01. The Regional Effect of Mental Health in the United States

What is the impact of mental health on mortality rates in the United States? Using mortality statistics from the CDC and Mental Health America metrics, we analyze county-level mortality rates, suicide rates, and mental health indicators across 18 age groups from 2000 to 2023. We employ Bayesian spatio-temporal models with conditional auto-regressive (CAR) priors on the spatial effects to account for both regional and temporal trends in mortality. With these models, we explore the relationship between regional mental health conditions and mortality outcomes. These models allow us to investigate the relationship between local mental health conditions and mortality outcomes while accounting for geographic and age-group variation. Our approach supports both retrospective analysis and forecasting, identifying regions where mental health is improving or deteriorating and quantifying rates of change. We specifically examine the impact of COVID-19 on mental health as it relates to mortality, and examine regions where the pandemic contributed to shifts in mortality trends. Our findings provide demographers, statisticians, actuaries, and public health professionals with evidence-based insights on when and how to incorporate mental health data into mortality modeling, enhancing the accuracy of demographic projections and risk assessment in insurance and public health applications.

mortality improvement

Bayesian modeling

spatial generalized linear model

conditional auto-regressive priors

mental health 

Mid-Level

Knowledge

Women in Statistics and Data Science 2025