ABSTRACT
Background and Aim
Metabolic syndrome significantly increases the risk of cardiovascular disease and type 2 diabetes. Hepatitis C virus (HCV) infection has been associated with an increased risk of metabolic syndrome. This study aims to explore this association to improve management strategies for HCV patients at risk of metabolic syndrome.
Methods
A cross‐sectional observational study was conducted in the Department of Medicine, Lahore General Hospital, Lahore, from December 3, 2022, to June 2, 2023. The study employed non‐probability consecutive sampling to include 115 patients diagnosed with HCV infection for at least 6 months. Metabolic syndrome was defined according to the National Cholesterol Education Program Adult Treatment Panel III criteria for Asian‐Americans. Statistical analysis was performed using Statistical Package for Social Sciences (SPSS) version 26.0.
Results
Out of 115 individuals with HCV infection, 36 (31.3%) were found to have metabolic syndrome. The condition was slightly more prevalent among males (33.3%) than females (29.3%), although this difference was not statistically significant (p = 0.642). A higher frequency of metabolic syndrome was observed in participants aged 31–45 years (34.8%) and 46–60 years (32.0%) compared to those aged 15–30 years (21.1%), but this variation was also not significant (p = 0.549). The duration of HCV infection showed no significant relationship with the presence of metabolic syndrome (p = 0.386). Multivariable logistic regression further confirmed that gender, age group, and duration of infection were not independently associated with metabolic syndrome.
Conclusions
This study indicates that while metabolic syndrome is fairly common among individuals with HCV infection and in older age, its occurrence does not show a significant association with gender, age, or the duration of infection. These results underscore the need for further studies to clarify the complex interplay between HCV and metabolic disturbances.
Keywords: age, duration of infection, gender, hepatitis C virus, metabolic syndrome
1. Introduction
Hepatitis C virus (HCV) infection is a significant global health concern. Although the global burden has declined by using antiviral therapy, yet the prevalence of HCV is alarmingly high in Pakistan, impacting nearly 6% of the population (10 million individuals) [1]. Chronic HCV infection is a major concern, as over 80% of affected individuals develop persistent infection. This condition leads to increased oxidative stress, triggering the release of pro‐inflammatory cytokines that contribute to tissue damage, progressive fibrosis, cirrhosis, hepatocellular carcinoma, and ultimately, end‐stage liver failure [2].
Metabolic Syndrome (MS) is a cluster of metabolic disorders, including hyperglycemia, abdominal obesity, hypertension, dyslipidemia, and insulin resistance. It is a well‐established risk factor for coronary artery disease, type 2 diabetes mellitus, and both microvascular and macrovascular complications. Several metabolic disturbances have been directly and indirectly associated with HCV infection [3]. The interplay between MS and chronic HCV infection has garnered increasing attention due to its significant impact on morbidity and mortality [2, 4, 5]. While chronic HCV infection predisposes individuals to metabolic complications, the presence of MS in HCV‐infected patients exacerbates disease progression, increasing the risks of hepatocellular carcinoma and advanced fibrosis [4, 5].
The impact of metabolic abnormalities on HCV progression has been highlighted in several studies. Recent reviews have emphasized that metabolic abnormalities, including insulin resistance and diabetes, should be recognized and managed alongside antiviral therapy to optimize long‐term hepatic and cardiovascular outcomes [4, 5]. Recent evidence indicates that HCV‐associated insulin resistance contributes to metabolic dysfunction and increases the risk of cardiovascular complications through chronic inflammation, endothelial dysfunction, and impaired insulin signaling [4, 5]. A systematic review and meta‐analysis by Ambrosino et al. further confirmed that chronic HCV infection is associated with a significantly increased risk of coronary artery and cerebrovascular disease, underscoring the importance of comprehensive metabolic and cardiovascular risk assessment in patients with chronic HCV infection [6].
