0.001
Serum trace elements
Fe (μmol/L)14.50 (10.12-20.35)9.70 (5.60-17.70)a8.75 (4.00-16.33)a0.002
Zn (μmol/L)10.20 (7.65-11.70)8.60 (7.00-10.30)9.80 (7.97-11.27)0.096
Mg (mmol/L)0.88 (0.84-0.93)0.84 (0.79-0.89)a0.79 (0.72-0.86)a,b< 0.001
Cu (μmol/L)15.50 (12.80-18.75)13.10 (11.50-18.20)14.90 (13.05-18.00)0.343
AdCa (mmol/L)2.29 (2.23-2.36)2.29 (2.23-2.36)2.35 (2.27-2.44)a,b< 0.001
Serum vitamins
VA (μmol/L)1.36 (1.26-1.49)1.32 (1.21-1.43)1.39 (1.22-1.58)0.185
VB1 (nmol/L)78.54 (55.85-93.38)88.42 (70.96-98.37)72.98 (60.79-87.23)a,b0.017
VB2 (μg/L)326.70 (294.21-358.53)322.07 (297.53-359.03)291.85 (270.09-352.24)a,b0.008
VB6 (μmol/L)19.09 (13.68-25.98)20.70 (13.95-26.19)20.60 (15.37-25.37)0.565
VB9 (nmol/L)20.55 (17.57-22.43)18.56 (16.56-21.79)19.45 (17.47-22.19)0.238
VC (μmol/L)37.61 (32.64-42.04)42.90 (36.32-51.75)a46.29 (43.16-49.36)a< 0.001
VE (μg/mL)12.79 (11.73-14.07)15.06 (13.60-16.86)a15.20 (13.51-16.44)a< 0.001
VB12 (pg/mL)279.94 (215.12-319.18)281.12 (211.05-356.19)279.21 (201.41-349.65)0.713
VD (nmol/L)57.65 (44.53-68.67)57.85 (48.75-67.03)46.20 (37.66-57.25)a,b< 0.001
Nutritional assessment tools
SGA0.153
1 (well-nourished)74 (89.16)89 (86.41)195 (80.91)
2 (malnourished)9 (10.84)14 (13.59)46 (19.09)
NRS-20020.243
1 (no nutritional risk)73 (87.95)86 (83.50)183 (79.91)
2 (at nutritional risk)10 (12.05)17 (16.50)46 (20.09)

ALC patients displayed signs of central adiposity, with significantly higher WC, HC, and AFT than HBV-C patients did, despite a comparable prevalence of ascites. Interestingly, while AC and AMC were reduced compared to HCs, these measurements remained significantly higher in ALC patients than in the HBV-C group, suggesting a unique body composition phenotype in the ALC cohort (Table 2).

The prevalence of malnutrition in the ALC and HBV-C cohorts according to the standard cutoff values for each method were as follows: BMI, 13/238 (7.14%) vs 5/103 (4.85%), P = 0.056; AC, 101/171 (59.06%) vs 55/60 (91.67%), P < 0.001; AMC, 36/164 (21.95%) vs 22/60 (36.67%), P = 0.075; TSF, 58/172 (33.72%) vs 18/60 (30.00%), P < 0.001; SGA, 46/241 (19.09%) vs 14/103 (13.59%), P = 0.153; NRS-2002, 46/229 (20.09%) vs 17/103 (16.50%), P = 0.243 (Figure 4). Although not statistically significant, the prevalence of malnutrition in ALC patients, as evaluated by the SGA and NRS-2002, was greater than that in HBV-C patients. Notably, 33.7% of ALC patients classified as malnourished by the SGA were misclassified as “normal weight” by their BMI, highlighting the limitations of BMI in this population (Figure 4).

