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Challenges and Opportunities in Estimating the Direct Effects of
Climate on Health
Joel Schwartz
Diane Gold Antonella Zanobetti
Harvard School of Public Health
Department of Environmental Health
What do we know about the Direct Effects of Temperature?
• More people die when it gets hot • More people die when it gets cold • More surprisingly, more people seem to
die when it is only moderately hot and when it is only moderately cold
• Could these effects at less extreme temperature by confounded?
Miami with and without control for Season
Cold effects sensitive to degrees of freedom
But should we control for season?
Schwartz J et al.
Detroit, Ml Honolulu, HI
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Von Klot and Schwartz, Environ Health 2012
A Standard Approach in Epidemiology
• Is Stratified Analyses • What if we look at effects of temperature
within month? • Also addresses the question of whether
the effect of a given temperature is independent of when it occurs (60 ° in December Vs in May)
Temperature and Mortality in New York
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What about Exposure
• What is the connection between airport temperature and temperature where you live?
• What is the connection to temperature you are exposed to?
• We used satellite remote sensing of radiance on a 1 km grid and calibrated it with air temperature readings
predicted air temperature (C)
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[] Selected locations
Kloog I, Chudnovsky A, Koutrakis P ,Schwartz et al. Sci Total Environ 2012 ;432:85-92
Scatterplot and regression results relating indoor to outdoor (a) temperature, (b) apparent temperature, (c) relative humidity, and (d) absolute humidity from May 2011 – April 2012, Greater Boston, Massachusetts. Red line, piecewise linear regression for (a) and (b) and linear regression for (c) and (d); black solid line, reference line placed at knot value; black dashed line, y=x (45 degree) reference line.
Nguyen J, Schwartz J, Dockery D
How can we examine Acclimatization?
• If weak acclimatization to cold is true – We expect the same effect of an unusually
cold day (say at the 1st percentile of temperature) in all cities, since it is equally unusual
– If absolute temperature matters, the effect at the 1st percentile should vary with temperature
– May also vary with other characteristics – Same for unusually hot days (99th percentile)
Extreme cold effect Extreme heat effect
New York City , NY Chicago, IL Boston, MA Houston, TX Detroit, MI Pittsburgh, PA Philadelphia, PA Atlanta, GA Clev eland, OH Seattle, WA Baltimore, MD Dallas, TX St Louis, MO Minneapolis, MN Sacramento, CA Columbus, OH Milwaukee, WI Cincinnati, OH Birmingham, AL Oklahoma City , OK San Francisco, CA Washington DC Kansas City , KS New Hav en, CT Portland, OR Nashv ille, TN New Orleans, LA Tulsa, OK Denv er, CO Charlotte, NC Salt Lake City , UT Jersey City , NJ Youngstown, OH Spokane, WA Albuquerque, NM Canton, OH Austin, TX Greensborough, NC Colorado Springs, CO Prov o, UT Boulder, CO Terra Haute, IN
Summary
2-day cummulative percent change in
-20 -15 -10 -5 0 5 10 15 20 25 30
New York City , NY Los Angeles, CA Chicago, IL Houston, TX Mami, FL Pittsburgh, PA St Louis, MO Boston, MA San Diego, CA Atlanta, GA Detroit, MI Baltimore, MD Philadelphia, PA Broward, FL Phoenix, AZ Clev eland, OH Dallas, TX Tampa, FL Kansas City , KS Honolulu, HI Minneapolis, MN New Hav en, CT Milwaukee, WI Cincinnati, OH Columbus, OH Washington DC Birmingham, AL Orlando, FL Oklahoma City , OK New Orleans, LA Nashv ille, TN Austin, TX Tulsa, OK Salt Lake City , UT Albuquerque, NM Jersey City , NJ Charlotte, NC Greensborough, NC Youngstown, OH Canton, OH Prov o, UT Terra Haute, IN
Summary
2-day cummulative percent chang
-20 -15 -10 -5 0 5 10 15 20 25 30
I2 =3% I2 =86%
Medina-Ramon M, Schwartz J et al.
