Research Article | Vol. 6, Issue 1 | Journal of Clinical Medical Research | Open Access |
A Single Center Prospective Observational Cohort Study on the Association of Asia Pacific Classification of Body Mass Index, Waist Circumference, Waist Hip Ratio with COVID-19 Outcomes and Severity in a Philippine Tertiary Hospital
Khia Anne Patricia S Quiwa1,2*
1Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, The Medical City, Philippines
2Department of Internal Medicine, The Medical City, Philippines
*Correspondence author: Khia Anne Patricia S Quiwa, Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, The Medical City, Philippines and Department of Internal Medicine, The Medical City, Philippines;
Email: [email protected]
Citation: Quiwa KAPS, et al. A Single Center Prospective Observational Cohort Study on the Association of Asia Pacific Classification of Body Mass Index, Waist Circumference, Waist Hip Ratio with COVID-19 Outcomes and Severity in a Philippine Tertiary Hospital. Jour Clin Med Res. 2025;6(1):1-16.
Copyright© 2025 by Quiwa KAPS, et al. All rights reserved. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Received 31 January, 2025 | Accepted 20 February, 2025 | Published 27 February, 2025 |
Abstract
Objective: This study aimed to determine the association between Asia-Pacific classification of body mass index, waist circumference and waist hip ratio and clinical outcomes of COVID-19 moderate & severe patients at the height of the COVID-19 pandemic.
Methods: This study involved adult patients diagnosed with COVID-19. 182 patients were analyzed and divided into 167 moderate and 15 severe COVID-19 patients. Primary outcomes (respiratory decompensation, septic shock and mortality) of patients were compared among Asia Pacific BMI groups.
Results: Among patients with moderate and severe COVID-19, 7 out of 10 patients were obese. Respiratory decompensation and sepsis were more frequently seen in obese patients. Obesity and waist circumference were significantly associated with the odds of respiratory decompensation (95% CI p=0.010 and p=0.002), however this association was not sustained upon adjustment for confounders. On univariate analysis, waist and hip circumferences were significantly associated with the odds of ICU admission (95% CI, p=.013 and p=.034), however after controlling for confounders, only hip ratio retained significant association. Among patients with severe COVID-19, there was insufficient evidence to support significant variations in distributions of outcomes of interest across Asia-Pacific Body Mass Index (BMI) groups.
Conclusion: Our study emphasized that although respiratory decompensation and sepsis were more frequently seen in obese patients. Progression of respiratory decompensation and mortality is not significantly associated with obesity as defined by the Asia Pacific BMI classification, warranting the need for larger prospective studies.
Keywords: Body Mass Index; Obesity; COVID-19
Introduction
Obesity has been postulated to aggravate the course of COVID-19 disease [1-6]. Few studies have focused on the association between COVID-19 infection and individual measures of visceral adiposity as measured by waist circumference and waist-hip ratio [3]. Visceral adiposity has been linked to cardiometabolic disorders and is known to be more metabolically active, secreting a variety of adipokines and pro-inflammatory cytokines, including tumor necrosis factor, C-reactive protein, Interleukin 6 (IL-6) and leptin [7]. Apart from insulin resistance and metabolic syndrome, elevated IL-6 levels are known to be related to airway diseases and recent studies report higher levels of IL-6 in COVID-19 non-survivors [7].
While previous studies have already identified overall obesity as a risk factor for severe courses of COVID-19, most studies only used body mass index [1-2,4,5]. There is no local data showing an association between body mass index, waist circumference and waist-hip ratio and how these different measures differ with one another in terms of which is more accurate or predictive of COVID-19 outcomes in Filipinos. Furthermore, it is expensive to obtain more accurate measures of visceral adiposity such as Computed Tomography (CT) based quantification of visceral adipose tissue [8].
Most studies on the association of Body Mass Index (BMI) and COVID-19 outcomes make use of the WHO classification and it has been a known fact that a BMI cut off of 30 kg/m2 is associated with a greater risk of death from COVID-19 [1,2]. There is paucity of data on outcomes for those patients stratified in different Asia-Pacific classifications of body mass index, waist circumference and waist hip ratio with moderate and severe COVID-19 disease in terms of progression of severity in patients requiring critical care or progression to mortality.
Data on the association of Asia-Pacific classification of body mass index, waist circumference, waist-to-hip ratio and COVID-19 outcomes may contribute to further understanding the mortality risk of Filipinos, particularly the survival of patients with lower or higher body mass index, waist circumference and visceral adiposity. Our study attempts to explain how a patient’s body mass index classification, waist circumference and waist-hip ratio affect COVID-19 outcomes in terms of severity requiring critical care or mortality, which is important both clinically and in public health. This study also aims to improve current practice in terms of the value of obtaining accurate anthropometric measurements in COVID-19 patients and in determining whether waist circumference and body mass index are associated with COVID-19 outcomes.
We hypothesize that patients with increased body mass index and visceral adiposity as measured by waist circumference and waist-hip ratio are at higher risk for developing severe outcomes from COVID-19. This prospective study aims to provide further insight into the risk stratification of patients with COVID-19 based on non-invasive measurements of height, weight, waist and hip circumference.
Material and Methods
Study Selection and Eligibility Criteria
This single-center prospective, analytical, observational cohort study included data from patients > 18 years old diagnosed with COVID-19 confirmed by nasopharyngeal swab Polymerase Chain Reaction (PCR) who were admitted at The Medical City from August 2021 to November 2021. A minimum sample size of 180 subjects was required for this study. The overall sample size provided was deemed to be sufficient to detect a significant relationship based on anticipated odds ratios and at 5% level of significance and 90% power.
