Factors Explaining Excess Stroke Prevalence in the US Stroke Belt
Higher risk and burden of stroke have been observed within the southeastern states (the Stroke Belt) compared with elsewhere in the United States. We examined reasons for these disparities using a large data set from a nationwide cross-sectional study. Self-reported data from the 2005 and 2007 Behav...
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| Veröffentlicht in: | Stroke (1970) 2009-10, Vol.40 (10), p.3336-3341 |
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| creator | YOULIAN LIAO GREENLUND, Kurt J CROFT, Janet B KEENAN, Nora L GILES, Wayne H |
| description | Higher risk and burden of stroke have been observed within the southeastern states (the Stroke Belt) compared with elsewhere in the United States. We examined reasons for these disparities using a large data set from a nationwide cross-sectional study.
Self-reported data from the 2005 and 2007 Behavioral Risk Factor Surveillance System were used (n=765,368). The potential contributors for self-reported stroke prevalence (n=27 962) were demographics (age, sex, geography, and race/ethnicity), socioeconomic status (education and income), common risk factors (smoking and obesity), and chronic diseases (hypertension, diabetes, and coronary heart disease). Multivariate logistic regression was used in the analysis.
The age- and sex-adjusted OR comparing self-reported stroke prevalence in the 11-state Stroke Belt versus non-Stroke Belt region was 1.25 (95% CI, 1.19 to 1.31). Unequal black/white distribution by region accounted for 20% of the excess prevalence in the Stroke Belt (OR reduced to 1.20; 1.15 to 1.26). Approximately one third (32%) of the excess prevalence was accounted either by socioeconomic status alone or by risk factors and chronic disease alone (OR, 1.12). The OR was further reduced to 1.07 (1.02 to 1.13) in the fully adjusted logistic model, a 72% reduction.
Differences in socioeconomic status, risk factors, and prevalence of common chronic diseases account for most of the regional differences in stroke prevalence. |
| doi_str_mv | 10.1161/STROKEAHA.109.561688 |
| format | Article |
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Self-reported data from the 2005 and 2007 Behavioral Risk Factor Surveillance System were used (n=765,368). The potential contributors for self-reported stroke prevalence (n=27 962) were demographics (age, sex, geography, and race/ethnicity), socioeconomic status (education and income), common risk factors (smoking and obesity), and chronic diseases (hypertension, diabetes, and coronary heart disease). Multivariate logistic regression was used in the analysis.
The age- and sex-adjusted OR comparing self-reported stroke prevalence in the 11-state Stroke Belt versus non-Stroke Belt region was 1.25 (95% CI, 1.19 to 1.31). Unequal black/white distribution by region accounted for 20% of the excess prevalence in the Stroke Belt (OR reduced to 1.20; 1.15 to 1.26). Approximately one third (32%) of the excess prevalence was accounted either by socioeconomic status alone or by risk factors and chronic disease alone (OR, 1.12). The OR was further reduced to 1.07 (1.02 to 1.13) in the fully adjusted logistic model, a 72% reduction.
Differences in socioeconomic status, risk factors, and prevalence of common chronic diseases account for most of the regional differences in stroke prevalence.</description><identifier>ISSN: 0039-2499</identifier><identifier>ISSN: 1524-4628</identifier><identifier>EISSN: 1524-4628</identifier><identifier>DOI: 10.1161/STROKEAHA.109.561688</identifier><identifier>PMID: 19679841</identifier><identifier>CODEN: SJCCA7</identifier><language>eng</language><publisher>Hagerstown, MD: Lippincott Williams & Wilkins</publisher><subject>Adolescent ; Adult ; Aged ; Behavioral Risk Factor Surveillance System ; Biological and medical sciences ; Black or African American ; Black People - statistics & numerical data ; Cardiovascular Diseases - epidemiology ; Causality ; Chronic Disease - epidemiology ; Cross-Sectional Studies ; Female ; Geography ; Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy ; Health Behavior ; Health Status Disparities ; Health Surveys ; Humans ; Life Style - ethnology ; Male ; Medical sciences ; Middle Aged ; Models, Statistical ; Nervous system (semeiology, syndromes) ; Neurology ; Obesity ; Prevalence ; Racial Groups ; Risk Factors ; Social Class ; Socioeconomic Factors ; Stroke - epidemiology ; United States - epidemiology ; Vascular diseases and vascular malformations of the nervous system ; White People - statistics & numerical data ; Young Adult</subject><ispartof>Stroke (1970), 2009-10, Vol.40 (10), p.3336-3341</ispartof><rights>2009 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c418t-d5de22cc2c0f9bca2e31fe91432355c4c4e04944254c144a27254a37b6312be63</citedby><cites>FETCH-LOGICAL-c418t-d5de22cc2c0f9bca2e31fe91432355c4c4e04944254c144a27254a37b6312be63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3685,27923,27924</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21998382$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19679841$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>YOULIAN LIAO</creatorcontrib><creatorcontrib>GREENLUND, Kurt J</creatorcontrib><creatorcontrib>CROFT, Janet B</creatorcontrib><creatorcontrib>KEENAN, Nora L</creatorcontrib><creatorcontrib>GILES, Wayne H</creatorcontrib><title>Factors Explaining Excess Stroke Prevalence in the US Stroke Belt</title><title>Stroke (1970)</title><addtitle>Stroke</addtitle><description>Higher risk and burden of stroke have been observed within the southeastern states (the Stroke Belt) compared with elsewhere in the United States. We examined reasons for these disparities using a large data set from a nationwide cross-sectional study.
