Ülkelerin Covid-19 Hastalığı Fatalite Hızlarıyla İlişkili Faktörlerin Araştırılması

Year 2022, Volume: 6 Issue: 2, 154 - 161, 30.08.2022

Elif Nur Yıldırım Öztürk , Mustafa Öztürk , Mehmet Uyar

https://doi.org/10.34084/bshr.1116335

Abstract

Amaç: Bu araştırmada ülkelerin Covid-19 hastalığı fatalite hızıyla ilişkili faktörlerin araştırılması amaçlanmıştır.
Yöntem: Araştırma ekolojik tiptedir. Araştırmada Covid-19 hastalığı fatalite hızlarıyla sosyoekonomik durum, doğumda beklenen sağlıklı yaşam umudu, 65 yaş ve üzeri nüfus yüzdesi, kardiyovasküler hastalık sıklığı, tütün kullanım sıklığı, İnsani Gelişmişlik İndeksi, Toplumsal Cinsiyet Eşitsizliği İndeksi ve Küresel Cinsiyet Uçurumu İndeksi gibi değişkenlerin ilişkisi araştırılmıştır. Verilerin özetlenmesinde ortalama, standart sapma, ortanca, minimum ve maksimum değerleri kullanılmıştır. Veriler arası ilişkilerin araştırılmasında Pearson/Spearman korelasyon katsayısı kullanılmış ve lineer regresyon modeli kurulmuşturtır. P<0,05 istatistiksel olarak anlamlı kabul edilmiştir.
Bulgular: Verilerinde eksiklik bulunmayan 130 ülke çalışmaya dahil edildi. Ülkelerin %12,3’ü düşük sosyoekonomik sınıftaydı. Yüz otuz ülkenin ortalama fatalite hızı 0.016±0.018 idi. Fatalite hızıyla tütün kullanım sıklığı hariç tüm değişkenler arasında istatistiksel olarak anlamlı ilişki belirlendi (p<0.05). Tüm değişkenler, fatalite hızının tahmini için oluşturulan çoklu doğrusal regresyon modeline dahil edildi. Modele istatistiksel olarak anlamlı katkı sağlayan tek değişken Küresel Cinsiyet Uçurumu İndeksi oldu.
Sonuç: Gelecekte ortaya çıkabilecek benzer salgın durumlarında bu değişkenlerin dikkate alınması ve bu değişkenlerle ilişkili koşulların küresel ölçekte iyileştirilmesi salgın kontrolünün sağlanması açısından önemli olabilir.

Keywords

Covid-19 pandemisi, fatalite hızı, ilişkili faktörler, ekolojik çalışma

Supporting Institution

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Project Number

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Thanks

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Investigation of Factors Associated with Countries’ Covid-19 Disease Fatality Rates

Abstract

Objective: In this study, it was aimed to investigate the factors associated with the Covid-19 disease fatality rate of countries.
Methods: The research is of ecological type. In the study, the relationship between Covid-19 disease fatality rates and variables like socioeconomic state, healthy life expectancy at birth, population ages 65 and above, cardiovascular disease frequency, tobacco use frequency, vaccination rates, Human Development Index, Gender Inequality Index and Global Gender Gap Index were investigated. Mean, standard deviation, median, minimum and maximum values were used to summarize data. Pearson/Spearman correlation coefficient was used to investigate the relationships and a linear regression model was established. P<0.05 was considered statistically significant.
Results: One hundred and thirty countries with no missing data were included in the study. Twelve point three percent of these countries were in low socioeconomic state. The mean fatality rate of 130 countries was 0.016±0.018. A statistically significant relationship was determined between fatality rate and all variables except tobacco use frequency (p<0.05). All the variables were included in the multiple linear regression model established for the prediction of the fatality rate. Among these variables, Global Gender Gap Index was the only variable that made a statistically significant contribution to the model.
Conclusion: Considering these variables in similar epidemic disease states that may occur in the future and improving the conditions related to these variables on a global scale may be important to ensure epidemic control.

Keywords

Covid-19 pandemic, Covid-19 pandemic, fatality rate, related factors, ecological study