Inclusion criteria included hospitalized, ambulatory, patients >18 years with COVID-19 confirmed by reverse transcription-polymerase chain reaction testing. The study participants belonged to the World Health Organization (WHO) clinical progression scales 4, 5 and 6, namely those who were hospitalized with no oxygen therapy, hospitalized with oxygen therapy through nasal prongs or mask and hospitalized who utilized non-invasive ventilation, respectively. Exclusion criteria excluded any patient who was unable to stand upright and/or have his/her waist and hip circumference measurements obtained, any patients who was pregnant as confirmed by history, patients with a “do not resuscitate/intubate” order, patients who dropped out or withdrew from the study before the 30 days from the time of admission or upon discharge, bedridden patients, patients classified as 7, 8, 9 and 10 according to the WHO clinical progression scale, namely, those who were intubated and mechanically ventilated with p02/Fi02 >150 or Sp02/Fi02 >200, those who were mechanically ventilated with p02/Fi02 ratio of <150 (Sp02/Fi02 <200) or on vasopressors, those who were mechanically ventilated with p02/Fi02 ratio of <150 and on vasopressors, on dialysis or on Extracorporeal Membrane Oxygenation (ECMO) and patients who expired, respectively. Patients who were unable to ambulate or stand up because of dementia, osteoarthritis, amputations and any physical disability were also excluded from the study. The selection process is shown in Fig. 1.
Figure 1: Patient enrolment and inclusion.
Study Procedures
This study was approved by the Institutional Review Board (IRB) and was made under the specifications and mandates of the IRB and Clinical and Translational Research Institute (CTRI) of The Medical City. This study adheres to the ethical considerations and ethical principles set out in relevant guidelines, including the Declaration of Helsinki, WHO guidelines, International Conference on Harmonization-Good Clinical Practice, Data Privacy Act of 2012 and the National Ethics Guidelines for Health Research 2017. The height, weight waist and hip circumference measurements were obtained. Laboratory and imaging data were obtained from the electronic medical records. Data elements included the following pertinent laboratory tests: hemoglobin (g/dL), absolute lymphocyte count, creatinine (g/dL), blood urea nitrogen (mg/dL), creatinine (mg/dL), estimated glomerular filtration rate (ml/min/1.73m2), alanine aminotransferase (U/L), alkaline phosphatase (U/L) CRP (mg/L), LDH (U/L), ferritin (ng/mL), sodium (mEq/L), potassium (mEq/L), chloride (mEq/L) and magnesium (mEq/L).
Primary Outcomes of Interest
The primary outcomes of interest were respiratory decompensation (progression to invasive or non-invasive ventilation from the time of admission up to any point within the 30-day follow-up period), sepsis, septic shock and hospital mortality. Secondary outcomes included a diagnosis of Acute Respiratory Distress Syndrome (ARDS) using the Berlin Criteria, Intensive Care Unit (ICU) admission, length of hospital stay and severity of COVID-19 defined by the World Health Organization (WHO) clinical progression scale. The primary outcomes and the secondary outcomes of patients with moderate and severe COVID-19 infection were compared among Asia Pacific BMI groups. Subgroup comparisons were performed to study the association of COVID-19 severity, visceral adiposity indicators namely waist circumference, hip circumference and waist-hip ratio with respiratory decompensation, ICU admission and mortality.
Statistical Analysis
STATA 15.0 (StataCorp SE, College Station, TX, USA) was used for data analysis. Descriptive statistics were used to summarize the general and clinical characteristics of the participants. Frequency and proportion were used for categorical variables. Shapiro-Wilk test was used to determine the normality distribution of continuous variables. Continuous quantitative data that met the normality assumption was summarized using mean and Standard Deviation (SD). Continuous variables which were normally distributed were compared using the Independent t-test. Otherwise, the non-parametric Mann-Whitney U test was used. For categorical variables, Chi-square test was used to compare the outcomes. If the expected percentages in the cells were less than 5%, Fisher’s Exact test was used instead. One-way ANOVA, Kruskal-Wallis test and Fisher’s Exact test were used to determine the difference of mean, median and frequency, respectively. Odds ratio and the corresponding 95% confidence intervals from binary logistic regression were computed to determine the association of BMI and visceral adiposity with clinical outcomes. All valid data were included in the analysis. Null hypothesis was rejected at 0.05α-level of significance.
Ethical Statement
This study was made under the specifications and mandates of the Institutional Review Board (IRB) and Clinical and Translational Research Institute (CTRI) of The Medical City. This study adheres to the ethical considerations and ethical principles set out in relevant guidelines, including the Declaration of Helsinki, WHO guidelines, International Conference on Harmonization-Good Clinical Practice, Data Privacy Act of 2012 and the National Ethics Guidelines for Health Research 2017.
Results
Study Characteristics
There were a total of 182 adult subjects, divided into 167 moderate and 15 severe COVID-19 patients (Table 1), with median age was 54.5 (range 20-86) years. 54% were male. Seven in 10 were obese by Asia-Pacific BMI classification. The mean (±SD) waist circumference, hip circumference and waist-hip ratio were 101.75 ± 14.27 cm, 102.65 ± 13.06 cm and 0.99 ± 0.07, respectively. The most common comorbidities of patients were hypertension (58%) and type 2 diabetes (52%) and more than a fourth (27%) were active smokers.
Results
Study Characteristics
There were a total of 182 adult subjects, divided into 167 moderate and 15 severe COVID-19 patients (Table 1), with median age was 54.5 (range 20-86) years. 54% were male. Seven in 10 were obese by Asia-Pacific BMI classification. The mean (±SD) waist circumference, hip circumference and waist-hip ratio were 101.75 ± 14.27 cm, 102.65 ± 13.06 cm and 0.99 ± 0.07, respectively. The most common comorbidities of patients were hypertension (58%) and type 2 diabetes (52%) and more than a fourth (27%) were active smokers.
