The Association between High Body Mass Index and Mortality Risk in Hospitalized Patients Diagnosed with COVID-19: A Meta-Analysis
DOI:
https://doi.org/10.26911/jepublichealth.2021.06.01.08Abstract
Background: COVID-19, caused by severe acute respiratory coronavirus 2 (SARS-CoV-2), emerged as a global pandemic with confirmed death cases of more than 1.27 million worldwide. Since the past pandemic, several studies discovered the adverse effects of excess fat accumulation on the severity of viral infections. This study aimed to investigate the association between high body mass index (BMI) and mortality risk in hospitalized COVID-19 patients based on four categories of high BMI ranges.
Subjects and Method: A systematic review and Meta-Analysis was conducted using search articles from electronic databases including PubMed, Google Scholar, and Scopus, published from 2019 to 2021. The keywords used to retrieve articles were "Body Mass Index" OR BMI OR Obesity OR Overweight) AND (Mortality OR Death) AND COVID-19 OR SARS-CoV-2. The included studies were full-text articles published in the English language, reporting adjusted odds ratios from multivariate analysis. The eligibility criteria were defined using PICO model. The article selection was conducted using PRISMA flow chart. The included studies were analyzed by the Review Manager 5.3 application.
Results: A total of nine cohort studies involving 12,907 COVID-19 patients with high BMI conducted from America, Europe, and Georgia regions was included in qualitative synthesis and Meta-Analysis. The pooled estimate showed hospitalized COVID-19 patients with morbid/ class III obesity had a higher risk of mortality (aOR= 1.77; 95% CI= 1.27 to 2.47; p= 0.001) than overweight (aOR= 1.10; 95% CI= 1.00 to 1.21; p= 0.060), class I (aOR= 1.16; 95% CI= 0.87 to 1.55; p= 0.300), and class II obesity (aOR= 1.54; 95% CI= 1.11 to 2.13; p= 0.009).
Conclusion: High BMI increases the risk of mortality in hospitalized COVID-19 patients. A potential dose-response relationship may exist between different categories of high BMI range and mortality risk in COVID-19 patients.
Keywords:
BMI, obesity , mortality, COVID-19, SARS-CoV-2Correspondence
Yuzana Maung. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java. Email: yuzmg5699@gmail.com. Mobile: +6281295346614.
BACKGROUND
COVID-19, caused by the severe acute respiratory coronavirus 2 (SARS-CoV-2), was first discovered in December 2019 in Wuhan, China (WHO, 2020). Since the first outbreak, the rapid transmission of the disease resulted in over 127 million con firmed cases of COVID-19 worldwide, including 2,787,593 deaths in March 2021. The most death caused by COVID-19 occurred in the Americas (1,340,530), followed by Europe (961,435), South-East Asia (218,604), Eastern Mediterranean (157,852), Africa (77,688), and Western Pacific (31,471) (WHO, 2021).
The clinical spectrum of SARS-CoV-2 ranged from no symptoms to severe illness, and many may even die. The most common symptoms were fever, cough, fatigue, shortness of breath, and muscle soreness (Chen et al., 2020). In severe cases, rapid progression to acute respiratory distress syn drome (ARDS), septic shock, blood clotting dysfunction, multiple organ failure, and even death has occurred (Tsai et al., 2021).
Obesity caused by excess fat accumu lation is one of the most serious diseases affecting people's health. It can cause morbidity by developing a wide range of non-communicable diseases and increasing the risk of infectious diseases (Wilding and Ralston, 2021). Several studies linked the negative impact of obesity on the severity of viral infections, including MERS, H1N1 influenza, and other seasonal influenza (Wilding and Ralston, 2021; Jain and Chaves, 2011).
Furthermore, in the case of COVID-19 infection, some studies discovered obesity as a risk factor for adverse outcome, in cluding the need for hospitalization, in-vasive mechanical ventilation, intubation, and death (Docherty et al., 2020; Giacomelli et al., 2020; Hajifathalian et al., 2020; Petrilli et al., 2020). Abnormal fat accumulation is related to increased risk of thromboembolism, cytokine storm, de creased respiratory system functions, and an increased risk of acute organ injuries, leading to fatal outcomes in COVID-19 patients (Mafort et al., 2016; Mehta et al., 2020).
However, despite recent epidemio logi cal studies discussing the impact of obesity on mortality risk in COVID-19 patients, the pooled effect from different BMI categories has not yet been evaluated to the best of the author's knowledge. Therefore, this study aimed to investigate the association between high BMI and mortality risk in hospitalized COVID-19 patients based on four categories of high BMI ranges using systematic review and Meta-Analysis.
