See the published version of this preprint at International Journal for Equity in Health.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
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Research
Hailun Liang
Johns Hopkins University Bloomberg School of Public Health
Corresponding Author
ORCiD: https://orcid.org/0000-0002-9917-411X
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Objective
This study applies the vulnerability framework and examines the combined effect of race and income on health insurance coverage in the US. Results of the study could assist policymakers in targeting limited resources on subpopulations likely most in need of assistance for insurance coverage.
Data sources
The household component of the US Medical Expenditure Panel Survey (MEPS-HC) in 2017 was used for the study.
Study design
Logistic regression models were used to estimate the associations between insurance coverage status and vulnerability measure, comparing insured with uninsured or partially insured, partially insured only, and uninsured only, respectively.
Data collection/extraction methods
We constructed a vulnerability measure that reflects the convergence of predisposing (race/ethnicity), enabling (income), and need (self-perceived health status) attributes of risk.
Principal findings
While income was a significant predictor of health insurance coverage (a difference of 6.1%-7.2% between high- and low-income Americans), race/ethnicity was independently associated with lack of insurance. The combined effect of income and race on insurance coverage was devastating as low-income minorities with bad health had 66% less odds of being insured instead of uninsured or partially insured than high-income Whites with good health.
Conclusions
Policymakers should target insurance coverage for the most vulnerable subpopulation, i.e., those who have low income and are racial/ethnic minorities.
Keywords
Convergence, United States, Health Insurance
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CURRENT STATUS: Published
View the published article at International Journal for Equity in Health.
Version 1
Posted 10 Dec, 2020
No community comments so far
Editorial decision: Major Revision
On 30 Jan, 2021
Review #3 received
Received 21 Jan, 2021
Review #2 received
Received 10 Jan, 2021
Review #4 received
Received 04 Jan, 2021
Reviewer #4 agreed
On 03 Jan, 2021
Reviewer #3 agreed
On 01 Jan, 2021
Review #1 received
Received 19 Dec, 2020
Reviewer #2 agreed
On 13 Dec, 2020
Editor assigned
On 02 Dec, 2020
Reviewers invited
Invitations sent on 02 Dec, 2020
Reviewer #1 agreed
On 02 Dec, 2020
Submission checks complete
On 02 Dec, 2020
Editor invited
On 02 Dec, 2020
First submitted
On 01 Dec, 2020
Metrics
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PDF Downloads: ...
HTML Views: ...
Subject Areas
Health Policy
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A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at International Journal for Equity in Health.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Hailun Liang
Johns Hopkins University Bloomberg School of Public Health
Corresponding Author
ORCiD: https://orcid.org/0000-0002-9917-411X
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at International Journal for Equity in Health.
Version 1
Posted 10 Dec, 2020
No community comments so far
Editorial decision: Major Revision
On 30 Jan, 2021
Review #3 received
Received 21 Jan, 2021
Review #2 received
Received 10 Jan, 2021
Review #4 received
Received 04 Jan, 2021
Reviewer #4 agreed
On 03 Jan, 2021
Reviewer #3 agreed
On 01 Jan, 2021
Review #1 received
Received 19 Dec, 2020
Reviewer #2 agreed
On 13 Dec, 2020
Editor assigned
On 02 Dec, 2020
Reviewers invited
Invitations sent on 02 Dec, 2020
Reviewer #1 agreed
On 02 Dec, 2020
Submission checks complete
On 02 Dec, 2020
Editor invited
On 02 Dec, 2020
First submitted
On 01 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Health Policy
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at International Journal for Equity in Health.
Objective
This study applies the vulnerability framework and examines the combined effect of race and income on health insurance coverage in the US. Results of the study could assist policymakers in targeting limited resources on subpopulations likely most in need of assistance for insurance coverage.
Data sources
The household component of the US Medical Expenditure Panel Survey (MEPS-HC) in 2017 was used for the study.
Study design
Logistic regression models were used to estimate the associations between insurance coverage status and vulnerability measure, comparing insured with uninsured or partially insured, partially insured only, and uninsured only, respectively.
Data collection/extraction methods
We constructed a vulnerability measure that reflects the convergence of predisposing (race/ethnicity), enabling (income), and need (self-perceived health status) attributes of risk.
Principal findings
While income was a significant predictor of health insurance coverage (a difference of 6.1%-7.2% between high- and low-income Americans), race/ethnicity was independently associated with lack of insurance. The combined effect of income and race on insurance coverage was devastating as low-income minorities with bad health had 66% less odds of being insured instead of uninsured or partially insured than high-income Whites with good health.
Conclusions
Policymakers should target insurance coverage for the most vulnerable subpopulation, i.e., those who have low income and are racial/ethnic minorities.
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