Severe COVID-19 patients had higher median days of illness on admission, ALT, LDH, ferritin and chloride compared to moderate COVID-19 patients (p < .05). The severe COVID-19 group had a higher proportion of patients that have the following medical interventions: vasopressors; nutritional support; endotracheal intubation; tracheostomy; NMBA; hemoperfusion; and tocilizumab.
All (n=182) | Moderate (n=167) | Severe (n=15) | P | |
Mean ± SD; Median (Range); Frequency (%) | ||||
Age, years | 54.5 (20-86) | 54 (20-86) | 59 (39-82) | .396* |
Sex | .999† | |||
Male | 98 (53.85) | 90 (53.89) | 8 (53.33) | |
Female | 84 (46.15) | 77 (46.11) | 7 (46.67) | |
BMI, kg/m2 | .999† | |||
<18.5 (underweight) | 2 (1.1) | 2 (1.2) | 0 | |
18.5-22.9 (normal) | 26 (14.29) | 24 (14.37) | 2 (13.33) | |
23.0-24.9 (overweight) | 26 (14.29) | 24 (14.37) | 2 (13.33) | |
≥25.0 (obese) | 128 (70.33) | 117 (70.06) | 11 (73.33) | |
Waist circumference, cm | 101.75 ± 14.27 | 101.84 ± 14.39 | 100.69 ± 13.31 | .765‡ |
Hip circumference, cm | 102.62 ± 13.06 | 102.86 ± 13.16 | 99.98 ± 12.03 | .415‡ |
Waist-hip ratio | 0.99 ± 0.07 | 0.99 ± 0.08 | 1.00 ± 0.04 | .285‡ |
Low-risk | 12 (6.59) | 12 (7.19) | 0 | .603† |
High-risk | 170 (93.41) | 155 (92.81) | 15 (100) | |
Co-morbidities | ||||
Neurologic | ||||
Stroke or TIA | 12 (6.59) | 9 (5.39) | 3 (20) | .064† |
Brain tumor | 1 (0.55) | 1 (0.6) | 0 | .918† |
Cardiac | ||||
Hypertension | 106 (58.24) | 97 (58.08) | 9 (60) | .999† |
Coronary disease | 17 (9.34) | 14 (8.38) | 3 (20) | .152† |
Heart failure | 2 (1.1) | 2 (1.2) | 0 | .999† |
Pulmonary | ||||
Asthma | 24 (13.19) | 24 (14.37) | 0 | .226† |
COPD | 7 (3.85) | 6 (3.59) | 1 (6.67) | .458† |
Pulmonary TB | 4 (2.2) | 4 (2.4) | 0 | .999† |
Renal | ||||
CKD | 2 (1.1) | 1 (0.6) | 1 (6.67) | .158† |
Liver | ||||
Chronic liver disease | 0 | 0 | 0 | – |
Liver cirrhosis | 0 | 0 | 0 | – |
Chronic hepatitis | 1 (0.55) | 1 (0.60) | 0 | .999† |
Hematologic disease | ||||
Anemia | 4 (2.2) | 4 (2.4) | 0 | .999† |
Coagulopathy disorder | 0 | 0 | 0 | – |
Endocrine | ||||
Type 1 DM | 1 (0.55) | 1 (0.60) | 0 | .999† |
Type 2 DM | 95 (52.2) | 87 (52.1) | 8 (53.33) | .999† |
Thyroid disease | 10 (5.49) | 9 (5.39) | 1 (6.67) | .587† |
Active smoking status | 50 (27.47) | 47 (28.14) | 3 (20) | .763† |
Smoking exposure, pack years | [N=50] 10 (1-50) | [N=47] 10 (1-50) | [N=3] 30 (2-35) | .324† |
Presenting symptoms | ||||
Fever | 156 (85.71) | 142 (85.03) | 14 (93.33) | .699† |
Cough | 159 (87.36) | 145 (86.83) | 14 (93.33) | .697† |
Colds | 75 (41.21) | 67 (40.12) | 8 (53.33) | .413† |
Difficulty breathing | 132 (72.53) | 118 (70.66) | 14 (93.33) | .072† |
Sore throat | 78 (42.86) | 69 (41.32) | 9 (60) | .182† |
Watery stool | 63 (34.62) | 56 (33.53) | 7 (46.67) | .396† |
Vomiting | 9 (4.95) | 9 (5.39) | 0 | .999† |
Seizure | 1 (0.55) | 1 (0.60) | 0 | .999† |
Muscle pain | 50 (27.47) | 43 (25.75) | 7 (46.67) | .126† |
Loss of smell | 89 (48.9) | 80 (47.9) | 9 (60) | .427† |
Loss of taste | 90 (49.45) | 80 (47.9) | 10 (66.67) | .187† |
Day of illness on admission | 7 (1-17) | 7 (1-16) | 8 (4-17) | .014 |
COVID-19 vaccination | .070† | |||
None | 93 (51.1) | 81 (48.5) | 12 (80) | |
First dose | 18 (9.89) | 18 (10.78) | 0 (0) | |
Second dose | 71 (39.01) | 68 (40.72) | 3 (20) | |
ECG finding | .099† | |||
Ischemia | 5 (2.79) | 4 (2.44) | 1 (6.67) | |
Tachyarrhythmia | 48 (26.82) | 42 (25.61) | 6 (40) | |
Bradyarrhythmia | 12 (6.7) | 10 (6.1) | 2 (13.33) | |
Normal sinus rhythm | 114 (63.69) | 108 (65.85) | 6 (40) | |
CO-RADS classification | .999† | |||
0 (not interpretable) | 1 (1.49) | 1 (1.59) | 0 | |
1 (very low) | 0 | 0 | 0 | |
2 (low) | 0 | 0 | 0 | |
3 (equivocal) | 0 | 0 | 0 | |
