Can reduction in infection and mortality rates from coronavirus be explained by an obesity survival paradox? An analysis at the US statewide level

Influence of obesity on mortality, mechanical ventilation time and mobility of critical patients with COVID-19

OBJECTIVE

To identify the influence of obesity on mortality, time to weaning from mechanical ventilation and mobility at intensive care unit discharge in patients with COVID-19.

METHODS

This retrospective cohort study was carried out between March and August 2020. All adult patients admitted to the intensive care unit in need of ventilatory support and confirmed to have COVID-19 were included. The outcomes included mortality, time on mechanical ventilation, and mobility at intensive care unit discharge.

RESULTS

Four hundred and twenty-nine patients were included, 36.6% of whom were overweight and 43.8% of whom were obese. Compared with normal body mass index patients, overweight and obese patients had lower mortality (p = 0.002) and longer intensive care unit survival (log-rank p < 0.001). Compared with patients with a normal body mass index, overweight patients had a 36% lower risk of death (p = 0.04), while patients with obesity presented a 23% lower risk (p < 0.001). There was no association between obesity and time on mechanical ventilation. The level of mobility at intensive care unit discharge did not differ between groups and showed a moderate inverse correlation with length of stay in the intensive care unit (r = -0.461; p < 0.001).

CONCLUSION

Overweight and obese patients had lower mortality and higher intensive care unit survival rates. The duration of mechanical ventilation and mobility level at intensive care unit discharge did not differ between the groups.

Is obesity a risk factor for melanoma?

OBJECTIVES

Are twofold: 1) to estimate the relationship between obesity (BMI ≥30) and the prevalence of melanoma in different US states and 2) to examine the possibility of defining a new risk group. This might enhance the possibility of detection, which in turn, might increase the survival rates of patients.

STUDY DESIGN

A cohort Study, based on data at the US statewide level in 2011-2017, where the dependent variable (the annual new melanoma cases per 100,000 persons) is adjusted for age.

METHOD

Quadratic regression analysis. This model permits a non-monotonic variation of obesity with new melanoma cases adjusted for age, where the control variable is the level of UV radiation.

RESULTS

Demonstrate a negative correlation between obesity and incidence of melanoma. This outcome is further corroborated for Caucasians.

CONCLUSIONS

We should continue to establish primary prevention of melanoma by raising photo protection awareness and secondary prevention by promoting skin screening (by physician or self) among the entire population group in all BMI ranges. Advanced secondary melanoma prevention including noninvasive diagnosis strategies including total body photography, confocal microscopy, AI strategies should focus the high-risk sub group of Caucasians with BMI < 30.

Association of body mass index with COVID-19 related in-hospital death

BACKGROUND

Patients with extreme body mass indices (BMI) could have an increased risk of death while hospitalized for COVID-19.

METHODS

The database of the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) was used to assess the time to in-hospital death with competing-risks regression by sex and between the categories of BMI.

RESULTS

Data from 12,137 patients (age 60.0 ± 16.2 years, 59% males, BMI 29.4 ± 6.9 kg/m2) of 48 countries were available. By univariate analysis, underweight patients had a higher risk of mortality than the other patients (sub-hazard ratio (SHR) 1.75 [1.44-2.14]). Mortality was lower in normal (SHR 0.69 [0.58-0.85]), overweight (SHR 0.53 [0.43-0.65]) and obese (SHR 0.55 [0.44-0.67]) than in underweight patients. Multivariable analysis (adjusted for age, chronic pulmonary disease, malignant neoplasia, type 2 diabetes) confirmed that in-hospital mortality of underweight patients was higher than overweight patients (females: SHR 0.63 [0.45-0.88] and males: 0.69 [0.51-0.94]).

CONCLUSION

Even though these findings do not imply changes in the medical care of hospitalized patients, they support the use of BMI category for the stratification of patients enrolled in interventional studies where mortality is recorded as an outcome.

