Evidence map›Paper›PMID 27197853›Full record

ArticleStroke2016

Reassessing the Stroke Belt: Using Small Area Spatial Statistics to Identify Clusters of High Stroke Mortality in the United States.

David N Karp, Catherine S Wolff, Douglas J Wiebe, Charles C Branas, Brendan G Carr, Michael T Mullen

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Stroke, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

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  6. Alzheimer's disease and related dementias among Medicare beneficiaries aged ≥ 65 years in rural America, by Census region and select demographic characteristics: 2020.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2025
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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

6 authors.

David N KarpFrom the Department of Biostatistics and Epidemiology (D.N.K., D.J.W., C.C.B.), Leonard Davis Institute of Health Economics (D.J.W., C.C.B., M.T.M.), and Department of Neurology (M.T.M.), University of Pennsylvania, Philadelphia; Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA (B.G.C.); and Duke University School of Medicine, Duke University, Durham, NC (C.S.W.).
Catherine S WolffFrom the Department of Biostatistics and Epidemiology (D.N.K., D.J.W., C.C.B.), Leonard Davis Institute of Health Economics (D.J.W., C.C.B., M.T.M.), and Department of Neurology (M.T.M.), University of Pennsylvania, Philadelphia; Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA (B.G.C.); and Duke University School of Medicine, Duke University, Durham, NC (C.S.W.).
Douglas J WiebeFrom the Department of Biostatistics and Epidemiology (D.N.K., D.J.W., C.C.B.), Leonard Davis Institute of Health Economics (D.J.W., C.C.B., M.T.M.), and Department of Neurology (M.T.M.), University of Pennsylvania, Philadelphia; Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA (B.G.C.); and Duke University School of Medicine, Duke University, Durham, NC (C.S.W.).
Charles C BranasFrom the Department of Biostatistics and Epidemiology (D.N.K., D.J.W., C.C.B.), Leonard Davis Institute of Health Economics (D.J.W., C.C.B., M.T.M.), and Department of Neurology (M.T.M.), University of Pennsylvania, Philadelphia; Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA (B.G.C.); and Duke University School of Medicine, Duke University, Durham, NC (C.S.W.).
Brendan G CarrFrom the Department of Biostatistics and Epidemiology (D.N.K., D.J.W., C.C.B.), Leonard Davis Institute of Health Economics (D.J.W., C.C.B., M.T.M.), and Department of Neurology (M.T.M.), University of Pennsylvania, Philadelphia; Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA (B.G.C.); and Duke University School of Medicine, Duke University, Durham, NC (C.S.W.).
Michael T MullenFrom the Department of Biostatistics and Epidemiology (D.N.K., D.J.W., C.C.B.), Leonard Davis Institute of Health Economics (D.J.W., C.C.B., M.T.M.), and Department of Neurology (M.T.M.), University of Pennsylvania, Philadelphia; Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA (B.G.C.); and Duke University School of Medicine, Duke University, Durham, NC (C.S.W.). Michael.mullen@uphs.upenn.edu.

Funding

Optimization modeling and comparative effectiveness of regionalized stroke careR01HS018362 · AHRQ · UNIVERSITY OF PENNSYLVANIA · PI BRANAS, CHARLES C. · 2010 to 2013
$1.8M
AHRQ HHS R01 HS018362
6 · The paper itself

Abstract

background and purposeThe stroke belt is described as an 8-state region with high stroke mortality across the southeastern United States. Using spatial statistics, we identified clusters of high stroke mortality (hot spots) and adjacent areas of low stroke mortality (cool spots) for US counties and evaluated for regional differences in county-level risk factors.

methodsA cross-sectional study of stroke mortality was conducted using Multiple Cause of Death data (Centers for Disease Control and Prevention) to compute age-adjusted adult stroke mortality rates for US counties. Local indicators of spatial association statistics were used for hot-spot mapping. County-level variables were compared between hot and cool spots.

resultsBetween 2008 and 2010, there were 393 121 stroke-related deaths. Median age-adjusted adult stroke mortality was 61.7 per 100 000 persons (interquartile range=51.4-74.7). We identified 705 hot-spot counties (22.4%) and 234 cool-spot counties (7.5%); 44.5% of hot-spot counties were located outside of the stroke belt. Hot spots had greater proportions of black residents, higher rates of unemployment, chronic disease, and healthcare utilization, and lower median income and educational attainment.

conclusionsClusters of high stroke mortality exist beyond the 8-state stroke belt, and variation exists within the stroke belt. Reconsideration of the stroke belt definition and increased attention to local determinants of health underlying small area regional variability could inform targeted healthcare interventions.

Indexed as

Geography, MedicalAgedCluster AnalysisCross-Sectional StudiesDiabetes MellitusEthnicityFemaleHealth ServicesHumansHypertensionMaleMiddle AgedObesityPrevalenceRisk FactorsSocioeconomic Factorsattentioncause of deathchronic diseaserisk factorsstroke

Identifiers

PMID27197853
PMCPMC4927355

What OpenQuestion holds

Textmetadata
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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.