https://doi.org/10.4081/monaldi.2021.1954
Risk factors for Covid-19 in India
Submitted: May 29, 2021
Accepted: August 9, 2021
Published: September 14, 2021
Accepted: August 9, 2021
Abstract Views: 1074
PDF: 517
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Like many developing countries, India was devastated by the raging pandemic of Covid 19. With the active involvement of the government and the community, the disaster was fought with. However, the impact was uneven across the country. The present study aimed to identify the factors responsible for variation in case burden of Covid-19. Data on demographic factors and co-morbidities were obtained from different sources available in the public domain. Descriptive statistics were used for comparison between states. A total of 30 states were taken into account. Correlation was used to find out association between different factors and the burden of Covid-19. Data on Covid were collected till 9th May, 2021. The burden of Covid-19 was strongly related to the literacy status and economy of the state (r = 0.574 and 0.730, respectively). The burden of self-reported hypertension and diabetes was also statistically linked to the burden of Covid-19 (r = 0.539 and 0.721, respectively). Overweight and obesity were also associated with the burden of Covid-19 (r = 0.614 and 0.561, respectively). Therefore, in areas with a high proportion of patients with co-morbidities, limited resources may be mobilized for a better outcome. As the states with poor literacy and health condition suffered the most, tailored intervention is wanted to reach the poor and vulnerable.
COVID19INDIA. Last accessed 9th May, 2021. Available from: https://www.covid19india.org/
Hawkins RB, Charles EJ, Mehaffey JH. Socio-economic status and COVID-19-related cases and fatalities. Public Health 2020;189:129-34.
DOI: https://doi.org/10.1016/j.puhe.2020.09.016
Badawi A, Ryoo SG. Prevalence of comorbidities in the Middle East respiratory syndrome coronavirus (MERS-CoV): a systematic review and meta-analysis. Int J Infect Dis 2016;49:129–33.
DOI: https://doi.org/10.1016/j.ijid.2016.06.015
Emami A, Javanmardi F, Pirbonyeh N, Akbari A. Prevalence of underlying diseases in hospitalized patients with COVID-19: a systematic review and meta-analysis. Arch Acad Emerg Med 2020;8:e35.
DOI: https://doi.org/10.1371/journal.pone.0241265
International Institute for Population Sciences (IIPS) and NPHCE, MoHFW. Longitudinal Ageing Study in India (LASI) Wave 1, 2017-18, Factsheets – States/UTs, International Institute for Population Sciences, Mumbai; 2020.
Government of India, Ministry of Finance, Department of Economic Affairs. Economic Survey 2020–21 Volume 2. Last accessed on 17th February, 2021. Available from: https://www.indiabudget.gov.in/economicsurvey/doc/echapter_vol2.pdf
Government of India, Ministry of Statistics and Program Implementation. Household social consumption on education in India. NSS 75th round. New Delhi; 2020.
Christy JS, Kaur K, Gurnani B, et al. Knowledge, attitude and practise toward COVID-19 among patients presenting to five tertiary eye care hospitals in South India - A multicentre questionnaire-based survey. Indian J Ophthalmol 2020;68:2385-90.
DOI: https://doi.org/10.4103/ijo.IJO_2522_20
Cifuentes MP, Rodriguez-Villamizar LA, Rojas-Botero ML, et al. Socioeconomic inequalities associated with mortality for COVID-19 in Colombia: a cohort nationwide study. J Epidemiol Community Health 2021;jech-2020-216275. Online ahead of print.
DOI: https://doi.org/10.1136/jech-2020-216275
Mena GE, Martinez PP, Mahmud AS, et al. Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile. Science 2021;372:eabg5298.
DOI: https://doi.org/10.1126/science.abg5298
Guan WJ, Ni ZY, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382:1708–20.
DOI: https://doi.org/10.1056/NEJMoa2002032
Wu C, Chen X, Cai Y, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan. China JAMA Intern Med 2020;180:934.