Figure 4
Figure 4 Comparison of nutritional status among the healthy controls, hepatitis B virus-related cirrhosis, and alcoholic liver cirrhosis groups. Percentage of patients with normal nutritional status and malnutrition assessed by anthropometric measurements and nutritional assessment tools according to standard cutoff values. A: Mid-arm circumference; B: Mid-arm muscular circumference; C: Triceps skinfold; D: Subjective global assessment (SGA) score; E: Nutritional risk screening 2002 (NRS-2002) score; F: Percentage of patients categorized as overweight, normal weight, and underweight based on body mass index (BMI) in healthy controls (HCs), hepatitis B virus-related cirrhosis (HBV-C), and alcoholic liver cirrhosis (ALC) groups; G: Comparison of SGA scores, BMI, and NRS 2002 scores showing visual comparisons of nutritional status and BMI categories among HCs, HBV-C, and ALC groups. AC: Mid-arm circumference; AMC: Mid-arm muscular circumference; TSF: Triceps skinfold; ALC: Alcoholic liver cirrhosis; HBV-C: Hepatitis B virus-related cirrhosis; HCs: Healthy controls; BMI: Body mass index; SGA: Subjective global assessment; NRS-2002: Nutritional risk screening 2002.
Nutritional indicator analysis in cirrhosis patients with different Child-Pugh classifications

Among ALC patients, compared with patients with Child-Pugh A disease, those with Child-Pugh B/C disease had significantly lower levels of Zn [8.00 (6.60-9.50) μmol/L vs 11.20 (9.80-13.35) μmol/L, P < 0.001], Mg [0.77 (0.69-0.83) mmol/L vs 0.83 (0.78-0.88) mmol/L, P < 0.05], and Ca [2.21 (2.07-2.32) mmol/L vs 2.29 (2.21-2.39) mmol/L, P < 0.05]. VB6 and VD levels declined significantly with disease progression, while VE and VB12 levels increased. Among ALC patients, the proportion of those with malnutrition increased in parallel with disease progression, as evidenced by a higher prevalence in those with Child-Pugh class B/C disease than in those with Child-Pugh class A disease. This correlation, however, was not apparent among HBV-C patients (Table 3).

Table 3 Nutritional indicator analysis in cirrhosis patients with different Child-Pugh classifications, n (%)/median (interquartile range).
VariablesHBV-C (n = 103)
ALC (n = 249)
Child A
Child B/C
Child A
Child B/C
Anthropometric
Height (m)1.68 (1.64-1.71)1.68 (1.62-1.71)1.68 (1.65-1.71)1.68 (1.63-1.70)
Weight (kg)63.00 (58.40-70.75)64.25 (60.00-70.47)63.10 (58.62-69.88)65.00 (57.80-71.00)
BMI (kg/m2)22.48 (20.76-25.15)24.04 (21.61-25.97)22.63 (20.99-24.67)23.41 (21.00-25.41)
WC (cm)78.00 (75.50-83.25)82.50 (77.00-89.25)85.00 (82.62-88.25)85.00 (80.00-90.00)
HC (cm)80.00 (80.00-83.50)85.50 (80.00-88.00)a92.00 (85.38-93.25)b89.00 (84.00-93.00)b
WHR0.97 (0.95-0.99)0.98 (0.95-1.01)0.95 (0.92-0.99)0.94 (0.92-1.01)
AC (cm)24.00 (22.00-24.60)24.00 (22.00-25.00)26.00 (24.00-28.40)b24.50 (22.00-28.00)
AMC (cm)20.55 (19.25-21.42)20.15 (18.17-22.25)22.20 (20.25-24.65)b21.50 (19.70-23.90)b
TSF (mm)10.00 (8.00-12.25)10.00 (7.50-12.00)10.00 (8.00-14.00)10.00 (6.00-13.00)
AFT (mm)10.00 (10.00-14.50)12.00 (10.00-17.00)20.00 (11.50-30.00)b18.00 (10.00-29.50)b
Serum trace elements
Fe (μmol/L)9.70 (5.65-17.62)9.70 (5.50-17.80)8.05 (3.10-14.02)9.10 (5.20-17.72)a
Zn (μmol/L)9.00 (7.40-11.40)8.25 (5.62-9.57)11.20 (9.80-13.35)b8.00 (6.60-9.50)a
Mg (mmol/L)0.84 (0.80-0.92)0.84 (0.77-0.88)0.83 (0.78-0.88)0.77 (0.69-0.83)a,b
Cu (μmol/L)12.90 (11.70-16.50)14.85 (11.50-19.65)13.55 (12.00-15.35)17.20 (14.70-20.00)a
AdCa (mmol/L)2.26 (2.15-2.37)2.14 (2.03-2.25)a2.29 (2.21-2.39)2.21 (2.07-2.32)a
Serum vitamins
VA (μmol/L)1.37 (1.25-1.46)1.27 (1.17-1.33)a1.36 (1.16-1.54)1.42 (1.29-1.62)b
VB1 (nmol/L)86.26 (67.93-94.52)93.28 (71.57-103.50)71.59 (58.27-83.61)b73.42 (62.73-91.45)b
VB2 (μg/L)319.38 (288.84-362.23)322.23 (301.15-335.15)302.25 (280.30-355.48)281.66 (261.11-338.71)b
VB6 (μmol/L)20.70 (13.80-25.20)20.74 (16.81-31.34)22.52 (16.29-27.41)18.48 (14.18-23.72)a
VB9 (nmol/L)19.50 (16.36-22.17)18.02 (16.82-21.29)18.95 (17.56-21.38)20.13 (17.43-22.29)
VC (μmol/L)43.82 (36.48-51.80)42.03 (36.12-51.70)46.01 (42.11-49.07)46.71 (45.18-49.81)
VE (μg/mL)14.95 (12.70-16.89)15.15 (14.59-16.72)14.84 (13.13-16.18)15.39 (13.72-16.77)a
VB12 (pg/mL)282.28 (205.37-380.36)272.09 (218.83-328.35)263.32 (195.96-338.30)284.14 (220.64-356.33)a
VD (nmol/L)63.25 (51.85-67.70)51.20 (46.42-61.45)a48.70 (42.70-60.25)b41.10 (34.80-55.64)a,b
Nutritional assessment tools
SGA
1 (well-nourished)46 (90.20)43 (82.69)95 (89.62)100 (74.07)
2 (malnourished)5 (9.80)9 (17.31)11 (10.38)35 (25.93)a
NRS-2002
1 (no nutritional risk)46 (90.20)40 (76.92)89 (85.58)94 (75.20)
2 (at nutritional risk)5 (9.80)12 (23.08)15 (14.42)31 (24.80)a