4 (high) | 0 | 0 | 0 | |
5 (very high) | 1 (1.49) | 1 (1.59) | 0 | |
6 (PCR+) | 65 (97.01) | 61 (96.83) | 4 (100) | |
Blood tests | ||||
Hematology | ||||
Hemoglobin, g/dL | [N=182]13.65 (8-17.9) | [N=167]13.6 (8-17.9) | [N=15]14.1 (10.4-15.9) | .945* |
ALC, x109/L | [N=181]6.7 (1-32.1) | [N=166]6.7 (2.8-32.1) | [N=15]9.1 (1-25.3) | .087* |
Renal markers | ||||
Creatinine, mg/dL | [N=182]0.86 (0.35-9.82) | [N=167]0.85 (0.35-9.82) | [N=15]0.88 (0.55-1.3) | .541* |
BUN, mg/dL | [N=127]12.04 (2.7-93) | [N=113]12.04 (2.7-93) | [N=14]17.65 (9.8-36.13) | .609* |
Liver markers | ||||
ALT, U/L | [N=175]38 (8-405) | [N=160]37.5 (8-405) | [N=15]41 (23-340) | .025* |
Alkaline phosphatase, U/L | [N=22]63.5 (17.6-242) | [N=19]58 (17.6-242) | [N=3]87 (43-106) | .702* |
Inflammatory markers | ||||
CRP, mg/L | [N=180]84.14 (0.59-757) | [N=165]82.23 (0.59-757) | [N=15]145.7 (42-258.5) | .128* |
LDH, U/L | [N=178]367 (120-3229) | [N=163]352 (120-3229) | [N=15]712 (279-1448) | .002* |
Ferritin, ng/mL | [N=181]1020 (0.58-17780) | [N=166]941 (0.58-17400) | [N=15]2533 (157-17780) | .002* |
Electrolytes | ||||
Sodium, mEq/L | [N=180]135 (103-145) | [N=165]135 (103-144) | [N=15]134 (117-145) | .614* |
Potassium, mEq/L | [N=179]4 (2.9-5.5) | [N=164]4 (2.9-5.5) | [N=15]4.1 (3.2-5.2) | .257* |
Chloride, mEq/L | [N=31]100 (73-114) | [N=25]100 (73-114) | [N=6]102 (88-112) | .900* |
Magnesium, mEq/L | [N=69]1.95 (1.46-3.16) | [N=59]1.95 (1.46-3.16) | [N=10]2.095 (1.95-2.43) | .032* |
Medical interventions | ||||
Vasopressor or inotrope | 25 (13.74) | 17 (10.18) | 8 (53.33) | <.001† |
Nutritional support | 31 (17.03) | 22 (13.17) | 9 (60) | <.001† |
Endotracheal intubation | 22 (12.09) | 13 (7.78) | 9 (60) | <.001† |
Tracheostomy | 5 (2.75) | 0 | 5 (33.33) | <.001† |
Prone positioning | 133 (73.08) | 122 (73.05) | 11 (73.33) | .999† |
NMBA | 19 (10.44) | 11 (6.59) | 8 (53.33) | <.001† |
Hemoperfusion | 15 (8.24) | 7 (4.19) | 8 (53.33) | <.001† |
CPT | 0 | 0 | 0 | – |
Steroids | 165 (90.66) | 151 (90.42) | 14 (93.33) | .999† |
Remdesivir | 159 (87.36) | 145 (86.83) | 14 (93.33) | .697† |
Tocilizumab | 88 (48.35) | 75 (44.91) | 13 (86.67) | .002† |
ALC: Absolute Lymphocyte Count; CO-RADS: COVID-19 Reporting and Data System; CPT: Convalescent Plasma Therapy; NMBA: Neuromuscular Blocking Agent. Statistical tests used: * – Mann-Whitney U test; † – Fisher’s Exact test; ‡ – Independent t-test |
Table 1: Clinical profiles and interventions, by COVID-19 severity.
Asia Pacific Classification of Body Mass Index and Clinical Outcomes
Among patients with moderate COVID-19, there was insufficient evidence to support significant variations in the incidences of septic shock, ICU admission, need for vasopressor and mortality across Asia-Pacific BMI groups. Respiratory decompensation and sepsis were more frequently seen in obese patients than in the other three BMI classes, but pairwise comparisons were unable to reveal statistical significance (Table 2).
Measured Outcome | All (n=167) | Underweight (n=2) | Normal (n=24) | Overweight (n=24) | Obese (n=117) | p |
| Frequency (%) |
| ||||
Respiratory decompensation | 100 (59.88) | 1 (50) | 10 (41.67) | 10 (41.67) | 79 (67.52) | .013* |
Sepsis | 31 (18.56) | 0 | 0 | 1 (4.17) | 30 (25.64) | .001* |
Septic shock | 18 (10.78) | 0 | 1 (4.17) | 0 | 17 (14.53) | .118 |
ICU admission | 18 (10.78) | 0 | 1 (4.17) | 0 | 17 (14.53) | .118 |
Need for vasopressor | 17 (10.18) | 0 | 1 (4.17) | 0 | 16 (13.68) | .145 |
Mortality | 14 (8.38) | 0 | 1 (4.17) | 1 (4.17) | 12 (10.26) | .680 |
Statistical test used: Fisher’s exact test. *Not significant on Bonferroni-adjusted pairwise comparisons. |
Table 2: Clinical outcomes in moderate COVID-19, by BMI class (n=167).
