Association of Maximum Temperature between Daily Hospital Emergency Visits for Cardiovascular and Cerebrovascular Diseases:a Case-Crossover Study / 环境与健康杂志

Objective To explore the association between the daily maximum temperature and hospital emergency visits for cardiovascular and cerebrovascular diseases ( ICD-10: I00～I99) in different seasons in Beijing, China. Methods The data of the daily hospital emergency visits for cardiovascular and cerebrovascular diseases (ICD-10: I00～I99) from a Level-3A hospital in Haidian district in Beijing during 2004-2006 and the corresponding meteorological, air pollution data were collected. The seasonal-stratified case-crossover design and Logistic multiple regression model was used for the data analysis. Results After adjusting the influence of relative humidity, wind speed and atmospheric pressure, for 1℃ increase in daily maximum temperature, the corresponding increase in the hospital emergency visits of the diseases was 17.3%(OR=1.173, 95%CI:1.149～1.197) and 4.2% (OR=1.042, 95%CI: 1.011～1.074) in spring and summer of the years, respectively (P0.05). Conclusion The increase of daily maximum temperature may be a risk factor for daily hospital emergency visits for cardiovascular and cerebrovascular diseases in spring and summer, however, it may be a preventive factor in autumn. The effects of air temperature on health should not be the same in seasons.

Determination of optimum daily maximum temperature using climate data

<p><b>OBJECTIVE</b>The relation between daily maximum temperature and mortality rate has a V-shaped pattern; the mortality rate is lowest at a certain temperature, that is, optimum temperature (OT), and the mortality rate increases when the temperature becomes higher or lower than OT. OT is associated with climate, but the relation between OT and long-term average temperature, which is a frequently used index of climate, had an outlier (Okinawa) even in Japan alone. Our objective is to determine the best climate index for OT estimation.</p><p><b>METHODS</b>We obtained death certificate data, meteorological data and population data for Japan from relevant government ministries. All the data obtained were from 1972 to 1995 except for Okinawa's mortality data (1973 to 1995). Using smoothing spline with the degree of freedom fixed to 6, we computed the OTs for 47 prefectures in Japan. These OTs were exhaustively compared with percentiles of daily maximum, average, and minimum temperatures, along with the long-term average temperature.</p><p><b>RESULTS</b>Among the candidates of the best climate index, 80 and 85 percentiles of daily maximum temperatures (Tmax80 and Tmax85) showed the highest correlation coefficient with OT (R>0.9, much higher than the R for the long-term average temperature, i.e., 0.63), and the regression models using Tmax80 and Tmax85 best regressed the OT, that is, the difference between the observed OT and the expected OT was smallest when Tmax80 or Tmax85 was used. Unlike previously used average of daily mean temperature, Tmax80 and Tmax85 made Okinawa a nonoutlier. This characteristic is desirable because Okinawa's being an outlier is due to its maritime climate and the capacity to accommodate a different type of climate may expand the applicability of OT estimation method to wider regions in the world. A direct comparison of OT with Tmax75 to Tmax90 revealed that the difference is smallest for the percentile between Tmax80 and Tmax85.</p><p><b>CONCLUSION</b>We considered that a daily maximum temperature between Tmax80 and Tmax85 is the best climate index for estimating OT in Japan.</p>

Determination of Optimum Daily Maximum Temperature Using Climate Data

Objective: The relation between daily maximum temperature and mortality rate has a V-shaped pattern; the mortality rate is lowest at a certain temperature, that is, optimum temperature (OT), and the mortality rate increases when the temperature becomes higher or lower than OT. OT is associated with climate, but the relation between OT and long-term average temperature, which is a frequently used index of climate, had an outlier (Okinawa) even in Japan alone. Our objective is to determine the best climate index for OT estimation. Methods: We obtained death certificate data, meteorological data and population data for Japan from relevant government ministries. All the data obtained were from 1972 to 1995 except for Okinawa’s mortality data (1973 to 1995). Using smoothing spline with the degree of freedom fixed to 6, we computed the OTs for 47 prefectures in Japan. These OTs were exhaustively compared with percentiles of daily maximum, average, and minimum temperatures, along with the long-term average temperature. Results: Among the candidates of the best climate index, 80 and 85 percentiles of daily maximum temperatures (Tmax80 and Tmax85) showed the highest correlation coefficient with OT (R>0.9, much higher than the R for the long-term average temperature, i.e., 0.63), and the regression models using Tmax80 and Tmax85 best regressed the OT, that is, the difference between the observed OT and the expected OT was smallest when Tmax80 or Tmax85 was used. Unlike previously used average of daily mean temperature, Tmax80 and Tmax85 made Okinawa a nonoutlier. This characteristic is desirable because Okinawa’s being an outlier is due to its maritime climate and the capacity to accommodate a different type of climate may expand the applicability of OT estimation method to wider regions in the world. A direct comparison of OT with Tmax75 to Tmax90 revealed that the difference is smallest for the percentile between Tmax80 and Tmax85. Conclusion: We considered that a daily maximum temperature between Tmax80 and Tmax85 is the best climate index for estimating OT in Japan.