State- and County-Level Social Capital as Predictors of County-Level Suicide Rates in the United States: A Lagged Multilevel Study

Abstract

From 1999 through 2017, age-adjusted suicide rates in the United States rose by 33% (from 10.5 to 14.0 per 100 000 population). Social capital, a key social determinant of health, could protect against suicide, but empirical evidence on this association is limited. Using multilevel data from the Centers for Disease Control and Prevention, we explored state- and county-level social capital as predictors of age-adjusted suicide rates pooled from 2010 through 2017 across 2112 US counties. In addition, we tested for causal mediation of these associations by state-level prevalence of depression. A 1-standard deviation increase in state-level social capital predicted lower county-level suicide mortality rates almost 2 decades later (0.87 fewer suicides per 100 000 population; P = .04). This association was present among non-Hispanic Black people and among men but not among non-Hispanic White people and women. We also found evidence of partial mediation by prevalence of depression. Our findings suggest that elevating state- and county-level social capital, such as through policy and local initiatives, may help to reverse the trend of rising suicide rates in the United States.

Keywords: United States; multilevel; social capital; suicide.

Figure

Coefficient estimates from multivariate linear regression analysis of county-level social capital (for years 1990, 1997, 2005, 2009, and 2014) and county-level age-adjusted pooled suicide rates (2010-2017), United States. All reported β estimates are rescaled to reflect a 1-standard deviation change. All models are adjusted for unemployment rate, median annual household income, percentage of non-Hispanic Black population, percentage of population aged ≥65, percentage of high school graduates, and population density at both the county and state levels; firearm ownership rate and marriage rate at the state level only; and percentage of population below the federal poverty level at the county level. Significance was measured using a 2-tailed t test, with P < .05 considered significant. Data sources: Centers for Disease Control and Prevention, Kim et al, Rupasingha et al, US Census Bureau, Schell et al, and Centers for Disease Control and Prevention.