Among patients with Child-Pugh class A disease, those with ALC had greater HC, AC, AMC, and AFT than those with HBV-C did. VB1 and VD levels were lower in ALC patients, whereas Zn levels were higher. No significant differences in malnutrition prevalence were found (Table 3).

In the Child-Pugh B/C subgroup, ALC patients retained higher HC, AMC, and AFT but exhibited markedly lower levels of Mg, VB1, VB2, and VD (all P < 0.001) compared to HBV-C patients did. The prevalence of malnutrition did not differ significantly between the groups (Table 3).

Analysis of nutritional indicators in ALC patients in relation to patient prognosis

This study further investigated the relationship between nutritional indicators and prognosis in patients with ALC. Patients were followed up for a median of 23.39 months, with a 16.2% liver-related mortality rate. Comparison between survivors (n = 202) and non-survivors (n = 39) revealed significant differences in baseline ALB, TBIL, prothrombin time, Child-Pugh class, body weight, AC, and AMC. Furthermore, levels of Zn, Mg, and VD were significantly lower in non-survivors. Both SGA and NRS-2002 identified a higher prevalence of malnutrition in the mortality group (Table 4).

Table 4 Nutritional indicator analysis with mortality, n (%)/median (interquartile range).
Variables
Survivors (n = 202)
Non-survivors (n = 39)
P value
Age (year)53.00 (45.00-60.00)55.00 (48.00-60.00)0.431
Height (m)1.68 (1.64-1.71)1.66 (1.63-1.70)0.192
Weight (kg)65.00 (58.40-72.10)60.90 (56.75-67.62)0.048
BMI (kg/m2)23.42 (21.00-25.37)22.41 (20.78-24.35)0.121
ALB (g/L)34.60 (30.45-38.55)30.00 (26.70-35.95)0.004
TBIL (μmol/L)18.00 (11.53-34.17)38.70 (21.95-72.35)< 0.001
PT (second)15.80 (14.80-17.42)17.70 (15.85-19.05)< 0.001
Fe (μmol/L)8.40 (3.80-16.00)12.35 (6.07-18.55)0.099
Zn (μmol/L)9.80 (8.50-12.25)6.60 (6.20-8.60)0.013
Mg (mmol/L)0.80 (0.74-0.86)0.76 (0.64-0.83)0.005
Cu (μmol/L)14.45 (12.28-18.70)16.20 (14.50-17.20)0.701
AdCa (mmol/L)2.37 (2.28-2.44)2.36 (2.24-2.44)0.382
VA (μmol/L)1.39 (1.21-1.57)1.53 (1.36-1.65)0.080
VB1 (nmol/L)71.80 (58.72-86.04)75.26 (63.32-94.57)0.369
VB2 (μg/L)291.38 (260.70-351.60)313.61 (280.28-355.67)0.237
VB6 (μmol/L)20.79 (15.35-25.70)21.48 (17.86-25.35)0.876
VB9 (nmol/L)19.45 (17.62-22.19)19.72 (17.43-22.74)0.955
VC (μmol/L)46.29 (43.89-49.24)50.77 (40.90-53.84)0.139
VE (μg/mL)15.13 (13.52-16.37)15.39 (14.51-17.24)0.329
VB12 (pg/mL)278.57 (197.57-344.99)304.80 (217.81-361.57)0.203
VD (nmol/L)48.00 (39.65-57.90)36.40 (32.20-41.50)0.007
WC (cm)85.00 (80.00-88.00)85.50 (80.50-92.00)0.471
HC (cm)89.50 (84.00-93.00)89.00 (84.25-93.50)0.763
WHR0.95 (0.92-1.01)0.95 (0.93-1.01)0.576
AC (cm)26.00 (23.50-28.10)23.00 (21.75-24.56)< 0.001
AMC (cm)22.20 (20.30-24.70)20.25 (19.65-21.80)0.009
