US County-Level Trends in Mortality Rates for Major Causes of Death, 1980-2014

Abstract

IMPORTANCECounty-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.OBJECTIVES 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. DESIGN, SETTING, AND PARTICIPANTSRedistribution 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. EXPOSURE County of residence.MAIN OUTCOMES AND MEASURES Cause-specific age-standardized mortality rates.RESULTS 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. CONCLUSIONS AND RELEVANCEIn 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.

Trends and Patterns of Disparities in Cancer Mortality Among US Counties, 1980-2014

“…11 A brief description of this approach and its application to cancer mortality is provided below. This research received institutional review board approval from the University of Washington.…”

Trends and Patterns of Geographic Variation in Cardiovascular Mortality Among US Counties, 1980-2014

“…This analysis used methods that are reported in detail elsewhere 5 and described briefly herein. This research received institutional review board approval from the University of Washington (human subjects application 46665).…”

“…17 A total of 1000 draws of m j,t,a were taken from the posterior distribution. These draws were raked 5,18 (ie, scaled along multiple dimensions) to ensure consistency between levels of the cause hierarchy (ie, at each level the sum of all child causes is equal to the estimate for the corresponding parent cause) and to ensure consistency with the most recent national estimates produced by the Global Burden of Disease study. 1 Mortality rates for both sexes combined were calculated from the population-weighted average of the sex-specific mortality rates.…”

Long-term trends in the PM<sub>2.5</sub>- and O<sub>3</sub>-related mortality burdens in the United States under emission reductions from 1990 to 2010

“…Previous health impact assessments have used national baseline mortality rates (Cohen et al, 2017;Silva et al, 2016aSilva et al, , 2016b, but baseline mortality rates can vary strongly within individual counties (supporting Figure S5; Dwyer-Lindgren et al, 2016). We performed sensitivity analyses by applying the national average baseline mortality rates for each disease to every county in the mortality burden calculations.…”