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

Associations between COVID-19 incidence, weight status, and social participation restrictions in the U.S.: evidence from the national population, cross-sectional study

BACKGROUND

To explore the associations between coronavirus infection incidence and weight status and social participation restrictions among community-dwelling adults in the United States.

METHODS

We analyzed data from the 2021 National Health Interview Survey (NHIS), which included a representative sample of 29,394 individuals (Coronavirus disease 2019 (COVID-19): 3,205) and a weighted total of 252,461,316 individuals (COVID-19: 31,697,404), considering the complex sampling design used in the survey.

RESULTS

Age, race/ethnicity, education level, family income index, body mass index (BMI), and smoking status were significantly associated with COVID-19 infection. Weight status was significantly correlated with social participation restrictions and strongly associated with COVID-19 infection, particularly among individuals who were overweight or obese.

CONCLUSION

Weight status was shown to be associated not only with social participation restrictions but also with COVID-19 infection among U.S. adults. Understanding the complex interplay between weight status, social participation, and COVID-19 is crucial for developing effective preventive measures and promoting overall well-being in the community population.

Limited efficacy of low-dose dexamethasone for the treatment of severe COVID-19 pneumonia: A retrospective study

BACKGROUND

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2. Its symptoms range from mild to severe, with the latter often being life-threatening. This study aims to assess the effects of low-dose dexamethasone (DEX) in mild-to-severe COVID-19 pneumonia and examine the final clinical outcomes to identify the optimal therapeutic dose.

METHODS

Clinical data from 132 patients hospitalized for COVID-19 pneumonia between January and October 2021 at Yamato Municipal Hospital were retrospectively analyzed. Based on the ratio of peripheral arterial oxygen saturation (SpO2) to inspired fraction of oxygen (FiO2), patients were categorized into the mild (>450, n = 65), moderate (315-450, n = 55), and severe (<315, n = 12) pneumonia groups. The event of interest was defined as the worsening of the patient's condition during treatment (need to increase FiO2 > 0.1). Patients were treated with low-dose DEX (6.6 mg/day) for 10 days.

RESULTS

The event-free survival rate decreased significantly in patients with severe pneumonia compared with in those with mild and moderate pneumonia (Bonferroni-adjusted p < 0.02). A total of 16 patients were treated with high-dose corticosteroids because of severe hypoxia. Recovery was observed in all discharged patients with respiratory condition improvement. Low SpO2/FiO2 at admission was significantly associated with serum C-reactive protein levels.

CONCLUSIONS

For Japanese patients with COVID-19, severe pneumonia, and SpO2/FiO2 of <315, it may be necessary to administer a dose of corticosteroids of >6.6 mg DEX.

Changes in Food Consumption, BMI, and Body Composition in Youth in the US during the COVID-19 Pandemic

Rates of childhood overweight/obesity have risen for decades; however, data show the prevalence increased at a faster rate during the COVID-19 pandemic. Pandemic-associated increases in youth's body mass index (BMI; kg/m2) have been attributed to decreases in reported physical activity; few studies have examined changes in food intake. We therefore examined changes in total energy, nutrient consumption, BMI, BMIz, and adiposity longitudinally over 3 years, comparing healthy youth aged 8-17 years assessed twice prior to the pandemic, to youth seen once before and once during the pandemic. The total energy intake and percent macronutrient consumption were assessed using a standardized, laboratory-based, buffet-style meal. Height and weight were measured and adiposity was collected via dual energy X-ray absorptiometry. Generalized linear model univariate analyses investigated differences between groups. One-hundred-fifteen youth (15.6 + 2.8 years 47.8% female; 54.8% White) from the Washington D.C., Maryland, and Virginia greater metropolitan area participated. In this secondary analysis, neither changes in total energy intake (p = 0.52) nor changes in nutrient consumption were significantly different between the two groups (ps = 0.23-0.83). Likewise, changes in BMI, BMIz, and adiposity (ps = 0.95-0.25) did not differ by group. Further research should investigate food intake and body composition, comparing youth with and without overweight/obesity to better identify those at greatest risk of excess weight gain during the pandemic.

