Evidence map›Paper›PMID 41154947›Full record

ArticleInternational journal of environmental research and public health2025

A Geographic Weighted Regression Analysis of the Health Opportunity Index and Stroke Prevalence in Health and Human Services Region 3.

Wanderimam R Tuktur, Bin Cai, Howell C Sasser, Rexford Anson-Dwamena

Abstract read
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Article in International journal of environmental research and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Wanderimam R TukturOffice of Health Equity, District of Columbia Department of Health, 2201 Shannon Pl SE, Washington, DC 20020, USA.ORCID 0000-0002-6859-5691
Bin CaiCollege of Health Sciences & Public Policy, Walden University, 100 Washington Avenue South, Suite 900, Minneapolis, MN 55401, USA.ORCID 0000-0003-0410-8820
Howell C SasserCollege of Health Sciences & Public Policy, Walden University, 100 Washington Avenue South, Suite 900, Minneapolis, MN 55401, USA.
Rexford Anson-DwamenaOffice of Health Equity, Virginia Department of Health, Richmond, VA 23219, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although stroke prevalence remains one of the leading causes of death and morbidity in the United States, there is paucity of ecological studies at the census tract level that elucidate geospatial associations between predictors of stroke prevalence in states across U.S. Health and Human Services Region 3 (HHS Region 3: Delaware, Maryland, Pennsylvania, Virginia, West Virginia, and the District of Columbia). This study operationalized the Health Opportunity Index (HOI) by exploring the geospatial relationship between the 13 indicators of the HOI and stroke prevalence at the census tract level in HHS Region 3 using four HOI indicator profiles: (a) neighborhood and built environment profile, (b) social and community context profile, (c) resource profile, and (d) economic profile. The methodological approach was quantitative using secondary data. The sample size was 8021 census tracts. The HOI was estimated for each census tract in the study area. Geographic weighted regression model was run to examine the varying strengths and direction of geospatial relationship of 13 HOI indicators and stroke prevalence across census tracts in HHS Region 3. The results showed variation in the geographic weighted regression (GWR) local estimated coefficients for each indicator across the study area, reflecting variation in the strength and direction of the associations. The findings of our study can guide the identification of geographic priorities for resource allocation, design of quality improvement interventions, inform policy creation and targeted local strategies for stroke prevention services across neighborhoods, support grant applications, and inform future research on stroke prevalence in HHS Region 3.

Indexed as

StrokeHumansPrevalenceRegression AnalysisUnited Statesgeographic weighted regressiongeospatialHealth and Human Services Region 3 (HHS Region 3)health disparitiesHealth Opportunity Index (HOI)neighborhood effectpopulation studypublic healthsocial determinants of healthstroke prevalence

Identifiers

PMID41154947
PMCPMC12562347

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