Among patients with severe COVID-19, there was insufficient evidence to support significant variations in distributions of outcomes of interest across Asia-Pacific BMI groups (Table 3).
Measured outcome | All (n=15) | Normal (n=2) | Overweight (n=2) | Obese (n=11) | p |
| Frequency (%) |
| |||
Respiratory decompensation | 13 (86.67) | 1 (50) | 2 (100) | 10 (90.91) | .476 |
Sepsis | 8 (53.33) | 1 (50) | 2 (100) | 5 (45.45) | .713 |
Septic shock | 8 (53.33) | 1 (50) | 2 (100) | 5 (45.45) | .713 |
ICU admission | 9 (60) | 1 (50) | 2 (100) | 6 (54.55) | .736 |
Need for vasopressor | 8 (53.33) | 1 (50) | 2 (100) | 5 (45.45) | .713 |
Mortality | 9 (60) | 1 (50) | 2 (100) | 6 (54.55) | .736 |
Statistical test used: Fisher’s exact test. |
Table 3: Clinical outcomes in severe COVID-19, by BMI class (n=15).
Univariate and Multivariate Analyses
Respiratory Decompensation
On univariable analysis, obesity and waist circumference were significantly associated with the odds of respiratory decompensation. However, this association was not sustained upon adjustment for comorbidities, smoking, COVID-19 vaccination history, day of illness on admission and use of investigational drugs (Table 4).
| Crude Odds Ratio (95% CI) | p | Adjusted Odds Ratio* (95% CI) | p |
BMI category |
|
|
|
|
Normal | Reference | – | Reference | – |
Underweight | 1.36 (0.08-24.27) | .833 | 4.03 (0.16-100.36) | .396 |
Overweight | 1.17 (0.39-3.50) | .780 | 0.64 (0.14-2.90) | .567 |
Obese | 3.11 (1.31-7.39) | .010 | 1.15 (0.36-3.67) | .810 |
Waist circumference, cm | 1.04 (1.01-1.06) | .002 | 1.02 (0.98-1.05) | .345 |
Hip circumference, cm | 1.02 (1.00-1.04) | .099 | 1.01 (0.97-1.04) | .679 |
Waist-hip ratio** |
|
| ||
Low risk | Reference | – | Reference | – |
High risk | 2.44 (0.74-8.01) | .142 | 1.36 (0.31-6.03) | .685 |
*Adjusted for the following variables: comorbidities, smoking status, COVID-19 vaccination history, day of illness on admission and investigational drugs (e.g., tocilizumab, remdesivir). **Low risk is ≤0.85 in females and ≤0.90 in males. |
Table 4: Association of visceral adiposity indicators with respiratory decompensation.
ICU Admission
On univariable analysis, waist and hip circumferences were both significantly associated with the odds of ICU admission. After controlling for potential confounders, only hip circumference retained significant association, with odds for the outcome increased by 5% (95% CI 1-10%) with every additional centimeter in hip circumference (Table 5).
| Crude Odds Ratio (95% CI) | p | Adjusted Odds Ratio* (95% CI) | p |
BMI category |
|
|
|
|
Normal | Reference | – | Reference | – |
Underweight | – | – | – | |
Overweight | 1.00 (0.13-7.69) | .999 | 0.67 (0.05-8.83) | .759 |
Obese | 2.63 (0.58-11.92) | .210 | 1.23 (0.17-8.62) | .837 |
Waist circumference, cm | 1.04 (1.01-1.07) | .013 | 1.04 (1.00-1.08) | .076 |
Hip circumference, cm | 1.03 (1.003-1.07) | .034 | 1.05 (1.01-1.10) | .029 |
Waist-hip ratio | ||||
Low risk** | Reference | – | Reference | – |
High risk | 1.99 (0.25-16.05) | .520 | 0.62 (0.05-7.09) | .698 |
*Adjusted for the following variables: comorbidities, smoking status, COVID-19 vaccination history, day of illness on admission and investigational drugs (e.g., tocilizumab, remdesivir). **Low risk is ≤0.85 in females and ≤0.90 in males. |
Table 5: Association of visceral adiposity indicators with ICU admission.
Mortality
BMI, waist circumference, hip circumference or WHR were not found to be significantly associated COVID-19 mortality, whether on univariable nor multivariable analysis (Table 6).
Mortality
BMI, waist circumference, hip circumference or WHR were not found to be significantly associated COVID-19 mortality, whether on univariable nor multivariable analysis (Table 6).
| Crude Odds Ratio (95% CI) | P | Adjusted Odds Ratio* (95% CI) | p |
BMI category |
|
|
|
|
Normal | Reference | – | Reference | – |
Underweight | – | – | – | – |
Overweight | 1.57 (0.24-10.24) | .640 | 0.57 (0.05-6.44) | .646 |
Obese | 1.96 (0.43-9.03) | .386 | 0.44 (0.06-3.38) | .428 |
Waist circumference, cm | 1.02 (0.99-1.05) | .195 | 1.02 (0.98-1.06) | .437 |
Hip circumference, cm | 1.01 (0.97-1.04) | .637 | 1.01 (0.96-1.06) | .653 |
Waist-hip ratio | ||||
Low risk** | Reference | – | Reference | – |
High risk | 3.98 (0.23-69.55) | .344 | 2.55 (0.12-52.39) | .543 |
*Adjusted for the following variables: comorbidities, smoking status, COVID-19 vaccination history, day of illness on admission and investigational drugs (e.g., tocilizumab, remdesivir). **Low risk is ≤0.85 in females and ≤0.90 in males. |
Table 6: Association of visceral adiposity indicators with mortality.
