County-Level Trends in Suicide Rates in the U.S., 2005–2015

Introduction

Understanding the geographic patterns of suicide can help inform targeted prevention efforts. Although state-level variation in age-adjusted suicide rates has been well documented, trends at the county-level have been largely unexplored. This study uses small area estimation to produce stable county-level estimates of suicide rates to examine geographic, temporal, and urban–rural patterns in suicide from 2005 to 2015.

Methods

Using National Vital Statistics Underlying Cause of Death Files (2005–2015), hierarchical Bayesian models were used to estimate suicide rates for 3,140 counties. Model-based suicide rate estimates were mapped to explore geographic and temporal patterns and examine urban–rural differences. Analyses were conducted in 2016–2017.

Results

Posterior predicted mean county-level suicide rates increased by >10% from 2005 to 2015 for 99% of counties in the U.S., with 87% of counties showing increases of >20%. Counties with the highest model-based suicide rates were consistently located across the western and northwestern U.S., with the exception of southern California and parts of Washington. Compared with more urban counties, more rural counties had the highest estimated suicide rates from 2005 to 2015, and also the largest increases over time.

Conclusions

Mapping county-level suicide rates provides greater granularity in describing geographic patterns of suicide and contributes to a better understanding of changes in suicide rates over time. Findings may inform more targeted prevention efforts as well as future research on community-level risk and protective factors related to suicide mortality.

Introduction

Suicide is a complex public health problem, influenced by multiple individual, community, and societal risk and protective factors.¹ Since 2008, suicide has ranked as the tenth leading cause of death in the U.S.,² and in 2015 accounted for more than 44,000 deaths.³

State differences in age-adjusted suicide rates (SRs) have been well documented, with Western states generally showing higher rates.4, 5 Although a more detailed understanding of geographic variation may be useful, attempts at estimating county-level SRs have been limited because the majority of counties report fewer than 20 suicide deaths per year. Direct estimates of SRs based on small numbers can be unstable and highly variable year to year, making it difficult to discern trends.⁶ To produce stable estimates, studies⁷ and web-based mapping tools3, 8 often aggregate over multiple years or states, potentially masking important trends and within-state variation, including urban–rural differences.9, 10

Previous studies have described urban–rural gradients in SRs and suggested that urban–rural differences may be widening, with SRs increasing more rapidly from 2000 to 2015 in less urban areas compared with more urban areas.¹⁰ However, county-level variation in SRs remains largely unexplored. More detailed examination of county-level patterns and trends, including urban–rural differences, can shed light on where SRs may have increased more rapidly and inform more targeted prevention efforts at the community level.¹

Small area estimation methods11, 12, 13, 14 can be used to produce stable estimates of mortality rates at the county level, borrowing strength from nearby counties and over time, and overcoming limitations related to aggregating data over time or larger geographic units. The objective of this study is to apply these methods to generate estimates of annual county-level SRs for 2005 through 2015¹⁵ in order to examine how SRs vary across counties in the U.S. and whether these patterns are consistent over time. Additionally, this study describes urban–rural disparities and trends, and the percentage of counties within each urban–rural category reporting larger or smaller increases in SRs over time.