Introduction

Globally, hepatitis B virus (HBV) remains a major public health threat, with an estimated 296 million people living with chronic infection and causing approximately 1.1 million annual deaths, primarily from cirrhosis and hepatocellular carcinoma1. In addition, HBV remains a significant public health challenge in Sub-Saharan Africa despite ongoing vaccination efforts, with the World Health Organization reporting high endemicity and substantial adult infection rates that lead to chronic complications such as cirrhosis and hepatocellular carcinoma2,3. Ethiopia, in particular, is a country of intermediate to high endemicity, with an estimated 5–7% of the general population4. Even among vaccinated individuals, breakthrough infections and inadequate immune responses are common across the region. Within this broader context, Ethiopia faces particular challenges where intermediate to high endemicity persists despite increasing vaccine coverage5. On the other hand, there is no nationwide routine vaccination program for adolescents or adults. Vaccination in these groups is largely limited to high-risk populations (e.g., healthcare workers) through specific occupational health programs, with coverage data being sparse and variable6.

Notably, over 22% of vaccinated Ethiopian adults fail to achieve protective antibody levels, a situation that may be influenced by host immunometabolic factors7. Factors such as underlying chronic inflammation, metabolic syndrome, nutritional status, and genetic predispositions may impair the humoral immune response to the vaccine antigen, leaving a substantial subset of the vaccinated population susceptible to infection8,9. Furthermore, the persistence of HBV infection post-vaccination underscores a critical public health concern, indicating possible gaps in vaccine effectiveness and sustained immune protection over time in this population10.

Lipid profiles such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride levels, and their ratios, along with inflammatory markers like C-reactive protein (CRP), have been implicated in modulating immune function10,11. Dysregulated lipid metabolism and chronic inflammation may impair vaccine responsiveness by altering immunological mechanisms essential for seroprotection12. Yet, in Ethiopia, there is limited understanding of how these immunometabolic factors influence the effectiveness of hepatitis B vaccination in adults13.

Research gaps exist particularly in the microbiological and immunological insights into the interplay between lipid profiles, inflammatory markers, and vaccine-induced immunity following HBV vaccination14. Most existing studies focus on seroprotection rates without exploring the underlying immunometabolic modulators that could inform tailored immunotherapeutic or nutritional interventions. Addressing these gaps could facilitate the development of immunometabolic interventions tailored to the Ethiopian population, ultimately improving vaccine outcomes, reducing HBV infection rates, and achieving better disease control. Therefore, this study aims to elucidate the seroprotection rate and examine how lipid profiles and inflammatory markers modulate immune responses following hepatitis B vaccination.

Materials and methods

Study design, setting, and period

A cross-sectional institutional-based study was carried out among healthcare providers vaccinated against hepatitis B virus across all hospitals in the northwestern region of Ethiopia, from May 22, 2024, to January 15, 2025.

Population

Fully vaccinated healthcare providers working in hospitals located in the northwestern region of Ethiopia were considered the source population. The study population, conversely, consisted of adult participants (aged 18 years or older) who were available during the data collection period, met the inclusion criteria, and providing informed consent to participate in the study.

Eligibility criteria

Healthcare providers currently working in hospitals within the northwestern region of Ethiopia and aged 18 years or older were included in the study. Additionally, participants needed to provide written informed consent and be employed during the data collection period from May to January 2025. Conversely, healthcare providers who declined to give informed consent, or were on leave or absent during the data collection timeframe were excluded. Furthermore, immunocompromised individuals or those receiving immunosuppressive therapy, individuals presenting with an acute illness like human immunodeficiency virus (HIV) and tuberculosis (TB) at the time of study enrollment, and those with severe metabolic or chronic diseases, namely diabetes, hypertension, cancer, cardiac disease, and renal disease that could confound immune or lipid responses were excluded from the study.

Operational definition

Adult

Defined as a person who has attained the age of 18 years.

Healthcare providers

Individuals who are authorized to deliver medical, diagnostic, treatment, or wellness services to patients.

Fully vaccinated

Refers to individuals who have completed the three doses of hepatitis B vaccine.

Non-seroprotected

Individuals whose anti-HBs levels are below the threshold (< 10 mIU/ml) at the time of study sampling.

Seroprotected

Refers to individuals who have developed protective levels of antibodies (≥ 10 mIU/ml) against hepatitis B virus.

A healthy diet

Is a self-reported dietary pattern meeting at least four of five criteria related to high fruit/vegetable and whole grain intake, lean/plant-based protein, limited processed foods, and use of healthy fats.