TSF (mm)10.00 (8.00-14.00)10.00 (7.50-11.25)0.175
AFT (mm)20.00 (11.50-31.00)15.00 (10.00-22.00)0.175
Ascites0.409
No or mild138 (68.32)24 (61.54)
Clinically overt ascites64 (31.68)15 (38.46)
Child< 0.001
A98 (48.51)6 (15.38)
B83 (41.09)16 (41.03)
C21 (10.40)17 (43.59)
SGA0.015
1 (well-nourished)162 (83.51)26 (66.67)
2 (malnourished)32 (16.49)13 (33.33)
NRS-20020.026
1 (no nutritional risk)153 (82.26)23 (65.71)
2 (at nutritional risk)33 (17.74)12 (34.29)

The Kaplan-Meier survival analysis demonstrated that, in addition to the well-established Child-Pugh classification, low levels of ALB and lower AC, as well as malnutrition, as evaluated by the SGA and NRS-2002, were significantly associated with diminished survival (Figure 5).

Figure 5
Figure 5 Kaplan-Meier survival curves for nutritional indicators in patients with alcoholic liver cirrhosis. A: Serum albumin concentration; B: Child-Pugh classification; C: Subjective global assessment score; D: Nutritional risk screening 2002 score; E: Mid-arm circumference range. ALB: Albumin; HR: Hazard ratio; CI: Confidence interval; AC: Mid-arm circumference; SGA: Subjective global assessment; NRS-2002: Nutritional risk screening 2002.

Multivariate Cox regression, utilizing continuous variables, was performed to evaluate independent risk factors (Table 5). In the basic model and after adjusting for age and BMI, our results revealed that patients with lower levels of Zn, Mg, VD, and AC had a greater risk of mortality. In the fully adjusted model (age, BMI, ALT level, ALB concentration, TBIL level, blood urea nitrogen level, and SGA score), the analysis revealed that low levels of Zn (HR = 0.51, 95%CI: 0.31-0.85; P = 0.010) and VD (HR = 0.92, 95%CI: 0.86-0.99; P = 0.017) remained independent predictors of mortality. Notably, AC remained a significant predictor (HR = 0.85; 95%CI: 0.75-0.96; P = 0.008), highlighting its clinical utility in prognostic stratification.

Table 5 Multivariate Cox analysis of the relationship between nutritional indicator and liver-related mortality.
VariablesModel 1
Model 2
Model 3
HR (95%CI)
P value
HR (95%CI)
P value
HR (95%CI)
P value
Zn0.65 (0.47-0.91)0.0120.62 (0.43-0.89)0.0090.51 (0.31-0.85)0.010
Mg0.03 (0.00-0.37)0.0050.02 (0.00-0.32)0.0050.06 (0.00-1.07)0.056
VD0.94 (0.90-0.99)0.0090.92 (0.87-0.97)0.0030.92 (0.86-0.99)0.017
AC0.83 (0.76-0.91)< 0.0010.83 (0.75-0.92)< 0.0010.85 (0.75-0.96)0.008
DISCUSSION

This study provides a comprehensive assessment of the nutritional status of male patients with ALC in southern China, revealing several distinct features compared to those with HBV-C and HCs. These findings highlight the complexity of nutritional alterations in patients with ALC and offer significant clinical implications.