Discussion
This is the first prospective observational cohort to investigate the influence of Asia-Pacific classification of Body Mass Index and visceral adiposity assessed by waist circumference and waist hip ratio on COVID-19 outcomes. According to the Asia Pacific classification, BMI is classified into four groups: underweight (<18.5 kg/m2), normal weight (18.5-22.9 kg/m2), overweight (23-24.9 kg/m2) and obese (> 25 kg/m2).
In our study involving 182 adult patients hospitalized with COVID-19, 127 or 70% of the patients were obese (BMI >25 kg/m2) by Asia-Pacific BMI classification. The mean waist circumference, hip circumference and waist-hip ratio were 101.75 ± 14.27 cm, 102.65 ± 13.06 cm and 0.99 ± 0.07, respectively. This proportion is consistent with a Philippine-based retrospective cohort study in 2017 examining the individual features of metabolic syndrome among 1367 subjects in a Philippine tertiary hospital [11]. In this study, 66.2% of the patients were obese and the mean BMI was 28.2 kg/m2 [11]. The mean waist circumference was documented at 96.8 cm [11].
Of the 182 patients, 167 presented with moderate COVID-19 and 15 patients had severe COVID-19. The incidence of severe COVID-19 infection in middle-aged patients was similar to that in older populations, which meant that the attributable risk may be similar in both groups. Our study findings show that in the obese group, most were male. There were no deaths recorded in the underweight group, although there were only two patients in this group. The mortality rate was lowest among those with normal BMI (7.69%).
On univariable analysis, waist and hip circumferences were both significantly associated with the odds of ICU admission. However, upon controlling for potential confounders, only hip circumference retained significant association with ICU admission. In particular, for every additional centimeter increase in hip circumference, the odds for the outcome of ICU admission increased by 5% (95% CI, p-value <0.05). In contrast, an observational study done in Ukraine determining mortality risks in 367 in-patients with COVID-19 found that only waist circumference (>105 centimeters) is an independent risk factor for severe COVID-19 outcomes particularly mortality [12]. Our hospital cohort of COVID-19 patients found no significant association between waist circumference and respiratory decompensation and mortality. To date, there are no studies showing the association of hip circumference alone with respiratory decompensation and mortality from COVID-19. While waist-hip ratio is based on the values of waist circumference and hip circumference, it provides a different measurement and perhaps may not always follow the trend of hip and waist circumference. For instance, a higher hip or waist circumference might not always indicate a higher waist-hip ratio.
Furthermore, our study found that BMI, waist circumference, hip circumference or waist-hip ratio were not found to be significantly associated COVID-19 mortality, whether on univariable or multivariable analysis. Several studies have investigated the association between COVID-19 and obesity, body mass index, waist circumference and waist-hip ratio, yet the mechanistic associations in Asians and in Filipinos remain unclear. Respiratory decompensation and sepsis were more frequently seen in obese patients (BMI > 25 kg/m2) than in the other three BMI classes. A possible explanation for the increased risk of developing respiratory decompensation and mortality among patients with higher BMI include difficulties in lung expansion, difficulties in ventilation and proning, which may complicate recovery time [13]. However, adjusting for confounders attenuated the significance of the association.
Furthermore, our study found that BMI, waist circumference, hip circumference or waist-hip ratio were not found to be significantly associated COVID-19 mortality, whether on univariable or multivariable analysis. Several studies have investigated the association between COVID-19 and obesity, body mass index, waist circumference and waist-hip ratio, yet the mechanistic associations in Asians and in Filipinos remain unclear. Respiratory decompensation and sepsis were more frequently seen in obese patients (BMI > 25 kg/m2) than in the other three BMI classes. A possible explanation for the increased risk of developing respiratory decompensation and mortality among patients with higher BMI include difficulties in lung expansion, difficulties in ventilation and proning, which may complicate recovery time [13]. However, adjusting for confounders attenuated the significance of the association.
In our study, we stratified our analysis of COVID-19 outcomes with measures of visceral adiposity since previous studies conclude that obesity and increased waist circumference are associated with severe COVID-19 outcomes and overall mortality [1,2,5,14]. Our study dealt with a smaller sample population compared to the earlier studies hence the possibility of selection bias due to the inclusion criteria. There were also significantly more obese patients (70% of the study population) and more moderate than severe COVID-19 patients (91.75% or 167 patients, vs 8.25% or 15 patients) which proved investigating significant differences between the two groups and their COVID-19 outcomes across the BMI classifications to be challenging. The associations were difficult to establish due to the uneven distribution of the subjects in each category, specifically because there were more patients analyzed in the moderate group versus severe and majority of the patients were obese. Thus, the interpretation of results should be viewed carefully. These factors may account for the association not retaining its significance upon adjustment for comorbidities, smoking, COVID-19 vaccination history, day of illness on admission and use of investigational drugs such as remdesivir and tocilizumab.
