title: Coronary heart disease prevalence and occupational structure in U.S. metropolitan areas: a multilevel analysis.
abstract: This research explored the link between coronary heart disease (CHD) prevalence and metropolitan-area level occupational structure among 137 metropolitan/micropolitan statistical areas (MMSA) in the United States. Using data from the 2006-2008 Behavioral Risk Factor Surveillance System and 2007 County Business Patterns, logistic mixed models were developed to estimate CHD prevalence between MMSAs controlling for individual-level socioeconomic characteristics and various types of occupational structure. Results showed that CHD prevalence was lower in MMSAs where their economy was dominated by 'tourism and resort' and 'the quaternary sector' and higher in MMSAs dominated by 'manufacturing', 'transportation and warehousing', and 'mining'. MMSA-level effects on CHD were found in 'tourism and resort' and 'the quaternary sector' having lower risk and 'mining' having higher risk of CHD. Although these effects prevailed in many MMSAs, some MMSAs did not fit into these effects. Additional analysis indicated a possible link between metropolitan population loss and higher CHD prevalence especially in the coal mining region of the Appalachian Mountains.
authors.affiliation: Department of Public Health, College of Health and Human Services, Western Kentucky University, 1906 College Heights Blvd, Bowling Green, KY 42101 USA. akihiko.michimi@wku.edu
authors.forename: Akihiko
authors.initials: A
authors.lastname: Michimi
authors.forename: Gregory
authors.initials: G
authors.lastname: Ellis-Griffith
authors.forename: Christine
authors.initials: C
authors.lastname: Nagy
authors.forename: Tina
authors.initials: T
authors.lastname: Peterson
mesh_terms: D000328:Adult; D000368:Aged; D040343:Behavioral Risk Factor Surveillance System; D002947:Cities / Q000453:epidemiology / Q000706:statistics & numerical data; D003327:Coronary Disease / Q000453:epidemiology* / Q000209:etiology; D004651:Employment / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009790:Occupations / Q000706:statistics & numerical data*; D015995:Prevalence; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology; D014505:Urban Population / Q000706:statistics & numerical data