Thought Believability and Anxious Feelings about COVID-19: A Case-Control Study in Northeastern Iran

Background

Believability and thoughts are considered as the pillars of behaviors over time, and anxious feelings are a risk factor for mental disorders, especially during the coronavirus disease (COVID-19) pandemic. This study aimed to explore the thought believability and anxious feelings of COVID-19 among infected and healthy families.

Methods

In this hospital-based matched case-control study, health surveillance files of COVID-19 patients were collected from January to June 2021 and were analyzed statistically. In this study, two questionnaires of demographic characteristics and the Believability of Anxious Feelings and Thoughts (BAFT) were used. Data were analyzed using the One-way ANOVA.

Results

Of 600 participants, 300 (50%) were PCR-confirmed and 300 (50%) were non-infected. Overall, 163 (54.33%) of infected people were male, 146 (48.67%) single, and 156 (52.00%) government employees. The results showed that the mean scores of physical anxiety (PA) and negative evaluation (NE) in the case group is significantly higher than the control group (P = 0.001); while emotional regulation (ER) in the control group was significantly higher than the case group (P = 0.001).

Conclusion

Having high believability to the risks of COVID-19 may be a predictor of preventive behaviors in individuals. Worrying about COVID-19 can increase the perceived risk of a pandemic in societies and consequence, increase the general public health.

Prerequisite for COVID-19 Prediction: A Review on Factors Affecting the Infection Rate

Since the year 2020, coronavirus disease 2019 (COVID-19) has emerged as the dominant topic of discussion in the public and research domains. Intensive research has been carried out on several aspects of COVID-19, including vaccines, its transmission mechanism, detection of COVID-19 infection, and its infection rate and factors. The awareness of the public related to the COVID-19 infection factors enables the public to adhere to the standard operating procedures, while a full elucidation on the correlation of different factors to the infection rate facilitates effective measures to minimize the risk of COVID-19 infection by policy makers and enforcers. Hence, this paper aims to provide a comprehensive and analytical review of different factors affecting the COVID-19 infection rate. Furthermore, this review analyses factors which directly and indirectly affect the COVID-19 infection risk, such as physical distance, ventilation, face masks, meteorological factor, socioeconomic factor, vaccination, host factor, SARS-CoV-2 variants, and the availability of COVID-19 testing. Critical analysis was performed for the different factors by providing quantitative and qualitative studies. Lastly, the challenges of correlating each infection risk factor to the predicted risk of COVID-19 infection are discussed, and recommendations for further research works and interventions are outlined.

COVID-19, Non-Communicable Diseases, and Behavioral Factors in the Peruvian Population ≥ 15 Years: An Ecological Study during the First and Second Year of the COVID-19 Pandemic

A range of health-related and behavioral risk factors are associated with COVID-19 incidence and mortality. In the present study, we assess the association between incidence, mortality, and case fatality rate due to COVID-19 and the prevalence of hypertension, obesity, overweight, tobacco and alcohol use in the Peruvian population aged ≥15 years during the first and second year of the COVID-19 pandemic. In this ecological study, we used the prevalence rates of hypertension, overweight, obesity, tobacco, and alcohol use obtained from the Encuesta Demográfica y de Salud Familiar (ENDES) 2020 and 2021. We estimated the crude incidence and mortality rates (per 100,000 habitants) and case fatality rate (%) of COVID-19 in 25 Peruvian regions using data from the Peruvian Ministry of Health that were accurate as of 31 December 2021. Spearman correlation and lineal regression analysis was applied to assess the correlations between the study variables as well as multivariable regression analysis adjusted by confounding factors affecting the incidence and mortality rate and case fatality rate of COVID-19. In 2020, adjusted by confounding factors, the prevalence rate of obesity (β = 0.582; p = 0.037) was found to be associated with the COVID-19 mortality rate (per 100,000 habitants). There was also an association between obesity and the COVID-19 case fatality rate (β = 0.993; p = 0.014). In 2021, the prevalence of obesity was also found to be associated with the COVID-19 mortality rate (β = 0.713; p = 0.028); however, adjusted by confounding factors, including COVID-19 vaccination coverage rates, no association was found between the obesity prevalence and the COVID-19 mortality rate (β = 0.031; p = 0.895). In summary, Peruvian regions with higher obesity prevalence rates had higher COVID-19 mortality and case fatality rates during the first year of the COVID-19 pandemic. However, adjusted by the COVID-19 vaccination coverage, no association between the obesity prevalence rate and the COVID-19 mortality rate was found during the second year of the COVID-19 pandemic.

