Food insecurity arises the likelihood of hospitalization in patients with COVID-19

Food insecurity, inflammation, and immune function among older US adults: Findings from the health and Retirement study

BACKGROUND

Food insecurity (FI) is a pressing public health concern among older adults and has been associated with adverse cardiovascular outcomes. Greater systemic inflammation may provide a pathway to explain these associations, but few studies have examined the link between FI and markers of inflammation. Thus, the objective of the present study was to evaluate the associations between FI and multiple inflammatory and immune functioning biomarkers using a nationally representative study of US adults aged > 50 years.

METHOD

Participants (n = 3,924) were drawn from the longitudinal Health and Retirement Study (HRS). Household FI was assessed using the six-item Short Form Food Security Survey Module from the 2013 HRS Health Care and Nutrition Study. Markers of inflammation (neutrophil-lymphocyte ratio, albumin, hs-CRP, IL6, IL10, IL-1Ra, sTNFR-1, and TGFβ-1) and immune functioning (CMV) were collected during the 2016 HRS Venous Blood Study. Multivariate logistic and linear regression models were used to evaluate associations between household FI and inflammatory and immune functioning biomarkers, adjusting for individual and household sociodemographic characteristics.

RESULTS

The weighted prevalence of FI was 18.8 %. Age and sex-adjusted mean showed that FI was associated with higher levels of inflammation and impaired immune functioning (Ps-value < 0.05). Older adults with FI had higher mean levels of albumin, hs-CRP, IL6, IL10, IL-1Ra, TGFß-1, and CMV seronegative and borderline (Ps-value < 0.05). Multivariate-adjusted regression model showed that FI was associated with high-risk categories of hs-CRP (OR 1.34, 95 % CI 1.06, 1.68), IL-6 (OR 1.66, 95 % CI 1.28, 2.14), IL-1Ra (OR 0.67, 95 % CI 0.48, 0.93), TGFß-1 (OR 1.87, 95 % CI 1.45, 2.42), seronegativity for CMV (OR 0.48, 95 % CI 0.35, 0.64).

CONCLUSION

In this nationally representative sample of older adults, FI was positively associated with multiple markers of systemic inflammation and impaired immune functioning. Public health efforts that directly work to reduce FI among older adults are warranted and may result in further improvements in their health and well-being.

Food insecurity in urban American Indian and Alaska Native populations during the COVID-19 pandemic

BACKGROUND

Food insecurity is an important social determinant of health that was exacerbated by the COVID-19 pandemic. Both food insecurity and COVID-19 infection disproportionately affect racial and ethnic minority groups, particularly American Indian and Alaska Native communities; however, there is little evidence as to whether food insecurity is associated with COVID-19 infection or COVID-19 preventive behaviors such as vaccination uptake. The purpose of this study was to evaluate associations between food insecurity, COVID-19 infection, and vaccination status among urban American Indian and Alaska Native adults seen at 5 clinics serving urban Native people.

METHODS

In partnership with health organizations in Alaska, Colorado, Kansas, Minnesota, and New Mexico, the study team conducted a cross-sectional survey in 2021 to assess food security status and attitudes, barriers, and facilitators for COVID-19 testing and vaccination. Logistic regression was used to examine the association of food security status with sociodemographic factors and COVID-19 infection and vaccination status. Marginal standardization was applied to present results as prevalence differences.

RESULTS

Among 730 American Indian and Alaska Native adults, the prevalence of food insecurity measured during the pandemic was 38%. For participants who reported persistent food security status before and during the pandemic (n = 588), the prevalence of food insecurity was 25%. Prevalence of COVID-19 infection and vaccination did not vary by food security status after adjustment for confounders.

CONCLUSIONS

High rates of food insecurity among American Indian and Alaska Native communities likely increased during the COVID-19 pandemic. However, despite the high prevalence of food insecurity, community-led efforts to reduce COVID-19 infection and increase vaccination uptake across Indian Health Service and Tribal healthcare facilities may have mitigated the negative impacts of the pandemic for families experiencing food insecurity. These successful approaches serve as an important reference for future public health efforts that require innovative strategies to improve overall health in American Indian and Alaska Native communities.

Food Insecurity in Urban American Indian and Alaska Native Populations During the COVID-19 Pandemic

Background

Food insecurity is an important social determinant of health that was exacerbated by the COVID-19 pandemic. Both food insecurity and COVID-19 infection disproportionately affect racial and ethnic minority groups, particularly American Indian and Alaska Native communities; however, there is little evidence as to whether food insecurity is associated with COVID-19 infection or COVID-19 preventive behaviors such as vaccination uptake. The purpose of this study was to evaluate associations between food insecurity, COVID-19 infection, and vaccination status among urban American Indian and Alaska Native adults seen at 5 clinics serving urban Native people.