Physical activity

Is self-reported engagement in any form of exercise, without specified frequency, duration, or intensity.

Determination of sample size and sampling methods

The sample size for this study was calculated using the single population proportion formula, assuming an estimated proportion of 50%. In the formula, n represents the sample size, p is the estimated proportion, q = 1-p, Z is the Z-score corresponding to the desired confidence level, and d is the margin of error. For this study, the proportion was set at p = 0.5 with q = 0.5, a 95% confidence level was used (where Z = 1.96), and d = 0.05. The calculation was performed as follows:

To accommodate for potential non-response, an additional 10% (38 participants) was added, resulting in a final sample size of 422 participants. The total sample size was then proportionally allocated to each hospital in the northwestern region of Ethiopia, and participants were selected through a simple random sampling technique.

Study variables

The primary dependent variable for this study was seroprotection status, a binary outcome defined as having anti-HBs antibody levels ≥ 10 mIU/mL (seroprotected) or < 10 mIU/mL (non-seroprotected). The independent variables were categorized into two main groups. The primary exposures of interest were immunometabolic and inflammatory markers, which included lipid profiles, specifically high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total Cholesterol (TC), and triglycerides (TG), along with their calculated ratios (TG/HDL, LDL/HDL, TC/HDL), and inflammatory markers, namely C-reactive protein (CRP) and the systemic immune-inflammatory index (SII).

A secondary set of independent variables comprised sociodemographic and clinical factors, treated as potential confounders. Sociodemographic variables included age, gender, marital status, household size, housing tenure, residence (rural/urban), monthly income, education level, employment status, working time, and shift pattern. Monthly income was categorized based on Ethiopian Birr (ETB) using current salary benchmarks for healthcare workers in Ethiopia, with the following categories: low income (< 10,000 ETB per month), middle income (10,000–15,000 ETB per month), and high income (> 15,000 ETB per month).

Clinical and behavioral variables consisted of body mass index (BMI) status, diet (categorized as healthy or unhealthy based on the study’s operational definition), and physical activity. The study aimed to determine how these independent variables were associated with the likelihood of achieving seroprotection. The analysis specifically identified high LDL and elevated SII as significant independent predictors of reduced seroprotection.

$$n = \frac{{{{\left( {\frac{{Za}}{2}} \right)}^2}pq}}{{{d^2}}}$$
$$n = {\text{ }}{(1.96)^2}*0.5*0.5\;\; = 384$$
$${\left( {0.05} \right)^2}$$

Data collection

Socio-demographic and clinical data were gathered using a structured questionnaire. Vaccination status of healthcare providers was verified through documented evidence of complete hepatitis B vaccination. Participants’ weight and height were measured, and BMI was subsequently calculated. Additionally, fasting venous blood samples, ranging from 7 to 9 milliliters, were obtained from each participant. All collected blood samples from hospitals across the northwestern region of Ethiopia were carefully transported in cold boxes equipped with ice packs to the Debre Markos Blood Bank Laboratory to ensure optimal preservation during transit. Serum was then separated from the blood samples by centrifugation and stored at -80 °C until further laboratory analysis.

To ensure quality control during data collection and laboratory testing, socio-demographic and clinical information was systematically gathered using a structured questionnaire, with vaccination status verified through documented evidence. Anthropometric measurements were precisely taken to calculate BMI. Venous blood samples (7–9 ml) were carefully collected, transported in temperature-controlled cold boxes with ice packs to maintain integrity, and processed promptly by centrifugation to separate serum, which was stored at -80 °C until analysis.

Definition, cut-off values, and laboratory tests of key parameters

Antibody levels (anti-HBs titers) for assessing seroprotection were measured for all study participants within the same standardized post-vaccination interval, which was [1–3 months] after the administration of the final vaccine dose. For the detection and quantification of anti-HBs, enzyme-linked immunosorbent assay (ELISA) (Monolisa™ Anti-HBs PLUS) was utilized. Absorbance measurements were taken spectrophotometrically at wavelengths of 450/620–700 nm. In addition, HDL-C, TG, LDL-C, and TC levels were analyzed using enzymatic colorimetric methods with automated Roche Cobas C111 clinical chemistry analyzers (Roche Diagnostics, Basel, Switzerland). Ratios including TG/HDL, LDL/HDL, and TC/HDL were calculated from these measured values.

