ArticleThe Lancet. Public health2023
County-level estimates of suicide mortality in the USA: a modelling study.
Article in The Lancet. Public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 20 citations in OpenAlex.
- Spatio-temporal trends and socio-environmental determinants of suicides in England (2002-2022): an ecological population-based study.The Lancet regional health. Europe · 2025Article
- Development and Validation of Prediction Models for Perceived and Unmet Mental Health Needs in the Canadian General Population: Model-Based Synthetic Estimation Study.JMIR public health and surveillance · 2025Article
- Uncertainties of Economic Policy and Government Management Stability Played Important Roles in Increasing Suicides in Japan from 2009 to 2023.International journal of environmental research and public health · 2024Article
- Predicting the Population Risk of Suicide Using Routinely Collected Health Administrative Data in Quebec, Canada: Model-Based Synthetic Estimation Study.JMIR public health and surveillance · 2024Article
- Suicide mortality rates in Japan before and beyond the COVID-19 pandemic era.PCN reports : psychiatry and clinical neurosciences · 2024Review
- The Spatio-Temporal Distribution of Suicide-related Emergency Calls in a European City: Age and Gender Patterns, and Neighborhood Influences.Psychosocial intervention · 2024Article
- Impacts of Complete Unemployment Rates Disaggregated by Reason and Duration on Suicide Mortality from 2009-2022 in Japan.Healthcare (Basel, Switzerland) · 2023Article
- Hindcasts and forecasts of suicide mortality in US: A modeling study.PLoS computational biology · 2023Observational
- Healthcare Utilization Following Implementation of a Pediatric Social Needs Screening Program.Journal of primary care & community healthObservational
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
backgroundSuicide is one of the leading causes of death in the USA and population risk prediction models can inform decisions on the type, location, and timing of public health interventions. We aimed to develop a prediction model to estimate county-level suicide risk in the USA using population characteristics.
methodsWe obtained data on all deaths by suicide reported to the National Vital Statistics System between Jan 1, 2005, and Dec 31, 2019, and age, sex, race, and county of residence of the decedents were extracted to calculate baseline risk. We also obtained county-level annual measures of socioeconomic predictors of suicide risk (unemployment, weekly wage, poverty prevalence, median household income, and population density) and state-level prevalence of major depressive disorder and firearm ownership from US public sources. We applied conditional autoregressive models, which account for spatiotemporal autocorrelation in response and predictors, to estimate county-level suicide risk.
findingsEstimates derived from conditional autoregressive models were more accurate than from models not adjusted for spatiotemporal autocorrelation. Inclusion of suicide risk and protective covariates further reduced errors. Suicide risk was estimated to increase with each SD increase in firearm ownership (2·8% [95% credible interval (CrI) 1·8 to 3·9]), prevalence of major depressive episode (1·0% [0·4 to 1·5]), and unemployment rate (2·8% [1·9 to 3·8]). Conversely, risk was estimated to decrease by 4·3% (-5·1 to -3·2) for each SD increase in median household income and by 4·3% (-5·8 to -2·5) for each SD increase in population density. An increase in the heterogeneity in county-specific suicide risk was also observed during the study period.
interpretationArea-level characteristics and the conditional autoregressive models can estimate population-level suicide risk. Availability of near real-time situational data are necessary for the translation of these models into a surveillance setting. Monitoring changes in population-level risk of suicide could help public health agencies select and deploy targeted interventions quickly.
fundingUS National Institute of Mental Health.
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