Obesity as a driver of international differences in COVID-19 death rates

Does sex modify the effect of pre-pandemic body mass index on the risk of Long COVID? Evidence from the longitudinal analysis of the Survey of Health, Ageing and Retirement in Europe

BACKGROUND

Research on Long COVID risk factors is ongoing. High body mass index (BMI) may increase Long COVID risk, yet no evidence has been established regarding sex differences in the relationship between BMI and the risk of Long COVID. Investigating the nature of this relationship was the main objective of this study.

METHODS

A population-based prospective study involving a sample of respondents aged 50 years and older (n = 4004) from 27 European countries that participated in the 2020 and 2021 Survey of Health, Ageing and Retirement in Europe's (SHARE) Corona Surveys and in Waves 7 and 8 of the main SHARE survey. Logistic regression models were estimated to produce unadjusted and adjusted estimates of the sex differences in the relationship between BMI and Long COVID.

RESULTS

Linear relationship for females, with probability of Long COVID increasing with BMI (68% at BMI = 18, 93% at BMI = 45). Non-linear relationship for males, with probability of Long COVID of 27% at BMI = 18, 68% at BMI = 33, and 40% at BMI = 45. Relationships remained significant after adjusting for known Long COVID risk factors (age and COVID-19 hospitalization), presence of chronic diseases, and respondents' place of residence.

CONCLUSION

Sex differences appear to play an important role in the relationship between BMI and risk of Long COVID. Overall, females were more likely to have Long COVID, regardless of their BMI. Males at the higher end of the BMI spectrum had a lower risk of Long COVID as opposed to their female counterparts. Sex-specific research is recommended for better understanding of Long COVID risk factors.

Childhood obesity prevention trials: A systematic review and meta-analysis on trial design and the impact of type 1 error

Effect sizes from previously reported trials are often used to determine the meaningful change in weight in childhood obesity prevention interventions because information on clinically meaningful differences is lacking. Estimates from previous trials may be influenced by statistical significance; therefore, it is important that they have a low risk of type 1 error. A systematic review and meta-analysis were conducted to report on the design of child obesity prevention randomized controlled trials and effectiveness according to risk of type 1 error. Eighty-four randomized controlled trials were identified. A large range of assumptions were applied in the sample size calculations. The most common primary outcome was BMI, with detectable effect size differences used in sample size calculations ranging from 0.25 kg/m2 (followed up at 2 years) to 1.1 kg/m2 (at 9 months) and BMI z-score ranging from 0.1 (at 4 years) to 0.67 (at 3 years). There was no consistent relationship between low risk of type 1 error and reports of higher or lower effectiveness. Further clarity of the size of a meaningful difference in weight in childhood obesity prevention trials is required to support evaluation design and decision-making for intervention and policy. Type 1 error risk does not appear to impact effect sizes in a consistent direction.

The politics of COVID-19: Differences between U.S. red and blue states in COVID-19 regulations and deaths

The study investigated infection variables and control strategies in 2020 and 2021 and their influence on COVID-19 deaths in the United States, with a particular focus on comparing red (Republican) and blue (Democratic) states. The analysis reviewed cumulative COVID-19 deaths per 100,000 by year, state political affiliation, and a priori latent factor groupings of mitigation strategies (lockdown days in 2020, mask mandate days, vaccination rates), social demographic variables (ethnicity, poverty rate), and biological variables (median age, obesity). Analyses first identified possible relationships between all assessed variables using K-means clustering for red, blue, and purple states. Then, a series of regression models were fit to assess the effects of mitigation strategies, social, and biological factors specifically on COVID-19 deaths in red and blue states. Results showed distinct differences in responding to COVID infections between red states to blue states, particularly the red states lessor adoption of mitigation factors leaving more sway on biological factors in predicting deaths. Whereas in blue states, where mitigation factors were more readily implemented, vaccinations had a more significant influence in reducing the probability of infections ending in death. Overall, study findings suggest politicalization of COVID-19 mitigation strategies played a role in death rates across the United States.

