The impact of obesity on the prognosis of COVID-19 patients: two pandemics at once

Authors

Abstract

AimThis study aimed to evaluate the impact of obesity on clinical outcomes and mortality in adults hospitalized with COVID-19 and to identify laboratory parameters with prognostic value in obese and non-obese patients.
MethodsA total of 258 patients hospitalized with confirmed COVID-19 between June 2020 and December 2021 were retrospectively analyzed. Patients were classified as obese (n = 125) and non-obese (n = 133). Demographic characteristics, laboratory findings, length of hospital stay, and mortality were compared.
ResultsThe mean age was 65 ± 15 years, and 125 (45%) patients were obese. The obese group (63.0 ± 15.7 years) was significantly younger than the non-obese group (68.1 ± 14.2 years; p = 0.007). Leukocyte, lymphocyte, c-reactive protein (CRP), lactate dehydrogenase (LDH), D-dimer, and ferritin levels were similar between groups. Length of hospital stay did not differ significantly. However, mortality was higher in obese patients (p = 0.013), and ICU admission was more frequent (36 vs. 16 cases; p = 0.007). Receiver operating characteristic (ROC) analysis showed that in obese patients, procalcitonin (area under the curve [AUC] = 0.862; p < 0.001) and D-dimer (AUC = 0.825; p = 0.001) had the strongest predictive value for mortality, followed by LDH (AUC = 0.739; p = 0.012) and ferritin (AUC = 0.716; p = 0.024). In non-obese patients, only LDH (AUC = 0.776; p < 0.001) and D-dimer (AUC = 0.711; p = 0.005) were significant predictors.
ConclusionObesity is associated with increased mortality and ICU admission in hospitalized COVID-19 patients and should be considered in clinical risk stratification.

Keywords

Introduction

The COVID-19 pandemic, which emerged at the end of 2019, has resulted in substantial global morbidity and mortality. SARS-CoV-2 infection presents across a broad clinical spectrum, ranging from asymptomatic infection to severe pneumonia and fatal acute respiratory distress syndrome (ARDS).¹ Several factors, including advanced age, comorbidities, variability in immune response, and obesity, have been identified as major determinants of disease prognosis.^2,3,4,5,6
Obesity is widely recognized as a global epidemic with continuously increasing prevalence.^{7,8,9,10,11,12,13,14} It adversely affects not only metabolic and cardiovascular health but also susceptibility to infectious diseases. Chronic low-grade inflammation in adipose tissue, excessive production of proinflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α), impaired immune cell function, and endothelial dysfunction may render individuals with obesity more vulnerable to infection.^2,3,4,5 In addition, comorbid conditions frequently associated with obesity—including type 2 diabetes mellitus, hypertension, and cardiovascular disease—may further worsen the prognosis of COVID-19.^2,5,10
Numerous studies have demonstrated that obesity is associated with increased rates of intensive care admission, mechanical ventilation, and mortality among patients with COVID-19.^1,7,10,11,13 However, data evaluating the prognostic impact of obesity in large hospitalized cohorts remain limited. Therefore, clarifying the relationship between obesity and COVID-19 clinical outcomes is essential for identifying high-risk populations and optimizing management strategies.
This study retrospectively evaluated the association between obesity and clinical outcomes in hospitalized patients with confirmed COVID-19, comparing mortality, laboratory parameters, and length of hospital stay between obese and non-obese groups.

Materials and Methods

This single-center retrospective cohort study evaluated patients hospitalized with confirmed COVID-19 between June 1, 2020, and December 31, 2021. Diagnosis and treatment were conducted according to national COVID-19 guidelines issued by the Turkish Ministry of Health.15
Patients aged ≥18 years with confirmed infection, available height and weight measurements, and complete clinical and laboratory data were included. Patients diagnosed solely on clinical or radiologic grounds, those lacking sufficient data to calculate body mass index (BMI), and those with incomplete laboratory records were excluded.
BMI was calculated using height and weight recorded at admission. Patients with BMI ≥ 30 kg/m² were classified as obese, whereas those with BMI < 30 kg/m² were classified as non-obese. Demographic characteristics, comorbidities, laboratory parameters (leukocyte, lymphocyte, c-reactive protein [CRP], procalcitonin, lactate dehydrogenase (LDH), D-dimer, ferritin), length of hospital stay, and mortality status were obtained from medical records. Informed consent was waived due to the retrospective design.
Ethical ApprovalThis study was approved by the Ethics Committee of Sancaktepe İlhan Varank Training and Research Hospital (Date: 10.09.2025, Decision No: 2025/302).
Statistical AnalysisData were analyzed using IBM SPSS Statistics Version 25.0. Distribution of continuous variables was assessed using the Kolmogorov–Smirnov test. Normally distributed variables were expressed as mean ± SD, whereas non-normally distributed variables were reported as median (IQR). Categorical variables were summarized as frequencies and percentages.
Between-group comparisons were performed using Student’s t-test for normally distributed variables, the Mann–Whitney U test for non-normally distributed variables, and the chi-square or Fisher’s exact test for categorical variables, as appropriate. Subgroup descriptive analyses were conducted according to age and sex. Multivariate regression analysis could not be performed because of insufficient comorbidity data. A p-value < 0.05 was considered statistically significant.
Reporting GuidelinesThis study was reported in accordance with the STROBE guidelines