Methods

In partnership with health organizations in Alaska, Colorado, Kansas, Minnesota, and New Mexico, the study team conducted a cross-sectional survey in 2021 to assess food security status and attitudes, barriers, and facilitators for COVID-19 testing and vaccination. Logistic regression was used to examine the association of food security status with sociodemographic factors and COVID-19 infection and vaccination status. Marginal standardization was applied to present results as prevalence differences.

Results

Among 730 American Indian and Alaska Native adults, the prevalence of food insecurity measured during the pandemic was 38%. For participants who reported persistent food security status before and during the pandemic (n=588), the prevalence of food insecurity was 25%. Prevalence of COVID-19 infection and vaccination did not vary by food security status after adjustment for confounders.

Conclusions

High rates of food insecurity among American Indian and Alaska Native communities likely increased during the COVID-19 pandemic. However, despite the high prevalence of food insecurity, community-led efforts to reduce COVID-19 infection and increase vaccination uptake across Indian Health Service and Tribal healthcare facilities may have mitigated the negative impacts of the pandemic for families experiencing food insecurity. These successful approaches serve as an important reference for future public health efforts that require innovative strategies to improve overall health in AIAN communities.

Plant-based diet and COVID-19 severity: results from a cross-sectional study

Although previous findings have shown the beneficial role of healthy eating pattern on the human immune system, the association between plant-based diet and COVID-19 severity has not yet been elucidated. This study aimed to determine the possible role of plant-based diet index (PDI) in COVID-19 severity. This cross-sectional, multicentral study was conducted on 141 patients with confirmed COVID-19. Dietary intakes of the patients were evaluated using a validated food frequency questionnaire. Then, PDI was compared between patients who needed to be hospitalised (considered severe cases), and those who got treatment at home (considered non-severe cases). After adjustment for confounders including age, sex, energy intake and body mass index, lower odds of hospitalisation were found for participants having a greater score of overall PDI (OR per 10 units increase: 0.42; 95% CI 0.22 to 0.80) and healthy PDI (OR per 10 unit increase: 0.45; 95% CI 0.26 to 0.78). In conclusion, our data presented that there is a relation between PDI and lower risk of hospitalisation in COVID-19 patients, possibly through boosting the immune function.

Bayesian model averaging for predicting factors associated with length of COVID-19 hospitalization

INTRODUCTION

The length of hospital stay (LOHS) caused by COVID-19 has imposed a financial burden, and cost on the healthcare service system and a high psychological burden on patients and health workers. The purpose of this study is to adopt the Bayesian model averaging (BMA) based on linear regression models and to determine the predictors of the LOHS of COVID-19.

METHODS

In this historical cohort study, from 5100 COVID-19 patients who had registered in the hospital database, 4996 patients were eligible to enter the study. The data included demographic, clinical, biomarkers, and LOHS. Factors affecting the LOHS were fitted in six models, including the stepwise method, AIC, BIC in classical linear regression models, two BMA using Occam's Window and Markov Chain Monte Carlo (MCMC) methods, and GBDT algorithm, a new method of machine learning.

RESULTS

The average length of hospitalization was 6.7 ± 5.7 days. In fitting classical linear models, both stepwise and AIC methods (R 2 = 0.168 and adjusted R 2 = 0.165) performed better than BIC (R 2 = 0.160 and adjusted = 0.158). In fitting the BMA, Occam's Window model has performed better than MCMC with R 2 = 0.174. The GBDT method with the value of R 2 = 0.64, has performed worse than the BMA in the testing dataset but not in the training dataset. Based on the six fitted models, hospitalized in ICU, respiratory distress, age, diabetes, CRP, PO2, WBC, AST, BUN, and NLR were associated significantly with predicting LOHS of COVID-19.

CONCLUSION

The BMA with Occam's Window method has a better fit and better performance in predicting affecting factors on the LOHS in the testing dataset than other models.

Impact of food insecurity and its influencing factors on the risk of malnutrition among COVID-19 patients

INTRODUCTION

Few studies focused on the impact of food insecurity severity on the risk of malnutrition among COVID-19 patients in Saudi Arabia.

OBJECTIVES

This study described the prevalence of food insecurity among COVID-19 patients, its severity, and its associated factors. Additionally, the impact of the severity of food insecurity on the risk of malnutrition was determined. It is hypothesized that food insecurity is associated with an increased risk of malnutrition among COVID-19 patients.

METHOD

A cross-sectional study was conducted in Al Madinah Al Munawarah in Saudi Arabia. Patients with confirmed COVID-19 and acute severe or nonsevere illness were enrolled. The Food Insecurity Experience Scale was used to determine the severity of food insecurity, and risk of malnutrition was assessed using the Malnutrition Screening Tool. Demographic characteristics, history of medical conditions, food intake, and body mass index (BMI) were assessed.