Chronic HCV infection has been recognized as a metabolic disorder due to its direct impact on lipid and glucose metabolism [4]. It induces hepatic steatosis and contributes to insulin resistance and diabetes [5, 6]. Chronic HCV infection is associated with profound alterations in lipid and glucose metabolism, contributing to insulin resistance, hepatic steatosis, and dyslipidemia. HCV interferes with hepatic lipid homeostasis by modulating very low‐density lipoprotein (VLDL) assembly and secretion and disrupting insulin signaling pathways, resulting in metabolic abnormalities that promote liver disease progression and increase cardiovascular risk [4, 5]. Furthermore, metabolic dysfunction and hepatic steatosis may accelerate hepatic fibrosis and adversely affect long‐term clinical outcomes despite successful antiviral therapy [4].
Several studies have investigated the prevalence of MS among patients with chronic HCV infection. A recent study conducted in 2024 by Wang et al. demonstrated that adults with chronic HCV infection and moderate‐to‐severe fatty liver had a significantly greater risk of metabolic syndrome [7]. Similarly, Medhioub et al. reported a high prevalence of metabolic syndrome among patients with chronic HCV infection, highlighting the close association between HCV and metabolic dysfunction [3]. In Pakistan, Qasim et al. found that 97 of 331 (29.3%) patients with chronic HCV infection fulfilled the diagnostic criteria for metabolic syndrome [8]. Likewise, Memon et al. also reported a substantial prevalence of metabolic syndrome among HCV‐infected patients in the Pakistani population, further emphasizing the importance of routine metabolic assessment in these patients.
There is substantial clinical importance to the complex link between metabolic syndrome and chronic HCV infection. Although HCV has a role in the emergence of metabolic problems, liver disease progression is accelerated, and treatment results are complicated by pre‐existing metabolic diseases. Creating all‐encompassing treatment plans that target metabolic disorders as well as viral infections requires an understanding of this reciprocal interaction. Given the high incidence of both HCV and MS in Pakistan, the purpose of this study is to investigate how they interact in order to improve clinical care and the effectiveness of treatment for those who are impacted.
2. Methodology
2.1. Study Population and Design
This study employed a cross‐sectional observational design, conducted in the Department of Medicine, Lahore General Hospital, Lahore, from December 3, 2022, to June 2, 2023. We utilized non‐probability consecutive sampling to recruit 115 patients diagnosed with Hepatitis C virus (HCV) infection for a minimum duration of 6 months. Ethical approval was obtained from the Institutional Review Board (IRB) of Lahore General Hospital (Reference: MED‐2021‐069‐17400).
2.2. Inclusion and Exclusion Criteria
Patients aged 15–60 years, of any gender, diagnosed cases of HCV confirmed by polymerase chain reaction (PCR) and ELISA for at least 6 months were included in this study. Patients with known diabetes mellitus or with concurrent infections such as hepatitis B, human immunodeficiency virus (HIV), or autoimmune hepatitis were excluded from the study. Patients with a history of alcohol consumption, decompensated chronic liver disease, or hepatocellular carcinoma, or with a history of renal or cardiac disease were also excluded from the study.
2.3. Study Variables
The independent variable was the presence of HCV infection. The dependent variable was the diagnosis of metabolic syndrome. The definition of metabolic syndrome was based on the National Cholesterol Education Program Adult Treatment Panel III criteria, specifically adapted for Asian‐Americans. The criteria include the presence of three or more of the following components: (1) abdominal obesity (waist circumference > 90 cm in men and > 80 cm in women), (2), elevated triglycerides (≥ 150 mg/dL), (3), reduced HDL cholesterol (< 40 mg/dL in men and < 50 mg/dL in women), (4), elevated blood pressure (systolic ≥ 130 mmHg or diastolic ≥ 85 mmHg), and (5) elevated fasting glucose (≥ 100 mg/dL).