In addition, participants were categorized according to clinically established thresholds. For Total TC, levels < 200 mg/dL were considered optimal, 200–239 mg/dL borderline, and ≥ 240 mg/dL elevated. For LDL-C, < 100 mg/dL was optimal, 100–159 mg/dL borderline, and ≥ 160 mg/dL elevated. For HDL-C, ≥ 60 mg/dL was optimal, 40–59 mg/dL intermediate, and < 40 mg/dL low. For TG, < 150 mg/dL was optimal, 150–199 mg/dL borderline, and ≥ 200 mg/dL elevated. For primary analyses, dyslipidemia was defined as meeting at least one of the following high-risk criteria: TC ≥ 240 mg/dL, LDL-C ≥ 160 mg/dL, HDL-C < 40 mg/dL, or TG ≥ 200 mg/dL.

Furthermore, CRP is a circulating biomarker of systemic inflammation. It was measured from serum samples using a high-sensitivity assay. CRP levels were determined quantitatively using a latex agglutination turbidimetric immunoassay, which involves the agglutination of latex particles coated with anti-CRP antibodies and measuring the turbidity spectrophotometrically, with results expressed in mg/L or mg/dL. For cardiovascular risk stratification, participants were classified into three tiers: low risk (< 1.0 mg/L), average risk (1.0–3.0 mg/L), and high risk (> 3.0 mg/L). For statistical modeling, elevated inflammation was defined as hs-CRP > 3.0 mg/L.

Moreover, the SII is an integrated inflammatory biomarker reflecting the balance between immune and inflammatory pathways. It was calculated using absolute cell counts from a standard complete blood count (CBC) data by the formula: neutrophil count multiplied by platelet count divided by lymphocyte count (SII=Lymphocyte count × Platelet count ∕ Neutrophil count). All assays were conducted following standard protocols, and samples were handled under appropriate storage and transport conditions to ensure accuracy. Currently, there is no universal, guideline-established clinical cut-off for SII, as it is primarily a research biomarker. Therefore, for this study, we adopted a data-driven and literature-supported approach.

To ensure quality control during laboratory analysis, laboratory assays, including ELISA for anti-HBs detection, enzymatic colorimetric methods for lipid profiling, and latex agglutination turbidimetric immunoassay for CRP quantification, were performed in strict accordance with standardized protocols using calibrated automated analyzers. Spectrophotometric measurements were taken at specified wavelengths to ensure consistency. Standards, or control materials, with known concentrations were run on the analyzer to verify that results fell within predefined limits that indicated acceptable accuracy and precision. Moreover, blank samples (which contained no analyte) were used as low activity or zero controls to identify any contamination or instrument errors in pipetting reagents or samples. The analyzer monitored the absorbance signal from blank measurements and checked for values above set thresholds indicating problems.

Moreover, the SII was accurately calculated from CBC parameters using a validated formula. All procedures adhered to rigorous handling, storage, and transport guidelines to maintain sample integrity and optimize result reliability throughout the study.

Data analysis

Data were initially entered into EpiData version 4.6 and then exported to SPSS version 26 for further analysis. Findings were displayed in text and table form. The crude prevalence ratio (CPR) was computed. Bivariate analysis involved assessing the association between each candidate independent variables and the outcome using the chi-square test, alongside calculation of risk estimates and 95% confidence intervals. Variables with a p-value less than 0.25 were selected for inclusion in the multivariable model. For the multivariable analysis, generalized linear models with a Poisson distribution, log link function, and robust standard errors were applied, with results presented as prevalence ratios and 95% confidence intervals. Statistical significance was set at a p-value below 0.05.

Ethical issues

The study received formal approval from the Institutional Research Ethics Review Committee (IRERC) of College of Health Sciences, Debre Markos University, in strict adherence to the principles outlined in the Declaration of Helsinki, with approval code [R/C/S/D/317/09/2024]. Furthermore, written informed consent was meticulously secured from each participant prior to their involvement in the study.

Results

Socio-demographic characteristics

The study consisted predominantly of individuals aged 36–55 years, representing 48.3% of the participants. Moreover, males made up 60.4% of the participants. Most participants were married (71.1%) and lived in households of 2–3 people (60.0%). A large majority rented their homes (82.9%) and resided in urban areas (64.2%). In addition, 64.9% reported a middle monthly income, 87.0% had a bachelor’s degree, and 90.3% were permanently employed, with most working full-time (95.7%) during day shifts (98.1%) (Table 1).