Discrepancy between biomarkers of lung injury and 1-year mortality in COVID-19

BACKGROUND

COVID-19 global pandemic started in late 2019 with the first wave. In this cross-sectional and observational study, we evaluated the associations between the biomarkers, COVID-19 pneumonia severity and 1-year mortality.

METHODS

A sample of 276 polymerase chain reaction (PCR)-positive patients for SARS-CoV-2 was included. Computerized tomography severity score (CT-SS) was used to assess the severity of COVID-19 pneumonia in 222 cases. Multivariate analyses were performed to find the predictors of CT-SS, severe CT-SS (≥20) and 1-year mortality. Biomarkers of ferritin, high-sensitive C-reactive protein (CRP), lactate dehydrogenase (LDH), cardiac troponin (cTn), neutrophil-to-lymphocyte ratio (NLR), uric acid (UA) and d-dimer were routinely measured.

RESULTS

Severe CT-SS (>20) was observed in 86 (31.2%) cases. Mortality was observed in 75 (27.2%) patients at 1 year. LDH displayed the highest predictive accuracy for severe CT-SS (AUC 0.741, sensitivity = 81% and specificity = 68%, cut-off value: 360 mg/dl). Linear regression analysis displayed that LDH predicted CT-SS [B = 11 (95% CI for B = 5-17, p < .001)]. Age was the most significant parameter that was associated with severe CT-SS (OR 0.96, 95% CI 0.92-0.99, p = .015). d-dimer was the only biomarker that predicted with 1-year mortality (OR 1.62, 95% CI 1.08-2.42, p = .020).

CONCLUSION

LDH is a sensitive and specific biomarker to determine patients with severe lung injury in COVID-19. d-dimer is the only biomarker that predicts 1-year mortality. Neither LDH nor CT-SS is associated with 1-year mortality.

COVID-19 and Lipid Disorders

An elevated cholesterol concentration has been suspected to increase the susceptibility for SARS-COV-2 infection. Cholesterol plays a central role in the mechanisms of the SARS-COV-2 infection. In contrast, higher HDL-cholesterol levels seem to be protective. During COVID-19 disease, LDL-cholesterol and HDL-cholesterol appear to be decreased. On the other hand, triglycerides (also in different lipoprotein fractions) were elevated. Lipoprotein(a) may increase during this disease and is most probably responsible for thromboembolic events. This lipoprotein can induce a progression of atherosclerotic lesion formation. The same is suspected for the SARS-COV-2 infection itself. COVID-19 patients are at increased risk of incident cardiovascular diseases, including cerebrovascular disorders, dysrhythmias, ischemic and non-ischemic heart disease, pericarditis, myocarditis, heart failure, and thromboembolic disorders. An ongoing lipid-lowering therapy, including lipoprotein apheresis, is recommended to be continued during the COVID-19 disease, though the impact of lipid-lowering drugs or the extracorporeal therapy on prognosis should be studied in further investigations.

