Evidence map›Paper›PMID 36006299›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2023

Factors Associated With Health Care Delays Among Adults Over 50 During the COVID-19 Pandemic.

Athena C Y Chan, Rodlescia S Sneed

Abstract read
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Athena C Y ChanDepartment of Family Social Science, University of Minnesota, Saint Paul, Minnesota, USA.ORCID 0000-0002-2870-4582
Rodlescia S SneedInstitute of Gerontology and Department of Psychology, Wayne State University, Detroit, Michigan, USA.

Funding

HRS Yrs29-34: Y33 SSA CoFundingU01AG009740 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jessica Faul, KENNETH M LANGA · 1990 to 2026
$555.8M
Michigan Center for Urban African American Aging Research - RESEARCH CORE (REC)P30AG015281 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Briana Mezuk · 1997 to 2026
$19.3M
The Flint Center for Health Equity SolutionsU54MD011227 · NIMHD · MICHIGAN STATE UNIVERSITY · PI SADLER, RICHARD CASEY · 2016 to 2020
$10.7M
NIA NIH HHS P30 AG015281NIA NIH HHS U01 AG009740NIH HHS P30 AG015281NIMHD NIH HHS L60 MD014430NIMHD NIH HHS U54 MD011227
6 · The paper itself

Abstract

backgroundAdults over 50 have high health care needs but also face high coronavirus disease 2019 (COVID-19)-related vulnerability. This may result in a reluctance to enter public spaces, including health care settings. Here, we examined factors associated with health care delays among adults over 50 early in the COVID-19 pandemic.

methodsUsing data from the 2020 wave of the Health and Retirement Study (N = 7 615), we evaluated how race/ethnicity, age, geographic region, and pandemic-related factors were associated with health care delays.

resultsIn our sample, 3 in 10 participants who were interviewed from March 2020 to June 2021 reported delays in medical or dental care in the early stages of the COVID-19 pandemic. Non-Hispanic Whites (odds ratio [OR]: 1.37; 95% confidence interval [CI]: 1.19-1.58) and those of other racial/ethnic backgrounds (OR: 1.31; 95% CI: 1.02-1.67) delayed care more than Non-Hispanic Blacks. Other factors associated with delayed care included younger age, living in the Midwest or West, knowing someone diagnosed with or who died from COVID-19, and having high COVID-19-related concerns. There were no differences in care delays among adults aged > 70; however, among those ≤ 70, those who knew someone diagnosed with COVID-19 were more likely to delay care than those who did not. Additionally, among those ≤ 70, Non-Hispanic Whites and those of other racial/ethnic backgrounds delayed care more than Non-Hispanic Blacks and Hispanics.

conclusionsThere is considerable heterogeneity in care delays among older adults based on age, race/ethnicity, and pandemic-related factors. As the pandemic continues, future studies should examine whether these patterns persist.

Indexed as

COVID-19Time-to-TreatmentAgedBlack or African AmericanDelivery of Health CareEthnicityHispanic or LatinoHumansPandemicsUnited StatesWhiteAgeCoronavirusGeographical regionHealth and Retirement StudyHealth care delayRace/Ethnicity

Identifiers

PMID36006299
PMCPMC9452159

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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.