Influenza epidemics, seasonality, and the effects of cold weather on cardiac mortality
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Published on: November 10, 2023
Stephanie von Klot1, Antonella Zanobetti, Joel Schwartz
1Department of Environmental Health, Exposure Epidemiology and Risk Program, Harvard School of Public Health, Boston, MA, USA.
Insights
Seasonal influenza epidemics significantly explain winter cardiac deaths, allowing for more parsimonious statistical models. Cold temperatures
Area of Science:
- Environmental epidemiology
- Public health surveillance
- Cardiovascular disease research
Background:
- Winter seasonality is linked to increased cardiac disease mortality.
- Competing hypotheses exist for this seasonal pattern.
- The study investigates the role of influenza epidemics in seasonal cardiac deaths.
Purpose of the Study:
- To quantify the contribution of influenza epidemics to seasonal cardiac mortality.
- To assess if influenza data allows for more parsimonious seasonal adjustment than traditional methods.
- To determine if accounting for influenza affects the association between temperature and cardiac events.
Main Methods:
- Utilized daily cardiac death counts and elderly influenza hospital admission data (1992-2000) across 48 US cities.
- Employed quasi-Poisson regression models to analyze associations between daily cardiac mortality and temperature.
- Compared models with and without influenza epidemic data for seasonal adjustment.
Main Results:
- Controlling for influenza admissions resulted in more parsimonious models with improved statistical fit (better GCV, lower serial correlation).
- Influenza epidemics accounted for approximately 2.3% of cardiac deaths during the study period.
- The association between cold temperature (0 to -5°C) and cardiac mortality risk (1.6% increase) was not significantly altered by adjusting for influenza.
Conclusions:
- Influenza epidemic data explained a substantial portion (18%) of the irregular seasonal variation in cardiac deaths.
- Incorporating epidemic data enabled more parsimonious modeling compared to using time-based smooth functions alone.
- The impact of cold ambient temperature on cardiac mortality is not confounded by influenza epidemics.
Background:
More people die in the winter from cardiac disease, and there are competing hypotheses to explain this. The authors conducted a study in 48 US cities to determine how much of the seasonal pattern in cardiac deaths could be explained by influenza epidemics, whether that allowed a more parsimonious control for season than traditional spline models, and whether such control changed the short term association with temperature.
Methods:
The authors obtained counts of daily cardiac deaths and of emergency hospital admissions of the elderly for influenza during 1992-2000. Quasi-Poisson regression models were conducted estimating the association between daily cardiac mortality, and temperature.
Results:
Controlling for influenza admissions provided a more parsimonious model with better Generalized Cross-Validation, lower residual serial correlation, and better captured Winter peaks. The temperature-response function was not greatly affected by adjusting for influenza. The pooled estimated increase in risk for a temperature decrease from 0 to -5°C was 1.6% (95% confidence interval (CI) 1.1-2.1%). Influenza accounted for 2.3% of cardiac deaths over this period.
Conclusions:
The results suggest that including epidemic data explained most of the irregular seasonal pattern (about 18% of the total seasonal variation), allowing more parsimonious models than when adjusting for seasonality only with smooth functions of time. The effect of cold temperature is not confounded by epidemics.
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Vaccinations
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Decreased Body Temperature
Causality in Epidemiology
