Effects of Extreme Temperatures on Cause-Specific Cardiovascular Mortality in China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Areas
2.2. Mortality Data
2.3. Meteorological and Air Pollution Data
2.4. Statistical Analysis
3. Results
3.1. Descriptive Statistics
City | Cause-Specific Cardiovascular | Group | Mean ± SD | Minimum | 25% | Median | 75% | Maximum |
---|---|---|---|---|---|---|---|---|
Beijing | CVD | All ages | 87 ± 18 | 49 | 73 | 84 | 100 | 154 |
Aged ≥ 65 | 70 ± 16 | 34 | 58 | 68 | 81 | 127 | ||
CBD | All ages | 40 ± 9 | 18 | 33 | 39 | 46 | 77 | |
Aged ≥ 65 | 32 ± 8 | 12 | 27 | 32 | 38 | 64 | ||
IHD | All ages | 38 ± 9 | 13 | 31 | 37 | 45 | 75 | |
Aged ≥ 65 | 31 ± 9 | 10 | 25 | 31 | 37 | 67 | ||
HPD | All ages | 2 ± 1 | 0 | 1 | 2 | 3 | 12 | |
Aged ≥ 65 | 2 ± 1 | 0 | 1 | 2 | 3 | 9 | ||
Shanghai | CVD | All ages | 35 ± 8 | 14 | 29 | 34 | 40 | 65 |
Aged ≥ 65 | 30 ± 8 | 11 | 24 | 29 | 35 | 61 | ||
CBD | All ages | 18 ± 5 | 6 | 14 | 17 | 21 | 34 | |
Aged ≥ 65 | 15 ± 4 | 4 | 12 | 14 | 18 | 30 | ||
IHD | All ages | 13 ± 4 | 2 | 9 | 12 | 15 | 28 | |
Aged ≥ 65 | 11 ± 4 | 1 | 9 | 11 | 14 | 27 | ||
HPD | All ages | 2 ± 1 | 0 | 1 | 1 | 2 | 6 | |
Aged ≥ 65 | 1 ± 1 | 0 | 0 | 1 | 2 | 6 |
City | Variables | Mean ± SD | Min | Percentiles | Max | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
1th | 10th | 25th | 50th | 75th | 90th | 99th | |||||
Beijing | Mean temperature (°C) | 13.6 ± 10.9 | −9.4 | −6.1 | −1.5 | 3.0 | 15.1 | 24.1 | 26.9 | 29.8 | 31.4 |
Relative humidity (%) | 52.5 ± 20.3 | 11.0 | 16.0 | 24.0 | 36.0 | 53.0 | 69.0 | 79.0 | 90.0 | 97.0 | |
PM10 (µg/m3) | 131.2 ± 8.2 | 7.0 | 17.9 | 45.5 | 74.0 | 116.0 | 162.0 | 238.0 | 403.3 | 600.0 | |
SO2 (µg/m3) | 39.9 ± 4.1 | 6.0 | 6.0 | 9.0 | 12.0 | 23.0 | 52.0 | 98.0 | 189.0 | 248.0 | |
NO2 (µg/m3) | 57.1 ± 2.4 | 10.0 | 19.2 | 28.8 | 40.0 | 52.8 | 68.8 | 88.8 | 132.8 | 152.0 | |
Shanghai | Mean temperature (°C) | 17.7 ± 8.9 | −3.4 | 0.5 | 5.3 | 9.8 | 18.7 | 25.2 | 28.9 | 32.4 | 34.6 |
Relative humidity (%) | 69.8 ± 12.2 | 30.0 | 38.0 | 53.0 | 62.0 | 71.0 | 79.0 | 84.5 | 91.0 | 95.0 | |
PM10 (µg/m3) | 84.4 ± 5.3 | 12.0 | 21.9 | 34.0 | 48.0 | 74.0 | 106.0 | 147.0 | 236.4 | 600.0 | |
SO2 (µg/m3) | 47.4 ± 2.9 | 10.0 | 12.0 | 18.0 | 26.0 | 40.0 | 62.0 | 86.0 | 138.2 | 235.0 | |
NO2 (µg/m3) | 55.0 ± 2.1 | 13.0 | 16.0 | 30.4 | 40.0 | 53.0 | 67.0 | 85.0 | 115.2 | 146 |
3.2. The Non-Linear Relationship between Mean Temperature and Cause-Specific Cardiovascular Mortality
3.3. The Cumulative Hot and Cold Effects of Temperature on Cause-Specific Cardiovascular Mortality
City | Lag | Hot Effects * (Relative Risks and 95% Confidence Intervals) | |||
---|---|---|---|---|---|
CVD | CBD | IHD | HPD | ||
Beijing | 0 | 1.02 (1.01, 1.04) a | 1.04 (1.02, 1.06) a | 1.02 (1.00, 1.04) a | 1.01 (0.94, 1.08) |
0–7 | 1.17 (1.12, 1.22) a | 1.24 (1.16, 1.32) a | 1.13 (1.06, 1.21) a | 1.25 (0.96, 1.61) | |