RESULTS

A total of 514 patients were enrolled, with 391 (76%) having acute nonsevere COVID-19 symptoms. A total of 14.2% of patients suffered from food insecurity. Of these, 17% had severe symptoms. The severity of food insecurity was influenced by patients' education (P = 0.02, 95% CI 0.019-0.225), weight loss (P = 0.0001, 95% CI 0.252-0.752), and loss of appetite (P = 0.0001, 95% CI 0.293-0.604). Fifteen percent of patients were at risk of malnutrition. Many obese patients suffered from severe COVID-19 symptoms (P = 0.029, 95% CI 0.02-0.539). The risk of malnutrition was associated with the severity of food insecurity (P = 0.001, 95% CI -0.056- -0.014), BMI (P = 0.049, 95% CI 0.000-0.042), and employment status (P = 0.034, 95% CI 0.002-0.048).

CONCLUSION

Food insecurity and the risk of malnutrition among COVID-19 patients should be assessed to prevent adverse health outcomes.

A spatial and contextual exposome-wide association study and polyexposomic score of COVID-19 hospitalization

Environmental exposures have been linked to COVID-19 severity. Previous studies examined very few environmental factors, and often only separately without considering the totality of the environment, or the exposome. In addition, existing risk prediction models of severe COVID-19 predominantly rely on demographic and clinical factors. To address these gaps, we conducted a spatial and contextual exposome-wide association study (ExWAS) and developed polyexposomic scores (PES) of COVID-19 hospitalization leveraging rich information from individuals' spatial and contextual exposome. Individual-level electronic health records of 50 368 patients aged 18 years and older with a positive SARS-CoV-2 PCR/Antigen lab test or a COVID-19 diagnosis between March 2020 and October 2021 were obtained from the OneFlorida+ Clinical Research Network. A total of 194 spatial and contextual exposome factors from 10 data sources were spatiotemporally linked to each patient based on geocoded residential histories. We used a standard two-phase procedure in the ExWAS and developed and validated PES using gradient boosting decision trees models. Four exposome measures significantly associated with COVID-19 hospitalization were identified, including 2-chloroacetophenone, low food access, neighborhood deprivation, and reduced access to fitness centers. The initial prediction model in all patients without considering exposome factors had a testing-area under the curve (AUC) of 0.778. Incorporation of exposome data increased the testing-AUC to 0.787. Similar findings were observed in subgroup analyses focusing on populations without comorbidities and aged 18-24 years old. This spatial and contextual exposome study of COVID-19 hospitalization confirmed previously reported risk factor but also generated novel predictors that warrant more focused evaluation.

The association between food insecurity status and COVID-19 in an Iranian population: a case-control study

Aim

The 2019 novel coronavirus epidemic (COVID-19) is a highly contagious viral disease with a high rate of morbidity and mortality. Food insecurity has frequently been linked to the emergence of infectious diseases. The present study was conducted to determine the association of food insecurity and socioeconomic status with COVID-19 in the Iranian population.

Subject and methods

The study was a case-control study including 248 participants (124 COVID-19-infected people with a positive PCR test and a history of clinical symptoms of COVID-19 and 124 non-infected people with a negative PCR test and no history of clinical symptoms of COVID-19 infection) aged 20 to 60 years. The participants in the two groups were matched based on age, sex, and BMI. Anthropometric and socioeconomic data were collected. Individuals' food insecurity status during the previous 12 months (before the disease for the case group) was assessed using a validated 18-item USDA questionnaire.

Results

About 44% of the controls and 76% of the case group were food-insecure (P < 0.001). After controlling for any possible confounders, only food insecurity and poor economic level increased the risk of COVID-19, by about three times (OR = 3.10; 95% CI = 1.44-6.68; P = 0.004) and 9.5 times (OR = 9.53; 95% CI = 3.73-24.30; P < 0.001), respectively.

Conclusion

Food insecurity and poor economic status are linked to an increased risk of COVID-19. Future prospective studies are needed to confirm these outcomes and identify the underlying mechanisms.

The Adverse Outcome Pathway Framework Applied to Neurological Symptoms of COVID-19

Several reports have shown that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the potential to also be neurotropic. However, the mechanisms by which SARS-CoV-2 induces neurologic injury, including neurological and/or psychological symptoms, remain unclear. In this review, the available knowledge on the neurobiological mechanisms underlying COVID-19 was organized using the AOP framework. Four AOPs leading to neurological adverse outcomes (AO), anosmia, encephalitis, stroke, and seizure, were developed. Biological key events (KEs) identified to induce these AOs included binding to ACE2, blood–brain barrier (BBB) disruption, hypoxia, neuroinflammation, and oxidative stress. The modularity of AOPs allows the construction of AOP networks to visualize core pathways and recognize neuroinflammation and BBB disruption as shared mechanisms. Furthermore, the impact on the neurological AOPs of COVID-19 by modulating and multiscale factors such as age, psychological stress, nutrition, poverty, and food insecurity was discussed. Organizing the existing knowledge along an AOP framework can represent a valuable tool to understand disease mechanisms and identify data gaps and potentially contribute to treatment, and prevention. This AOP-aligned approach also facilitates synergy between experts from different backgrounds, while the fast-evolving and disruptive nature of COVID-19 emphasizes the need for interdisciplinarity and cross-community research.