The effect of obesity on the mortality of hospitalized adults with COVID-19 considering the human development index: A systematic review and meta-analysis

The objective of this study is to verify the association between obesity and mortality in hospitalized patients with SARS-CoV-2 taking into account the Human Development Index (HDI). A search was performed in the PubMed, Virtual Health Library (Lilacs/Bireme/VHL Brazil), Embase, Web of Science, and Scopus databases from inception to May 2022. To be eligible, studies had to have cohort or case-control designs, be conducted with hospitalized adults (≥18 years old), and evaluate mortality rates between with obesity and without obesity individuals with SARS-CoV-2 confirmed by laboratory tests. The analyses were performed in Stata 12.0 using relative risk (RR) as a summary measure. Heterogeneity was explored by meta-regression and subgroup analyses considering the HDI, age, sex, and follow-up period. Out of 912 studies screened, 49 studies were eligible for qualitative synthesis, and 33 studies were eligible for quantitative analysis, representing 42,905 patients. The mortality risk from SARS-CoV-2 was higher in individuals with obesity compared with without obesity individuals only in the subgroups of patients <60 years old (RR = 1.31; 95% CI 1.18-1.45, I2  = 0.0%) and living in countries with a low HDI (RR = 1.28; 95% CI 1.10-1.48, I2  = 45.4%).

Association of government effectiveness, logistics performance, IT systems and income with COVID-19 mortality

The COVID-19 pandemic has unprecedentedly shaken the public health system worldwide. It has been one of the greatest humanitarian crises faced by all countries, regardless of their economic prosperity. However, some countries have been able to minimize the deaths caused by the coronavirus even in the face of a large number of cases, while others have failed to control the death rate even in a comparatively small number of cases. This study explores possible causes of this disparity using cross-sectional data from 126 countries associated with demography, governance, income level, the extent of ICT maturity and the geographical divide. The results of this study suggest that while government effectiveness is negatively associated with the COVID-19 death rate, the logistics performance of governments is positively linked to the COVID-19 mortality rate. The ICT maturity proxied through online service delivery did not confirm its association with the COVID-19 mortality rate. This study informs that poverty and the location of countries do not necessarily influence COVID-19 deaths. Hence, it behoves governments to focus on improving government effectiveness and putting in place more effective and efficient mobility systems, healthcare supply chains and digital administration to address the global health crisis posed by the COVID-19 pandemic and mitigate its harsh effects, including mortality.

Survival analysis and mortality predictors of COVID-19 in a pediatric cohort in Mexico

Background

The new coronavirus SARS-CoV-2 pandemic has been relatively less lethal in children; however, poor prognosis and mortality has been associated with factors such as access to health services. Mexico remained on the list of the ten countries with the highest case fatality rate (CFR) in adults. It is of interest to know the behavior of COVID-19 in the pediatric population. The aim of this study was to identify clinical and sociodemographic variables associated with mortality due to COVID-19 in pediatric patients.

Objective

Using National open data and information from the Ministry of Health, Mexico, this cohort study aimed to identify clinical and sociodemographic variables associated with COVID-19 mortality in pediatric patients.

Method

A cohort study was designed based on National open data from the Ministry of Health, Mexico, for the period April 2020 to January 2022, and included patients under 18 years of age with confirmed SARS-CoV-2 infection. Variables analyzed were age, health services used, and comorbidities (obesity, diabetes, asthma, cardiovascular disease, immunosuppression, high blood pressure, and chronic kidney disease). Follow-up duration was 60 days, and primary outcomes were death, hospitalization, and requirement of intensive care. Statistical analysis included survival analysis, prediction models created using the Cox proportional hazards model, and Kaplan-Meier estimation curves.

Results

The cohort included 261,099 cases with a mean age of 11.2 ± 4 years, and of these, 11,569 (4.43%) were hospitalized and 1,028 (0.39%) died. Variables associated with risk of mortality were age under 12 months, the presence of comorbidities, health sector where they were treated, and first wave of infection.