SUBJECTS AND METHOD
1.Study Design
This was a systematic review and Meta-Analysis of observational cohort studies comparing the high BMI with normal BMI on the risk of mortality in hospitalized COVID-19 patients. A comprehensive search was conducted to collect the relevant articles from the electronic database such as PubMed, Google Scholar, and Scopus, published from 2019 to 2021. The following keywords were used to retrieve articles: "Body Mass Index" OR BMI OR Obesity OR Overweight) AND (Mortality OR Death) AND COVID-19 OR SARS-CoV-2. Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline was used reporting this Meta-Analysis.
2.Inclusion Criteria
The articles were included with following reasons: (1) Full-text articles with observa tional cohort study published in the English language; (2) Studies emphasized on mor tality risk of COVID-19 patients based on four different categories of high BMI range; and (3) The reported results were from multivariate analysis with adjusted odds ratios (aOR).
3.Exclusion Criteria
The articles were excluded with following reasons: (1) Articles reported only crude odds ratio (OR) resulted from bivariate analysis; (2) The effect measure used was aRR/ aHR, rather than aOR; (3) Reported outcomes other than mortality related to high BMI in COVID-19 patients.
4.Operational Definition of Variables
Mortality was defined by the status of death in hospitalized patients diagnosed with COVID-19. It was categorized as dead or alive. The instrument used was do cument confirmation of death related to COVID-19.
High Body Mass Index (BMI) means BMI above the normal or healthy weight range of 18.5-24.9 (kg/m2). BMI was cate gorized into overweight (25.0-29.9 kg/m2), class I obesity (30-34.9 kg/m2), class II obesity (35-39.9 kg/m2), and class III/ morbid obesity (≥40 kg/m2). The instru ment used was the body weighing scale and stadiometer.
5.Data Analysis
The data processing was carried out using the Review Manager (RevMan 5.3). The association between high BMI and mor tality risk in COVID-19 patients was evaluated based on BMI categories: over weight, class I obesity, class II obesity, and morbid/ class III obesity. Odds ratios with 95% CIs were calculated from adjusted ORs. The Forest plot was drawn to present pooled estimate effect of high BMI. The heterogeneity among included studies was presented by the intuitive index (I2). Fixed effect model Meta-Analysis was used for homogenous data and random effect model for heterogeneous data across studies. Publication bias was investigated using a funnel plot.
Figure 1. PRISMA Flow Diagram
RESULTS
A total of 2,313 articles were identified through electronic databases. After re moved the duplications, 1,988 articles were screened. Of these, 67 articles were assess ed for eligibility criteria. A total of 9 articles that met the quality assessment were included in the quantitative synthesis using Meta-Analysis. Six of the nine included studies were conducted in the United States, two in Europe, including Italy and France, and one in Georgia. The process of selecting articles was presented in Figure 1. The studies quality assessment using the Cohort Study Checklist published by the CASP (Critical Appraisal Skills Program) was presented in Table 2.
Four forest plots were drawn to investigate the pooled effect from each BMI category on the mortality risk of COVID-19 patients. Only class III obesity was eva luat ed across all nine included studies, while the other categories of high BMI were evaluated across seven studies. The forest plot in Figure 2 showed that COVID-19 patients with overweight had 1.10 times as many mortality risks as patients with normal BMI (aOR= 1.10; 95% CI= 1.00 to 1.21), but it was not statistically significant (p= 0.060). The I2 was 48%, indicating low heterogeneity in included studies; thus, a fixed-effect model was used. The funnel plot in Figure 3 showed asymmetrical distribution of plots with five plots on the left and two on the right. It indicated publication bias with the underestimated effect of overweight across studies.
The forest plot in Figure 4 showed that COVID-19 patients with class I obesity had 1.16 times as many mortality risks as patients with normal BMI (aOR= 1.16; 95% CI= 0.87 to 1.55), but it was not statistically significant (p= 0.300). The I2 was 71%, indicating moderate heterogeneity in in cluded studies; thus, a random-effect model was used. The funnel plot in Figure 5 showed symmetrical distribution of plots with four plots on the left and three on the right, indicating no publication bias.
The forest plot in Figure 6 showed that COVID-19 patients with class II obesity BMI range had 1.54 times as many mortality risks as normal BMI (aOR= 1.54; 95% CI= 1.11 to 2.13), and it was statis tically significant (p= 0.009).
The I2 was 65%, indicating moderate hetero geneity in included studies; thus, a random-effect model was used. The funnel plot in Figure 7 showed symmetrical distribution of plots with four plots on the left and three on the right, indicating no publication bias.
