1
|
Kayı İ, Gönen M, Sakarya S, Eryiğit ÖY, Ergönül Ö. Gender-Based Socio-Economic Inequalities in the Pre-Vaccination Era of the COVID-19 Pandemic in Istanbul: A Neighborhood-Level Analysis of Excess Mortality. Healthcare (Basel) 2024; 12:1406. [PMID: 39057549 PMCID: PMC11276765 DOI: 10.3390/healthcare12141406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 06/30/2024] [Accepted: 07/01/2024] [Indexed: 07/28/2024] Open
Abstract
Worldwide excess mortality (EM) data have the potential to provide a better estimation of the impact of the pandemic. This study aims to investigate and map the inequalities in EM in Istanbul during the pre-vaccination era of the COVID-19 pandemic in 2020 and its association with selected demographic and socio-economic variables at the neighborhood level according to gender. This ecological study was conducted with the EM data of Istanbul. The EM data were obtained from the Istanbul Metropolitan Municipality (IMM) and analyzed according to socio-demographic indicators (gender, age), neighborhood-level indicators (population density, educational attainment) and neighborhood vulnerability (socio-economic and transportation) for the 808 neighborhoods, then presented separately according to gender to examine gender-specific factors. Socio-economic and transportation vulnerability indexes are provided the IMM. The excess mortality rate per 1000 (EMR) in 2020 has been calculated by using the number of deaths in the years 2018-2019. We have mapped EMRs of each neighborhood and used linear regression analysis in three datasets to examine gender specific factors. EMRs in Istanbul showed two peaks one in April and one in November. Male EMRs were higher compared to females in Istanbul during the pre-vaccination era of the pandemic. Higher EMRs were observed in neighborhoods with a higher share of 50+ year old age groups and higher neighborhood socio-economic vulnerability scores. Neighborhood socio-economic vulnerability was significantly associated with EMRs in males but not in females. Unequal distribution of EM between neighborhoods underlines the need for gender-specific pandemic measures to alleviate the burden of the COVID-19 pandemic, especially in socio-economically vulnerable settings. Increased use of area-based indicators with a gender perspective can enhance pandemic measures.
Collapse
Affiliation(s)
- İlker Kayı
- Department of Public Health, School of Medicine, Koc University, Istanbul 34010, Türkiye;
- Department of Global Health, Graduate School of Health Sciences, Koc University, Istanbul 34450, Türkiye
| | - Mehmet Gönen
- Department of Industrial Engineering, College of Engineering, Koc University, Istanbul 34450, Türkiye;
- Koc University Is Bank Research Center for Infectious Diseases, Koc University Hospital, Istanbul 34010, Türkiye;
| | - Sibel Sakarya
- Department of Public Health, School of Medicine, Koc University, Istanbul 34010, Türkiye;
- Department of Global Health, Graduate School of Health Sciences, Koc University, Istanbul 34450, Türkiye
| | | | - Önder Ergönül
- Koc University Is Bank Research Center for Infectious Diseases, Koc University Hospital, Istanbul 34010, Türkiye;
- Department of Infectious Diseases and Clinical Microbiology, School of Medicine, Koc University, Istanbul 34450, Turkey
| |
Collapse
|
2
|
Hosseinpoor AR, Nambiar D, Kirkby K, Ruano AL, McFeeley S. The many revelations of and about inequality data in the context of COVID-19: introducing a special issue on COVID-19 and inequality. Int J Equity Health 2023; 21:194. [PMID: 36703195 PMCID: PMC9878472 DOI: 10.1186/s12939-022-01820-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Affiliation(s)
- Ahmad Reza Hosseinpoor
- Department of Data and Analytics, Division of Data, Analytics and Delivery for Impact, World Health Organization, 20, Avenue Appia, CH-1211, Geneva 27, Switzerland.
| | - Devaki Nambiar
- grid.3575.40000000121633745Department of Data and Analytics, Division of Data, Analytics and Delivery for Impact, World Health Organization, 20, Avenue Appia, CH-1211 Geneva 27, Switzerland
| | - Katherine Kirkby
- grid.3575.40000000121633745Department of Data and Analytics, Division of Data, Analytics and Delivery for Impact, World Health Organization, 20, Avenue Appia, CH-1211 Geneva 27, Switzerland
| | - Ana Lorena Ruano
- grid.7914.b0000 0004 1936 7443Center for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Stephen McFeeley
- grid.3575.40000000121633745Department of Data and Analytics, Division of Data, Analytics and Delivery for Impact, World Health Organization, 20, Avenue Appia, CH-1211 Geneva 27, Switzerland
| |
Collapse
|