Table 1 Socio-demographic characteristics of the study participants.
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Cross-tabulation of immunoprotection by socio-demographic factors

Of all study participants, 73.7% (n = 311/422; 95% CI: 69.0–78.0%) were seroprotected (had anti-HBs ≥ 10 mIU/mL). Immunoprotection status varied across age groups, with the 36–55 years category having the highest proportions of both seroprotected (47.9%) and non-seroprotected individuals (49.5%). Furthermore, males showed higher rates of seroprotection (63.0%) than females. Participants with a bachelor’s degree exhibited a greater percentage of seroprotection (88.1%) (Table 2).

Table 2 Immunoprotection status of study participants with their socio-demographic Characteristics.
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Immunoprotection status by lipid profiles, inflammatory markers, and clinical variables

Participants with a normal BMI demonstrated a high rate of seroprotection (83.3%). Similarly, individuals with normal HDL levels showed seroprotection in 83.0% of cases. Additionally, inflammatory markers such as CRP and the systemic immune-inflammation index (SII) indicated that participants with normal levels exhibited seroprotection rates of 82.0% and 83.6%, respectively. Moreover, participants following a healthy diet also had a high proportion of seroprotection (80.7%) (Table 3).

Table 3 Immunoprotection Status of Study Participants with Their Respective Lipid Profiles, Inflammatory Markers, and Clinical Variables.
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Risk factors analysis

Participants with low high density HDL levels were twice as likely to be non-seroprotected compared to those with normal HDL (CPR = 2.0; 95% CI: 1.2–3.3; p = 0.008), although the APR was not statistically significant (p = 0.857). Elevated LDL/HDL ratio, high TC, and high TG were all significantly associated with increased prevalence of non-.

seroprotection based on crude prevalence ratios, but none showed significant association after adjustment. In addition, high CRP was linked to a 2.7 times higher likelihood of non-seroprotection (CPR = 2.7; 95% CI: 1.6–4.3; p = 0.001), though this effect was not significant after controlling for confounders.

On the other hand, High LDL was strongly associated with a higher likelihood of non-seroprotection (immunresponse reduction) (CPR = 2.6; 95% CI: 1.6–4.1; p = 0.001), and this association remained significant after adjustment (APR = 0.67; 95% CI: 0.46 to 0.97; p = 0.032). Similarly, the SII showed the strongest association, with a threefold higher risk of non-seroprotection in participants with high SII levels (CPR = 3.1; 95% CI: 1.9–5.1; p = 0.001), and this remained significant even after adjustment (APR = 0.61; 95% CI: 0.40 to 0.93; p = 0.021) (Table 4).

Table 4 Crude and adjusted prevalence ratio analysis of risk factors for immunoprotection status.
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Discussion

This study provides valuable insights into the immunometabolic factors associated with hepatitis B vaccine-induced seroprotection among healthcare workers in northwestern Ethiopia15. The findings highlight the complex interplay between lipid metabolism, inflammation, and immune responsiveness, factors that contribute significantly to vaccine efficacy in endemic settings13,16. Understanding these relationships is critical given the persistent burden of HBV infection despite expanding vaccination coverage in the region17.

In this study, the overall seroprotection rate among participants who completed the hepatitis B vaccination series was 73.7% (95% CI: 69.0–78.0%). On the other hand, lower results were reported from China (45.2–46.5%)18,19. This may be due to this study focused on healthcare workers who were likely younger, healthier adults with fewer comorbidities compared to broader population groups in China, where differences in age distribution, nutritional status, and general health could influence immune responses and seroprotection rates after vaccination20,21. Moreover, variations in vaccine type and administration, including differences in vaccine formulations (such as recombinant versus plasma-derived vaccines) and immunization schedules, may also contribute to efficacy differences22,23.

Additionally, immunometabolic and genetic factors play a role; the Ethiopian study highlights the influence of lipid profiles and systemic immune-inflammation on vaccine response24, while the Chinese populations may have had higher rates of metabolic diseases or differing immunogenetic backgrounds leading to lower seroprotection9. Methodological differences such as the timing of antibody level assessment, the sensitivity of seroprotection assays, and thresholds used to define protection can further impact observed rates, as natural waning of antibodies over time without boosters may result in lower seroprotection depending on when measurements were taken25,26. Furthermore, differences in health system and vaccine program quality, including cold chain management, vaccine storage conditions, and healthcare infrastructure, can influence vaccine potency and efficacy, with varying health system capacities between the two settings contributing to differences in immune response outcomes27,28.