Conclusion

Based on data in the National database, we show that the pediatric fatality rate due to SARS-CoV-2 is similar to that seen in other countries. Access to health services and distribution of mortality were heterogeneous. Vulnerable groups were patients younger than 12 months and those with comorbidities.

Impact of good governance, economic growth and universal health coverage on COVID-19 infection and case fatality rates in Africa

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has disrupted lives across all countries and communities. It significantly reduced the global economic output and dealt health systems across the world a serious blow. There is growing evidence showing the progression of the COVID-19 pandemic and the impact it has on health systems, which should help to draw lessons for further consolidating and realizing universal health coverage (UHC) in all countries, complemented by more substantial government commitment and good governance, and continued full implementation of crucial policies and plans to avert COVID-19 and similar pandemic threats in the future. Therefore, the objective of the study was to assess the impact of good governance, economic growth and UHC on the COVID-19 infection rate and case fatality rate (CFR) among African countries.

METHODS

We employed an analytical ecological study design to assess the association between COVID-19 CFR and infection rate as dependent variables, and governance, economic development and UHC as independent variables. We extracted data from publicly available databases (i.e., Worldometer, Worldwide Governance Indicators, Our World in Data and WHO Global Health Observatory Repository). We employed a multivariable linear regression model to examine the association between the dependent variables and the set of explanatory variables. STATA version 14 software was used for data analysis.

RESULTS

All 54 African countries were covered by this study. The median observed COVID-19 CFR and infection rate were 1.65% and 233.46%, respectively. Results of multiple regression analysis for predicting COVID-19 infection rate indicated that COVID-19 government response stringency index (β = 0.038; 95% CI 0.001, 0.076; P = 0.046), per capita gross domestic product (GDP) (β = 0.514; 95% CI 0.158, 0.87; P = 0.006) and infectious disease components of UHC (β = 0.025; 95% CI 0.005, 0.045; P = 0.016) were associated with COVID-19 infection rates, while noncommunicable disease components of UHC (β = -0.064; 95% CI -0.114; -0.015; P = 0.012), prevalence of obesity among adults (β = 0.112; 95% CI 0.044; 0.18; P = 0.002) and per capita GDP (β = -0.918; 95% CI -1.583; -0.254; P = 0.008) were associated with COVID-19 CFR.

CONCLUSIONS

The findings indicate that good governance practices, favourable economic indicators and UHC have a bearing on COVID-19 infection rate and CFR. Effective health system response through a primary healthcare approach and progressively taking measures to grow their economy and increase funding to the health sector to mitigate the risk of similar future pandemics would require African countries to move towards UHC, improve governance practices and ensure economic growth in order to reduce the impact of pandemics on populations.

Socio-cultural Correlates of the COVID-19 Outcomes

While basically all countries have been hit by the COVID-19 pandemic, the impact has varied in large degrees among countries. In the present study, national differences in six COVID-19 indicators (COVID-19 deaths per capita, excess mortality, change in GDP per capita, vaccination rate, stringency index, and overall impact of the pandemic) were studied in relation to socio-economic and Hofstede's cultural dimensions by using the latest data available. The results differed to some degree from the studies conducted in the earlier stage of the pandemic. COVID-19 deaths per capita were predicted by Uncertainty Avoidance (UA) and Indulgence (IVR); excess mortality by UA; the impact of pandemics by Power Distance (PDI), Long-term Orientation (LTOWS) and IVR; change in GDP per capita by PDI; vaccination rate by Individualism and UA; and Stringency Index by LTOWS. In addition to further clarifying the role of cultural dimensions in the pandemic, three conclusions can be drawn. First, the pandemic reached different countries at different times, which is reflected in the results. The conclusion about the role of socio-economic and cultural factors can be drawn only after the pandemic. Second, cultural dimensions were related to COVID-19 measures only when socio-economic indicators were not considered but lost their significance when socio-economic variables were entered into the models. Cultural dimensions influence the outcome variables via socio-economic factors. Third, earlier studies have focused mainly on COVID-19 deaths. The impact of the COVID-19 pandemic is a complex phenomenon and cannot be reduced to the death rate.

