-
- Suman Chakrabarti, Leigh C Hamlet, Jessica Kaminsky, and S V Subramanian.
- Department of Global Health, University of Washington Schools of Public Health and Medicine, Seattle.
- JAMA Netw Open. 2021 Apr 1; 4 (4): e217373.
ImportanceAn accurate understanding of the distributional implications of public health policies is critical for ensuring equitable responses to the COVID-19 pandemic and future public health threats.ObjectiveTo identify and quantify the association of race/ethnicity-based, sex-based, and income-based inequities of state-specific lockdowns with 6 well-being dimensions in the United States.Design, Setting, And ParticipantsThis pooled, repeated cross-sectional study used data from 14 187 762 households who participated in phase 1 of the population-representative US 2020 Household Pulse Survey (HPS). Households were invited to participate by email, text message, and/or telephone as many as 3 times. Data were collected via an online questionnaire from April 23 to July 21, 2020, and participants lived in all 50 US states and the District of Columbia.ExposuresIndicators of race/ethnicity, sex, and income and their intersections.Main Outcomes And MeasuresUnemployment; food insufficiency; mental health problems; no medical care received for health problems; default on last month's rent or mortgage; and class cancellations with no distance learning. Race/ethnicity, sex, income, and their intersections were used to measure distributional implications across historically marginalized populations; state-specific, time-varying population mobility was used to measure lockdown intensity. Logistic regression models with pooled repeated cross-sections were used to estimate risk of dichotomous outcomes by social group, adjusted for confounding variables.ResultsThe 1 088 314 respondents (561 570 [51.6%; 95% CI, 51.4%-51.9%] women) were aged 18 to 88 years (mean [SD], 51.55 [15.74] years), and 826 039 (62.8%; 95% CI, 62.5%-63.1%) were non-Hispanic White individuals; 86 958 (12.5%; 95% CI, 12.4%-12.7%), African American individuals; 86 062 (15.2%; 95% CI, 15.0%-15.4%), Hispanic individuals; and 50 227 (5.6%; 95% CI, 5.5%-5.7%), Asian individuals. On average, every 10% reduction in mobility was associated with higher odds of unemployment (odds ratio [OR], 1.3; 95% CI, 1.2-1.4), food insufficiency (OR, 1.1; 95% CI, 1.1-1.2), mental health problems (OR, 1.04; 95% CI, 1.0-1.1), and class cancellations (OR, 1.1; 95% CI, 1.1-1.2). Across most dimensions compared with White men with high income, African American individuals with low income experienced the highest risks (eg, food insufficiency, men: OR, 3.3; 95% CI, 2.8-3.7; mental health problems, women: OR, 1.9; 95% CI, 1.8-2.1; medical care inaccessibility, women: OR, 1.7; 95% CI, 1.6-1.9; unemployment, men: OR, 2.8; 95% CI, 2.5-3.2; rent/mortgage defaults, men: OR, 5.7; 95% CI, 4.7-7.1). Other high-risk groups were Hispanic individuals (eg, unemployment, Hispanic men with low income: OR, 2.9; 95% CI, 2.5-3.4) and women with low income across all races/ethnicities (eg, medical care inaccessibility, non-Hispanic White women: OR, 1.8; 95% CI, 1.7-2.0).Conclusions And RelevanceIn this cross-sectional study, African American and Hispanic individuals, women, and households with low income had higher odds of experiencing adverse outcomes associated with the COVID-19 pandemic and stay-at-home orders. Blanket public health policies ignoring existing distributions of risk to well-being may be associated with increased race/ethnicity-based, sex-based, and income-based inequities.
Notes
Knowledge, pearl, summary or comment to share?You can also include formatting, links, images and footnotes in your notes
- Simple formatting can be added to notes, such as
*italics*
,_underline_
or**bold**
. - Superscript can be denoted by
<sup>text</sup>
and subscript<sub>text</sub>
. - Numbered or bulleted lists can be created using either numbered lines
1. 2. 3.
, hyphens-
or asterisks*
. - Links can be included with:
[my link to pubmed](http://pubmed.com)
- Images can be included with:
![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
- For footnotes use
[^1](This is a footnote.)
inline. - Or use an inline reference
[^1]
to refer to a longer footnote elseweher in the document[^1]: This is a long footnote.
.