So it looks like
• The effects of the coldest 1% of days are the same everywhere in the US
• So warming the winteris unlikely to reduce deaths
• The effects of the hottest 1% of days differs substantially across US cities
• So even if we use the dose-response fromcity A which already has the predicted temperature for city B,we will expect changes in mortality
Effect modification by medical condition and subject and area level characteristics of the effect of extreme hot and extreme cold
temperature (1th and 99th percentiles of temperature) on total mortality: meta-analysis of 123 and 111 U.S. cities respectively
during the period 1985–2006, among Medicare enrollees. 1.15
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Zanobetti A, O’ Neill M, Gronlund C, Schwartz J, ATS conference, 2012
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Alzheimer's Dementia Afib Non-white race
High % poverty
High % no High School
Cohort Study of Medicare Participants in 135 US Cities
• Follow a population over time and look atlife expectancy
• What is the Exposure? – Problem – Life expectancy in Finland and Greece is
about the same – Possible Answer – Variability of summer temperature predicts
mortality differences
Hazard Ratio (HR) and 95% Confidence Intervals (CI) for a 1 °C increase in yearly summer temperature standard deviation across the 135 U.S. cities in four cohorts
Summer (June-August) HR 95% CI
Adjusting for ozone
COPD 1.037 1.019 1.055
Diabetes 1.040 1.022 1.059
MI 1.038 1.021 1.055
CHF 1.028 1.013 1.042
Zanobetti A, O’ Neill M, Gronlund C, Schwartz J, Proc Natl Acad Sci USA, 2012, 24;109(17):6608-13
What are potential Mechanisms
• Particularly at less extreme temperatures?
Percent increase in blood pressure for 10 degree increase in temperature and apparent
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70 Diabetic subjects (322 obs) VA NAS, 928 men (2343 obs)
Hoffmann B, Gold DR, et al. Environ Health Perspect, Halonen JI, Zanobetti A, Sparrow D, Vokonas PS, Schwartz J 2012;120(2):241-6 Occup Environ Med. 2011;68(4):296-301
Changes in mm (95% CI) in brachial artery diameter (BAD) before and after occlusion, for an IQR increase in the prior 24 hours, 2-day and 5-day average temperature (TEMP) and
absolute humidity (AH) in diabetic subjects. 0.3
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Zanobetti, Gold DR, et al. , Am J Respir Critic Care Med Vol 185. pp. A3203
Risk factors for cardiovascular disease
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100 heart failure sbjects (285 obs)
VA NAS,673 men (1254 obs) VA NAS,478 men (862 obs)
Wilker E, et al. Environ Health Perspec 2012, 120(8):1083-7 Halonen J, et al. Environ Res, 2011;111(2):281-7. Halonen J, et al. Environ Health; 2010: 9:42.
Impact of Meteorological Variables on Atrial Fibrillation
Matched Parameters included in model IQR Odds Ratio (95% CI) P
Adjusted for: Outdoor temperature --- 6.3°C 1.13 (0.89, 1.43) 0.32
Indoor Temperature 6.3°C 1.01 (0.75, 1.37) 0.93 Absolute Humidity 6.3°C 0.96 (0.72, 1.28) 0.79
Absolute Humidity --- 3.5 g/m3 1.33 (1.02, 1.74) 0.037 Outdoor Temperature 3.5 g/m3 1.37 (0.98, 1.90) 0.061 Indoor Temperature 3.5 g/m3 1.28 (0.96, 1.70) 0.093
IQR, interquartile range; CI, confidence interval. * All models were adjusted for the 24-hour moving average barometric pressure, 2-hour moving average particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) concentration, and matched on month, day of the week, and hour.
Nguyen J, Dockery D, et al
Effect of temperature on Heart Rate Variability and
Ren C, et al. Am J Epidemiol 2011;173(9):1013-21
Effects of temperature variability on QTc (ms)
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Mehta A, Schwartz J, Zanobetti A, et al.