Effect of Obesity among Hospitalized Cancer Patients with or without COVID-19 on a National Level

Cancer and obesity are well-known prognostic factors in COVID-19. Our objective was to study the effect of obesity (and its severity) on the risk of intensive care unit (ICU) admission, severe complications, and in-hospital mortality, in a population of cancer patients hospitalized with or without COVID-19. All patients hospitalized in France for cancer from 1 March 2020 to 28 February 2022 were included from the French national administrative database. The effect of obesity was estimated in COVID-19 and in non-COVID-19 cancer patients using logistic and survival regressions, taking into account age, sex, comorbidities, and different types of cancer. Among the 992,899 cancer patients, we identified 53,090 patients with COVID-19 (5.35%), of which 3260 were obese (6.1%). After adjustment, for patients with or without COVID-19, there is an increased risk of ICU admission or severe complications in obese patients, regardless of the type of obesity. Regarding in-hospital mortality, there is no excess risk associated with overall obesity. However, massive obesity appears to be associated with an increased risk of in-hospital mortality, with a significantly stronger effect in solid cancer patients without COVID-19 and a significantly stronger effect in hematological cancer patients with COVID-19. This study showed that in France, among hospitalized patients with cancer and with or without COVID-19, increased vigilance is needed for obese patients, both in epidemic and non-epidemic periods. This vigilance should be further strengthened in patients with massive obesity for whom the risk of in-hospital mortality is higher, particularly in epidemic periods for patients with hematological cancers.

Obesity Impact on SARS-CoV-2 Infection: Pros and Cons "Obesity Paradox"-A Systematic Review

BACKGROUND

During the last years, the COVID-19 pandemic meets the pandemic generated by obesity, raising many questions regarding the outcomes of those with severe forms of infection.

METHODS

The present systematic review summarises and analyses the data providing evidence for or against the "obesity-paradox" in COVID-19 patients. After applying the inclusion and exclusion criteria, 23 studies were included. We also analysed the presumably underlying basic mechanisms.

RESULTS

The patients with a body mass index (BMI) of 30-40 kg/m2 presented severe symptoms that led to intensive care unit (ICU) admission but not increased death rate. Those with a higher degree of obesity, with a BMI higher than 40 kg/m2, led to a rise in the death rate, particularly in young patients. Obesity was associated with a higher rate of ICU admission but was not determined as an independent predictor of increased mortality. In contrast, some studies suggest a strong association between obesity or morbid obesity and the risk of death.

CONCLUSIONS

The existence of "obesity-paradox" cannot be stated; our study presents obesity as a critical risk factor in the evolution of COVID-19.

To lockdown or not against COVID19: Can the power of education provide the answer?

Global education is a well-known positive externality associated with children-parents knowledge spillover. More education may also lead to increased communication among family members regarding health knowledge and skills acquired at or after school, positively affecting health behavior. One important aspect that should be considered by policy makers is the potential promotion of social behavior adapted to the COVID2019 pandemic via the education system. The current study attempts to investigate the relationships between infection and recovery rates from coronavirus and the educational achievement of the population at the US statewide level. Based on the ranking of US States (including US sponsored areas) according to the percent of the population that completed high school and above from the top (93%) to the bottom (68.9%), findings suggest that as the level of educational achievement drops, projected infection rates rise and projected recovery rates drop. Research findings demonstrate the importance of educational achievement in addressing the coronavirus pandemic. Specifically, avoiding closings and opening the school systems under the appropriate limitations may have the long-run effect of children-parents knowledge spillover regarding the COVID19 pandemic. This, in turn, might promote public re-education and spread the adoption of desirable social behavior under conditions of COVID19 pandemic, such as, social distancing and wearing masks.

