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

Abstract

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.

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

“…Among health-related variables, body mass index has been found to be associated with COVID-19. Sarmadi et al 37 have performed an ecological study, utilizing global databases (from the WHO and the NCD Risk Factor Collaboration, or NCD-RisC), to dissect the correlation between age-standardized body mass index and the risk of contracting COVID-19 in terms of incidence and mortality ratio. Authors were able to find a positive correlation, which was stronger in nations and territories with younger populations (like developing countries).…”

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

“…The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-CoV-2 virus emerged from Wuhan, China [ 1 ] and caused more than 250 million infected people and 5 million death up to 10 November 2020. COVID-19 is associated with multiple affecting factors such as air pollution, sociodemographic indices, which have a two-way relationship [ 2 , 3 ]. After about 2 years, many countries especially developed countries with mass vaccination, have not yet been able to fully restore their social and economic activities to pre-2020 levels [ 4 , 5 ].…”

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

“…Since COVID-19 was announced as a pandemic on March 11 2020, scientists started to study and analyze the spread of the virus and its associated factors. Several studies focused on the global scale, while other studies investigated smaller scales and examined specific variables’ correlation to COVID-19 [ 14 ]. In a study, the authors presented the sectors that were disrupted globally, namely: tourism, restaurants, leisure, entertainment, travel, sports, etc.…”

“…[ 15 ]. Another study presented the comparison between developed and developing countries, where increased COVID-19 cases and deaths were present in developed countries compared to developing countries [ 14 ].…”

“…More specifically, research on the correlation with health issues has been applied and presents a correlation to various health issues. A multivariable linear regression analysis on global data of COVID-19 cases and deaths recorded a high correlation of cases and deaths with high cholesterol and high body mass [ 14 ]. Moreover, the correlation is stronger in the younger population [ 14 ].…”