Evidence map›Paper›PMID 40465555›Full record

ArticlePloS one2025

Economic factors associated with county-level mental health - United States, 2019.

Michele L F Bolduc, Parya Saberi, Torsten B Neilands, Carla I Mercado, Shanice Battle Johnson, Zoe R F Freggens, Desmond Banks, Rashid Njai, Kai McKeever Bullard

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Michele L F BolducOffice of Minority Health, Office of Health Equity, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America.ORCID 0000-0002-1261-0290
Parya SaberiDivision of Prevention Science, Department of Medicine, University of California, San Francisco, California, United States of America.ORCID 0000-0002-3793-5112
Torsten B NeilandsDivision of Prevention Science, Department of Medicine, University of California, San Francisco, California, United States of America.
Carla I MercadoOffice of Minority Health, Office of Health Equity, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America.
Shanice Battle JohnsonOffice of Minority Health, Office of Health Equity, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America.
Zoe R F FreggensOffice of Minority Health, Office of Health Equity, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America.ORCID 0000-0001-7677-596X
Desmond BanksOffice of Minority Health, Office of Health Equity, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America.
Rashid NjaiOffice of Minority Health, Office of Health Equity, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America.ORCID 0000-0002-4181-1892
Kai McKeever BullardDivision of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, CDC, Atlanta, Georgia, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A better understanding of whether and how economic factors impact mental health can inform policy and program decisions to improve mental health. This study looked at the association between county-level economic factors and the prevalence of self-reported poor mental health among adults in United States counties in 2019, overall and disaggregated for urban and rural counties. General dominance analyses were completed to rank-order the relative influence of the selected variables in explaining county prevalence of adults reporting > 14 poor mental health days in the last 30 days ("poor mental health"). The highest weighted variables were assessed for the statistical significance of their relationships with county-level poor mental health through multiple linear regression. Across all models, the four highest-ranked economic factors were household income, receipt of Supplemental Security Income, population with a college degree, and receipt of Supplemental Nutrition Assistance Program benefits. The overall, rural, and urban models explained over 68% of the variation in poor mental health prevalence between counties. Urban and rural models showed notable differences in the top factors associated with poor mental health and opposite associations between poor mental health and population with public insurance. The findings from this study indicate a significant association between several economic factors and poor mental health, which may inform decision makers in addressing mental health in the United States.

Indexed as

Economic FactorsMental DisordersMental HealthAdultFemaleHumansMaleMiddle AgedPrevalenceRural PopulationSocioeconomic FactorsUnited StatesUrban PopulationYoung Adult

Identifiers

PMID40465555
PMCPMC12136295

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Registered trials

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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.