1. Seasonal Variation of Total and Cardiac Death Rates Across Different Climates Bryan G. Schwartz, MD 1 Robert A. Kloner, MD, PhD 1,2 1 Heart Institute, Good Samaritan Hospital; 2 Department of Internal Medicine, Division of Cardiovascular Medicine, Keck School of Medicine at the University of Southern California, Los Angeles, California USA

3. # of CAD Deaths Degrees F

5. Seasonal Variation – Prior studies EventEffect on mortality 10°C ↓ in 5-day average temp ↑ risk of MI (RR 1.1) 10°C ↓ 13% ↑ in MI and coronary deaths Temperature ↓ 0°C ↑ risk of sudden cardiac death (RR 1.2) winter cold wave ( ↓ temp, strong winds, ↓ humidity) ↑ mortality June-August in New South Wales (winter) ↑ CAD deaths (2.8%) Meta-analysis: 8 of 12 studies report ↑ in MI during cold in winter Wolf. Circ 2009;120:735 Danet. Circ 1999;100:e1 Gerber. JACC 2006;48:287 Cech. Israel J Med Sci 1977;13:451 Weerasinghe. Heart 2002;88:30 Bhaskaran. Heart 2009;95:1760

6. Seasonal Variation – Methods Obtain daily death certificate data from 2005-08 for a variety of climates, compare seasonal patterns Hot: Texas (24 million), Georgia (9), Maricopa County (4) Moderate: Los Angeles County (10), West ½ of Washington (5) Cold: Massachusetts (6.5), Pennsylvania (12.5) Death certificate data from state health departments Total deaths, Circulatory deaths, Ischemic heart disease deaths Population data from US Census Bureau

7. Ave Seasonal Apparent Temp (°C) 40 30 20 10 0 1/1 4/1 7/1 10/1 12/31 TX temp LA temp PA temp Average Seasonal Apparent Temperature in Texas, Pennsylvania and Los Angeles

8. Seasonal Variation – Hypothesis The winter peak in death rates would be greater in climates with colder winters

9. Seasonal Variation – Methods Converted daily number of deaths to daily death rates (assuming constant population change) Los Angeles County: population 10 million Average seasonal values for each day of year: 19-day centered moving average Median of 4 years’ daily value TotalCirculatoryIschemic HD Daily # of deaths1626237 Daily rate /100,000 pop1.60.60.4

10. 1/1 4/1 7/1 10/1 12/31 Circulatory Death Rate (per 100,000 population/day) Average Circulatory Death Rate

11. Seasonal Variation – Methods Calculated variation around the mean: Daily death rate / average daily death rate Daily % change from average annual death rate

12. 1/1 4/1 7/1 10/1 12/31 Normalized Circulatory Death Rate +20% +10% average -10% -20% Daily % Change from Average

13. Seasonal Variation – Methods Average seasonal curves were used to identify the peak and trough 8-day periods Using the raw daily death rates, calculated maximum % change: Peak values – trough values = maximum % change (32 values) Compared maximum % change using one-way ANOVA

14. TX AZ GA LA WA PA MA Maximum % Change Maximum Percent Change in 7 Different Climates ANOVA P=0.54 P=0.54 40% 35% 30% 25% 20%

15. Seasonal Variation – Conclusions The U shaped curve of circulatory death rates was very similar in 7 locations studied with different climates Circulatory death rates are 26-36% higher during the winter Explanations: People acclimate to their local climate Other factors influence seasonal variation of circulatory death rates Habits: diet, exercise, weight Hours of daylight: depression Respiratory infection

16. Citations 1. Kloner RA, et al. Circulation 1999;100:1634. 2. Wolf. Circulation 2009;120:735 3. Danet. Circulation 1999;100:e1 4. Gerber. J Am Coll Cardiol 2006;48:287 5. Cech. Israel J Med Sci 1977;13:451 6. Weerasinghe. Heart 2002;88:30 7. Bhaskaran. Heart 2009;95:1760