The analysis also revealed sociodemographic differences in seroprotection rates. Adults aged 36–55 years showed the highest seroprotection (47.9%), possibly reflecting optimal immune responsiveness in this middle-age range compared to younger or older adults29. This is consistent with immunosenescence patterns observed worldwide, where older age correlates with diminished vaccine efficacy30. In addition, this may be due to middle-aged adults typically have a fully matured and functional immune system that responds efficiently to vaccines31, whereas younger children and adolescents may still be developing their immune responses, and immune function often declines with age in older adults (immunosenescence), leading to weaker vaccine responses32. Studies indicate that older adults, especially those aged 56 and above, exhibit decreased seroprotection rates and antibody responses to the hepatitis B vaccine due to the natural aging of the immune system reducing its ability to generate adequate protective antibodies33,34. On the other hand, middle-aged adults generally achieve optimal immune response with standard vaccine doses, while younger and older groups may require adjusted dosages; for instance, adults aged 25 and older may benefit from higher antigen doses to maintain robust seroconversion rates35.

In addition, male participants exhibited higher seroprotection rates (63.0%) than females, a finding that may result from sex-based immunological differences, hormonal influences, or lifestyle factors impacting immune function36. While some studies generally show females tend to mount stronger antibody responses to vaccines due to factors like estrogen stimulating immune cell activity, there is evidence that male sex hormones such as testosterone can modulate immune responses differently37. In certain contexts, males may show higher seroprotection rates possibly due to variations in immune regulation influenced by sex hormones and genetic differences related to immune genes on sex chromosomes38. Additionally, lifestyle factors and body composition differences may impact vaccine absorption and efficacy differently between males and females39.

From a clinical perspective, there was a high seroprotection rate among individuals with a normal BMI (83.3%) and those with a healthy diet (80.7%), although these factors did not show a statistically significant association. This is because of a normal BMI is often associated with better immune function and vaccine responsiveness, as excess body fat or obesity has been linked to diminished antibody responses to hepatitis B vaccine40,41. In other words, obesity is associated with a reduced antibody response due to factors such as systemic inflammation, impaired T cell function, and altered B cell activity, all of which can blunt the body’s ability to produce protective antibodies after vaccination42. In contrast, individuals with a normal BMI typically have more robust immune responses, allowing for higher antibody titers and better vaccine effectiveness43. This enhanced immune responsiveness in those with normal BMI leads to a higher seroprotection rate following hepatitis B vaccination compared to their overweight or obese counterparts41.

Additionally, a healthy diet provides essential nutrients that support the immune system, such as vitamins, minerals, and antioxidants, which can enhance the body’s ability to produce effective protective antibodies after vaccination44. Furthermore, nutrients such as vitamins (e.g., vitamin E, vitamin D), minerals (e.g., selenium, zinc), antioxidants, and certain phytochemicals have antiviral and hepatoprotective effects that support the body’s immune response against hepatitis B virus45. These nutrients can boost the production and activity of immune cells and antibodies, reduce inflammation, and inhibit viral replication, thereby improving vaccine-induced immunity32. Moreover, a healthy diet sustains liver health, which is crucial for effective immune function since hepatitis B primarily affects the liver. This nutritional support results in higher antibody levels and a stronger seroprotection rate following vaccination46.

Furthermore, participants with favorable lipid level, particularly normal HDL (83.0%), showed increased rates of seroprotection, while participants with dyslipidemia had higher proportions of non-seroprotection18. Notably, low HDL levels were associated with doubled crude risk of non-seroprotection but lost significance after adjustment, suggesting confounding by other variables. These findings are consistent with established immunological evidence indicating that lipid metabolism profoundly influences immune cell function. HDL cholesterol is known for its anti-inflammatory properties and role in modulating adaptive immunity13.

The study also assessed lipid ratios like LDL/HDL, TG/HDL, and TC/HDL. Elevated LDL/HDL ratio and other lipid abnormalities showed crude associations with non-seroprotection but lost significance after adjustment, indicating that LDL cholesterol level itself might be the primary immunometabolic driver influencing vaccine responsiveness (APR = 0.67; 95% CI: 0.46 to 0.97; p = 0.032) rather than broader lipid abnormalities. This is due to Elevated LDL is pro-inflammatory and can induce dysfunctional immune responses47. LDL’s contribution to immune dysregulation may occur via its role in promoting oxidative stress, activating inflammasomes, and impairing dendritic cell function, key processes that undermine vaccine-induced antibody production. Studies indicate that elevated LDL, often associated with dyslipidemia and metabolic disturbances, correlates with a decreased likelihood of achieving seroprotection after vaccination18,48. This is partly because high LDL levels contribute to systemic inflammation and oxidative stress, which can disrupt immune cell function and reduce the efficacy of the vaccine-induced immune response49.