0–14 | 1.18 (1.11, 1.25) a | 1.25 (1.15, 1.34) a | 1.15 (1.05, 1.24) a | 1.39 (1.01, 1.92) a | |
0–27 | 1.13 (1.04, 1.22) a | 1.21 (1.08, 1.35) a | 1.11 (0.98, 1.24) | 1.36 (0.87, 2.14) | |
Shanghai | 0 | 1.00 (0.98, 1.02) | 1.00 (0.96, 1.02) | 1.01 (0.97, 1.05) | 1.01 (0.90, 1.16) |
0–7 | 1.05 (0.97, 1.14) | 1.01 (0.91, 1.12) | 1.07 (0.94, 1.22) | 1.21 (0.79, 1.86) | |
0–14 | 1.10 (0.99, 1.20) | 1.07 (0.95, 1.21) | 1.08 (0.93, 1.25) | 1.21 (0.71, 1.93) | |
0–27 | 1.02 (0.89, 1.16) | 1.01 (0.85, 1.20) | 0.99 (0.80, 1.23) | 0.97 (0.47, 2.01) |
3.4. The Stratification of Seasonal Analysis for the Cumulative Hot and Cold Effects on Mortality from Cause-Specific Cardiovascular Diseases
City | Lag | Cold Effects * (Relative Risks and 95% Confidence Intervals) | |||
---|---|---|---|---|---|
CVD | CBD | IHD | HPD | ||
Beijing | 0 | 1.01 (0.99, 1.03) | 1.01 (0.98, 1.03) | 1.02 (0.99, 1.04) | 1.03 (0.93, 1.13) |
0–7 | 1.11 (1.05, 1.17) a | 1.10 (1.02, 1.19) a | 1.12 (1.03, 1.21) a | 1.21 (0.88, 1.65) | |
0–14 | 1.21 (1.13, 1.28) a | 1.18 (1.07, 1.29) a | 1.19 (1.09, 1.31) a | 1.22 (0.85, 1.74) | |
0–27 | 1.35 (1.24, 1.46) a | 1.27 (1.14, 1.42) a | 1.39 (1.24, 1.57) a | 1.64 (1.06, 2.55) a | |
Shanghai | 0 | 0.99 (0.97, 1.02) | 0.98 (0.96, 1.01) | 1.01 (0.98, 1.05) | 0.97 (0.87, 1.08) |
0–7 | 1.01 (0.94, 1.09) | 0.99 (0.90, 1.09) | 1.05 (0.94, 1.18) | 0.85 (0.57, 1.25) | |
0–14 | 1.05 (0.97, 1.14) | 1.08 (0.97, 1.21) | 1.02 (0.89, 1.16) | 0.81 (0.52, 1.27) | |
0–27 | 1.14 (1.02, 1.27) a | 1.11 (0.95, 1.29) | 1.16 (1.03, 1.34) a | 0.86 (0.47, 1.57) |
City | Cause | Hot Effects Lag 0–14 (Warm Period) | Cold Effects Lag 0–27 (Cold Period) |
---|---|---|---|
Beijing | CVD | 1.32 (1.16,1.51) a | 1.35 (0.80,2.26) |
CBD | 1.31 (1.09,1.57) a | 1.11 (0.52,2.36) | |
IHD | 1.33 (1.08,1.62) a | 1.36 (0.74,3.38) | |
HPD | 3.04 (1.42,6.48) a | 1.56 (0.02,8.70) | |
Shanghai | CVD | 1.14 (0.93,1.40) | 1.07 (0.60,1.90) |
CBD | 1.14 (0.87,1.50) | 1.10 (0.49,2.45) | |
IHD | 0.99 (0.71,1.38) | 1.10 (0.42,2.86) | |
HPD | 1.56 (0.50,4.83) | 0.98 (0.10,5.60) |
3.5. The Hot and Cold Effects of Temperature for Older People Who Died from Cause-Specific Cardiovascular Diseases
4. Sensitivity Analysis
5. Discussion
6. Conclusions
Acknowledgements
Author Contributions
Conflicts of Interest
Abbreviations
CVD | cardiovascular disease |
CBD | cerebrovascular disease |
IHD | ischemic heart disease |
HPD | hypertensive disease |
RH | relative humidity |
MT | mean temperature |
PM10 | aerodynamic diameter less than 10 microns |
DLNM | distributed lag non-linear model |
AIC | Akaike information criterion |
Appendix
Factors * | Beijing | Shanghai |
---|---|---|
Population (million) | 17.55 | 19.21 |
Birth rate (‰) | 8.06 | 8.64 |
Mortality rate (‰) | 4.56 | 5.94 |
Natural growth rate (‰) | 3.50 | 2.70 |
Age structure (proportion, %) | ||
0–14 | 9.90 | 7.56 |
15–64 | 79.98 | 78.36 |
≥65 | 10.09 | 14.08 |