DOI: https://doi.org/10.1001/jamainternmed.2020.0994
Guo W, Li M, Dong Y, et al. Diabetes is a risk factor for the progression and prognosis of COVID-19. Diabetes Metab Res Rev 2020;e3319. Online ahead of print.
DOI: https://doi.org/10.1002/dmrr.3319
Mehta P, McAuley DF, Brown M, et al. COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet 2020;395:1033–4.
DOI: https://doi.org/10.1016/S0140-6736(20)30628-0
Rao S, Lau A, So HC. Exploring diseases/traits and blood proteins causally related to expression of ACE2, the putative receptor of SARS-CoV-2: a Mendelian randomization analysis highlights tentative relevance of diabetes-related traits. Diabetes Care 2020;43:1416–26.
DOI: https://doi.org/10.2337/dc20-0643
Erener S. Diabetes, infection risk and COVID-19. Mol Metab 2020;39:101044.
DOI: https://doi.org/10.1016/j.molmet.2020.101044
Yadav R, Acharjee A, Salkar A, et al. Mumbai mayhem of COVID-19 pandemic reveals important factors that influence susceptibility to infection. EClinicalMedicine 2021;35:100841.
DOI: https://doi.org/10.1016/j.eclinm.2021.100841
Marimuthu Y, Kunnavil R, Anil NS, et al. Clinical profile and risk factors for mortality among COVID-19 in patients at a tertiary care centre in Bengaluru, India. Monaldi Arch Chest Dis 2021;1724. Online ahead of print.
DOI: https://doi.org/10.4081/monaldi.2021.1724
Guo T, Fan Y, Chen M, et al. Cardiovascular implications of fatal outcomes of patients with Coronavirus Disease 2019 (COVID-19). JAMA Cardiol 2020;5:811-8.
DOI: https://doi.org/10.1001/jamacardio.2020.1017
Zhang T, Huang WS, Guan W, et al. Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression. J Thorac Dis 2020;12:7429-41.
DOI: https://doi.org/10.21037/jtd-20-1743
Shi S, Qin M, Cai Y, et al. Characteristics and clinical significance of myocardial injury in patients with severe coronavirus disease 2019. Eur Heart J 2020;41:2070-9.
DOI: https://doi.org/10.1093/eurheartj/ehaa408
Puntmann VO, Carerj ML, Wieters I, et al. Outcomes of cardiovascular magnetic resonance imaging in patients recently recovered from Coronavirus Disease 2019 (COVID-19). JAMA Cardiol 2020;5:1265-73.
DOI: https://doi.org/10.1001/jamacardio.2020.3557
Richardson S, Hirsch JS, Narasimhan M, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York city area. JAMA 2020;323:2052–9.
DOI: https://doi.org/10.1001/jama.2020.6775
Hernández-Garduño, E. Obesity is the comorbidity more strongly associated for Covid-19 in Mexico. A case-control study. Obes Res Clin Pract 2020;14:375-9.
DOI: https://doi.org/10.1016/j.orcp.2020.06.001
de Lusignan S, Dorward J, Correa A, et al. Risk factors for SARS-CoV-2 among patients in the Oxford Royal College of General Practitioners Research and Surveillance Centre primary care network: a cross-sectional study. Lancet Infect Dis 2020;20:1034-42.
DOI: https://doi.org/10.1016/S1473-3099(20)30371-6
Dhurandhar NV, Bailey D, Thomas D. Interaction of obesity and infections. Obes Rev 2015;16:1017–29.
DOI: https://doi.org/10.1111/obr.12320
Alkhathami MG, Advani SM, Abalkhail AA, et al. Prevalence and mortality of lung comorbidities among patients with COVID-19: A systematic review and meta-analysis. Lung India 2021;38:S31-40.
DOI: https://doi.org/10.4103/lungindia.lungindia_497_20
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Roy, Manas Pratim. 2021. “Risk Factors for Covid-19 in India”. Monaldi Archives for Chest Disease 92 (2). https://doi.org/10.4081/monaldi.2021.1954.
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