Mortality rates and excess mortality due to extreme high temperature

Mortality shows a seasonal variation, highest during wintertime and lowest during summer. Mortality is higher in January by 9-10% than the yearly mean, while lowest mortality is recorded in July and August; the mean difference is around 10%. Mortality data of the period studied are summarized in Fig. 44.1. The mean daily mortality of the region - based on the reported data was 84.5 death cases, out of which 64.9 deaths occurred in Budapest and 199.6 cases in County Pest, which meant 2.96 cases per 100 000 inhabitants in the region, 3.82 cases in Budapest and 1.17 cases per 100 000 in County Pest. A difference was observed also concerning the place of death: 75% of deaths occurred in hospitals in Budapest; this rate was only 57% in County Pest.

Daily mortality (number and %) in the CHR June 1 - August 31, 2007

Budapest

Region

Budapest

County Pest

Region at home in hospital

Fig. 44.1 Daily mortality in the CHR between June 1 and August 31, 2007.

Previous assessment of time series of mortality and temperature showed that summer heat is an important risk factor of mortality (Paldy, 2004). Mortality rate increases in relation to the increase of daily mean temperature (Fig. 44.2).

Daily mean mortality in relation to temperature in the CHR, June 1-August 31, 2007

120 I 100

3 20

Daily mean mortality in relation to temperature in the CHR, June 1-August 31, 2007

120 I 100

3 20

in hospital at home total in hospital at home total

¡3 total [J] under 25 °C 0 above 25 °C □ above 27 °C

Fig. 44.2 Association of daily temperature and mortality between June 1 and August 31, 2007 in the CHR.

The slope becomes steeper with the increase of temperature. In average, mortality was by 14% higher on days when daily mean temperature was above 25°C compared to the mortality of days with mean temperature lower than 25°C, this difference was 8% concerning mortality at home. Mean mortality on days with daily mean temperature above 27°C was by 29% higher in hospitals and by 26% higher at home than on days with mean temperature lower than 25°C. The observed similar increase of mortality supports the fact that the impact of heat affects not only seriously ill patients who need hospital treatment but also other groups of population, however, to somewhat less extent.

The computation of excess mortality was based on the temperature threshold values of the first and second level of heat alert and the temperature values measured in the downtown were used. The baseline mortality was the mean mortality of days with daily mean temperature lower than 25°C. In the year 2007 the number of such "cool" days was 46, which equals to the half of the summer season. Figures. 44.3 and 44.4 show the number and percentage of excess deaths on days when the mean temperature was above 25 and 27°C (the threshold of second and third level of heat alert) as well as above 30°C - never been recorded before.

Excess mortality due to high temperature in the CHR, June 1-August 31, 2007

Excess mortality due to high temperature in the CHR, June 1-August 31, 2007

at home in hospital total

Fig. 44.3 Excess mortality due to high temperature between June 1 and August 31, 2007 in the CHR.

On days when mean temperature was above 25°C the excess mortality was 320 cases related to mean mortality on cool days. On days when the mean temperature was above 27°C excess mortality was 373 cases, and on days with mean temperature above 30°C, the excess was 230 cases. The rate of mortality was around three times higher in hospitals than out of them, this increased in relation to the increase of temperature.

Excess mortality (%) due to high temperature in the CHR, June 1 - August 31, 2007

at home in hospital total at home in hospital total

Fig. 44.4 Excess mortality (%) due to high temperature between June 1 and August 31, 2007 in the CHR.

The description of daily data can help assess the relationship between temperature and mortality. Daily death cases showed a great variation with considerable deviation (Fig. 44.5). The minimum and maximum values of mortality at home were 10 and 43 cases respectively; these values in hospital were 36 and 115 cases respectively. The mean deviance from the summer mean was 6.8 cases of mortality at home and 12.8 cases in hospital representing 28 and 21% of mean mortality, respectively. Daily death counts were above the mean mortality with the exception of 1-2 days, variation was much higher in 2 months.