A second key observation is the significant role of inflammation in modulating vaccine response. Elevated CRP, a widely used marker of systemic inflammation, was initially linked with a 2.7-fold increased risk of non-seroprotection in crude analysis. However, this association attenuated after adjusting for confounders, suggesting that CRP alone may inadequately capture the complexity of immune-inflammatory states relevant to vaccine efficacy50.

In contrast, the SII, a composite marker incorporating neutrophil, platelet, and lymphocyte counts, displayed the strongest and most robust association with immunoseroprotection status. Participants with high SII had more than three times the risk of non-seroprotection, and this relationship remained statistically significant after adjustment (APR = 0.61; 95% CI: 0.40 to 0.93; p = 0.021). SII is increasingly recognized as a sensitive indicator of chronic immune activation and immune dysregulation, capturing nuanced inflammatory dynamics that single markers like CRP fail to reflect51. The immunological basis for this may lie in the effect of chronic inflammation on adaptive immune compartment functionality51. The findings have important implications for public health strategies aiming to optimize hepatitis B vaccination outcomes in Ethiopia and similar settings. Given the robust associations between elevated LDL cholesterol, SII, and non-seroprotection, integrating assessments of immunometabolic status into vaccination programs could facilitate early identification of individuals at risk of inadequate vaccine response. More importantly, these insights open avenues for novel immunometabolic interventions alongside traditional vaccination strategies. Lifestyle modifications targeting lipid reduction and inflammation control, such as dietary counseling, physical activity promotion, and pharmacological lipid-lowering agents, may synergistically enhance vaccine-induced immunity. Furthermore, adjunctive therapies targeting systemic inflammation may hold promise for improving immune memory and antibody titers in vulnerable populations.

Tailoring booster dose schedules or employing higher vaccine doses for individuals with unfavorable immunometabolic profiles could also be explored as practical approaches to mitigate breakthrough infections. These personalized vaccination strategies align with the emerging field of precision vaccinology, which advocates for considering host factors like metabolic and inflammatory status to maximize vaccine effectiveness.

Strengths and limitations of the current study

This study benefits from a well-designed cross-sectional approach among a fully vaccinated, well-characterized group of healthcare providers representative of the local population. The comprehensive assessment of lipid class profiles, inflammatory markers, and precise immune seroprotection measurements contribute to the robustness and relevance of the findings.

However, the study’s cross-sectional nature limits causal inference; temporal relationships between dyslipidemia, inflammation, and vaccine response cannot be definitively established. Longitudinal cohort studies or interventional trials are warranted to confirm causality and evaluate the efficacy of immunometabolic modifications on vaccine outcomes. Moreover, exclusion of immunocompromised individuals and those with severe metabolic disease limits generalizability to populations with such conditions, who may be at even greater risk of poor vaccine response.

Potential residual confounding by unmeasured variables such as genetic factors, co-infections, or environmental exposures could influence the observed associations. In addition, data on the time elapsed since vaccination was not detailed, which may affect antibody levels due to natural waning over time. Moreover, our analysis was limited by the lack of data on the timing of the last hepatitis B vaccine dose. As anti-HBs titers are known to wane over time, the absence of this variable represents a potential unmeasured confounder. Individuals with more recent vaccination would be more likely to exhibit seroprotection, independent of other factors like diet or inflammation studied here. This limitation means that the associations we observed should be interpreted as the relationship between modifiable risk factors (e.g., diet, SII) and current seroprotection status within a population with heterogeneous vaccination histories.

Conclusions and recommendations

This study highlights the significant influence of lipid metabolism and systemic immune-inflammatory status on hepatitis B vaccine-induced seroprotection among Ethiopian healthcare providers. High LDL cholesterol and SII were independently associated with increased risk of vaccine non-seroprotection (immune reduction). These findings emphasize the need for integrating immunometabolic assessments into public health vaccination programs and suggest promising avenues for adjunctive interventions to optimize vaccine effectiveness. Addressing these metabolic and inflammatory determinants could contribute to improved control of HBV infection and progress toward elimination goals in high-burden settings.