J Korean Med Sci.  2021 Apr;36(13):e100. 10.3346/jkms.2021.36.e100.

Interaction Effects between COVID-19 Outbreak and Community Income Levels on Excess Mortality among Patients Visiting Emergency Departments

• Jung E
• Ro YS
• Ryu HH
• Shin SD
• Moon S

• KMID: 2514757
• DOI: http://doi.org/10.3346/jkms.2021.36.e100

Abstract

Background
The objective of this study was to examine the effect of the coronavirus disease 2019 (COVID-19) outbreak on excess in-hospital mortality among patients who visited emergency departments (EDs) and to assess whether the excess mortality during the COVID-19 pandemic varies by community income level.
Methods
This is a cross-sectional study using the National Emergency Department Information System (NEDIS) database in Korea. The study population was defined as patients who visited all 402 EDs with medical conditions other than injuries between January 27 and May 31, 2020 (after-COVID) and for the corresponding time period in 2019 (before-COVID). The primary outcome was in-hospital mortality. The main exposure was the COVID-19 outbreak, and the interaction variable was county per capita income tax. We calculated the risk-adjusted in-hospital mortality rates by COVID-19 outbreak, as well as the difference-in-difference of risk-adjusted rates between the before-COVID and after-COVID groups according to the county income tax using a multilevel linear regression model with the interaction term.
Results
A total of 11,662,167 patients (6,765,717 in before-COVID and 4,896,450 in afterCOVID) were included in the study with a 1.6% crude in-hospital mortality rate. The riskadjusted mortality rate in the after-COVID group was higher than that in the before-COVID group (1.82% vs. 1.50%, difference: 0.31% [0.30 to 0.33]; adjusted odds ratio: 1.22 [1.18 to 1.25]). The excess in-hospital mortality rate of the after-COVID in the lowest quartile group of county income tax was significantly higher than that in the highest quartile group (difference-in-difference: 0.18% (0.14 to 0.23); P-for-interaction: < 0.01).
Conclusion
During the COVID-19 pandemic, there was excess in-hospital mortality among patients who visited EDs, and there were disparities in excess mortality depending on community socioeconomic positions.

Keyword

COVID-19; Excess Mortality; Socioeconomic Position

Reference

1. World Health Organization. WHO coronavirus disease (COVID-19) dashboard. Accessed December 5, 2020. http://covid19.who.int/table.

2. Calderón-Larrañaga A, Vetrano DL, Rizzuto D, Bellander T, Fratiglioni L, Dekhtyar S. High excess mortality in areas with young and socially vulnerable populations during the COVID-19 outbreak in Stockholm Region, Sweden. BMJ Glob Health. 2020; 5(10):e003595.

3. Birkmeyer JD, Barnato A, Birkmeyer N, Bessler R, Skinner J. The impact of the covid-19 pandemic on hospital admissions in the United States. Health Aff (Millwood). 2020; 39(11):2010–2017. PMID: 32970495.

4. Hawkins RB, Charles EJ, Mehaffey JH. Socio-economic status and COVID-19-related cases and fatalities. Public Health. 2020; 189:129–134. PMID: 33227595.

5. Rahmatinejad Z, Tohidinezhad F, Reihani H, Rahmatinejad F, Pourmand A, Abu-Hanna A, et al. Prognostic utilization of models based on the APACHE II, APACHE IV, and SAPS II scores for predicting in-hospital mortality in emergency department. Am J Emerg Med. 2020; 38(9):1841–1846. PMID: 32739855.

6. Murao S, Yamakawa K, Kabata D, Kinoshita T, Umemura Y, Shintani A, et al. Effect of earlier door-to-CT and door-to-bleeding control in severe blunt trauma: a retrospective cohort study. Research Square. Forthcoming. 2020; DOI: 10.21203/rs.3.rs-23452/v1.

7. Galobardes B, Shaw M, Lawlor DA, Lynch JW, Davey Smith G. Indicators of socioeconomic position (part 1). J Epidemiol Community Health. 2006; 60(1):7–12.

8. Bassuk SS, Berkman LF, Amick BC 3rd. Socioeconomic status and mortality among the elderly: findings from four US communities. Am J Epidemiol. 2002; 155(6):520–533. PMID: 11882526.