The Protective Effect of Coronavirus Disease 2019 (COVID-19) Vaccination on Postacute Sequelae of COVID-19: A Multicenter Study From a Large National Health Research Network

Background

Coronavirus disease 2019 (COVID-19) vaccines have been proven to decrease the severity of acute-phase infection; however, little is known about their effect on postacute sequelae of COVID-19 (PASC).

Methods

Patients with confirmed COVID-19 diagnosis and minimum age of 18 years with 3-month follow-up postdiagnosis between 21 September 2020 and 14 December 2021 were identified from the TriNetX Research Network platform. The primary outcomes consisted of new-onset or persistent symptoms, new-onset diagnoses, and death and were compared between vaccine and no-vaccine groups.

Results

At baseline, 1 578 719 patients with confirmed COVID-19 were identified and 1.6% (n = 25 225) completed vaccination. After matching, there were no differences (P > .05) in demographics or preexisting comorbidities. At 28 days following COVID-19 diagnosis, the incidence of hypertension was 13.52 per 1000, diabetes was 5.98 per 1000, thyroid disease was 3.80 per 1000, heart disease was 15.41 per 1000, and mental disorders was 14.77 per 1000 in the vaccine cohort. At 90 days following COVID-19 diagnosis, the relative risk of hypertension was 0.33 (95% confidence interval [CI], .26-.42), diabetes was 0.28 (95% CI, .20-.38), heart disease was 0.35 (95% CI, .29-.44), and death was 0.21 (95% CI, .16-.27). Differences in both 28- and 90-day risk between the vaccine and no-vaccine cohorts were observed for each outcome, and there was enough evidence (P < .05) to suggest that these differences were attributed to the vaccine.

Conclusions

Our data suggest that COVID-19 vaccine is protective against PASC symptoms, new onset of health conditions, and mortality.

Impact of environmental and individual factors on COVID-19 mortality in children and adolescents in Mexico: An observational study

Background

During the Covid-19 pandemic, children and adolescents faced poverty, potentially dying from preventable causes, or missing out essential vaccines. The aim of this study was to assess potential environmental and individual factors associated to COVID-19 mortality in children and adolescents in Mexico.

Methods

This cross-sectional study analysed the official data of 131,001 children under 10 years of age and adolescents between 10 and 19 years of age with COVID-19 disease, in Mexico. Participants were diagnosticated between March 2020 and June 13, 2021. The environmental variables such as malnutrition, vaccination coverage and social lag index were evaluated at the state level. Multilevel models were fitted to evaluate the association between environmental and individual factors and COVID-19 mortality.

Findings

A total of 773 (0.6%) children and adolescents died due to COVID-19. Younger age (OR = 0.878, 95%CI: 0.869-0.888), diabetes (OR = 3.898, 95%CI: 2.596-5.851), immunosuppression (OR = 5.410, 95%CI: 4.088-7.158), obesity (OR = 1.876, 95%CI: 1.397-2.521), hypertension (OR = 1.906, 95%CI: 1.239-2.932), cardiovascular disease (OR = 2.288, 95%CI: 1.482-3.531), and chronic kidney disease (OR = 13.250, 95%CI: 9.066-19.350) were associated with mortality. COVID-19 mortality was directly associated with social lag index and malnutrition (OR_{very high} = 2.939, 95%CI: 1.111-7.775, and OR = 1.390, 95%CI: 1.073-1.802, respectively), and inversely associated with population density (OR = 0.374, 95%CI: 0.204-0.688). Finally, children and adolescents living in areas with a higher percentage of people with incomplete education (OR = 1.045, 95%CI: 1.011-1.081), of children of school age of 6–14 years who do not attend school (OR = 1.266, 95%CI: 1.032-1.554), and of illiterate population aged 15 and over (OR = 1.086, 95%CI: 0.999-1.179) were associated with a higher risk of COVID-19 mortality.