The National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) definition adapted for Asian‐Americans was chosen to define metabolic syndrome for three practical reasons. First, the ATP III framework is widely used in regional HCV/metabolic research and therefore facilitates direct comparison with prior Pakistani and neighboring‐region studies, improving the interpretability of prevalence estimates and enabling meta‐analytic pooling in future reviews. Second, the Asian‐American waist circumference and BMI adjustments better reflect the cardiometabolic risk profile seen in populations with lower mean BMI but higher central adiposity, which is comparable to South Asian phenotypes encountered in our setting. Third, ATP III is simple to apply in routine clinical practice (relying on commonly measured variables: waist circumference, blood pressure, fasting glucose, triglycerides, and HDL), increasing translational utility for hospital‐based screening. Nonetheless, we acknowledge that alternative definitions (e.g., IDF or South‐Asian‐specific cutoffs) use lower waist circumference thresholds and put greater emphasis on central obesity; therefore, prevalence estimates can vary by definition. For transparency, sensitivity analyses using IDF or South‐Asian criteria are recommended in future work to assess the robustness of estimates and to align findings with other studies that adopt those definitions.
2.4. Data Collection Tools
A self‐structured proforma was used for data collection. It included sections on sociodemographic characteristics, anthropometric measurements (height, weight, BMI, waist circumference), clinical history (duration of HCV infection), and laboratory investigations (LFTs, BSR, lipid profile). The diagnosis of metabolic syndrome was based on standardized criteria and was managed as per hospital protocol.
2.5. Data Collection Procedure
After obtaining informed consent, eligible participants were recruited from the Hepatitis Clinic at Lahore General Hospital. Data were collected through direct interviews and clinical examinations. Relevant laboratory tests were performed, and results were documented in the structured proforma. Confidentiality of patient data was ensured throughout the study.
2.6. Statistical Analysis
Statistical analyses were conducted using SPSS version 26.0. Descriptive statistics, including mean and standard deviation (SD), were calculated for continuous variables and frequencies with percentages for categorical variables.
A multivariable logistic regression analysis was performed to assess the independent association of age group, gender, and duration of HCV infection with the presence of metabolic syndrome. These variables were selected a priori based on their clinical relevance and availability within the study dataset. Model results were reported as adjusted odds ratios (aORs) with corresponding 95% confidence intervals (CIs).
No formal adjustment for multiple comparisons was performed because the analyses were exploratory in nature. Therefore, the possibility of type I error due to multiple testing cannot be completely excluded and should be considered when interpreting the findings.
3. Results
3.1. Demographics
Out of 115 participants enrolled in the study, 57 (49.6%) were males, and 58 (50.4%) were females, showing an almost equal gender distribution. The age‐wise distribution revealed that 19 participants (16.5%) were between 15 and 30 years, 46 (40.0%) were between 31 and 45 years, and 50 (43.5%) were between 46 and 60 years. Regarding the duration of hepatitis C virus (HCV) infection, 58 individuals (50.4%) reported having the infection for 1–5 years, while 57 (49.6%) had been affected for more than 5 years.
Metabolic syndrome was present in 36 participants (31.3%), while 79 (68.7%) did not meet the diagnostic criteria for it. The mean age of the study population was 41.05 ± 11.58 years. The mean height was 1.73 ± 0.037 meters, and the average weight was 75.61 ± 8.78 kg. The mean BMI was 25.29 ± 3.36, while the mean waist circumference was 81.97 ± 7.58 cm. Mean systolic blood pressure (SBP) was 136.04 ± 11.89 mmHg, and diastolic blood pressure (DBP) averaged 81.26 ± 4.84 mmHg (Table 1).
Table 1.
Baseline clinical and demographic characteristics of study participants.
| Variable | Total cohort (N = 115) |
|---|---|
| Age (years) | 41.05 ± 11.58 |
| Height (m) | 1.73 ± 0.04 |
| Weight (kg) | 75.61 ± 8.78 |
| Body mass index (kg/m2) | 25.29 ± 3.36 |
| Waist circumference (cm) | 81.97 ± 7.58 |
| Systolic BP (mmHg) | 136.04 ± 11.89 |
| Diastolic BP (mmHg) | 81.26 ± 4.84 |
| Fasting blood sugar (mg/dL) | 110.15 ± 17.70 |
| Triglycerides (mg/dL) | 150.24 ± 23.35 |
| Total cholesterol (mg/dL) | 180.63 ± 20.51 |
| HDL cholesterol (mg/dL) | 55.78 ± 12.14 |
| AST (IU/L) | 62.52 ± 8.76 |
| GGT (IU/L) | 118.98 ± 14.44 |
Note: Continuous variables are presented as mean ± standard deviation.