9. Winkleby MA, Cubbin C. Influence of individual and neighbourhood socioeconomic status on mortality among black, Mexican-American, and white women and men in the United States. J Epidemiol Community Health. 2003; 57(6):444–452. PMID: 12775792.

10. Rawshani A, Svensson AM, Zethelius B, Eliasson B, Rosengren A, Gudbjörnsdottir S. Association between socioeconomic status and mortality, cardiovascular disease, and cancer in patients with type 2 diabetes. JAMA Intern Med. 2016; 176(8):1146–1154. PMID: 27367969.

11. Lee SY, Song KJ, Shin SD, Ro YS, Hong KJ, Kim YT, et al. A disparity in outcomes of out-of-hospital cardiac arrest by community socioeconomic status: a ten-year observational study. Resuscitation. 2018; 126:130–136. PMID: 29481908.

12. Chang I, Ro YS, Shin SD, Song KJ, Park JH, Kong SY. Association of dispatcher-assisted bystander cardiopulmonary resuscitation with survival outcomes after pediatric out-of-hospital cardiac arrest by community property value. Resuscitation. 2018; 132:120–126. PMID: 30237060.

13. Davis JR, Wilson S, Brock-Martin A, Glover S, Svendsen ER. The impact of disasters on populations with health and health care disparities. Disaster Med Public Health Prep. 2010; 4(1):30–38. PMID: 20389193.

14. Rossen LM, Branum AM, Ahmad FB, Sutton P, Anderson RN. Excess deaths associated with COVID-19, by age and race and ethnicity—United States, January 26–October 3, 2020. MMWR Morb Mortal Wkly Rep. 2020; 69(42):1522–1527. PMID: 33090978.

15. Jung E, Park JH, Lee SY, Ro YS, Hong KJ, Song KJ, et al. Mechanical chest compression device for out-of-hospital cardiac arrest: a nationwide observational study. J Emerg Med. 2020; 58(3):424–431. PMID: 32178958.

16. Cha WC, Ahn KO, Shin SD, Park JH, Cho JS. Emergency department crowding disparity: a nationwide cross-sectional study. J Korean Med Sci. 2016; 31(8):1331–1336. PMID: 27478347.

17. Johns Hopkins Coronavirus Resource Center. COVID-19 map. Updated 2020. Accessed December 12, 2020. https://coronavirus.jhu.edu/map.html.

18. Burn-Murdoch J, Giles C. UK suffers second-highest death rate from coronavirus. Updated 2020. Accessed December 12, 2020. https://www.ft.com/content/6b4c784e-c259-4ca4-9a82-648ffde71bf0.

19. Magnani C, Azzolina D, Gallo E, Ferrante D, Gregori D. How large was the mortality increase directly and indirectly caused by the COVID-19 epidemic? An analysis on all-causes mortality data in Italy. Int J Environ Res Public Health. 2020; 17(10):E3452. PMID: 32429172.

20. Roberton T, Carter ED, Chou VB, Stegmuller AR, Jackson BD, Tam Y, et al. Early estimates of the indirect effects of the COVID-19 pandemic on maternal and child mortality in low-income and middle-income countries: a modelling study. Lancet Glob Health. 2020; 8(7):e901–8. PMID: 32405459.

21. Hernández-Vásquez A, Gamboa-Unsihuay JE, Vargas-Fernández R, Azañedo D. Excess mortality in Metropolitan Lima during the COVID-19 pandemic: A district level comparison. Medwave. 2020; 20(8):e8031. PMID: 33017383.

22. Drefahl S, Wallace M, Mussino E, Aradhya S, Kolk M, Brandén M, et al. A population-based cohort study of socio-demographic risk factors for COVID-19 deaths in Sweden. Nat Commun. 2020; 11(1):5097. PMID: 33037218.

23. de Lusignan S, Dorward J, Correa A, Jones N, Akinyemi O, Amirthalingam G, 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(9):1034–1042. PMID: 32422204.

24. Östlin P, Diderichsen F. Equity-Oriented National Strategy for Public Health in Sweden. Copenhagen, Denmark: WHO Regional Office for Europe;2001.