Interpretation

Malnutrition, social lag index and population density are key factors to understand COVID-19 mortality in children and adolescents. Also, age and pre-existing comorbidities were also associated with worse COVID-19 prognosis.

Funding

No funding was secured for this study.

Hospital management of hyperglycemia in the context of COVID-19: evidence-based clinical considerations

The COVID-19 pandemic led to an unprecedented crisis, and early on, it has been shown that diabetes is an important risk factor for complications and mortality in infected patients, as demonstrated by several studies. Moreover, hyperglycemia, regardless of whether patients have diabetes, is associated with poorer outcomes, which suggests that adequate monitoring and treatment of elevated glycemia in the hospital setting can improve patient outcomes. In patients with COVID-19, glycemic control may be impaired as a consequence of the infection itself (aggravating pre-existing diabetes and potentially precipitating new-onset diabetes), inflammation, or corticosteroid use-a well-established therapy to reduce COVID-19 complications, especially in the intensive care unit. This article reviews the link between diabetes and hyperglycemia, and COVID-19, with a brief review of potential mechanisms, along with emerging evidence on the effect of glycemic control on COVID-19 outcomes, especially in hospital settings.

Strategies to Mitigate Chemotherapy and Radiation Toxicities That Affect Eating

Background: Cancer and its therapy is commonly associated with a variety of side effects that impact eating behaviors that reduce nutritional intake. This review will outline potential causes of chemotherapy and radiation damage as well as approaches for the amelioration of the side effects of cancer during therapy. Methods: Information for clinicians, patients, and their caregivers about toxicity mitigation including nausea reduction, damage to epithelial structures such as skin and mucosa, organ toxicity, and education is reviewed. Results: How to anticipate, reduce, and prevent some toxicities encountered during chemotherapy and radiation is detailed with the goal to improve eating behaviors. Strategies for health care professionals, caregivers, and patients to consider include (a) the reduction in nausea and vomiting, (b) decreasing damage to the mucosa, (c) avoiding a catabolic state and muscle wasting (sarcopenia), and (d) developing therapeutic alliances with patients, caregivers, and oncologists. Conclusions: Although the reduction of side effects involves anticipatory guidance and proactive team effort (e.g., forward observation, electronic interactions, patient reported outcomes), toxicity reduction can be satisfying for not only the patient, but everyone involved in cancer care.

A global country-level analysis of the relationship between obesity and COVID-19 cases and mortality

AIM

To assess the association of country-level obesity prevalence with COVID-19 case and mortality rates, to evaluate the impact of obesity prevalence on worldwide variation.

METHODS

Data on COVID-19 prevalence and mortality, country-specific governmental actions, socioeconomic, demographic, and healthcare capacity factors were extracted from publicly available sources. Multivariable negative binomial regression was used to assess the independent association of obesity with COVID-19 case and mortality rates.

RESULTS

Across 168 countries for which data were available, higher obesity prevalence was associated with increased COVID-19 mortality and prevalence rates. For every 1% increase in obesity prevalence, the mortality rate was increased by 8.3% (incidence rate ratio [IRR] 1.083, 95% confidence interval [CI] 1.048-1.119; P < 0.001) and the case rate was higher by 6.6% (IRR 1.066, 95% CI 1.035-1.099; P < 0.001). Additionally, higher median population age, greater female ratio, higher Human Development Index (HDI), lower population density, and lower hospital bed availability were all significantly associated with higher COVID-19 mortality rate. In addition, stricter governmental actions, higher HDI and lower mean annual temperature were significantly associated with higher COVID-19 case rate.

CONCLUSION

These findings demonstrate that obesity prevalence is a significant and potentially modifiable risk factor of increased COVID-19 national caseload and mortality. Future research to study whether weight loss improves COVID-19 outcomes is urgently required.

