The COVID-19 (Coronavirus disease 2019) pandemic is posing a threat to communities and healthcare systems worldwide. Malnutrition, in all its forms, may negatively impact the susceptibility and severity of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) infection in both children and older adults. Both undernutrition and obesity have been evoked as conditions associated with a higher susceptibility to the infection and poor prognosis. In turn, the COVID-19 infection may worsen the nutritional status through highly catabolic conditions, exposing individuals to the risk of malnutrition, muscle wasting, and nutritional deficiencies. Accordingly, the relationship between malnutrition and COVID-19 is likely to be bidirectional. Furthermore, the modification of nutritional behaviors and physical activity, required to limit the spread of the virus, are posing a challenge to health at both the extremes of life. Thus far, even the most advanced healthcare systems have failed to address the alarming consequences of malnutrition posed by this pandemic. If not properly addressed, we may run the risk that new and old generations will experience the consequences of COVID-19 related malnutrition.
Reference | Study Design and Sample | Aim | Relevant Results |
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Gastrointestinal symptoms/Anorexia | |||
Pan et al., 2020 [28] | Cross-sectional study; 204 COVID-19 patients; mean age 52.9 (SD 16) years |
Investigate the prevalence and outcomes of COVID-19 patients with digestive symptoms. | 103 patients (50.5%) reported digestive symptoms, including lack of appetite (81 [78.6%] cases), diarrhea (35 [34%] cases), vomiting (4 [3.9%] cases), and abdominal pain (2 [1.9%] cases). |
Zheng et al., 2020 [29] | Cross-sectional study; 1320 patients; median age 50 (IQR 40–57) years. | Compare clinical characteristics and outcomes between patients with and without GI symptoms. | 192 patients (14.5%) reported gastrointestinal symptoms, including diarrhea (107 [55.7%] cases), abdominal pain (11 [5.7%] cases), anorexia (62 [32.3%] cases), nausea and vomiting (57 [29.7%] cases). |
Redd et al., 2020 [30] | Multicenter cohort study; 318 patients; mean age 63.4 (SD 16.6) years. | Examine prevalence and features of GI manifestations associated with SARS-CoV-2 infection | 61.3% of patients reported at least 1 gastrointestinal symptom on presentation, most commonly loss of appetite (34.8%), diarrhea (33.7%), and nausea (26.4%). |
Meng et al., 2020 [31] | Review | Assess the relationship between olfactory dysfunction and COVID-19. | Anosmia ranged from 33.9 to 68% with female dominance. |
Parasa et al., 2020 [25] | Systematic review and meta-analysis of 23 published and 6 preprint studies; 4805 patients; mean age 52.2 (SD 14.8) years | Examine incidence rates of gastrointestinal symptoms among patients with COVID-19 infection. | 12% of patients with COVID-19 infection reported gastrointestinal symptoms, including diarrhea (7.4%), nausea, and vomiting (4.6%). |
Undernutrition | |||
Bedock et al., 2020 [3] | Observational longitudinal study; 114 COVID-19 patients, mean age 59.9 (SD 15.9) years. | Examine the association between malnutrition and disease severity at admission and the impact of malnutrition on clinical outcomes (i.e., ICU transfer or death). | The overall prevalence of malnutrition was 42.1% (moderate: 23.7%, severe: 18.4%). The prevalence of malnutrition reached 66.7% in patients admitted from ICU. |
Rouget et al., 2020 [24] | Prospective observational cohort study; 80 COVID-19 patients; median age 59.5 (IQR 49.5–68.5). | Evaluate the prevalence of malnutritionin patients hospitalized for COVID-19. | The prevalence of malnutrition was 37.5% with 26% of hospitalized patients who presented severe malnutrition. |
Li et al., 2020 [32] | Cross-sectional study; 182 COVID-19 older patients; mean age 68.5 (SD 8.8) years. | Investigate the prevalence of malnutrition and its related factors in older patients with COVID-19. | 96 patients (52.7%) were malnourished and 50 patients (27.5%) were at risk of malnutrition |
Yu et al., 2020 [33] | Retrospective survey study; 139 patients with COVID-19; mean age 61.47 (SD 14.76) years. | Examine the association of malnutrition with duration of hospitalization in patients with COVID-19. | 75 patients had nutritional risk (53.96%). Compared with the patients in the normal nutrition group, the hospitalization time was longer (15.67 [SD 6.26] days versus 27.48 [SD 5.04] days, p = 0.001) |
Allard et al., 2020 [34] | Retrospective study; 108 COVID-19 patients; mean age 61.8 (SD 15.8). | Determine the percentage of malnutrition and its prognosis in patients admitted for COVID-19. | 42 (38.9%) patients were malnourished. Moderate or severe nutritional risk was found in 83 (84.7%) patients. Malnutrition was not associated with COVID-19 severity, while nutritional risk was associated with severe COVID-19 (p < 0.01). |