Self-reported data from the 2005 and 2007 Behavioral Risk Factor Surveillance System were used (n=765,368). The potential contributors for self-reported stroke prevalence (n=27 962) were demographics (age, sex, geography, and race/ethnicity), socioeconomic status (education and income), common risk factors (smoking and obesity), and chronic diseases (hypertension, diabetes, and coronary heart disease). Multivariate logistic regression was used in the analysis.
The age- and sex-adjusted OR comparing self-reported stroke prevalence in the 11-state Stroke Belt versus non-Stroke Belt region was 1.25 (95% CI, 1.19 to 1.31). Unequal black/white distribution by region accounted for 20% of the excess prevalence in the Stroke Belt (OR reduced to 1.20; 1.15 to 1.26). Approximately one third (32%) of the excess prevalence was accounted either by socioeconomic status alone or by risk factors and chronic disease alone (OR, 1.12). The OR was further reduced to 1.07 (1.02 to 1.13) in the fully adjusted logistic model, a 72% reduction.
Differences in socioeconomic status, risk factors, and prevalence of common chronic diseases account for most of the regional differences in stroke prevalence.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Behavioral Risk Factor Surveillance System</subject><subject>Biological and medical sciences</subject><subject>Black or African American</subject><subject>Black People - statistics & numerical data</subject><subject>Cardiovascular Diseases - epidemiology</subject><subject>Causality</subject><subject>Chronic Disease - epidemiology</subject><subject>Cross-Sectional Studies</subject><subject>Female</subject><subject>Geography</subject><subject>Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy</subject><subject>Health Behavior</subject><subject>Health Status Disparities</subject><subject>Health Surveys</subject><subject>Humans</subject><subject>Life Style - ethnology</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Models, Statistical</subject><subject>Nervous system (semeiology, syndromes)</subject><subject>Neurology</subject><subject>Obesity</subject><subject>Prevalence</subject><subject>Racial Groups</subject><subject>Risk Factors</subject><subject>Social Class</subject><subject>Socioeconomic Factors</subject><subject>Stroke - epidemiology</subject><subject>United States - epidemiology</subject><subject>Vascular diseases and vascular malformations of the nervous system</subject><subject>White People - statistics & numerical data</subject><subject>Young Adult</subject><issn>0039-2499</issn><issn>1524-4628</issn><issn>1524-4628</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpFkE1PwkAQhjdGI4j-A2N60VtxZ7_aPVYCYiTBCJyb7TLVamlxtxj999ZQ8TRvZp53Dg8hl0CHAApuF8vn-eM4mSZDoHooFag4PiJ9kEyEQrH4mPQp5TpkQuseOfP-jVLKeCxPSQ-0inQsoE-SibFN7Xww_tqWpqiK6qWNFr0PFo2r3zF4cvhpSqwsBkUVNK8YrBZ_tzssm3NykpvS40U3B2Q1GS9H03A2v38YJbPQCoibcC3XyJi1zNJcZ9Yw5JCjBsEZl9IKK5AKLQSTwoIQhkVtMjzKFAeWoeIDcrP_u3X1xw59k24Kb7EsTYX1zqcqUkpTLltQ7EHrau8d5unWFRvjvlOg6a-69KCu3eh0r66tXXX_d9kG1_-lzlULXHeA8daUuTOVLfyBY6B1zGPGfwCwXHYn</recordid><startdate>20091001</startdate><enddate>20091001</enddate><creator>YOULIAN LIAO</creator><creator>GREENLUND, Kurt J</creator><creator>CROFT, Janet B</creator><creator>KEENAN, Nora L</creator><creator>GILES, Wayne H</creator><general>Lippincott Williams & Wilkins</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20091001</creationdate><title>Factors Explaining Excess Stroke Prevalence in the US Stroke Belt</title><author>YOULIAN LIAO ; GREENLUND, Kurt J ; CROFT, Janet B ; KEENAN, Nora L ; GILES, Wayne H</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c418t-d5de22cc2c0f9bca2e31fe91432355c4c4e04944254c144a27254a37b6312be63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Behavioral Risk Factor Surveillance System</topic><topic>Biological and medical sciences</topic><topic>Black or African American</topic><topic>Black People - statistics & numerical data</topic><topic>Cardiovascular Diseases - epidemiology</topic><topic>Causality</topic><topic>Chronic Disease - epidemiology</topic><topic>Cross-Sectional Studies</topic><topic>Female</topic><topic>Geography</topic><topic>Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy</topic><topic>Health