Moving Toward Health Policy that Respects Both Science and People Living with Obesity

Through four decades of rising obesity, health policy has been mostly ineffective. Prevention policies failed to reverse rising trends in prevalence, partly because they are often based on biased mental models about what should work to prevent obesity, rather than empiric evidence for what does work. Bias toward people living with obesity harms health, while contributing to poor access to effective care that might serve to improve it. Better public policy will come from an increased application of objective obesity science, research to fill knowledge gaps, and respect for the human dignity of people who live with obesity.

Association of obesity with postacute sequelae of COVID-19

Obesity is a major risk factor for the development of severe coronavirus disease 2019 (COVID-19) infection and mortality. However, it is not known whether patients with obesity are at a greater risk of developing postacute sequelae of COVID-19 (PASC). In a median follow-up time of 8 months and counting from 30 days following a positive viral test of 2839 patients who did not require intensive care unit admission and survived the acute phase of COVID-19, 1230 (43%) patients required medical diagnostic tests, 1255 (44%) patients underwent hospital admission, and 29 (1%) patients died. Compared with patients with a normal body mass index (BMI), the risk of hospital admission was 28% and 30% higher in patients with moderate and severe obesity, respectively. The need for diagnostic tests to assess different medical problems, compared with patients with normal BMI, was 25% and 39% higher in patients with moderate and severe obesity, respectively. The findings of this study suggest that moderate and severe obesity (BMI ≥ 35 kg/m² ) are associated with a greater risk of PASC.

covid19.Explorer: a web application and R package to explore United States COVID-19 data

Appearing at the end of 2019, a novel virus (later identified as SARS-CoV-2) was characterized in the city of Wuhan in Hubei Province, China. As of the time of writing, the disease caused by this virus (known as COVID-19) has already resulted in over three million deaths worldwide. SARS-CoV-2 infections and deaths, however, have been highly unevenly distributed among age groups, sexes, countries, and jurisdictions over the course of the pandemic. Herein, I present a tool (the covid19.Explorer R package and web application) that has been designed to explore and analyze publicly available United States COVID-19 infection and death data from the 2020/21 U.S. SARS-CoV-2 pandemic. The analyses and visualizations that this R package and web application facilitate can help users better comprehend the geographic progress of the pandemic, the effectiveness of non-pharmaceutical interventions (such as lockdowns and other measures, which have varied widely among U.S. states), and the relative risks posed by COVID-19 to different age groups within the U.S. population. The end result is an interactive tool that will help its users develop an improved understanding of the temporal and geographic dynamics of the SARS-CoV-2 pandemic, accessible to lay people and scientists alike.

Socio-demographic and health factors drive the epidemic progression and should guide vaccination strategies for best COVID-19 containment

We propose and study an epidemiological model on a social network that takes into account heterogeneity of the population and different vaccination strategies. In particular, we study how the COVID-19 epidemics evolves and how it is contained by different vaccination scenarios by taking into account data showing that older people, as well as individuals with comorbidities and poor metabolic health, and people coming from economically depressed areas with lower quality of life in general, are more likely to develop severe COVID-19 symptoms, and quicker loss of immunity and are therefore more prone to reinfection. Our results reveal that the structure and the spatial arrangement of subpopulations are important epidemiological determinants. In a healthier society the disease spreads more rapidly but the consequences are less disastrous as in a society with more prevalent chronic comorbidities. If individuals with poor health are segregated within one community, the epidemic outcome is less favorable. Moreover, we show that, contrary to currently widely adopted vaccination policies, prioritizing elderly and other higher-risk groups is beneficial only if the supply of vaccine is high. If, however, the vaccination availability is limited, and if the demographic distribution across the social network is homogeneous, better epidemic outcomes are achieved if healthy people are vaccinated first. Only when higher-risk groups are segregated, like in elderly homes, their prioritization will lead to lower COVID-19 related deaths. Accordingly, young and healthy individuals should view vaccine uptake as not only protecting them, but perhaps even more so protecting the more vulnerable socio-demographic groups.