Obesity | |||
Suleyman et al., 2020 [35] | Case series; 463 patients with COVID-19; mean age 57.5 (SD 16.8) years | Describe the clinical characteristics and outcomes of patients with COVID-19 infection. | Severe obesity (i.e., BMI ≥ 40) was independently associated with intensive care unit admission (OR: 2.0; 95% CI: 1.4–3.6; p = 0.02) |
Petrilli et al., 2020 [36] | Prospective cohort study; 5279 COVID-19 patients; median age 54 (IQR 38–66) years. | Examine outcomes of people admitted to hospital with COVID-19. | Any increase in BMI (i.e., BMI > 40) was strongly associated with hospital admission (OR: 2.5; CI: 1.8–3.4; average marginal effect: 14%) |
Simonnet et al., 2020 [37] | Retrospective cohort study; 124 COVID-19 patients admitted in ICU; median age 60 (IQR 51–70) years. | Analyze the relationship between clinical characteristics, including BMI, and the requirement for invasive mechanical ventilation. | Obesity (BMI > 30 kg/m2) and severe obesity (BMI > 35 kg/m2) were present in 47.6% and 28.2% of cases, respectively. The proportion of patients who required IMV increased with BMI categories (p < 0.01, Chi square test for trend) |
Hajifathalian et al., 2020 [38] | Retrospective review; 770 COVID-19 patients; mean age of 63.5 (SD 17) years | Examine the role of obesity in the clinical course of COVID-19 patients. | Obese patients were more likely to present with fever, cough and shortness of breath. Obesity was also associated with a significantly higher rate of ICU admission or death (RR = 1.58, p = 0.002) |
Busetto et al., 2020 [39] | Retrospective cohort study; 92 COVID-19 patients; mean age 70.5 (SD 13.3) years | Assess the relationship between the severity of COVID-19 and obesity classes according to BMI. | A higher need for assisted ventilation and a higher admission to intensive or semi-intensive care units were observed in patients with overweight and obesity (p < 0.01 and p < 0.05, respectively) |
Malik et al., 2021 [40] | Meta-analysis of 14 studies; 10, 233 confirmed COVID-19 patients; | Assess the effect of obesity on outcomes in the COVID-19 hospitalizations. | The overall prevalence of obesity was 33.9% (3473/10,233). COVID-19 patient with obesity had higher odds of poor outcomes (OR: 1.88; 95% CI: 1.25–2.80; p = 0.002). |
Ho et al., 2020 [41] | Systematic Review and Meta-analysis of 61 studies; 270, 241 patients. | Examine the relationship between COVID-19 and obesity. | The pooled prevalence of obesity was 27.6% (95% CI: 22.0–33.2). Obesity was not significantly associated with increased ICU admission or critical illness (OR: 1.25, 95% CI: 0.99–1.58, p = 0.062) but was significantly associated with more severe disease (OR: 3.13, 95% CI: 1.41–6.92, p = 0.005), mortality (OR: 1.36, 95% CI: 1.09–1.69, p = 0.006) and a positive COVID-19 test (OR: 1.50, 95% CI: 1.25–1.81, p < 0.001). |
Huang et al., 2020 [42] | Systematic review and meta-analysis of 33 studies (30 studies defined obesity via BMI and 3 studies using VAT adiposity); 45, 650 subjects. | Investigate the effects of obesity with the risk of severe disease among patients with COVID-19. | Higher BMI was associated with severe COVID-19 (OR 1.67, 95% CI: 1.43–1.96; p < 0.001), hospitalization (OR 1.76; 95% CI: 1.21–2.56, p = 0.003), ICU admission (OR 1.67, 95% CI: 1.26–2.21, p < 0.001), IMV requirement (OR: 2.19, 95% CI: 1.56–3.07, p < 0.001), and death (OR 1.37, 95% CI: 1.06–1.75, p = 0.014). Severe COVID-19 cases showed significantly higher VAT (SMD: 0.50, 95% CI: 0.33–0.68, p < 0.001), hospitalization (SMD: 0.49, 95% CI: 0.11–0.87; p = 0.011), ICU admission (SMD: 0.57, 95% CI: 0.33–0.81; p < 0.001) and IMV support (SMD: 0.37, 95% CI: 0.03–0.71; p = 0.035). |
Reference | Study Design and Sample | Aim | Relevant Results |
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Gastrointestinal symptoms | |||
Lu et al., 2020 [16] | Observational study; 171 children with COVID-19; median age 6.7 years (range 1 day–15 years) |
Describe the epidemiologic characteristics, clinical features, and radiologic findings of children with COVID-19. | Children had a milder clinical course compared to adults. GI symptoms were not very common in children. 15 patients presented diarrhea (8.8%) and 11 (6.4%) vomiting. |
Garazzino et al., 2020 [17] | Observational multicentre study; 168 children with COVID-19. | Collect preliminary data on COVID-19 presentation in children | In children, GI symptoms were frequent (18%). |
Giacomet et al., 2020 [18] | Observational retrospective multicentre study; 127 children with COVID-19 | Explore the presence of GI symptoms in children with COVID-19 and the potential correlation between GI symptoms and severity of illness | GI symptoms were present in 28.3% of the children enrolled. COVID-19 severity was positively correlated with the presence of GI symptoms. |
Undernutrition | |||