Analysis of Excess All-Cause Mortality and COVID-19 Mortality in Peru: Observational Study

During the COVID-19 pandemic, an excess of all-cause mortality has been recorded in several countries, including Peru. Most excess deaths were likely attributable to COVID-19. In this study, we compared the excess all-cause mortality and COVID-19 mortality in 25 Peruvian regions to determine whether most of the excess deaths in 2020 were attributable to COVID-19. Excess deaths were calculated as the difference between the number of observed deaths from all causes during the COVID-19 pandemic (in 2020) and the number of expected deaths in 2020 based on a historical from recent years (2017–2019). Death data were retrieved from the Sistema Informatico Nacional de Defunciones (SINADEF) at the Ministry of Health of Peru from January 2017 to December 2020. Population counts were obtained from projections from Peru’s Instituto Nacional de Estadística e Informática (INEI). All-cause excess mortality and COVID-19 mortality were calculated by region per 100,000 population. Spearman’s test and linear and multiple regression models were used to estimate the correlation between excess all-cause mortality and COVID-19 mortality per 100,000 population. Excess all-cause death rates varied widely among regions (range: 115.1 to 519.8 per 100,000 population), and COVID-19 mortality ranged between 83.8 and 464.6 per 100,000 population. There was a correlation between the all-cause excess mortality and COVID-19 mortality (r = 0.90; p = 0.00001; y = 0.8729x + 90.808; R² = 0.84). Adjusted for confounding factors (mean age in the region, gender balance, and number of intensive care unit (ICU) beds), the all-cause excess mortality rate was correlated with COVID-19 mortality rate (β = 0.921; p = 0.0001). These findings suggest that most of the excess deaths in Peru are related to COVID-19. Therefore, these findings can help decision-makers to understand the high COVID-19 mortality rates in Peru.

Associations Between Gestational Weight Gain and Adverse Birth Outcomes: A Population-Based Retrospective Cohort Study of 9 Million Mother-Infant Pairs

Background

Gestational weight gain (GWG) reflects maternal nutrition during pregnancy. However, the associations between maternal GWG and adverse birth outcomes are inconclusive.

Objective

We aimed to examine the associations between maternal GWG and adverse birth outcomes according to maternal pre-pregnancy body mass index (BMI) categories in a large, multiethnic and diverse population in the U.S.

Study Design

We used nationwide birth certificate data from the National Vital Statistics System to examine the association of GWG (below, within and above the Institute of Medicine [IOM] guidelines) with six adverse birth outcomes (preterm birth, low birthweight, macrosomia, small for gestational age [SGA], large for gestational age [LGA], and low Apgar score) according to the pre-pregnancy BMI categories (underweight to obesity grade 3). Multivariable logistic regression analyses were performed to estimate the odds ratios (ORs) and 95% confidence intervals (CIs).

Results

A total of 9,191,842 women aged 18–49 years at delivery with live singleton births were included. Among them, 24.5% of women had GWG below IOM guidelines, 27.6% within the guidelines, and 47.9% above the guidelines. Compared with maternal GWG within guidelines, GWG below guidelines was associated with higher odds of preterm birth (OR = 1.52, 95%CI = 1.51–1.53), low birthweight (OR = 1.46, 95%CI = 1.45–1.47) and SGA (OR = 1.44, 95%CI = 1.43–1.45). In contrast, maternal GWG above guidelines was associated with higher odds of macrosomia (OR = 2.12, 95%CI = 2.11–2.14) and LGA (OR = 2.12, 95%CI = 2.11–2.14). In addition, maternal GWG below or above guidelines had slightly higher odds of low Apgar score (below guidelines: OR = 1.04, 95%CI = 1.03–1.06, above guidelines: OR = 1.17, 95%CI = 1.15–1.18). The results were largely similar among women with GWG below or above guidelines across pre-pregnancy BMI categories of underweight, overweight, and obesity grade 1 to grade 3.

Conclusion

Pregnant women with GWG below or above the IOM guidelines have increased odds of selected adverse infant birth outcomes. Monitoring maternal GWG could enable physicians to provide tailored nutrition and exercise advice as well as prenatal care to pregnant women to reduce the likelihood of adverse birth outcomes.

