Biological and Sociodemographic Variables Associated with Covid-19 Outcomes: Bayesian Analysis of Data From 170 Countries Suggests A Cautious Outlook on Obesity Impact

Smarajit Maiti; Nirmalya K.  Sinha; Tamal Kanti Ghosh; Sumandev  Chakrabortty

Smarajit Maiti Ph D, Haldia Institute of Health Sciences, ICARE Complex, Hatiberia, Purba Medinipur, WB, India
Nirmalya K. Sinha Department of Nutrition, Department of NSS, Raja Narendra Lal Khan Women’s College (Autonomous), Midnapore, West Bengal, India
Tamal Kanti Ghosh Ph D, Jagannath Gupta Institute of Medical Sciences & Hospital, North Kolkata, India
Sumandev Chakrabortty Midnapore Medical College & Hospital, Midnapore, West Bengal, India

Keywords: COVID-19 Pandemic, Health and Hygiene, Socioeconomic Status, Communicable and Non- Communicable Diseases, Correlation

Abstract

Background: COVID-19 claimed 6,492,948 deaths from 607,497,755 infections until August 2022. In 2021 and 2022, several SARS CoV-2 variants increased infection or mortality.

Objectives: We analysed the impact of nutritional state and epidemiological-sociodemographic factors on the COVID-19 outcome. Methods: Presently, WHO-defined factors, health or hygiene and metabolic-disorders, i.e., nutritional status (obesity) and lockdown, were considered for association studies with the Total Confirmed Cases/million (TCC/m) and Case-Fatality-Rate (CFR) from COVID-19 in 170 countries. Bayesian-probabilistic analysis was utilised to facilitate intricate hierarchical modelling, effectively managing confounding factors. Normal statistics, including ANOVA, Tukey’s post-hoc test, Pearson’s correlation, canonical correlation, step-wise/linear-regression, were conducted, and x square-test were performed for non-parametric variables.

Results: CFR positively correlated with air pollution (r equal to 0.95), TB incidence (r equal to 0.95), and GDP per capita (r equal to minus 0.83). The contour plot, which shows CFR vs. GDP & Air Pollution, reveals that CFR rises when GDP falls and air pollution rises. Compared to TCC205, CFR205 is tightly controlled (0.790–0.815), indicating little variability. Higher categories of diabetes- obesity are associated with somewhat higher CFR205, suggesting a small rising trend. Instead of at the extremes, TCC205 peaks in communities with mid-level prevalence of diabetes and obesity, which is not definitive. Bayesian critical analysis of posterior distribution suggests no distinct relation between obesity and diabetes with COVID-19 and indicates the interacting influence of other confounding factors. Densely populated areas are affected more, and that has been significantly restrained by lockdown/quarantine (x square equal to 85.4; p less than 0.001or x square equal to 58.09; p less than 0.01).

Conclusions: Environmental pollution, other diseases like severe TB, and lower GDP promoted adverse COVID outcomes. Findings from the Bayesian approach highlight the need for cautious interpretation of the influence of different factors on COVID-19.

DOI: https://doi.org/10.24321/0019.5138.202658

How to cite this article:
Maiti S, Sinha N K, Ghosh T K, Chakrabortty S. Biological and Sociodemographic Variables
Associated with Covid-19 Outcomes: Bayesian Analysis of Data From 170 Countries Suggests A
Cautious Outlook on Obesity Impact. J CommunDis. 2026;58(3):83-94.

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