Project Number

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References

• 1. Emin Alıcılar H, Güneş G, Çöl M. Evaluation of awareness, attitudes and behaviors related to Covid-19 pandemic in society. ESTUDAM Public Health Journal. 2020; 5: 1-16.
• 2. Kaya O. COVID-19 Vaccines. Med J SDU. 2021; suppl-1: 31-35
• 3. Arıkan İ. Health education and individual behavioral models for the preparing future epidemics: Covid-19 sample. ESTUDAM Public Health Journal. 2020; 5 (COVID-19 suppl): 70-78.
• 4. Erkal E, Ses AG, Aydın S, et al. Non-pharmaceutical public health measures to prevent the transmission of Covid-19 in community. ESTUDAM Public Health Journal. 2020; 5: 79-95.
• 5. Kılıç B. Social determinants and Covid-19. Çöl M Ed. Covid-19 from a public health perspective. First Edition. Ankara. Turkish Clinics. 2021: 14-20.
• 6. Upshaw TL, Brown C, Smith R, et al. Social determinants of COVID-19 incidence and outcomes: A rapid review. PLOS ONE. 2021; 16(3): e0248336.
• 7. Banik A, Nag T, Chowdhury SR, et al. Why do COVID-19 fatality rates differ across countries? An explorative cross-country study based on select ındicators. Global Business Review. 2020; 21(3): 607-625.
• 8. Coccia M. High health expenditures and low exposure of population to air pollution as critical factors that can reduce fatality rate in COVID-19 pandemic crisis: A global analysis. Environmental Research. 2021; 199: 111339.
• 9. Puziol de Oliveira R, Alberto Achcar J, Aparecido Nunes A. Modeling the incidence and death rates of COVID-19 pandemic in different regions of the world. Epidemiologic Methods. 2020; 9(supple-1): 20200017.
• 10. World Health Organization. Coronavirus (Covid-19) dashboard. Available from https://covid19.who.int/table (Access date: 08.04.2022)
• 11. World Health Organization. The Global Health Observatory. Health Workforce. Available from https://www.who.int/data/gho/data/themes/topics/indicator-groups/indicator-group-details/GHO/sdg-target-3.c-health-workforce (Access date: 08.04.2022)
• 12. The World Bank. Country Classifications by Income: FY 2021-2022. Available from https://datatopics.worldbank.org/world-development-indicators/the-world-by-income-and-region.html (Access date: 08.04.2022)
• 13. The World Bank. Population ages 65 and above (% of total population). Available from https://databank.worldbank.org/reports.aspx?source=2&series=SP.POP.65UP.TO.ZS&country=# (Access date: 08.04.2022)
• 14. World Health Organization. World Health Statistics 2021 Monitoring Health fort the Sustainable Development Goals. Switzerland. 2021. Available from https://apps.who.int/iris/bitstream/handle/10665/342703/9789240027053-eng.pdf (Access date: 08.04.2022)
• 15. The Institute for Health Metrics and Evaluation (IHME). Global Health Data Exchange 2019. Available from http://ghdx.healthdata.org/gbd-results-tool?params=gbd-api-2019-permalink/f8a0d9c0a3f20728ed41900616580915 (Access date: 08.04.2022)
• 16. World Health Organization. Global Report on Trends in Prevalence of Tobacco Use 2000-2025. Third Edition. Geneva. 2019. Available from https://www.who.int/publications/i/item/who-global-report-on-trends-in-prevalence-of-tobacco-use-2000-2025-third-edition (Access date: 08.04.2022)
• 17. Global Burden of Disease 2020 Health Financing Collaborator Network. Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050. The Lancet. 2021; 398: 1317-1343.
• 18. Our World in Data. Coronavirus (Covid-19) Vaccinations. Available from https://ourworldindata.org/covid-vaccinations (Access date: 08.04.2022)
• 19. United Nations Development Programme. Human Development Reports-HDI 2020. Available from http://hdr.undp.org/en/composite/HDI (Access date: 08.04.2022)
• 20. United Nations Development Programme. Human Development Reports-GII 2020. Available from http://hdr.undp.org/en/composite/GII (Access date: 08.04.2022)
• 21. World Economic Forum. Global Gender Gap Report 2021. Available from http://www3.weforum.org/docs/WEF_GGGR_2021.pdf (Access date: 08.04.2022)
• 22. Alpar R. Applied Statistics and Validity-Reliability with Examples from Sports, Health and Educational Sciences. Third Edition. Detay Publishing: Ankara, Turkey. 2014.
• 23. Jain VK, Iyengar K, Vaish A, et al. Differential mortality in COVID-19 patients from India and western countries. Diabetes and Metabolic Syndrome: Clinical Research and Reviews. 2020; 14(5): 1037-1041.
• 24. Upadhyay AK, Shukla S. Correlation study to identify the factors affecting COVID-19 case fatality rates in India. Diabetes and Metabolic Syndrome: Clinical Research and Reviews. 2021; 15(3): 993-999.
• 25. Mehraeen E, Karimi A, Barzegary A, et al. Predictors of mortality in patients with COVID-19-a systematic review. European Journal of Integrative Medicine. 2020; 40: 101226.
• 26. Sepandi M, Taghdir M, Alimohamadi Y, et al. Factors associated with mortality in COVID-19 patients: a systematic review and meta-analysis. Iran J Public Health. 2020; 49(7): 1211-1221.
• 27. Upadhyaya A, Koirala S, Ressler R, et al. Factors affecting COVID-19 mortality: an exploratory study. Journal of Health Research. 2020; 36(1): 166-175.
• 28. Goh HP, Mahari WI, Ahad NI, et al. Risk factors affecting COVID-19 case fatality rate: A quantitative analysis of top 50 affected countries. Progress In Microbes & Molecular Biology. 2020; 3(1): 1-7.
• 29. Pan J, st. Pierre JM, Pickering TA, et al. Coronavirus disease 2019 (COVID-19): A modeling study of factors driving variation in case fatality rate by country. International Journal of Environmental Research and Public Health. 2020; 17(21): 1-11.
• 30. Velasco JM, Tseng WC, Chang CL. Factors affecting the cases and deaths of Covid-19 victims. International Journal of Environmental Research and Public Health. 2021; 18(2): 1-10.
• 31. Sorci G, Faivre B, Morand S. Explaining among-country variation in COVID-19 case fatality rate. Scientific Reports. 2020; 10(1): 18909.
• 32. Sornette D, Mearns E, Schatz M, et al. Interpreting, analysing and modelling COVID-19 mortality data. Nonlinear Dynamics. 2020; 101(3): 1751-1776.
• 33. Hasan MN, Haider N, Stigler FL, et al. The global case-fatality rate of COVID-19 has been declining since may 2020. American Journal of Tropical Medicine and Hygiene. 2021; 104(6): 2176-2184.
• 34. Teixeira da Silva JA, Tsigaris P. Policy determinants of COVID-19 pandemic–induced fatality rates across nations. Public Health. 2020; 187: 140-142.