Models for the relationship between ambient temperature and daily mortality.

Area of Science:

• Environmental epidemiology
• Biostatistics
• Public health

Background:

• Ambient temperature is a key factor in daily mortality.
• The temperature-mortality relationship is nonlinear and has delayed effects.
• Understanding this relationship is crucial for controlling confounding in time-series analyses, especially for air pollution.

Purpose of the Study:

• To review and extend models for nonlinear, multilag temperature-mortality relationships.
• To explore flexible modeling frameworks beyond traditional spline and threshold models.
• To assess the persistence of temperature effects on mortality over extended lags.

Main Methods:

• Comparison of polynomial, natural cubic spline, and linear threshold models.
• Application of a novel "cross-basis" function framework for flexible multilag modeling.
• Analysis of mortality data from London to evaluate model performance.

Main Results:

• Evidence of temperature-mortality relationships extending up to two weeks.
• Smoothly varying models demonstrated the best fit.
• Lag-stratified threshold models offered the most interpretable results.

Conclusions:

• A broad spectrum of multilag nonlinear temperature-mortality associations can be effectively modeled.
• Increased awareness and application of advanced modeling options can enhance research.
• Improved modeling aids in better controlling for temperature as a confounder.