Akseer et al., 2020 [63] | Review | Identify main risk factors for maternal and child undernutrition during the COVID-19 pandemic and provide guidance to reduce the consequent undernutrition | Children and mothers’ risk of undernutrition may be increase during the pandemic due to food insecurity/poor diet quality, reduced income/limited financial resources, restricted health services, interrupted education, unhealthy household environment. |
Headey et al., 2020 [69] | Global health projection study | Provide an overview on the impact of COVID-19 on childhood malnutrition and nutrition-related mortality using three different projection models. | Low- and middle-income countries are expected to have an average 7.9% decrease in the gross national income, which might associate to an increase in moderate to severe wasting (chronic malnutrition) in children (up to 14.3%). Together with a projected year average reduction in nutrition and health services coverage of about 25% such event may lead to about 128,605 additional death in children <5 years during 2020. |
Roberton et al., 2020 [70] | Global health projection study | Estimate the additional child (<5 years) and maternal deaths resulting from potential health systems disruption and decreased access to food. | A reduction by 9.8–51.9% of the coverage of essential maternal and child health interventions might result in increased prevalence of wasting by 10–50% and additional child and maternal death in 2020. |
Obesity/Overweight | |||
Nogueira-de-Almeida et al., 2020 [20] | Clinical review | Examine the factors contributing to increased COVID-19 susceptibility and severity in obese children and adolescents. | Obesity related risk factors such as chronic subclinical inflammation, impaired immune response, and association with communicable diseases may explain the increased evidence of higher severity and mortality rate for COVID-19 in the adult as well as in the young population. |
Storz, 2020 [73] | Review | Present supporting evidence that the COVID-19 pandemic will aggravate the childhood obesity | Through multiple factors (lockdown and movement restrictions, quarantine, home-confinement, and social distancing, school closures, pandemic insecurity and economic hardship) COVID-19 will create an obesogenic environment, increasing childhood obesity |
Browne et al., 2020 [14] | Report | Address the impact of COVID-19 on children with obesity and propose potential interventions to reduce the negative outcome. | Children with obesity may face biopsychosocial risks during COVID-19, which may lead to stress and consequent impaired inflammation and immune response to COVID-19 Access to timely, comprehensive healthcare is critical during the pandemic. |
Leon-Abarca, 2020 [4] | Observational study; 21,161 subjects under 18 years old | Identify risk factors and pre-existing conditions associated with COVID-19 illness in childhood. | Obesity (3.1%) was among the most common pre-existing condition in children with COVID-19. Children with obesity had 4.5-fold probability of presenting pneumonia and 2.5-fold probability of being hospitalized. |
Kass et al., 2020 [5] | Observational study; 265 COVID-19 patients admitted to hospital |
Investigate the correlation between BMI and age in COVID-19 patients admitted to the ICU | Significant inverse correlation between age and BMI was observed, suggesting that younger individuals with COVID-19 admitted to hospital and those requiring ICU support are more likely to be obese. |
Zhang et al., 2020 [6] | Observational retrospective study; 53 young patients (20 to 45 years). |
Examine the risk factors of mortality in young patients with COVID-19 with specific attention to the relationships between obesity and COVID-19 mortality. | In young patients, obesity (high BMI) was strongly associated with high risk of mortality for SARS-CoV-2 infection. In addition, aggravated inflammatory response, enhanced cardiac injury and increased coagulation activity were also reported as contributing mechanism to the high mortality, compared to the COVID-19 survivor counterpart. |
Deng et al., 2020 [7] | Observational retrospective study; 65 COVID-19 hospitalized patients aged 18 to 40 years | Explore the indicators for COVID-19 severity in young patients aged 18 to 40 years. | In young adults, severe COVID-19 cases had higher BMI compared to moderate cases (average 29.23 vs. 22.79 kg/m2, p < 0.01). |
An R., 2020 [74] | National health projection study |
Project the impact of the COVID-19 pandemic on childhood obesity by simulating the BMI z-score trajectory of a representative cohort under a control scenario without COVID-19 or under 4 alternative scenarios with COVID-19. | Relative to the control scenario without COVID-19, scenarios 1, 2, 3, and 4 were associated with an increase in the mean BMI z-score |
This entry is adapted from the peer-reviewed paper 10.3390/nu13051616