Results

Sex distribution was comparable between groups (p = 0.320). Mean age was significantly lower in obese patients than in non-obese patients (63.0 ± 15.7 vs. 68.1 ± 14.2 years; p = 0.007).
The most common comorbidities were hypertension (52.3%), diabetes mellitus (37.6%), and respiratory disease (22.1%), with no significant differences between groups (all p > 0.05).
Laboratory parameters did not differ significantly between groups. Although D-dimer levels were numerically higher in the non-obese group, the difference was not statistically significant (p=0.080).
Clinical outcomes differed significantly. Mortality and ICU admission rates were higher among obese patients (20.8% vs. 9.0%, p = 0.013; and 36 vs. 16 cases, p = 0.007, respectively).
Receiver operating characteristic (ROC) analysis demonstrated distinct prognostic patterns. In obese patients, procalcitonin and D-dimer showed the strongest predictive performance for mortality, whereas LDH and ferritin showed moderate predictive value. CRP and lymphocyte count did not demonstrate discriminatory ability. In the non-obese group, only LDH and D-dimer showed significant predictive performance.
Detailed laboratory findings and ROC analysis results are presented in Supplementary Table 1 and Table 2.

Discussion

This study demonstrates that obesity significantly increases mortality risk among hospitalized patients with COVID-19. Mortality in obese patients was nearly twice that of non-obese patients, consistent with previous international studies identifying obesity as a major determinant of disease severity and adverse outcomes. Multicenter intensive care investigations have reported high obesity prevalence among severe COVID-19 cases and increased need for mechanical ventilation with rising BMI.¹¹ Other studies have similarly shown that obesity predisposes patients to critical illness and severe disease progression.⁴ Large cohort analyses have also demonstrated that obesity independently increases in-hospital mortality risk, particularly among younger individuals.⁹
Despite being younger, obese patients in this study exhibited higher mortality, suggesting that obesity may offset the survival advantage typically associated with younger age. Comorbidity distributions were similar between groups, indicating that the observed mortality difference cannot be explained solely by comorbidity burden. Obesity itself may therefore function as an independent contributor to adverse outcomes through mechanisms including inflammatory dysregulation, endothelial dysfunction, and impaired immune responses. These findings are consistent with systematic reviews and meta-analyses demonstrating associations between higher BMI and increased COVID-19 severity and mortality.^1,7,13
Several pathophysiological mechanisms may underlie the more severe clinical course observed in obese individuals. Adipose tissue expresses elevated levels of angiotensin-converting enzyme 2 (ACE2), the receptor facilitating viral entry, potentially increasing viral burden.2 Chronic low-grade inflammation and excessive cytokine production may amplify systemic inflammatory responses and contribute to multiorgan involvement.3,5 Insulin resistance and endothelial dysfunction promote hypercoagulability and thrombotic complications, while obesity-related restrictive lung physiology reduces pulmonary reserve and exacerbates hypoxemia and respiratory failure.^4,7
In obese patients, procalcitonin and D-dimer demonstrated the strongest predictive performance for mortality, suggesting that inflammatory escalation and coagulation abnormalities play prominent prognostic roles. LDH was predictive in both groups, supporting the role of cellular injury and tissue hypoxia in disease progression. Ferritin predicted mortality only in obese patients, consistent with chronic inflammatory activation. In contrast, CRP and lymphocyte count showed limited prognostic value, possibly due to baseline inflammation and altered immune responses associated with obesity.
Management of obese patients with COVID-19 presents several clinical challenges. Airway management and ventilator adaptation may be technically more difficult. Obesity also increases procedural risk, including during prone positioning. Pharmacokinetic alterations may require dose adjustments, complicating pharmacotherapy. Furthermore, impaired vaccine response has been reported in individuals with obesity.² These considerations emphasize the importance of early monitoring and aggressive management strategies, particularly regarding respiratory support and anticoagulation.
Our findings align with recent evidence demonstrating that obesity remains an important determinant of in-hospital COVID-19 outcomes. In a large retrospective cohort study, Dumitru et al. reported higher rates of severe disease and greater pulmonary involvement among obese hospitalized patients. Consistent with this observation, mortality and ICU admission rates in our study were significantly higher among obese patients despite younger age.

Limitations

This study has several strengths, including a relatively large sample size and comprehensive laboratory evaluation, particularly the use of ROC analyses to assess prognostic markers. However, limitations should be acknowledged. The retrospective single-center design may limit generalizability, and the lack of detailed cause-of-death data precluded stratified mortality analysis. Although results indicate an association between obesity and adverse outcomes, they do not definitively establish causality. Larger prospective multicenter studies controlling for confounding variables are required.

Conclusion

In this cohort, obesity was associated with higher mortality and increased ICU admission among hospitalized patients with COVID-19. However, given the retrospective design and lack of multivariate adjustment for comorbidities, these findings should be interpreted cautiously. Overall, the results support existing evidence indicating that obesity adversely affects COVID-19 prognosis. Incorporating BMI into clinical risk assessment and implementing closer monitoring and targeted management strategies for obese patients may help reduce mortality.

Declarations

Abbreviations

ACE2: angiotensin-converting enzyme 2
ARDS: acute respiratory distress syndrome
AUC: area under the curve
BMI: body mass index
COVID-19: coronavirus disease 2019
CRP: c-reactive protein
IL-6: interleukin-6
IQR: interquartile range
LDH: lactate dehydrogenase
ROC: receiver operating characteristic
SD: standard deviation
SPSS: statistical package for the social sciences
STROBE: strengthening the reporting of observational studies in epidemiology
TNF-α: tumor necrosis factor alpha

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