Life expectancy | 76.10 | 78.14 |
Education level (proportion, %) | ||
unschooled | 3.10 | 4.10 |
Primary school | 13.00 | 13.30 |
Junior middle school | 30.30 | 33.80 |
High school | 22.80 | 25.20 |
College or above | 30.80 | 23.60 |
City | Lag | Hot Effects * | |||
---|---|---|---|---|---|
Cardiovascular | Cerebrovascular | Ischemic Heart Disease | Hypertensive Disease | ||
Beijing | 0 | 1.04 (1.02, 1.06) a | 1.06 (1.02, 1.09) a | 1.04 (1.01, 1.07) a | 1.03 (0.93, 1.14) |
0–7 | 1.26 (1.18, 1.35) a | 1.37 (1.25, 1.51) a | 1.21 (1.10, 1.34) a | 1.32 (0.90, 1.93) | |
0–14 | 1.26 (1.16, 1.37) a | 1.38 (1.23, 1.55) a | 1.22 (1.07, 1.37) a | 1.38 (0.86, 2.19) | |
0–27 | 1.15 (1.03, 1.29) a | 1.27 (1.09, 1.50) a | 1.13 (0.95, 1.33) | 1.32 (0.69, 2.52) | |
Shanghai | 0 | 1.01 (0.98, 1.04) | 0.99 (0.95, 1.03) | 1.03 (0.98, 1.09) | 1.03 (0.87, 1.23) |
0–7 | 1.08 (0.98, 1.20) | 1.00 (0.87, 1.15) | 1.15 (0.98, 1.36) | 1.30 (0.74, 2.28) | |
0–14 | 1.10 (0.98, 1.24) | 1.05 (0.90, 1.22) | 1.12 (0.92, 1.35) | 1.22 (0.64, 2.30) | |
0–27 | 1.01 (0.87, 1.19) | 1.01 (0.81, 1.24) | 0.98 (0.92, 1.35) | 1.02 (0.42, 2.46) |
City | Lag | Cold Effects * | |||
---|---|---|---|---|---|
Cardiovascular | Cerebrovascular | Ischemic Heart Disease | Hypertensive Disease | ||
Beijing | 0 | 1.02 (1.00, 1.05) a | 1.01 (0.98, 1.04) | 1.04 (1.00, 1.07) a | 1.06 (0.92, 1.21) |
0–7 | 1.21 (1.11, 1.31) a | 1.16 (1.04, 1.30) a | 1.23 (1.10, 1.38) a | 1.52 (0.97, 2.37) | |
0–14 | 1.38 (1.26, 1.51) a | 1.33 (1.17, 1.52) a | 1.36 (1.19, 1.55) a | 1.68 (1.02, 2.78) a | |
0–27 | 1.60 (1.44, 1.78) a | 1.48 (1.28, 1.72) a | 1.64 (1.41, 1.92) a | 2.53 (1.41, 4.53) a | |
Shanghai | 0 | 1.01 (0.98, 1.04) | 1.00 (0.96, 1.03) | 1.03 (0.99, 1.08) | 0.99 (0.86, 1.14) |
0–7 | 1.09 (1.00, 1.21) a | 1.07 (0.94, 1.21) | 1.16 (0.99, 1.35) | 0.93 (0.56, 1.55) | |
0–14 | 1.17 (1.06, 1.30) a | 1.20 (1.04, 1.38) a | 1.15 (0.97, 1.16) | 0.86 (0.49, 1.52) | |
0–27 | 1.31 (1.15, 1.49) a | 1.23 (1.03, 1.38) a | 1.35 (1.09, 1.66) a | 0.91 (0.45, 1.84) |
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Wang, X.; Li, G.; Liu, L.; Westerdahl, D.; Jin, X.; Pan, X. Effects of Extreme Temperatures on Cause-Specific Cardiovascular Mortality in China. Int. J. Environ. Res. Public Health 2015, 12, 16136-16156. https://doi.org/10.3390/ijerph121215042
Wang X, Li G, Liu L, Westerdahl D, Jin X, Pan X. Effects of Extreme Temperatures on Cause-Specific Cardiovascular Mortality in China. International Journal of Environmental Research and Public Health. 2015; 12(12):16136-16156. https://doi.org/10.3390/ijerph121215042
Chicago/Turabian StyleWang, Xuying, Guoxing Li, Liqun Liu, Dane Westerdahl, Xiaobin Jin, and Xiaochuan Pan. 2015. "Effects of Extreme Temperatures on Cause-Specific Cardiovascular Mortality in China" International Journal of Environmental Research and Public Health 12, no. 12: 16136-16156. https://doi.org/10.3390/ijerph121215042