The observed hematologic profile, characterized by significantly decreased erythropoiesis (RBC/Hb) but relatively preserved leukopoiesis and thrombopoiesis (WBC/PLT) in ALC patients, is intriguing. This likely stems from the dual effects of alcohol: Direct myelosuppression via acetaldehyde-mediated toxicity to erythroid progenitors, and reactive leuko-thrombocytosis driven by alcohol-induced systemic inflammation. Previous studies have identified anemia and systemic inflammation as strong and independent predictors of hepatic decompensation in patients with liver cirrhosis[22]. In our study, the NLR was significantly elevated, while the PLR and SII were reduced in ALC patients. An elevated NLR reflects alcohol-induced innate immune activation coupled with adaptive immune suppression, correlating closely with disease severity[23]. Specifically, the NLR serves as a simple and effective predictor of 30-day mortality in ALC[24]. Conversely, the decreased PLR and SII likely result from alcohol-induced myelosuppression and portal hypertension-induced splenic sequestration. This “high NLR, low PLR/SII” profile underscores ALC-specific immune dysregulation, serving as a marker for both disease activity and prognosis[25-27].

ALC patients exhibited more pronounced elevations in the AST/ALT ratio, GGT, ALP, and TBIL, aligning with the known hepatotoxic effects of alcohol on biliary and mitochondrial functions. Hypoalbuminemia was severe in both cirrhosis groups. In ALC specifically, exceptionally low ALB levels reflect profound hepatic synthetic dysfunction and malnutrition. This is likely driven by acetaldehyde-induced endoplasmic reticulum stress, which impairs protein synthesis, and alcohol-associated malabsorption[28]. Furthermore, systemic inflammation and endotoxemia exacerbate hypoproteinemia as ALB is consumed during acute-phase reactions[29]. These findings emphasize the urgent need for aggressive nutritional support and ALB replacement in ALC patients, particularly given ALB’s role in binding toxins and modulating systemic inflammation.

Patients with ALC are highly prone to VB deficiency. VB1 deficiency can lead to serious complications, such as Wernicke’s encephalopathy, which often mimics hepatic encephalopathy. In this study, both VB1 and VB2 levels were significantly lower in ALC patients than in HBV-C patients. Early detection and treatment of these deficiencies are critical[11]. VD deficiency was also prevalent and, in our cohort, correlated with adverse clinical outcomes, consistent with previous reports[30,31]. VD plays a crucial role in immune function and bone health, and its deficiency is associated with increased mortality, bacterial infections, and portal hypertension complications. The lower VD levels in ALC may result from ethanol-induced impairment of hepatic 25-hydroxylation.

Trace elements are essential for cellular antioxidant pathways. Our study revealed that serum levels of Mg and Ca were lower in ALC patients than in HCs or HBV-C patients, particularly in those with Child-Pugh class B/C disease. Chronic alcohol consumption has been linked to Mg deficiency, which influences liver disease progression[32]. Mg deficiency manifests in symptoms such as taste disturbances, decreased appetite, muscle spasms, and weakness, which can further exacerbate malnutrition[33,34]. In the context of ALD, Mg deficiency disrupts metabolism and promotes hepatic lipid deposition[35]. Additionally, low Ca levels are closely linked to VD deficiency. While Zn levels were initially higher in ALC than in HBV-C patients, they declined sharply as the disease progressed, supporting previous evidence of a dynamic relationship between zinc levels and disease severity in ALC patients[36]. Zinc is an essential trace element involved in multiple biological processes, including immune function, wound healing, and antioxidant defense. Its deficiency has been linked to increased susceptibility to infections and poor clinical outcomes in cirrhotic patients[33,37]. Our multivariate Cox regression analysis demonstrated that low Zn levels are independently associated with increased mortality, suggesting Zn is a valuable prognostic biomarker.