Behavior</topic><topic>Health Status Disparities</topic><topic>Health Surveys</topic><topic>Humans</topic><topic>Life Style - ethnology</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Models, Statistical</topic><topic>Nervous system (semeiology, syndromes)</topic><topic>Neurology</topic><topic>Obesity</topic><topic>Prevalence</topic><topic>Racial Groups</topic><topic>Risk Factors</topic><topic>Social Class</topic><topic>Socioeconomic Factors</topic><topic>Stroke - epidemiology</topic><topic>United States - epidemiology</topic><topic>Vascular diseases and vascular malformations of the nervous system</topic><topic>White People - statistics & numerical data</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>YOULIAN LIAO</creatorcontrib><creatorcontrib>GREENLUND, Kurt J</creatorcontrib><creatorcontrib>CROFT, Janet B</creatorcontrib><creatorcontrib>KEENAN, Nora L</creatorcontrib><creatorcontrib>GILES, Wayne H</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Stroke (1970)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>YOULIAN LIAO</au><au>GREENLUND, Kurt J</au><au>CROFT, Janet B</au><au>KEENAN, Nora L</au><au>GILES, Wayne H</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Factors Explaining Excess Stroke Prevalence in the US Stroke Belt</atitle><jtitle>Stroke (1970)</jtitle><addtitle>Stroke</addtitle><date>2009-10-01</date><risdate>2009</risdate><volume>40</volume><issue>10</issue><spage>3336</spage><epage>3341</epage><pages>3336-3341</pages><issn>0039-2499</issn><issn>1524-4628</issn><eissn>1524-4628</eissn><coden>SJCCA7</coden><abstract>Higher risk and burden of stroke have been observed within the southeastern states (the Stroke Belt) compared with elsewhere in the United States. We examined reasons for these disparities using a large data set from a nationwide cross-sectional study.
Self-reported data from the 2005 and 2007 Behavioral Risk Factor Surveillance System were used (n=765,368). The potential contributors for self-reported stroke prevalence (n=27 962) were demographics (age, sex, geography, and race/ethnicity), socioeconomic status (education and income), common risk factors (smoking and obesity), and chronic diseases (hypertension, diabetes, and coronary heart disease). Multivariate logistic regression was used in the analysis.
The age- and sex-adjusted OR comparing self-reported stroke prevalence in the 11-state Stroke Belt versus non-Stroke Belt region was 1.25 (95% CI, 1.19 to 1.31). Unequal black/white distribution by region accounted for 20% of the excess prevalence in the Stroke Belt (OR reduced to 1.20; 1.15 to 1.26). Approximately one third (32%) of the excess prevalence was accounted either by socioeconomic status alone or by risk factors and chronic disease alone (OR, 1.12). The OR was further reduced to 1.07 (1.02 to 1.13) in the fully adjusted logistic model, a 72% reduction.
Differences in socioeconomic status, risk factors, and prevalence of common chronic diseases account for most of the regional differences in stroke prevalence.</abstract><cop>Hagerstown, MD</cop><pub>Lippincott Williams & Wilkins</pub><pmid>19679841</pmid><doi>10.1161/STROKEAHA.109.561688</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; American Heart Association Journals; Journals@Ovid Complete; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | Adolescent Adult Aged Behavioral Risk Factor Surveillance System Biological and medical sciences Black or African American Black People - statistics & numerical data Cardiovascular Diseases - epidemiology Causality Chronic Disease - epidemiology Cross-Sectional Studies Female Geography Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy Health Behavior Health Status Disparities Health Surveys Humans Life Style - ethnology Male Medical sciences Middle Aged Models, Statistical Nervous system (semeiology, syndromes) Neurology Obesity Prevalence Racial Groups Risk Factors Social Class Socioeconomic Factors Stroke - epidemiology United States - epidemiology Vascular diseases and vascular malformations of the nervous system White People - statistics & numerical data Young Adult |
| title | Factors Explaining Excess Stroke Prevalence in the US Stroke Belt |
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