Our study attempted to examine the risk associated with unit increases in Asia Pacific classification of Body Mass Index, however we found that in patients afflicted with moderate and severe COVID-19, there were no significant variations in distributions of outcomes of interest (respiratory decompensation, sepsis, septic shock and mortality) across Asia-Pacific BMI groups. A large population-based study, of which a large population had a BMI lower than 30 kg/m2, found that having a Body Mass Index (BMI) of 30 kg/m2 or higher was associated with a slightly greater risk of death from COVID-19 than a BMI of less than 30 kg/m2 [2]. A community-based prospective cohort study found a significant positive linear association between increasing BMI and admission to hospital and to ICU due to COVID-19, with significantly higher risk for every BMI unit increase, with each unit increase in BMI above 23 kg/m2 associated with increased risk of hospital admission and death due to COVID-19 particularly among people aged 20-39 years [1]. In another study, they found that risks for hospitalization, ICU admission and death were lowest among patients with BMIs of 24.2 kg/m2, 25.9 kg/m2 and 23.7 kg/m2, respectively and that the risk increased with increasing body mass index [4]. A plausible explanation for not finding a significant interaction between COVID-19 outcomes and BMI groups in our study is that a large proportion (70%) of the study population are obese or have a BMI higher than 25 kg/m2.
Limitations
Due to the nature of the study and the inclusion criteria, the study population was limited to patients who belonged in the WHO severity scales 4, 5 and 6 and this population may not be representative of severity of risk in the general population. Another limitation of our study was that we did not include prevalence rates of individual features of metabolic syndrome, such as elevated triglyceride levels, low high density lipoprotein levels, elevated fasting blood sugar and incidence of diabetes and hypertension in the assessment and these may be valuable to include in larger studies to further characterize the risk profile of Filipinos. Furthermore, the level of control of co-morbidities of the study population was not analyzed, which would account as an important confounder. There was bias in measurement of the waist-hip circumference, since the patients are supposed to be measured in an upright position. Therefore, patients who were unable to stand at admission due to dyspnea or respiratory distress had to be excluded from analysis, hence introducing selection bias. Due to the number of patients to whom this applied (39 out of 221), the influence on the results may be substantial. The limitations may also be explained by difficulty in completing parameters during the pandemic in the local setting. Our final limitation is that our data collection was done during the height of the COVID-19 surge involving the Delta variant and the results may not be representative of the patients afflicted by the other variants such as the Omicron variant.
Conclusion
Our findings from this single center prospective cohort emphasize that although the COVID-19 mortality rate was lowest among those with normal BMI (7.69%), progression severity and respiratory decompensation were not significantly associated with obesity as defined by the Asia Pacific BMI classification. This finding warrants confirmation in future studies with a representative sample size in each Asia pacific body mass index category. Further evaluation with larger prospective cohorts would prove to be useful, since body mass index is an important modifiable risk factor that may guide national health policy creation in terms of prioritization of populations for risk reduction and vaccination against COVID-19 infection. Although still unproven, interventions that reduce weight and visceral adiposity (waist circumference, waist-hip ratio) may reduce the risk of severe COVID-19 outcomes in Filipinos.
Clinical pearls for endocrinologists and clinicians should include the information that a non-invasive measurement of height, weight, waist and hip circumference on patients afflicted with COVID-19 may help in the acquisition of more robust data sets which may help shed light on further implications of the Asia Pacific classification of body mass index and measures of visceral adiposity on the outcomes of COVID-19 infection in Filipinos.
Consent for Publication
The authors declare that there is no conflict of interest regarding the publication of this paper.
Funding
The author(s) received no funding for this work.
Authors’ Contributions
All authors contributed to the writing of the manuscript.
Acknowledgement
Not applicable.
References
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Supplemental Tables
| Under weight (n=2) | Normal (n=26) | Over weight (n=26) | Obese (n=128) | p |
Frequency (%) |
| ||||
Co-morbidities | |||||
Neurologic | |||||
Stroke or TIA | 0 | 1 (3.85) | 3 (11.54) | 8 (6.25) | .671 |
Brain tumor | 0 | 0 | 0 | 1 (0.78) | .999 |
Cardiac | |||||
Hypertension | 1 (50) | 16 (61.54) | 12 (46.15) | 77 (60.16) | .569 |
Coronary disease | 0 | 3 (11.54) | 0 | 14 (10.94) | .358 |
Heart failure | 0 | 0 | 0 | 2 (1.56) | .999 |
Pulmonary | |||||
Asthma | 0 | 2 (7.69) | 4 (15.38) | 18 (14.06) | .772 |
COPD | 0 | 2 (7.69) | 1 (3.85) | 4 (3.13) | .524 |
Pulmonary TB | 0 | 2 (7.69) | 0 | 2 (1.56) | .233 |
Renal | |||||
CKD | 0 | 0 | 0 | 2 (1.56) | .999 |
Liver | |||||
Chronic liver disease | 0 | 0 | 0 | 0 | – |
Liver cirrhosis | 0 | 0 | 0 | 0 | – |
Chronic hepatitis | 0 | 0 | 1 (3.85) | 0 | .297 |
Hematologic disease | |||||
Anemia | 0 | 1 (3.85) | 0 | 3 (2.34) | .759 |
Coagulopathy disorder | 0 | 0 | 0 | 0 | – |
Endocrine | |||||
Type 1 DM | 0 | 0 | 0 | 1 (0.78) | .999 |
Type 2 DM | 2 (100) | 9 (34.62) | 12 (46.15) | 72 (56.25) | .088 |
Thyroid disease | 0 | 2 (7.69) | 1 (3.85) | 7 (5.47) | .887 |
Presenting symptoms | |||||
Fever | 2 (100) | 18 (69.23) | 20 (76.92) | 116 (90.63) | .016 |
Cough | 1 (50) | 18 (69.23) | 21 (80.77) | 119 (92.97) | .001 |
Colds | 2 (100) | 8 (30.77) | 10 (38.46) | 55 (42.97) | .271 |
Difficulty breathing | 2 (100) | 13 (50) | 16 (61.54) | 101 (78.91) | .008 |
Sore throat | 2 (100) | 4 (15.38) | 7 (26.92) | 65 (50.78) | <.001 |
Watery stool | 0 | 5 (19.23) | 3 (11.54) | 55 (42.97) | .002 |
Vomiting | 0 | 1 (3.85) | 1 (3.85) | 7 (5.47) | .429 |
Seizure | 0 | 1 (3.85) | 0 | 0 | .297 |
Muscle pain | 0 | 4 (15.38) | 10 (38.46) | 36 (28.13) | .259 |
Loss of smell | 2 (100) | 8 (30.77) | 11 (42.31) | 68 (53.13) | .065 |
Loss of taste | 2 (100) | 10 (38.46) | 12 (46.15) | 66 (51.56) | .363 |
Table 1: Comorbidities and presenting symptoms by BMI class.
