Longitudinal analyses of the relationship between development density and the COVID-19 morbidity and mortality rates : Early evidence from 1,165 metropolitan counties in the United States
Copyright © 2020 Elsevier Ltd. All rights reserved..
This longitudinal study aims to investigative the impacts of development density on the spread and mortality rates of COVID-19 in metropolitan counties in the United States. Multilevel Linear Modeling (MLM) is employed to model the infection rate and the mortality rate of COVID-19, accounting for the hierarchical (two-level) and longitudinal structure of the data. This study finds that large metropolitan size (measured in terms of population) leads to significantly higher COVID-19 infection rates and higher mortality rates. After controlling for metropolitan size and other confounding variables, county density leads to significantly lower infection rates and lower death rates. These findings recommend that urban planners and health professionals continue to advocate for compact development and continue to oppose urban sprawl for this and many other reasons documented in the literature, including the positive relationship between compact development and fitness and general health.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2020 |
|---|---|
| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:64 |
|---|---|
| Enthalten in: |
Health & place - 64(2020) vom: 15. Juli, Seite 102378 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Hamidi, Shima [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| Anmerkungen: |
Date Completed 07.09.2020 Date Revised 11.01.2021 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1016/j.healthplace.2020.102378 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM313140472 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM313140472 | ||
| 003 | DE-627 | ||
| 005 | 20231225145928.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2020 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.healthplace.2020.102378 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1043.xml |
| 035 | |a (DE-627)NLM313140472 | ||
| 035 | |a (NLM)32738578 | ||
| 035 | |a (PII)S1353-8292(20)30524-4 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Hamidi, Shima |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Longitudinal analyses of the relationship between development density and the COVID-19 morbidity and mortality rates |b Early evidence from 1,165 metropolitan counties in the United States |
| 264 | 1 | |c 2020 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 07.09.2020 | ||
| 500 | |a Date Revised 11.01.2021 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2020 Elsevier Ltd. All rights reserved. | ||
| 520 | |a This longitudinal study aims to investigative the impacts of development density on the spread and mortality rates of COVID-19 in metropolitan counties in the United States. Multilevel Linear Modeling (MLM) is employed to model the infection rate and the mortality rate of COVID-19, accounting for the hierarchical (two-level) and longitudinal structure of the data. This study finds that large metropolitan size (measured in terms of population) leads to significantly higher COVID-19 infection rates and higher mortality rates. After controlling for metropolitan size and other confounding variables, county density leads to significantly lower infection rates and lower death rates. These findings recommend that urban planners and health professionals continue to advocate for compact development and continue to oppose urban sprawl for this and many other reasons documented in the literature, including the positive relationship between compact development and fitness and general health | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 700 | 1 | |a Ewing, Reid |e verfasserin |4 aut | |
| 700 | 1 | |a Sabouri, Sadegh |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Health & place |d 1997 |g 64(2020) vom: 15. Juli, Seite 102378 |w (DE-627)NLM094517339 |x 1873-2054 |7 nnns |
| 773 | 1 | 8 | |g volume:64 |g year:2020 |g day:15 |g month:07 |g pages:102378 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.healthplace.2020.102378 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 64 |j 2020 |b 15 |c 07 |h 102378 | ||