Abstract
Objective
To examine and compare the predictive capacities of four temperature metrics on firearm violence: daily maximum temperature, daily apparent maximum temperature, daily deviation from normal temperature, and consecutive days of high heat.
Method
We analyzed daily firearm violence incidents in Syracuse, New York from 2010–2022 using Generalized Linear Autoregressive Moving Average models. Daily maximum temperature, and daily deviation from normal temperature were directly obtained from the National Centers for Environmental Information. Daily apparent maximum temperature was created by combining daily maximum temperature with humidity data derived from windchill and heat index calculations. Consecutive days of high heat was calculated using daily maximum temperature and counting the number of successive days above 90 degrees Fahrenheit (32.2 degrees Celsius). We examined both univariate models for each temperature metric and multivariate models containing multiple temperature variables simultaneously.
Results
Over the 12-year period, Syracuse averaged nearly two firearm violence incidents per day. In univariate analyses, all temperature metrics demonstrated statistically significant relationships with daily firearm violence, with incidence rate ratios between 1.01 and 1.02 per degree Fahrenheit increase (1.02 and 1.04 per degree Celsius increase). However, multivariate analyses revealed more complex patterns. When daily maximum temperature was included with other metrics, it remained the only significant predictor, with each standard deviation increase associated with a 25% increase in daily incidents. When daily apparent maximum temperature replaced daily maximum temperature, daily deviation from normal temperature became the sole significant predictor, with each standard deviation increase associated with a 12% increase in incidents.
Conclusions
Findings suggest different temperature dimensions might be related to firearm violence through distinct pathways. Absolute temperature effects and relative temperature deviations represent separate constructs that independently contribute to weather-gun violence relationships. This complexity supports the need for comprehensive monitoring systems that track both extreme temperatures and departures from seasonal norms to identify periods of elevated risk.