Number of excess deaths in hospitals and at home in relation to daily mean temperature in the Central Region of Hungary , 2007

. Mortality in hospitals

Mortality at home

Daily mean temperature

--Mortality under 25 °C

Heat Alarm 3. level

Heat Alarm 3. level

0 MhumMMIMLIiLllMMIMnhMIIMMMMlllllllLMJlMMMMlMihlMnllnl 0 1 5 9 13 17 21 25 29 3 7 11 15 19 23 27 31 4 8 12 16 20 24 28

Fig. 44.5 Daily in/out of hospital death counts and daily mean temperature in CHR in 2007.

Heat warning ¡tedl

0 MhumMMIMLIiLllMMIMnhMIIMMMMlllllllLMJlMMMMlMihlMnllnl 0 1 5 9 13 17 21 25 29 3 7 11 15 19 23 27 31 4 8 12 16 20 24 28

June July August

Fig. 44.5 Daily in/out of hospital death counts and daily mean temperature in CHR in 2007.

Based on the analysis of daily mortality during and after the July heat wave the following can be stated concerning mortality displacement (harvesting). A temporal decrease of daily mortality can be expected after an event (a heat wave) causing a rapid increase in mortality. The event affects the vulnerable population, and another similar event might not display an effect on the remaining resistant group of population. This could result in a temporal decrease of daily mortality; however, such an effect cannot be detected in the mortality data after the July heat wave. After the heat wave, the number of death cases remained in the range of daily variation. The minimum of daily mortality was recorded in a different period of the summer. The June and August heat waves did not cause an excess mortality; displacement could not be detected after these events. No harvesting effect could be seen during the summer 2007, which supported the assumption that excess mortality could be attributed to the impact of heat.

The number of excess death cases is shown in Table 44.2. The baseline value was the mean mortality of days with mean temperature under 25°C. Daily mortality slightly differed from the mean mortality of cool days during the first heat wave; it was even smaller than the mean. During the July heat wave with heat records, daily mortality significantly increased and stayed high, 278 excess cases were recorded during the 10-day period, which mean a 33% increase in daily mortality. Maximum mortality was recorded on July 20 with 43 cases at home and 115 cases in hospitals which were almost twice as much as the average counts on the cool days. During the August heat wave, affecting Central and Eastern Hungary mortality increased to a small extent, by around 1%.

Table 44.2 Excess mortality in CHR in relation to mean mortality of days with mean temperature < 25°C during 2007 heat waves.

June 19-23 alert second level 5 days

July 15-24 alert third level 10 days

August 23-26 heat warning 4 days

Number of death cases

400

1123

341

Number of excess death cases

-22.5

278

3

Mean daily excess death cases

-4.5

27.8

0.75

Daily excess mortality (%)

-5.3

32.9

0.9

An attempt was made to estimate the rate of excess mortality for the country by considering the rates of mortality in the capital and in County Pest, the settlement structure of the country and the rate of population in different types of settlements. Assuming that association between mortality and temperature values did not differ significantly in bigger towns and in their agglomeration form that of the Central Hungarian Region, the findings valid for the Central Hungarian Region can be extrapolated for the country. During the 10 days of the heat wave, 218 excess death cases occurred in Budapest and 60 in the County of Pest (out of the 278 cases), which mean 13 and 5.2 cases, respectively, per 100 000 population.

The total number of population of the cities with more than 100 000 inhabitants is 1.6 million. Excess mortality in these ten cities is 210 cases assuming mortality rates similar to Budapest. The population of the remaining part of Hungary is 5.55 million, where the excess mortality can be 290 cases assuming situation similar to County Pest. On this basis the total excess mortality due to the July heat wave can be 780 cases during the 10 days, corresponding to 7.8 cases per 100 000. An additional factor can also be considered based on the data of the Central Statistical Office. The rate of hospital beds is higher in the Central Hungarian Region than the national average; it is by 16% higher for 2.85 million inhabitants than elsewhere. As around 60% of excess mortality occurred in hospitals, this is by 10% higher in the Central Hungarian Region than in other parts of the country, meaning an excess of 28 death cases. If the number of excess cases is corrected by this number on national level, then the total number of excess might be 730 cases.

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