AHA 2012 Slide Presentation Cardiac Death Seasonal

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Seasonal Variation
of Total and Cardiac Death Rates
Across Different Climates
Bryan G. Schwartz, MD1
Robert A. Kloner, MD, PhD1,2
1Heart
Institute, Good Samaritan Hospital;
2Department of Internal Medicine, Division of Cardiovascular Medicine,
Keck School of Medicine at the University of Southern California,
Los Angeles, California USA
# of CAD
Deaths
Degrees F
Seasonal Variation – Prior studies
Event
Effect 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
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
Ave Seasonal Apparent Temp (°C)
Average Seasonal Apparent Temperature
in Texas, Pennsylvania and Los Angeles
4040
TX temp
LA temp
PA temp
3030
2020
1010
0
01/1/2005
1/1
4/2/2005
4/1
7/2/2005
7/1
10/1/2005
10/1
12/31/2005
12/31
Seasonal Variation – Hypothesis
 The winter peak in death rates would be greater in climates
with colder winters
Seasonal Variation – Methods
 Converted daily number of deaths to daily death rates (assuming
constant population change)
Los Angeles County: population 10 million
Daily # of deaths
Daily rate /100,000 pop
Total
Circulatory
Ischemic HD
162
1.6
62
0.6
37
0.4
 Average seasonal values for each day of year:
 19-day centered moving average
 Median of 4 years’ daily value
Average Circulatory Death Rate
(per 100,000 population/day)
Circulatory Death Rate
1.2
TX
AZ
GA
LA
WA
PA
MA
1
0.8
0.6
0.4
1/1
1/1/2005
4/1
4/1/2005
7/1
6/30/2005
10/1
9/28/2005
12/27/2005
12/31
Seasonal Variation – Methods
 Calculated variation around the mean:
 Daily death rate / average daily death rate
 Daily % change from average annual death rate
Normalized Circulatory Death Rate
Daily % Change from Average
+20%
1.2
TX
AZ
GA
LA
WA
PA
MA
+10%
1.1
average
1
-10%
0.9
-20%
0.8
1/1
1/1/2005
4/1
4/1/2005
7/1
6/30/2005
10/1
9/28/2005
12/27/2005
12/31
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
Maximum % Change
Maximum Percent Change in 7 Different Climates
40%
35%
30%
25%
P=0.54
20%
ANOVA P=0.54
TX
AZ
GA
LA
WA
PA
MA
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
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
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