Abbreviations: AST, aspartate aminotransferase; BMI, body mass index; BP, blood pressure; GGT, gamma‐glutamyl transferase; HDL, high‐density lipoprotein.
Metabolic and biochemical parameters showed moderate variability. The mean fasting blood sugar (FBS) was 110.15 ± 17.70 mg/dL. Triglycerides (TGs) averaged 150.24 ± 23.35 mg/dL, while total cholesterol levels were 180.63 ± 20.51 mg/dL. HDL cholesterol had a mean value of 55.78 ± 12.14 mg/dL. Liver enzymes showed higher variability, with AST averaging 62.52 ± 8.76 IU/L and GGT averaging 118.98 ± 14.44 IU/L (Table 1).
3.2. Association of Metabolic Syndrome With Gender, Age, and HCV Duration
The prevalence of metabolic syndrome was slightly higher among males (33.3%) compared to females (29.3%). However, the χ 2 test revealed no statistically significant association between gender and metabolic syndrome (χ 2 = 0.216, p = 0.642). This finding was consistent with Fisher's Exact Test (p = 0.691) and other statistical measures such as the Likelihood Ratio and Linear‐by‐Linear Association. Effect size indicators, including Phi (0.043) and Cramer's V (0.043), also confirmed the absence of a meaningful relationship between gender and metabolic syndrome.
Age group analysis showed that metabolic syndrome was more common among participants aged 31–45 years (34.8%) and 46–60 years (32.0%) compared to those aged 15–30 years (21.1%). However, this trend was not statistically significant (χ 2 = 1.199, p = 0.549). Both the Likelihood Ratio (p = 0.531) and the Linear‐by‐Linear Association (p = 0.527) supported this result. The weak association was further indicated by Phi and Cramer's V values of 0.102.
When comparing the duration of HCV infection, 16 participants with 1–5 years of infection and 20 participants with more than 5 years had metabolic syndrome. The χ 2 test showed no significant relationship between HCV duration and metabolic syndrome (χ 2 = 0.752, df = 1, p = 0.386). Other tests, including the Continuity Correction (p = 0.505), Likelihood Ratio (p = 0.385), and Fisher's Exact Test (p = 0.426, two‐sided), also indicated no significant difference. Both Phi (−0.081) and Cramer's V (0.081) values supported the conclusion of a negligible association.
3.3. Multivariable Logistic Regression Analysis
A multivariable logistic regression model was used to assess the independent association of gender, age group, and duration of HCV infection with metabolic syndrome. The model's explanatory power was limited, as indicated by low Pseudo R 2 values (Cox and Snell = 0.018, Nagelkerke = 0.026, McFadden = 0.015).
The likelihood ratio tests demonstrated that none of the predictors—gender (aOR = 0.82, 95% CI: 0.36–1.88, p = 0.636), age 15–30 years (aOR = 1.74, 95% CI: 0.49–6.20, p = 0.396), and HCV duration 1–5 years (aOR = 1.39, 95% CI: 0.62–3.13, p = 0.429) were not independently associated with metabolic syndrome (Table 2). The intercept (β = 0.695, p = 0.152) was also non‐significant, suggesting that other unmeasured variables may be contributing factors.
Table 2.
Likelihood ratio tests for independent predictors in the logistic regression model.
| Effect | −2 Log likelihood of reduced model | χ 2 | df | p value |
|---|---|---|---|---|
| Gender | 37.97 | 0.22 | 1 | 0.636 |
| Age group | 38.91 | 1.17 | 2 | 0.558 |
| Duration of HCV | 38.37 | 0.63 | 1 | 0.428 |
Note: The χ 2 statistic represents the difference in −2 log‐likelihoods between the full final model and a reduced model omitting the specified effect.
Abbreviations: df, degrees of freedom; HCV, hepatitis C virus.
