Population-weighted exposure to green spaces tied to lower COVID-19 mortality rates: A nationwide dose-response study in the USA

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2022.05.24.22275549: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: Thank you for sharing your code and data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    4.3 Limitations and future research opportunities: This study has several limitations, which pose opportunities for future research. This is an ecological study using aggregated data at the county level. It is subjected to ecological fallacy. Future studies can use individual level data or experimental studies to confirm the causal relations and the potential underlying mechanisms (Jiang et al., 2021). Second, the unit of analysis is the county due to the availability of COVID-19 mortality data and other confounding variable. Though county data are widely used in nationwide studies, future studies should use finer-grained data (i.e., census tract level data). Different scales of analyses may reveal different associations between neighborhood greenspace and health outcomes (Richardson et al., 2012). Third, our research investigated associations using data from 2020, but the situation has continued to evolve with the emergence of vaccines and COVID-19 variants (e.g., Delta and Omicron). Future studies should consider the new situations accordingly.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.