Evidence map›Paper›PMID 26086690›Full record

ArticleHealth & place2015

Place as a predictor of health insurance coverage: A multivariate analysis of counties in the United States.

Lisa Cacari Stone, Blake Boursaw, Sonia P Bettez, Tennille Larzelere Marley, Howard Waitzkin

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Health & place, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Review
  7. Quantifying and explaining variation in life expectancy at census tract, county, and state levels in the United States.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  8. Article
  9. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Lisa Cacari StonePublic Health Program, Department of Family & Community Medicine, University of New Mexico Health Sciences Center, MSC 095060, 1 University, Albuquerque, NM 87131, United States; Robert Wood Johnson Foundation Center for Health Policy, University of New Mexico Health Sciences Center, MSC 095060, 1 University, Albuquerque, NM 87131, United States; Community Engagement Core, NM CARES Health Disparities Center, University of New Mexico Health Sciences Center, MSC 095060, 1 University, Albuquerque, NM 87131, United States; U.S.-Mexico Border Center of Excellence Consortium, University of New Mexico Health Sciences Center, MSC 095060, 1 University, Albuquerque, NM 87131, United States. Electronic address: Lcacari-stone@salud.unm.edu.
Blake BoursawCollege of Nursing, University of New Mexico, MSC09 5350, 1 University of New Mexico, Albuquerque, NM 87131, United States. Electronic address: bboursaw@salud.unm.edu.
Sonia P BettezRWJF Center for Health Policy, University of New Mexico, PO Box 90, Corrales, NM 87048-0090, United States. Electronic address: spbettez@unm.edu.
Tennille Larzelere MarleyAmerican Indian Studies at Arizona State University, United States. Electronic address: Tennille.Marley@asu.edu.
Howard WaitzkinRobert Wood Johnson Foundation Center for Health Policy, University of New Mexico Health Sciences Center, MSC 095060, 1 University, Albuquerque, NM 87131, United States; Department of Sociology, University of New Mexico; Department of Internal Medicine, University of Illinois; School of Public Health, University of Puerto Rico, 5406 East Drive, Loves Park, IL 61111, United States. Electronic address: waitzkin@unm.edu.

Funding

Transdisciplinary Research, Equity and Engagement Center for Advancing Behavioral HealthU54MD004811 · NIMHD · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI CACARI STONE, LISA MARIE · 2017 to 2022
$8.7M
NIMHD NIH HHS U54 MD004811
6 · The paper itself

Abstract

This study assessed the importance of county characteristics in explaining county-level variations in health insurance coverage. Using public databases from 2008 to 2012, we studied 3112 counties in the United States. Rates of uninsurance ranged widely from 3% to 53%. Multivariate analysis suggested that poverty, unemployment, Republican voting, and percentages of Hispanic and American Indian/Alaskan Native residents in a county were significant predictors of uninsurance rates. The associations between uninsurance rates and both race/ethnicity and poverty varied significantly between metropolitan and non-metropolitan counties. Collaborative actions by the federal, tribal, state, and county governments are needed to promote coverage and access to care.

Indexed as

Insurance, HealthCensusesEthnicityHealth Services AccessibilityHumansInsurance CoverageLocal GovernmentPovertyResidence CharacteristicsUnemploymentUnited StatesCounty governmentHealth care accessHealth reformInsurance coverage

Identifiers

PMID26086690
PMCPMC6528484

What OpenQuestion holds

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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.