Effect of Meteorology on Lung Function
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Lepeule J, Schwartz J
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Decrease in Temperature and MI Incidence and ischemic stroke
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Madrigano J, Schwartz J, et al.Epidemiol, in press Mostofsky E, Mittleman M, et al. International Stroke conference 2013
Clustering days according to weather parameters 1
Mean (SD) 2
Mean (SD) 3
Mean (SD) 4
Mean (SD) 5
Mean (SD) # of days 1523 1308 1145 946 834 max T today (C) SD Hourly Temp (C) Water Vapor Pressure (mbar) Sea-Level Pressure (mbar) Ozone (ppb) Wind Speed (m/s) PM2.5 TEOM (ug/m3) Sulfur Dioxide (ppb)
6(5) 2(1) 5(2)
1022(6) 18 (9) 5(1)
10 (5) 7(4)
19 (4) 2(1)
14 (4) 1016(6)
22 (9) 4(1)
10 (5) 3(2)
8(6) 2(1) 6(3)
1007(7) 24 (9) 7(2) 7(4) 4(3)
29 (3) 3(1)
20 (4) 1013(5)
35 (12) 5(1)
16 (9) 3(2)
20 (6) 4(1) 9(3)
1017(7) 27 (11) 5(1)
10 (5) 4(3)
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Austin E, Koutrakis P, Zanobetti A, Gold D, Schwartz J, et al
Citations • Zanobetti A, et al. Summer temperature variability and long-term survival among elderly people with chronic
disease. Proc Natl Acad Sci USA, 2012, 24;109(17):6608-13. • Hoffmann B, et al. Opposing Effects of Particle Pollution, Ozone and Ambient Temperature on Arterial Blood
Pressure. Environ Health Perspect, 2012;120(2):241-6. • Halonen J, et al. Outdoor temperature is associated with serum HDL and LDL. Environ Res, 2011;111(2):281-7. • Halonen J, et al. Relationship between outdoor temperature and blood pressure. Occup Environ Med.
2011;68(4):296-301 • Halonen J, et al. Associations between outdoor temperature and markers of inflammation: a cohort study.
Environ Health; 2010: 9:42. • Ren C, et al. Ambient Temperature, Air Pollution, and Heart Rate Variability in an Aging Population. Am J
Epidemiol 2011;173(9):1013-21. • Wilker E, et al. Ambient temperature and biomarkers of heart failure: a repeated measures analysis. Environ
Health Perspec 2012 Aug;120(8):1083-7. • Zanobetti A, et al. Effects of air pollution and temperature on vascular function in people with diabetes. Abstracts
ISEE. 2011, Barcelona, Spain. Environ Health Perspect • Zanobetti A et al. Effects Of Temperature And Water Vapor Pressure On Vascular Function In People With
Diabetes, ATS conference, Am J Respir Critic Care Med Vol 185. pp. A3203 • Mostofsky E et al. Short-Term Changes in Ambient Temperature and Risk of Ischemic Stroke. Abstract submitted
to the International Stroke conference 2013 • Zanobetti A, et al. Assessing Effect Modification By Zipcode Area Level Characteristic, Personal Characteristics
And Specific Cause Of Admission In A Multi-City Case-Only Analysis. Abstract to ATS conference, 2012 • Kloog I et al. Temporal and spatial assessments of minimum air temperature using satellite surface temperature
measurements in Massachusetts, USA. Sci Total Environ 2012 ;432:85-92. • Madrigano J et al. Temperature, Myocardial Infarction, and Mortality: Effect Modification by Individual and Area-
Level Characteristics, Epidemiol, in press
Acknowledgments • NIEHS R21 ES020695 • NIEHS R21 AG040027-01 • NIEHS R21 ES020194 • NIEHS PO1 ES-09825 • NIEHS P30 ES000002-49 • US EPA grant RD 83479801
• Our Climate Change R21s led to: – an RO1 proposal to evaluate indoor and outdoor
temperature/humidity and land use effects on cardiovascular and sleep outcomes in the longitudinal Jackson (Mississippi) Heart Study.
– An R21 proposal to identify the chronic effects associated with longterm exposure to fluctuations in temperature and absolute humidity,adaptation, and to investigate the health consequences of increasing variability of summertime temperatures with different future scenarios