OBJECTIVE: Many cardiovascular deaths can be avoided through primary prevention to address cardiovascular disease (CVD) risk factors or better access to quality medical care. In this cross-sectional study, we examined the relationship between four county-level health factors and rates of avoidable death from CVD during 2006-2010. METHODS: We defined avoidable deaths from CVD as deaths among U.S. residents younger than 75 years of age caused by the following underlying conditions, using International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes: ischemic heart disease (I20-I25), chronic rheumatic heart disease (I05-I09), hypertensive disease (I10-I15), or cerebrovascular disease (I60-I69). We stratified county-level death rates by race (non-Hispanic white or non-Hispanic black) and age-standardized them to the 2000 U.S. standard population. We used County Health Rankings data to rank county-level z scores corresponding to four health factors: health behavior, clinical care, social and economic factors, and physical environment. We used Poisson rate ratios (RRs) and 95% confidence intervals (CIs) to compare rates of avoidable death from CVD by health-factor quartile. RESULTS: In a comparison of worst-ranked and best-ranked counties, social and economic factors had the strongest association with rates of avoidable death per 100,000 population from CVD for the total population (RR=1.49; 95% CI 1.39, 1.60) and for each racial/ethnic group (non-Hispanic white: RR=1.37; 95% CI 1.29, 1.45; non-Hispanic black: RR=1.54; 95% CI 1.42, 1.67). Among the non-Hispanic white population, health behaviors had the next strongest association, followed by clinical care. Among the non-Hispanic black population, we observed a significant association with clinical care and physical environment in a comparison of worst-ranked and best-ranked counties. CONCLUSION: Social and economic factors have the strongest association with rates of avoidable death from CVD by county, which reinforces the importance of social and economic interventions to address geographic disparities in avoidable deaths from CVD.
OBJECTIVE: Many cardiovascular deaths can be avoided through primary prevention to address cardiovascular disease (CVD) risk factors or better access to quality medical care. In this cross-sectional study, we examined the relationship between four county-level health factors and rates of avoidable death from CVD during 2006-2010. METHODS: We defined avoidable deaths from CVD as deaths among U.S. residents younger than 75 years of age caused by the following underlying conditions, using International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes: ischemic heart disease (I20-I25), chronic rheumatic heart disease (I05-I09), hypertensive disease (I10-I15), or cerebrovascular disease (I60-I69). We stratified county-level death rates by race (non-Hispanic white or non-Hispanic black) and age-standardized them to the 2000 U.S. standard population. We used County Health Rankings data to rank county-level z scores corresponding to four health factors: health behavior, clinical care, social and economic factors, and physical environment. We used Poisson rate ratios (RRs) and 95% confidence intervals (CIs) to compare rates of avoidable death from CVD by health-factor quartile. RESULTS: In a comparison of worst-ranked and best-ranked counties, social and economic factors had the strongest association with rates of avoidable death per 100,000 population from CVD for the total population (RR=1.49; 95% CI 1.39, 1.60) and for each racial/ethnic group (non-Hispanic white: RR=1.37; 95% CI 1.29, 1.45; non-Hispanic black: RR=1.54; 95% CI 1.42, 1.67). Among the non-Hispanic white population, health behaviors had the next strongest association, followed by clinical care. Among the non-Hispanic black population, we observed a significant association with clinical care and physical environment in a comparison of worst-ranked and best-ranked counties. CONCLUSION: Social and economic factors have the strongest association with rates of avoidable death from CVD by county, which reinforces the importance of social and economic interventions to address geographic disparities in avoidable deaths from CVD.
Authors: Alan S Go; Dariush Mozaffarian; Véronique L Roger; Emelia J Benjamin; Jarett D Berry; Michael J Blaha; Shifan Dai; Earl S Ford; Caroline S Fox; Sheila Franco; Heather J Fullerton; Cathleen Gillespie; Susan M Hailpern; John A Heit; Virginia J Howard; Mark D Huffman; Suzanne E Judd; Brett M Kissela; Steven J Kittner; Daniel T Lackland; Judith H Lichtman; Lynda D Lisabeth; Rachel H Mackey; David J Magid; Gregory M Marcus; Ariane Marelli; David B Matchar; Darren K McGuire; Emile R Mohler; Claudia S Moy; Michael E Mussolino; Robert W Neumar; Graham Nichol; Dilip K Pandey; Nina P Paynter; Matthew J Reeves; Paul D Sorlie; Joel Stein; Amytis Towfighi; Tanya N Turan; Salim S Virani; Nathan D Wong; Daniel Woo; Melanie B Turner Journal: Circulation Date: 2013-12-18 Impact factor: 29.690
Authors: Paul D James; Russell Wilkins; Allan S Detsky; Peter Tugwell; Douglas G Manuel Journal: J Epidemiol Community Health Date: 2007-04 Impact factor: 3.710
Authors: Bongeka Z Zuma; Justin T Parizo; Areli Valencia; Gabriela Spencer-Bonilla; Manuel R Blum; David Scheinker; Fatima Rodriguez Journal: J Am Heart Assoc Date: 2021-03-03 Impact factor: 5.501
Authors: Miriam E Van Dyke; Kelli A Komro; Monica P Shah; Melvin D Livingston; Michael R Kramer Journal: Prev Med Date: 2018-04-04 Impact factor: 4.637