Overall, these results indicate that demographic factors (gender, age, duration of HCV) and measured clinical variables did not show statistically significant associations with the presence of metabolic syndrome in this study population.
4. Discussion
This study aimed to evaluate the frequency of metabolic syndrome in patients with hepatitis C virus (HCV) infection, a significant public health issue due to its association with both liver and metabolic disorders. Our findings highlight the prevalence of metabolic syndrome among HCV‐infected individuals and explore the demographic and clinical factors influencing its occurrence.
The study included 115 participants, with an almost equal gender distribution (49.6% males and 50.4% females). The age distribution indicated a higher prevalence of metabolic syndrome in older age groups, with 43.5% of participants aged 46–60 years, 40.0% aged 31–45 years, and 16.5% aged 15–30 years. The mean age of participants was 41.5 ± 11.58 years, suggesting that middle‐aged individuals are at higher risk of both HCV‐related liver disease and metabolic complications.
Metabolic syndrome was diagnosed in 31.3% of the participants, aligning with previous studies that report a higher prevalence of metabolic syndrome among HCV‐infected individuals compared to the general population. This underscores the importance of regular metabolic monitoring in HCV patients.
A significant age‐related increase in metabolic syndrome prevalence was observed. In the 15–30 years age group, only 21.1% had metabolic syndrome, while the prevalence increased to 32.0% in the 46–60 years group and further to 34.8% in the 31–45 years group. This trend suggests that chronic HCV infection and prolonged metabolic stress contribute to a higher likelihood of developing metabolic syndrome over time. Similar findings have been reported by Banks et al., who found the highest prevalence of metabolic syndrome and diabetes mellitus in HCV patients aged 60 years. Although metabolic syndrome was more prevalent in males (33.3%) compared to females (29.3%) in the present study, this difference was not statistically significant (p = 0.642). These findings are in contrast with Oliveira et al., who reported a higher prevalence of metabolic syndrome in females (55.6%) [9]. Işık et al. similarly reported a more pronounced gender disparity, with metabolic syndrome affecting 55.8% of females and only 17.3% of males based on ATP III criteria, and 65.4% of females compared to 30.8% of males according to IDF criteria [10]. Likewise, Banks et al. reported an overall metabolic syndrome prevalence of 35.0% among patients with chronic HCV and identified women as having a higher risk of metabolic syndrome compared with men [11]. Interestingly, the duration of HCV infection did not significantly impact the prevalence of metabolic syndrome. Participants with an HCV infection duration of 1–5 years had a prevalence of 49.6%, while those with a duration of more than 5 years had a prevalence of 50.4%. This suggests that the presence of HCV itself, rather than its duration, may be a more critical factor in the development of metabolic syndrome. These findings contrast with those of Qasim et al., who reported that 61.9% of patients with more than 3 years of HCV infection had metabolic syndrome [8]. Similarly, Bashir, Ashraf, and Anwar found higher metabolic syndrome rates in patients with longer infection durations [12].
The mean body mass index (BMI) was 25.29 ± 3.36 kg/m2, indicating that most participants were overweight but not obese. The mean waist circumference was 81.97 ± 7.58 cm, a key indicator of metabolic risk. Elevated waist circumference was a common finding in previous studies, including those by Oliveira et al. and Sabet et al., further confirming its association with metabolic syndrome [9, 13].
Blood pressure levels were elevated in this cohort, with mean systolic blood pressure (SBP) at 136.04 ± 11.89 mmHg and diastolic blood pressure (DBP) at 81.26 ± 4.84 mmHg. Hypertension is a critical component of metabolic syndrome, and our findings reinforce previous research by Qasim et al. and Huang et al., which emphasize the need for routine blood pressure monitoring in HCV‐infected individuals [8, 14].
Fasting blood sugar (FBS) levels averaged 110.15 ± 17.70 mg/dL, indicating impaired glucose tolerance and an increased risk of diabetes. Dyslipidemia was evident, with mean triglyceride (TG) levels at 150.24 ± 23.35 mg/dL and total cholesterol levels at 180.63 ± 20.5 mg/dL. Although the mean high‐density lipoprotein (HDL) level remained within normal limits (55.78 ± 12.14 mg/dL), the combination of elevated TG and borderline total cholesterol suggests a mixed dyslipidemia profile. Elevated fasting glucose and dyslipidemia have also been reported by Oliveira et al. and Hanouneh et al., further supporting their prevalence in HCV‐infected patients [9, 15].
