Cargando…
Tokyo and New York: A Study in the Contrasting Effects of Socioeconomic Status on Coronavirus Disease 2019 Outcomes
OBJECTIVES: It is still not known why cases of coronavirus disease 2019 during the first wave in Tokyo have fallen without lockdown restrictions. People with low socioeconomic status are not dominant among coronavirus disease 2019 patients in Tokyo in contrast with New York, where the opposite demog...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498128/ https://www.ncbi.nlm.nih.gov/pubmed/32984839 http://dx.doi.org/10.1097/CCE.0000000000000221 |
_version_ | 1783583446179774464 |
---|---|
author | Hifumi, Toru Ishikawa, Yohei Otani, Norio Ishimatsu, Shinichi Urashima, Mitsuyoshi |
author_facet | Hifumi, Toru Ishikawa, Yohei Otani, Norio Ishimatsu, Shinichi Urashima, Mitsuyoshi |
author_sort | Hifumi, Toru |
collection | PubMed |
description | OBJECTIVES: It is still not known why cases of coronavirus disease 2019 during the first wave in Tokyo have fallen without lockdown restrictions. People with low socioeconomic status are not dominant among coronavirus disease 2019 patients in Tokyo in contrast with New York, where the opposite demographics have been in play. Thus, we set out to examine the association between socioeconomic status and the rate of coronavirus disease 2019 infections using public data from Tokyo. DESIGN: We obtained data from each of the 23 wards of Tokyo, showing population size, density, age, sex, number of graduates, income, and hospital attendance numbers. Coronavirus disease 2019 infections were gathered for 2 separate days: April 9, 2020, when new daily coronavirus disease 2019 infections were at their peak during the first wave in Japan; and May 9, 2020, to observe any changes in incidence over the preceding month. SETTING: The primary outcome was set as the number of coronavirus disease 2019 infections per 100,000 population. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: By conducting simple linear regression modeling, the incidence of cases on April 9 was associated significantly with four variables: population age greater than 65 years (%), university rate, hospital, and income. Using these four variables, multivariate linear regression analyses demonstrated that only income remained significant (p = 0.006 at April 9 and p = 0.03 at May 9). This indicates that the highest case numbers were dominant in high-income areas, and affected fewer patients in districts in the low-income areas. CONCLUSIONS: The result of the current study is exactly opposite to the data from New York. This may be considered one of the main reasons why the rate of death and new patients of coronavirus disease 2019 has been so low in Tokyo. That is, appropriate hygienic status, free access to hospital by ambulance, and universal health insurance system may contribute to the outcome in such low-income areas. |
format | Online Article Text |
id | pubmed-7498128 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-74981282020-09-24 Tokyo and New York: A Study in the Contrasting Effects of Socioeconomic Status on Coronavirus Disease 2019 Outcomes Hifumi, Toru Ishikawa, Yohei Otani, Norio Ishimatsu, Shinichi Urashima, Mitsuyoshi Crit Care Explor Brief Report OBJECTIVES: It is still not known why cases of coronavirus disease 2019 during the first wave in Tokyo have fallen without lockdown restrictions. People with low socioeconomic status are not dominant among coronavirus disease 2019 patients in Tokyo in contrast with New York, where the opposite demographics have been in play. Thus, we set out to examine the association between socioeconomic status and the rate of coronavirus disease 2019 infections using public data from Tokyo. DESIGN: We obtained data from each of the 23 wards of Tokyo, showing population size, density, age, sex, number of graduates, income, and hospital attendance numbers. Coronavirus disease 2019 infections were gathered for 2 separate days: April 9, 2020, when new daily coronavirus disease 2019 infections were at their peak during the first wave in Japan; and May 9, 2020, to observe any changes in incidence over the preceding month. SETTING: The primary outcome was set as the number of coronavirus disease 2019 infections per 100,000 population. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: By conducting simple linear regression modeling, the incidence of cases on April 9 was associated significantly with four variables: population age greater than 65 years (%), university rate, hospital, and income. Using these four variables, multivariate linear regression analyses demonstrated that only income remained significant (p = 0.006 at April 9 and p = 0.03 at May 9). This indicates that the highest case numbers were dominant in high-income areas, and affected fewer patients in districts in the low-income areas. CONCLUSIONS: The result of the current study is exactly opposite to the data from New York. This may be considered one of the main reasons why the rate of death and new patients of coronavirus disease 2019 has been so low in Tokyo. That is, appropriate hygienic status, free access to hospital by ambulance, and universal health insurance system may contribute to the outcome in such low-income areas. Lippincott Williams & Wilkins 2020-09-15 /pmc/articles/PMC7498128/ /pubmed/32984839 http://dx.doi.org/10.1097/CCE.0000000000000221 Text en Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. |
spellingShingle | Brief Report Hifumi, Toru Ishikawa, Yohei Otani, Norio Ishimatsu, Shinichi Urashima, Mitsuyoshi Tokyo and New York: A Study in the Contrasting Effects of Socioeconomic Status on Coronavirus Disease 2019 Outcomes |
title | Tokyo and New York: A Study in the Contrasting Effects of Socioeconomic Status on Coronavirus Disease 2019 Outcomes |
title_full | Tokyo and New York: A Study in the Contrasting Effects of Socioeconomic Status on Coronavirus Disease 2019 Outcomes |
title_fullStr | Tokyo and New York: A Study in the Contrasting Effects of Socioeconomic Status on Coronavirus Disease 2019 Outcomes |
title_full_unstemmed | Tokyo and New York: A Study in the Contrasting Effects of Socioeconomic Status on Coronavirus Disease 2019 Outcomes |
title_short | Tokyo and New York: A Study in the Contrasting Effects of Socioeconomic Status on Coronavirus Disease 2019 Outcomes |
title_sort | tokyo and new york: a study in the contrasting effects of socioeconomic status on coronavirus disease 2019 outcomes |
topic | Brief Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498128/ https://www.ncbi.nlm.nih.gov/pubmed/32984839 http://dx.doi.org/10.1097/CCE.0000000000000221 |
work_keys_str_mv | AT hifumitoru tokyoandnewyorkastudyinthecontrastingeffectsofsocioeconomicstatusoncoronavirusdisease2019outcomes AT ishikawayohei tokyoandnewyorkastudyinthecontrastingeffectsofsocioeconomicstatusoncoronavirusdisease2019outcomes AT otaninorio tokyoandnewyorkastudyinthecontrastingeffectsofsocioeconomicstatusoncoronavirusdisease2019outcomes AT ishimatsushinichi tokyoandnewyorkastudyinthecontrastingeffectsofsocioeconomicstatusoncoronavirusdisease2019outcomes AT urashimamitsuyoshi tokyoandnewyorkastudyinthecontrastingeffectsofsocioeconomicstatusoncoronavirusdisease2019outcomes |