The forest plot in Figure 8 showed that COVID-19 patients with class III obesity BMI range had 1.77 times as many mortality risks as normal BMI (aOR= 1.77; 95% CI= 1.27 to 2.47), and it was statis tically significant (p= 0.001). The I2 was 86%, indicating high heterogeneity in in cluded studies; thus, a random-effect model was used. The funnel plot in Figure 9 showed symmetrical distribution of plots with five plots on the left and four on the right, indicating no publication bias.
Table 2. Critical Appraisal Checklist for Cohort Study
No. | Critical Appraisal Checklists | Publication (Authors and Year) |
| |||||||
Czernichow et al. (2020) | Guerson Gil et al. (2020) | Gupta et al. (2020) | Halasz et al. (2020) | Kim et al. (2021) | Klang et al. (2020) | Nyabera et al. (2020) | Shah et al. (2020) | Yoshida et al. (2021) | ||
1. | Did the study address a clearly focused issue? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
2. | Was the cohort recruited in an acceptable way? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
3. | Was the exposure COVID-19 accurately measured to minimize bias? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
4. | Was the outcome (status mortality) accurately measured to minimize bias? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
5. | Have the authors identified all-important confounding factors? Have the authors took account of the confounding factors in the design and/ or analysis? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
6. | Was the follow-up of subjects complete enough? Was the follow-up of subjects long enough? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
7. | Was the result of this study reported in aOR? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
8. | How precise were the results? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
9. | Do you believe the results? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
10. | Can the results be applied to the local population? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
11. | Do the results of this study fit with other available evidence? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
12. | What are the implications of this study for practice? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Total | 12 | 12 | 12 | 12 | 12 | 12 | 12 | 12 | 12 |
Yes = 1; No = 0
Table 1. Characteristics of included studies for Meta-Analysis
Country | Study Design | Sample | P (Population) | I (Intervention) | C (Comparison) | O (Outcome) | ||
COVID-19 | BMI Range (kg/m2) | |||||||
Halasz et al. (2020) | Italy
| Retro spective Cohort | Total = 242 Non survivor = 78 | 25-29.9= 104 (41%), 30-34.9= 11 (14%), 35-39.9 = 3 (3%), ≥40 = 5 (6%) | Hospitalized COVID-19 patients | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Gupta et al. (2020) | United States | Prospec tive Cohort | Total = 2,215
| Not stated | Hospitalized COVID-19 patients | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Czernichow et al. (2020) | France | Prospec tive Cohort | Total = 4,056 Non survivor = 483 | 25-29.9 = 239, 30-34.9 = 145, 35-39.9 = 63, ≥40 = 36 | Hospitalized COVID-19 patients | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Shah et al. (2020) | Georgia | Retro spective Cohort | Total= 522 Non survivor= 92 (17.6%) | ≥30= 52 (62%) ≥40= 23 (25%) | Hospitalized COVID-19 patients | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Guerson-Gil et al. (2021) |
New York | Retro spective Cohort | Total= 3,530 | 25-29.9= 700, 30-34.9= 809, ≥35-39.9= 663 | Hospitalized COVID-19 patients | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Yoshida et al. (2021) | USA | Retro spective Cohort | Total = 776 | 25-29.9=198 (25.7%), 30-34.9=157 (20.4%), 35-39.9=118 (15.3%), ≥40 = 134 (17.4%) | Hospitalized COVID-19 patients | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Klang et al. (2020) | New York | Retro spective Cohort | Total= 572 Non survivor= 60 (10.5%) | ≥30= 16 (26.7%) ≥40= 19 (31.7%) | Adult patients aged <50 years diag nosed with COVID-19 in hospital | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Nyabera et al. (2020) | New York | Retro spective Cohort | Total= 290 | 25-29.9=75 (25.9%), 30-34.9=52 (17.9%), 35-39.9= 17 (5.9%), ≥40= 20 (6.9%) | Hospitalized COVID-19 patients | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Kim et al. (2021) | New York | Retro spective Cohort | Total= 10,861 | 25-29.9= 4,021, 30-34.9= 2,345, 35-39.9= 990, ≥40= 755 | Hospitalized COVID-19 patients | COVID-19 patients with higher BMI | COVID-19 patients with normal BMI | Mortality |
Figure 2. Forest Plot of Association between Overweight and Mortality Risk in Hospitalized COVID-19 Patients
Figure 3. Funnel Plot of Association between Overweight and Mortality Risk in Hospitalized COVID-19 Patients
Figure 4. Forest Plot of Association between Class I Obesity and Mortality Risk in Hospitalized COVID-19 Patients
Figure 5. Funnel Plot of Association between Class I Obesity and Mortality Risk in Hospitalized COVID-19 Patients
Figure 6. Forest Plot of Association between Class II Obesity and Mortality Risk in Hospitalized COVID-19 Patients
Figure 7. Funnel Plot of Association between Class II Obesity and Mortality Risk in Hospitalized COVID-19 Patients
Figure 8. Forest Plot of Association between Class III Obesity and Mortality Risk in Hospitalized COVID-19 Patients
Figure 9. Funnel Plot of Association between Class III Obesity and Mortality Risk in Hospitalized COVID-19 Patients
DISCUSSION
This systematic review and Meta-Analysis investigated the association of high BMI and the risk of mortality in hospitalized COVID-19 patients based on four categories of high BMI range. All nine studies included in this review used an observa tional cohort design only to strengthen the validity of the results.