Elevated liver enzymes were observed, with mean aspartate aminotransferase (AST) at 62.52 ± 8.76 U/L and gamma‐glutamyl transferase (GGT) at 118.98 ± 14.44 U/L. These findings indicate ongoing hepatic inflammation, a hallmark of chronic HCV infection, which contributes to metabolic disturbances. Oliveira et al. also identified elevated GGT levels as a significant predictor of metabolic syndrome.
The development of the two‐generation DAA in 2011 was a significant breakthrough in the management of hepatitis C [16]. The first generation DAAs targeted viral replication by inhibiting NS3/4A protease, an enzyme crucial for replication [17]. Protease inhibitors such as telaprevir improved SVR rates to 67%–79% in treatment‐naive genotype 1 patients, compared with approximately 40% with PEG‐IFN and ribavirin alone [18, 19]. Further understanding of the HCV life cycle led to the development of second‐ and third‐generation DAAs targeting NS5A and NS5B proteins, including sofosbuvir and dasabuvir [17].
The development of pan‐genotypic regimens further improved treatment efficacy, with combination therapies achieving SVR rates exceeding 95%, shorter treatment durations of approximately 8–12 weeks, and fewer adverse effects [20, 21, 22, 23, 24].
Recent advances in hepatitis C management, particularly the widespread use of direct‐acting antivirals (DAAs), have important implications for the metabolic health of patients with HCV. Achieving Sustained Virologic Response (SVR) reduces hepatic inflammation and the metabolic effects of active HCV infection. Several studies have reported improvements in insulin resistance, glycemic control, and inflammatory markers following viral eradication, likely due to reduced inflammatory signaling and improved hepatic and peripheral insulin sensitivity. However, metabolic changes after SVR are not uniformly beneficial. In particular, increases in total and LDL‐cholesterol have been reported, possibly due to the resolution of HCV‐associated hypolipidemia. HCV proteins, including core and NS5A, can also interfere with insulin signaling and lipid metabolism, contributing to hepatic steatosis and insulin resistance. Therefore, although DAA‐induced viral clearance may improve glycemic control and inflammation, lipid profiles and other metabolic risk factors should continue to be monitored after treatment. These findings highlight the importance of assessing metabolic abnormalities in HCV patients, particularly those at risk of metabolic syndrome, to support appropriate long‐term management [25, 26, 27].
From a public‐health and clinical perspective, these dynamics have three practical consequences relevant to our findings. First, cross‐sectional prevalence of metabolic syndrome among HCV patients will increasingly reflect a heterogeneous mix of treatment‐naive, currently treated, and cured individuals; studies should therefore report DAA exposure and SVR status. Second, clinicians must monitor metabolic parameters both before and after antiviral therapy, expecting possible improvements in glucose metabolism but also potential rises in LDL cholesterol that may require lipid management. Third, while viral eradication mitigates many HCV‐linked metabolic disturbances, residual risk remains, particularly among individuals with established central adiposity or long‐standing insulin resistance, so lifestyle modification and standard cardiometabolic risk management remain essential adjuncts to antiviral care.
Taken together, these findings propose that metabolic disturbances in HCV infection are caused by a complex interplay of viral factors, host inflammatory responses, insulin resistance, hepatic steatosis, and treatment‐related metabolic changes following DAA therapy. This complexity may partially explain why age, gender, and duration of infection were not significantly associated with metabolic syndrome in our study. Subsequently, factors beyond those included in our multivariable model may contribute substantially to the development of metabolic syndrome among patients with HCV.
