Evidence map›Paper›PMID 36530218›Full record

ArticleDialogues in health2023

A Neighborhood-level analysis of mental health distress and income inequality as quasi-longitudinal risk of reported COVID-19 infection and mortality outcomes in Chicago.

Stephen D Ramos, Lynn Kannout, Humza Khan, Lynne Klasko-Foster, Briana N C Chronister, Steff Du Bois

Open access · goldAbstract read
In one paragraph

Article in Dialogues in health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Stephen D RamosUniversity of California San Diego, Division of Infectious Diseases and Global Public Health, Department of Medicine, San Diego, CA 92093, USA.
Lynn KannoutIllinois Institute of Technology, Department of Psychology, Chicago, IL 60616, USA.
Humza KhanIllinois Institute of Technology, Department of Psychology, Chicago, IL 60616, USA.
Lynne Klasko-FosterBrown University, Department of Psychiatry and Human Behavior, Providence, RH 02912, USA.
Briana N C ChronisterHerbert Wertheim School of Public Health, University of California San Diego, San Diego, CA 92093, USA.
Steff Du BoisIllinois Institute of Technology, Department of Psychology, Chicago, IL 60616, USA.
Illinois Institute of Technology · USBrown University · USSan Diego State University · USUniversity of California, San Diego · US

Funding

Training Program in Substance Use, HIV and Related InfectionsT32DA023356 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Natasha Martin, Steffanie A Strathdee · 2007 to 2026
$7.8M
Advanced data analytics training for behavioral and social sciences researchT32MH122376 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HEKLER, ERIC, POLITIS, DIMITRIS · 2020 to 2024
$1.3M
NIDA NIH HHS T32 DA023356NIMH NIH HHS T32 MH122376
6 · The paper itself

Abstract

Extant literature investigates the impact of COVID-19 on mental health outcomes, however there is a paucity of work examining mental health distress as a risk factor for COVID-19 outcomes. While systemic variables like income inequality relate to both mental health and COVID-19, more work is needed to test theoretically informed models including such variables. Using a social-ecological framework, we aimed to address these gaps in the literature by conducting a neighborhood-level analysis of potential mental health distress and systemic- (income inequality) level predictors of reported COVID-19 infection and mortality over time in Chicago. Neighborhood-level comparisons revealed differences in mental health distress, income inequality, and reported COVID-19 mortality, but not reported COVID-19 infection. Specifically, Westside and Southside neighborhoods generally reported higher levels of mental health distress and greater concentration of poverty. The Central neighborhood showed a decline in reported mortality rates over time. Multi-level negative binomial models established that Zip-codes with greater mental health distress were at increased reported COVID-19 infection risk, yet lower mortality risk; Zip-codes with more poverty were at increased reported COVID-19 infection risk, yet lower mortality risk; and Zip-codes with the highest percentage of People of Color were at decreased risk of reported COVID-19 mortality. Taken together, these findings substantiate Chicago neighborhood-level disparities in mental health distress, income inequality, and reported COVID-19 mortality; identify unique differential associations of mental health distress and income inequality to reported COVID-19 infection and reported mortality risk; and, offer an alternative lens towards understanding COVID-19 outcomes in terms of race/ethnicity.

Indexed as

COVID-19 infectionCOVID-19 mortalityIncome inequalityMental health distressNeighborhood-level analysis

Identifiers

PMID36530218
PMCPMC9731648
OpenAlexW4311141296

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.