Temperature-Suicide Associations using DLNM

There has been much research on the associations between weather variables and suicide rates. Unfortunately, the state of understanding has remained rather stagnant due to many contradictory findings. Recent research has made use of distributed-lag nonlinear modeling (DLNM) to quantify how suicide rates tend to change with anomalous temperatures. The purpose of this project is to build upon those previous findings by analyzing a longer period of record that includes more recent suicide data (1975–2010) than has been published before as well as studying more locations across the USA. DLNM is used to relate those suicide data to daily surface temperature data representative of the study locations. Results suggest some consistency with previous findings as seasonally warmer temperatures are associated with increased suicides, but spatial and temporal variations are also evident.