title: US County-Level Trends in Mortality Rates for Major Causes of Death, 1980-2014.
abstract: County-level patterns in mortality rates by cause have not been systematically described but are potentially useful for public health officials, clinicians, and researchers seeking to improve health and reduce geographic disparities.
  
  
  
  To demonstrate the use of a novel method for county-level estimation and to estimate annual mortality rates by US county for 21 mutually exclusive causes of death from 1980 through 2014.
  
  
  
  Redistribution methods for garbage codes (implausible or insufficiently specific cause of death codes) and small area estimation methods (statistical methods for estimating rates in small subpopulations) were applied to death registration data from the National Vital Statistics System to estimate annual county-level mortality rates for 21 causes of death. These estimates were raked (scaled along multiple dimensions) to ensure consistency between causes and with existing national-level estimates. Geographic patterns in the age-standardized mortality rates in 2014 and in the change in the age-standardized mortality rates between 1980 and 2014 for the 10 highest-burden causes were determined.
  
  
  
  County of residence.
  
  
  
  Cause-specific age-standardized mortality rates.
  
  
  
  A total of 80 412 524 deaths were recorded from January 1, 1980, through December 31, 2014, in the United States. Of these, 19.4 million deaths were assigned garbage codes. Mortality rates were analyzed for 3110 counties or groups of counties. Large between-county disparities were evident for every cause, with the gap in age-standardized mortality rates between counties in the 90th and 10th percentiles varying from 14.0 deaths per 100 000 population (cirrhosis and chronic liver diseases) to 147.0 deaths per 100 000 population (cardiovascular diseases). Geographic regions with elevated mortality rates differed among causes: for example, cardiovascular disease mortality tended to be highest along the southern half of the Mississippi River, while mortality rates from self-harm and interpersonal violence were elevated in southwestern counties, and mortality rates from chronic respiratory disease were highest in counties in eastern Kentucky and western West Virginia. Counties also varied widely in terms of the change in cause-specific mortality rates between 1980 and 2014. For most causes (eg, neoplasms, neurological disorders, and self-harm and interpersonal violence), both increases and decreases in county-level mortality rates were observed.
  
  
  
  In this analysis of US cause-specific county-level mortality rates from 1980 through 2014, there were large between-county differences for every cause of death, although geographic patterns varied substantially by cause of death. The approach to county-level analyses with small area models used in this study has the potential to provide novel insights into US disease-specific mortality time trends and their differences across geographic regions.
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Laura
authors.initials: L
authors.lastname: Dwyer-Lindgren
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Amelia
authors.initials: A
authors.lastname: Bertozzi-Villa
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Rebecca W
authors.initials: RW
authors.lastname: Stubbs
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Chloe
authors.initials: C
authors.lastname: Morozoff
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Kutz
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Chantal
authors.initials: C
authors.lastname: Huynh
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Ryan M
authors.initials: RM
authors.lastname: Barber
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Katya A
authors.initials: KA
authors.lastname: Shackelford
authors.affiliation: Department of Public Health, Erasmus MC, Rotterdam, the Netherlands.
authors.forename: Johan P
authors.initials: JP
authors.lastname: Mackenbach
authors.affiliation: Department of Public Health, Erasmus MC, Rotterdam, the Netherlands.
authors.forename: Frank J
authors.initials: FJ
authors.lastname: van Lenthe
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Abraham D
authors.initials: AD
authors.lastname: Flaxman
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Mohsen
authors.initials: M
authors.lastname: Naghavi
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Ali H
authors.initials: AH
authors.lastname: Mokdad
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle.
authors.forename: Christopher J L
authors.initials: CJ
authors.lastname: Murray
mesh_terms: D002423:Cause of Death; D006801:Humans; D009026:Mortality / Q000639:trends*; D014481:United States