| All (n=182) | Under weight (n=2) | Normal (n=26) | Over weight (n=26) | Obese (n=128) | p |
| Frequency (%) |
| ||||
Respiratory decompensation | 113 (62.09) | 1 (50) | 11 (42.31) | 12 (46.15) | 89 (69.53) | .009 |
Sepsis | 39 (21.43) | 0 | 1 (3.85) | 3 (11.54) | 35 (27.34) | .016 |
Septic shock | 26 (14.29) | 0 | 2 (7.69) | 2 (7.69) | 22 (17.19) | .509 |
ICU admission | 27 (14.84) | 0 | 2 (7.69) | 2 (7.69) | 23 (17.97) | .441 |
Need for vasopressor | 25 (13.74) | 0 | 2 (7.69) | 2 (7.69) | 21 (16.41) | .573 |
Mortality | 23 (12.64) | 0 | 2 (7.69) | 3 (11.54) | 18 (14.06) | .689 |
Statistical test used: Fisher’s exact test. |
Table 2: Clinical outcomes by BMI class.
| All (n=93) | Normal (n=14) | Overweight (n=16) | Obese (n=63) | p |
| Frequency (%) |
| |||
Respiratory decompensation | 61 (65.59) | 6 (42.86) | 7 (43.75) | 48 (76.19) | .008 |
Sepsis | 24 (25.81) | 0 | 3 (18.75) | 21 (33.33) | .020 |
Septic shock | 18 (19.35) | 0 | 2 (12.50) | 16 (25.40) | .069 |
ICU admission | 19 (20.43) | 0 | 2 (12.50) | 17 (26.98) | .042 |
Need for vasopressor | 18 (19.35) | 0 | 2 (12.50) | 16 (25.40) | .069 |
Mortality | 18 (19.35) | 0 | 3 (18.75) | 15 (23.81) | .106 |
Statistical test used: Fisher’s exact test. |
Table 3: Clinical outcomes in unvaccinated COVID-19 patients by BMI class (n=93).
| All (n=18) | Overweight (n=2) | Obese (n=16) | p |
| Frequency (%) |
| ||
Respiratory decompensation | 12 (6.67) | 2 (100) | 10 (62.50) | .529 |
Sepsis | 2 (11.11) | 0 | 2 (12.50) | .999 |
Septic shock | 2 (11.11) | 0 | 2 (12.50) | .999 |
ICU admission | 2 (11.11) | 0 | 2 (12.50) | .999 |
Need for vasopressor | 2 (11.11) | 0 | 2 (12.50) | .999 |
Mortality | 1 (5.56) | 0 | 1 (6.25) | .999 |
Statistical test used: Fisher’s exact test. |
Table 4: Clinical outcomes in partially vaccinated COVID-19 patients by BMI class (n=18).
| All (n=71) | Underweight (n=2) | Normal (n=12) | Overweight (n=8) | Obese (n=49) | p |
| Frequency (%) |
| ||||
Respiratory decompensation | 40 (56.34) | 1 (50) | 5 (41.67) | 3 (37.50) | 31 (63.27) | .333 |
Sepsis | 13 (18.31) | 0 | 1 (8.33) | 0 | 12 (24.49) | .342 |
Septic shock | 6 (8.45) | 0 | 2 (16.67) | 0 | 4 (8.16) | .592 |
ICU admission | 6 (8.45) | 0 | 2 (16.67) | 0 | 4 (8.16) | .592 |
Need for vasopressor | 5 (7.04) | 0 | 2 (16.67) | 0 | 3 (6.12) | .392 |
Mortality |
|
|
| |||
Statistical test used: Fisher’s exact test. |
Table 5: Clinical outcomes in fully vaccinated COVID-19 patients by BMI class (n=71).
Author Info
Khia Anne Patricia S Quiwa1,2*
1Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, The Medical City, Philippines
2Department of Internal Medicine, The Medical City, Philippines
*Correspondence author: Khia Anne Patricia S Quiwa, Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, The Medical City, Philippines and Department of Internal Medicine, The Medical City, Philippines;
Email: [email protected]
Copyright
Khia Anne Patricia S Quiwa1,2*
1Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, The Medical City, Philippines
2Department of Internal Medicine, The Medical City, Philippines
*Correspondence author: Khia Anne Patricia S Quiwa, Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, The Medical City, Philippines and Department of Internal Medicine, The Medical City, Philippines;
Email: [email protected]
Copyright© 2025 by Quiwa KAPS, et al. All rights reserved. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation
Citation: Quiwa KAPS, et al. A Single Center Prospective Observational Cohort Study on the Association of Asia Pacific Classification of Body Mass Index, Waist Circumference, Waist Hip Ratio with COVID-19 Outcomes and Severity in a Philippine Tertiary Hospital. Jour Clin Med Res. 2025;6(1):1-16.