Regression Analysis for COVID-19 Infections and Deaths Based on Food Access and Health Issues

COVID-19, or SARS-CoV-2, is considered as one of the greatest pandemics in our modern time. It affected people's health, education, employment, the economy, tourism, and transportation systems. It will take a long time to recover from these effects and return people's lives back to normal. The main objective of this study is to investigate the various factors in health and food access, and their spatial correlation and statistical association with COVID-19 spread. The minor aim is to explore regression models on examining COVID-19 spread with these variables. To address these objectives, we are studying the interrelation of various socio-economic factors that would help all humans to better prepare for the next pandemic. One of these critical factors is food access and food distribution as it could be high-risk population density places that are spreading the virus infections. More variables, such as income and people density, would influence the pandemic spread. In this study, we produced the spatial extent of COVID-19 cases with food outlets by using the spatial analysis method of geographic information systems. The methodology consisted of clustering techniques and overlaying the spatial extent mapping of the clusters of food outlets and the infected cases. Post-mapping, we analyzed these clusters' proximity for any spatial variability, correlations between them, and their causal relationships. The quantitative analyses of the health issues and food access areas against COVID-19 infections and deaths were performed using machine learning regression techniques to understand the multi-variate factors. The results indicate a correlation between the dependent variables and independent variables with a Pearson correlation R2-score = 0.44% for COVID-19 cases and R2 = 60% for COVID-19 deaths. The regression model with an R2-score of 0.60 would be useful to show the goodness of fit for COVID-19 deaths and the health issues and food access factors.

Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world

In the present paper, we aimed to determine the influence of various non-pharmaceutical interventions (NPIs) enforced during the first wave of COVID-19 across countries on the spreading rate of COVID-19 during the second wave. For this purpose, we took into account national-level climatic, environmental, clinical, health, economic, pollution, social, and demographic factors. We estimated the growth of the first and second wave across countries by fitting a logistic model to daily-reported case numbers, up to the first and second epidemic peaks. We estimated the basic and effective (second wave) reproduction numbers across countries. Next, we used a random forest algorithm to study the association between the growth rate of the second wave and NPIs as well as pre-existing country-specific characteristics. Lastly, we compared the growth rate of the first and second waves of COVID-19. The top three factors associated with the growth of the second wave were body mass index, the number of days that the government sets restrictions on requiring facial coverings outside the home at all times, and restrictions on gatherings of 10 people or less. Artificial intelligence techniques can help scholars as well as decision and policy-makers estimate the effectiveness of public health policies, and implement "smart" interventions, which are as efficacious as stringent ones.

Air quality index variation before and after the onset of COVID-19 pandemic: a comprehensive study on 87 capital, industrial and polluted cities of the world

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic provided an opportunity for the environment to reduce ambient pollution despite the economic, social and health disruption to the world. The purpose of this study was to investigate the changes in the air quality indexes (AQI) in industrial, densely populated and capital cities in different countries of the world before and after 2020. In this ecological study, we used AQI obtained from the free available databases such as the World Air Quality Index (WAQI). Bivariate correlation analysis was used to explore the correlations between meteorological and AQI variables. Mean differences (standard deviation: SD) of AQI parameters of different years were tested using paired-sample t-test or Wilcoxon signed-rank test as appropriate. Multivariable linear regression analysis was conducted to recognize meteorological variables affecting the AQI parameters.

RESULTS

AQI-PM2.5, AQI-PM10 and AQI-NO2 changes were significantly higher before and after 2020, simultaneously with COVID-19 restrictions in different cities of the world. The overall changes of AQI-PM2.5, AQI-PM10 and AQI-NO2 in 2020 were - 7.36%, - 17.52% and - 20.54% compared to 2019. On the other hand, these results became reversed in 2021 (+ 4.25%, + 9.08% and + 7.48%). In general, the temperature and relative humidity were inversely correlated with AQI-PM2.5, AQI-PM10 and AQI-NO2. Also, after adjusting for other meteorological factors, the relative humidity was inversely associated with AQI-PM2.5, AQI-PM10 and AQI-NO2 (β = - 1.55, β = - 0.88 and β = - 0.10, P < 0.01, respectively).

CONCLUSIONS

The results indicated that air quality generally improved for all pollutants except carbon monoxide and ozone in 2020; however, changes in 2021 have been reversed, which may be due to the reduction of some countries' restrictions. Although this quality improvement was temporary, it is an important result for planning to control environmental pollutants.