Can Obesity Prevalence Explain COVID-19 Indicators (Cases, Mortality, and Recovery)? A Comparative Study in OECD Countries

SARS-CoV-2 virus disease (COVID-19) is declared a global pandemic with multiple risk factors. Obesity is considered by several researchers as one of the serious risk factors for SARS-CoV-2 virus complications based on recent empirical studies. Yet, other scholars argue in favor of the existence of an obesity survival paradox and criticize the former group of studies on the grounds that they lack controls for race, socioeconomic status, or quality of care. The objective of the current study is to analyze the potential relationships between different SARS-CoV-2 virus indicators and obesity on a country-wide level based on an OECD report. In an attempt to test the counterintuitive possibility of an obesity survival paradox, the proposed empirical model relaxes the assumption of monotonic change by applying the quadratic design and testing which one of the two competing models (i.e., quadratic or linear) better fits the data. Findings suggest more complex relationships between SARS-CoV-2 virus indices and obesity rates than previously thought. Consequently, ethical guidelines referring to priority in intubation and intensive care treatments-published by the Israeli Ministry of Health in April 2020-should account for these complex relationships between obesity and SARS-CoV-2 virus. Indeed, there is a linear increase in mortality rate from SARS-CoV-2 virus with an elevated prevalence of obesity. Yet, other indicators, such as the number of infected per 10,00,000 persons, rates of severe SARS-CoV-2 virus cases, rates of recovered SARS-CoV-2 virus patients, and SARS-CoV-2 virus, as the cause of death exhibit quadratic, rather than linear, patterns. The reasons for these nonlinear patterns might be explained by several conditions such as increased metabolic reserves, more aggressive treatment, other non-SARS-CoV-2 virus complications for obese persons, and unidentified factors that should be examined in future research.

The fatter, the better in old age: the current understanding of a difficult relationship

PURPOSE OF REVIEW

Obesity has shown a protective effect on mortality in older adults, also known as the obesity paradox, but there are still controversies about this relationship.

RECENT FINDINGS

Recent studies have shown a J or U-shaped relationship between BMI and mortality, wherein an optimal range is described between 22 and 37 kg/m2 depending on the condition. Many mechanisms can explain this protective effect of higher BMI, fat/muscle mass storage, more aggressive treatment in obese individuals, loss of bone mineral content and selection bias. However, BMI must be used with caution due to its limitations to determine body composition and fat distribution.

SUMMARY

Although BMI is an easy tool to evaluate obesity, its protective effect may be present to certain extend, from normal range to class I obesity (BMI 30-34.9 kg/m2), but then it becomes detrimental. Skeletal muscle mass and muscle function associated with adipose tissue assessment can add valuable information in the risk stratification. Further studies should be performed prospectively, adjust BMI for cofounding variable and consider other elderly subpopulations. To promote healthy ageing, excessive fat mass should be avoided and maintenance or improvement of skeletal muscle mass and muscle function should be stimulated in older adults.

COVID-19, body mass index and cholesterol: an ecological study using global data

Background

Coronavirus disease 2019 (COVID-19) is now globally considered a serious economic, social and health threat. A wide range of health related factors including Body Mass Index (BMI) is reported to be associated with the disease. In the present study, we analyzed global databases to assess the correlation of BMI and cholesterol with the risk of COVID-19.

Methods

In this ecological study, we used age-standardized BMI and cholesterol levels as well as the incidence and mortality ratio of COVID-19 at the national-levels obtained from the publicly available databases such as the World Health Organization (WHO) and NCD Risk Factor Collaboration (NCD-RisC). Bivariate correlation analysis was applied to assess the correlations between the study variables. Mean differences (standard deviation: SD) of BMI and cholesterol levels of different groups were tested using independent sample t-test or Mann–Whitney rank test as appropriate. Multivariable linear regression analysis was performed to identify variables affecting the incidence and mortality ratio of COVID-19.

Results

Incidence and mortality ratio of COVID-19 were significantly higher in developed (29,639.85 ± 20,210.79 for cases and 503.24 ± 414.65 for deaths) rather than developing (8153.76 ± 11,626.36 for cases and 169.95 ± 265.78 for deaths) countries (P < 0.01). Results indicated that the correlations of BMI and cholesterol level with COVID-19 are stronger in countries with younger population. In general, the BMI and cholesterol level were positively correlated with COVID-19 incidence ratio (β = 2396.81 and β = 30,932.80, p < 0.01,‌ respectively) and mortality ratio (β = 38.18 and β = 417.52, p < 0.05,‌ respectively) after adjusting for socioeconomic and demographic factors.