The findings of this study elucidated that a high BMI was associated with an increased risk of mortality in COVID-19 patients. Furthermore, this study discover ed a possible dose-response relationship effect of higher BMI on mortality risk. There was a higher mortality risk of COVID-19 in class III obesity patients (aOR= 1.77; 95% CI= 1.27 to 2.47; p= 0.001) compared to overweight (aOR= 1.10; 95% CI= 1.00 to 1.21; p= 0.060), class I (aOR= 1.16; 95% CI= 0.87 to 1.55; p= 0.300), and class II obesity (aOR= 1.54; 95% CI= 1.11 to 2.13; p= 0.009).
The patients with BMI ranges of class II and III obesity demonstrated a moderate causal relationship, and it was statistically significant. In contrast, overweight and class I obesity demonstrated a weak causal relationship on the risk of COVID-19 mor ta lity, and it was not statistically sig nificant.
This study results aligned with the study conducted by Palaiodimos et al. (2020) with significant results of severe obesity (BMI= ≥35 kg/m2) increased the risk of in-hospital mortality (aOR= 3.78; 95% CI= 1.45 to 9.83) along with the need of oxygen requirements and intubation. A large cohort study from 88 US hospitals also revealed that obesity classes I, II, and III were associated with progressively higher risks of in-hospital death or me chani cal ventilation compared to indivi duals of normal weight (Hendren et al., 2021). A J-shape association between BMI and risk of death was occurred, even after adjusting for obesity-related comorbidities, including metabolic and cardiovascular diseases (Tartof et al., 2020).
Besides COVID-19 pathogenesis, se veral mechanisms increase disease severity in obese patients. COVID-19 patients with obesity had significantly higher acute-phase reactants such as serum ferritin, erythron cyte sedimentation rate, C-reactive protein (CRP), and D-dimer (Mehanna et al., 2021). They also have a higher rate of proinflam ma tory cytokine transcription, including tumor necrosis factor-α (TNF-α), inter leukin-1 (IL-1), and interleukin-6 (IL-6). These inflammatory cytokines then up regulate the concentration and synthesis of CRP in the liver and develop feedback loops of acute phase reactants and chronic inflammation (Guglielmi et al., 2021; Chiap petta et al., 2020).
In addition, adipose tissue also ex pressed angiotensin II (ATII), which was recognized as a receptor for SARS-CoV-2 antigen, resulting in a more vulnerable COVID-19 infection target (Seidu et al., 2021). The risk of thromboembolism, re duced lung mechanism, and proinflamma-tory cytokine cascade due to excess fat accumulation may add to the severity of COVID-19 infection (Mafort et al., 2016; Mehanna et al., 2021).
There are limitations to this review. The majority of included studies were from America (mostly from the USA), which may restrict the generalized ability to non-America individuals, including Asia, the Mediterranean, and the Middle East. Due to data constraints, only class III obesity can be applied to all included nine studies. Lastly, the researcher only included articles written in English, which may have resulted in non-English articles omission.
In conclusion, severe obesity may be a strong risk factor for mortality in COVID-19 patients with the potential of dose-response relationship effect of higher BMI on mortal ity risk. Future studies should consider subgroup analysis accounting clinical and demographic characteristics and dose-response relationship Meta-Analysis to en sure the evidence of the relationship be tween high BMI and mortality risk of COVID-19 patients.
AUTHOR CONTRIBUTION
Study conception and design: Yuzana Maung, Bhisma Murti
Data collection: Yuzana Maung, Eti Poncorini Pamungkasari
Data analysis and interpretation: Yuzana Maung, Bhisma Murti
Drafting of the article: All authors
Critical revision of the article: Eti Poncorini Pamungkasari, Bhisma Murti
CONFLICT OF INTEREST
The authors declare there were no conflicts of interest.
FUNDING AND SPONSORSHIP
Self-funded.
ACKNOWLEDGEMENT
We would like to thank the Masters Program in Public Health, Universitas Sebelas Maret, for supporting this manuscript's publication. The contents of this manuscript were entirely the responsibility of the authors.
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2021-07-11
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Vol. 6 No. 1 (2021)
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