Our study highlights a distinctive nutritional and body composition phenotype in ALC patients compared to HBV-C patients. Although ALC patients exhibited higher nutritional risk scores (SGA and NRS-2002), their anthropometric measurements exhibited a unique phenotype characterized by apparent central adiposity (increased WC, HC, and AFT) and relatively higher AC and AMC. This should be interpreted with caution, as it likely reflects a complex interplay of metabolic and endocrine disturbances unique to chronic alcohol consumption. Firstly, the “isocaloric” effect of alcohol plays a pivotal role. Alcohol is an energy-dense substance (7.1 kcal/g) that contributes a substantial proportion of daily caloric intake in ALC. Additionally, dietary habits associated with alcohol consumption in China, which are frequently characterized by the concurrent intake of high-calorie, high-fat, and high-protein foods, may further contribute to this specific “fatty” phenotype[38-40]. Secondly, chronic alcohol abuse significantly disrupts the hypothalamic-pituitary-gonadal axis, often leading to a decreased testosterone-to-estrogen ratio. This hormonal imbalance promotes shift in fat distribution, explaining the significantly higher HC and AFT observed in our ALC cohort[40,41]. Furthermore, we must address the potential for sarcopenia being obscured by fluid retention and adiposity. While AC values were significantly lower in ALC patients than in HCs, the decrease was less dramatic than in the HBV-C group, especially among those with Child-Pugh A disease. This suggests that muscle wasting is indeed present but is likely masked by subclinical interstitial edema or local tissue water retention common in alcoholic liver injury which may artificially inflate anthropometric measurements even in the absence of overt ascites[40]. This phenomenon, analogous to sarcopenic obesity where excess adiposity masks underlying muscle depletion, appears to operate through a distinct mechanism in ALC involving alcohol-specific fluid redistribution and hormonal perturbations[11,40]. Future research should ideally incorporate objective gold-standard assessments such as CT-based SMI or DXA, alongside functional measures like handgrip strength, to achieve a more accurate and multidimensional evaluation of sarcopenia. Nevertheless, our results demonstrate that lower AC values remain significantly associated with a poorer prognosis in ALC. Given that AC is a low-cost, easily obtained anthropometric measure, it remains a highly practical tool for routine nutritional screening, particularly where advanced imaging like SMI or DXA is unavailable.

Beyond individual anthropometric markers, our study underscores the global impact of malnutrition on disease progression. We observed that the proportion of malnourished patients increases in parallel with disease severity. Furthermore, higher SGA and NRS-2002 scores were significantly associated with shorter survival times in the ALC cohort. These findings highlight the critical importance of early screening and proactive nutritional treatment. Systematic use of these tools allows for the early identification of high-risk patients who may otherwise be overlooked due to the misleading “fatty” phenotype of alcoholic cirrhosis, ultimately facilitating more timely and effective clinical interventions.

Several limitations should be acknowledged. First, the single-center design and the inclusion of a male-only cohort reflecting regional epidemiology and social stigma surrounding female alcohol consumption limit generalizability to female patients. Second, body composition was assessed via anthropometry rather than gold-standard methods (e.g., CT-SMI, DXA). Third, while Ca was corrected for hypoalbuminemia, standardized correction methods for Zn and Mg remain lacking. Despite these limitations, the identified nutritional patterns and their prognostic significance remain robust. Future multi-center studies with sex-balanced cohorts and objective body composition assessments are warranted.

CONCLUSION

Our study reveals that male patients with ALC in southern China exhibit a distinct nutritional phenotype characterized by profound deficiencies in Zn, Mg, and VD, alongside a sarcopenic obesity-like pattern. While central adiposity and subclinical edema may mask underlying muscle wasting, reduced AC remains a robust, independent predictor of poor prognosis. These findings underscore the necessity of etiology-specific nutritional assessment. Early screening and targeted micronutrient supplementation are essential to mitigate disease progression and improve survival in this high-risk population.

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Footnotes

Peer review: Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Gastroenterology and hepatology

Country of origin: China

Peer-review report’s classification

Scientific quality: Grade A, Grade B, Grade B

Novelty: Grade B, Grade B, Grade B

Creativity or innovation: Grade A, Grade B, Grade B

Scientific significance: Grade B, Grade B, Grade C

P-Reviewer: Ji KK, MD, China; Shrivastav D, PhD, Assistant Professor, India S-Editor: Fan M L-Editor: A P-Editor: Wang WB

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