This study provides valuable insights into the prevalence of metabolic syndrome among HCV‐infected individuals, emphasizing the need for comprehensive metabolic assessment in this population. Strengths of the study include a well‐defined cohort with a balanced gender distribution and detailed biochemical profiling, enhancing the robustness of the analysis. Nonetheless, the findings should be interpreted in light of certain limitations, including the cross‐sectional design, relatively small sample size, and the inability to account for several potentially important confounding factors such as BMI, comorbidities, lifestyle characteristics, and treatment status.
5. Limitations
Several limitations must be acknowledged. The cross‐sectional design precludes establishing causal relationships between HCV infection and metabolic syndrome. Additionally, the sample size, although adequate, may limit generalizability to broader populations. Furthermore, the use of non‐probability consecutive sampling from a single tertiary‐care center may have introduced selection bias and may limit the generalizability of the results. The reliance on self‐reported duration of HCV infection may introduce recall bias. Future research should focus on longitudinal studies to explore causal relationships and the long‐term impact of HCV treatment on metabolic syndrome. The multivariable logistic regression model was restricted to age, gender, and duration of HCV infection and did not account for other clinically relevant confounders, including BMI, comorbid medical conditions, lifestyle factors, and HCV treatment status. Therefore, residual confounding may have influenced the observed associations.
A further limitation of this study is the use of the ATP III criteria alone for the diagnosis of metabolic syndrome. As prevalence estimates may vary according to the diagnostic definition used, the findings should be interpreted with caution when compared with studies employing IDF or South Asian‐specific criteria. Sensitivity analyses using alternative definitions were not performed and warrant evaluation in future research.
6. Conclusions
In conclusion, this study found a high prevalence of metabolic syndrome among HCV‐infected patients, particularly in older age groups. However, no statistically significant association was observed between metabolic syndrome and age, gender, or duration of HCV infection. Given the cross‐sectional design and absence of a non‐HCV comparison group, these findings describe the prevalence of metabolic syndrome within the studied HCV population and do not establish an association between HCV infection and metabolic syndrome. The findings highlight the importance of comprehensive metabolic monitoring, risk assessment, and appropriate management in patients with HCV. Further multicenter studies, prospective studies with appropriate comparison groups, are recommended to clarify the relationship between HCV infection and metabolic syndrome.
Author Contributions
Muhammad Awais: conceptualization, data curation, project administration, supervision, validation, visualization, writing – original draft, writing – review and editing. Maryam Ilyas: project administration, supervision, validation, visualization, writing – original draft, writing – review and editing. Muhammad Husnain Ahmad: writing – original draft, writing – review and editing, visualization. Muhammad Taha Shaukat: validation, visualization, writing – original draft, writing – review and editing. Abdul Waheed: validation, visualization, writing – original draft, writing – review and editing. Aniqa Iqbal: validation, visualization, writing – original draft, writing – review and editing. Muhammad Umar Nadeem: validation, visualization, writing – original draft, writing – review and editing. Nimra Mahmood: validation, visualization, writing – original draft, writing – review and editing. Ali Gohar: project administration, supervision, validation, visualization, writing – original draft, writing – review and editing. Hamza Zaheer: validation, visualization, writing – original draft, writing – review and editing. Ahmed Zia: writing – original draft, writing – review and editing, visualization, validation. Masab Ali: writing – original draft, writing – review and editing, visualization, validation.
Funding
The authors have nothing to report.
Ethics Statement
Ethical approval for this study was obtained from the Institutional Review Board (IRB) of Lahore General Hospital.
Consent
Informed consent was obtained from all participants prior to data collection. The purpose of the study, as well as the voluntary nature of participation, was explained, and all participants had the opportunity to ask questions regarding the study.
Conflicts of Interest
The authors declare no conflicts of interest.
Transparency Statement
The corresponding author affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.
Acknowledgments
We would like to thank all the participants at Lahore General Hospital for their participation in this study. Special thanks to the Institutional Review Board for ethical approval and the research team for their dedication and efforts in completing this study.
Data Availability Statement
The data and materials used in this study are available upon request from the corresponding author. Requests will be considered based on the study's ethical guidelines and data sharing protocols.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data and materials used in this study are available upon request from the corresponding author. Requests will be considered based on the study's ethical guidelines and data sharing protocols.