Conclusion

Countries with higher BMI or cholesterol at aggregate levels had a higher ratios of COVID-19 incidence and mortality. The aggregated level of cholesterol and BMI are important risk factors for COVID-19 major outcomes, especially in developing countries with younger populations. We recommend monitoring and promotion of health indicices to better prevent morbidity and mortality of COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11715-7.

Body mass index and severity/fatality from coronavirus disease 2019: A nationwide epidemiological study in Korea

OBJECTIVE

Obesity has been reported as a risk factor for severe coronavirus disease 2019 (COVID-19) in recent studies. However, the relationship between body mass index (BMI) and COVID-19 severity and fatality are unclear.

RESEARCH DESIGN AND METHODS

This study included 4,141 COVID-19 patients who were released from isolation or had died as of April 30, 2020. This nationwide data was provided by the Korean Centers for Disease Control and Prevention Agency. BMI was categorized as follows; < 18.5 kg/m2, 18.5-22.9 kg/m2, 23.0-24.9 kg/m2, 25.0-29.9 kg/m2, and ≥ 30 kg/m2. We defined a fatal illness if the patient had died.

RESULTS

Among participants, those with a BMI of 18.5-22.9 kg/m2 were the most common (42.0%), followed by 25.0-29.9 kg/m2 (24.4%), 23.0-24.9 kg/m2 (24.3%), ≥ 30 kg/m2 (4.7%), and < 18.5 kg/m2 (4.6%). In addition, 1,654 (41.2%) were men and 3.04% were fatalities. Multivariable analysis showed that age, male sex, BMI < 18.5 kg/m2, BMI ≥ 25 kg/m2, diabetes mellitus, chronic kidney disease, cancer, and dementia were independent risk factors for fatal illness. In particular, BMI < 18.5 kg/m2 (odds ratio [OR] 3.97, 95% CI 1.77-8.92), 25.0-29.9 kg/m2 (2.43, 1.32-4.47), and ≥ 30 kg/m2 (4.32, 1.37-13.61) were found to have higher ORs than the BMI of 23.0-24.9 kg/m2 (reference). There was no significant difference between those with a BMI of 18.5-22.9 kg/m2 (1.59, 0.88-2.89) and 23.0-24.9 kg/m2.

CONCLUSIONS

This study demonstrated a non-linear (U-shaped) relationship between BMI and fatal illness. Subjects with a BMI of < 18.5 kg/m2 and those with a BMI ≥ 25 kg/m2 had a high risk of fatal illness. Maintaining a healthy weight is important not only to prevent chronic cardiometabolic diseases, but also to improve the outcome of COVID-19.

Some Questions to Our Chinese Colleagues Pioneering Research Into Coronavirus Disease 2019 (COVID-19)

A pandemic has developed, so physicians worldwide are particularly interested in the experiences of their Chinese Colleagues which are frequently cited. To assess the long-term pulmonary, cardiac, neurologic, and psychiatric consequences after COVID-19, the outcome of patients included in the early publications and the association with baseline findings is of particular interest. Thus, we review the methods of early Coronavirus disease 2019 (COVID-19) publications. Reports published before March 19th 2020, comprising >40 patients were included, considering especially cardiologic aspects. It remains unclear whether patients were described several times, or they were different patients. Only patients with confirmed COVID-19 were described, and no differences in findings of patients with initially suspected and later confirmed, or excluded infection. It remains unclear in how many cases information was missing, since missing values were not reported. Medication before hospital admission, level of education and occupation, household size and composition, weight or body mass index are lacking. No details about electrocardiographic findings are given. Patients still in follow-up, constituting the major part of observations, were excluded. The data should be re-analyzed. A comparison between confirmed and excluded cases could be carried out. By now, in November 2020, the reported patients will most probably have recovered. Thus, it would be possible to differentiate prognostic indicators more precisely. Laboratory tests and electrocardiograms could be analyzed in more detail to shed light on the spectrum of this disease and to solve some of the unanswered questions related with COVID-19.