Commentary: People's vulnerability to heat wave
*Shanghai Urban Environment Meteorology Center, Pudong New Area, Shanghai 200135, China. E-mail: jianguot{at}21cn.com
Accepted 17 January 2008
Heat or anomalously hot weather that lasts for several days, usually accompanied by high humidity, and often called ‘a heat wave’, has a clear impact on human health, including a rise in mortality and morbidity. Several investigations have demonstrated differences in the impact of heat waves on morbidity and mortality in different years1–3 and, that the reductions in heat-related morbidity and mortality were not attributable to differences in heat levels alone—changes in public health preparedness and response may also have contributed to these reductions. Fouillet's study on the impact of the 2006 heat wave on mortality changes in France since the catastrophic European heat wave of summer 20034 further attracts our attention to this issue. The comparison of the observed and expected mortalities during the 2006 heat wave has shown that 2065 excess deaths occurred throughout France during the extreme temperature events, and the authors suggest this finding may be related to the establishment of preventive measures in the context of the National Heat Plan.
People's vulnerability to heat depends on climatic factors (such as the frequency of heat waves) and on individual risk factors, including medical, behavioural and environmental factors, for example age, gender, pre-existing disease, use of certain medications, level of hydration, living alone, housing condition (building type or living on a higher floor); and the presence and use of air-conditioning in the home or residential institution. It also can be said that the vulnerability to heat wave is a function of sensitivity (the exposure–response relationship, the characteristics of the population), the exposure to heat wave (its density and durations) and, the adaptation measures and actions in place to reduce the loss of life. So, it is complicated to discern whether the people's vulnerability to heat wave has really been changed.
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Optimum indicator to explain the exposure–response relationship |
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 Top Optimum indicator to explain... Combination of pollution and...Characteristics of the...Intervention measuresReferences |
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The daily maximum temperature alone has not been considered as a good indicator of the human thermal environment; night-time temperature and many other kinds of thermal indices such as heat index, humidex, apparent temperature, and the temperature-humidity index, etc.—most of them two-parameter indices—have been developed to describe the complex conditions of heat exchange between the human body and its thermal environment.5 Furthermore, a set of comprehensive biometeorological indices (PET, SET, PT*, etc) derived from human-environment heat budget models are also used to assess the thermal environment.6
All of the indices cited above are absolute; that is, a particular meteorological variable is considered to have the same impact on the human body no matter where or when it occurs. There is much value to absolute indices, as they provide a measure of intensity for heat events. However, humans also respond to weather in a relative way; that is, we respond differently to the weather depending upon the frequency of the particular extreme episode. This is due to the human body's ability to adapt, at least to a certain level. There is growing interest in relative biometeorological indices that have the capability of taking human differential responses into account (i.e. HeRATE, Health Related Assessment of the Thermal Environment7 and Heat Stress Index (HSI), of Watts and Kalkstein8). It is a good idea to define a cumulative maximum temperature variable (CTmax) as the sum of the number of degrees above a threshold temperature to depict the duration and intensity of the extreme temperature events, but a cut-off point (27°C) may have its seasonality by taking the long-term and short-term adaptation into consideration.
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Combination of pollution and excessive heat impacts on human health |
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Considerable research indicates that human mortality is significantly affected by both ambient meteorological conditions on a particular day, as well as atmospheric pollutant levels. The stagnant atmospheric conditions common during heat waves can trap pollutants in urban areas, exacerbating the negative impacts of the heat wave.9–11 Tressol's paper12 presents an analysis of both MOZAIC profiles above Frankfurt and Lagrangian dispersion model simulations for the 2003 European heat wave, and find that in addition to the high positive anomalies of temperature for the heat wave period (2–14 August 2003), compared with non-heat-wave periods, the ozone and carbon monoxide levels also present strong anomalies (both
+40 ppbv) during the heat wave. How about the air pollution level in 2006? Strong epidemiological studies indicate that air pollutant (i.e. ozone, PM10) concentrations are important co-exposures during heat waves. For example, between 21% and 38% of the excess deaths in the 2003 heat wave were estimated to be attributable to ozone and PM10.13 It remains unclear how the combination of pollution and excessive heat impacts on human health. |
Characteristics of the population and other socioeconomic status |
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Reductions in heat-related mortality were not attributable to differences in heat levels alone. Changes in characteristics of the population may also have contributed to these reductions. Epidemiological studies indicate that risks in men and women do not differ significantly. Studies, however, vary concerning the age at which vulnerability is shown to increase. Older people are more vulnerable to heat because of intrinsic changes in the regulatory system and/or because of the presence of drugs that interfere with normal homeostasis. Most population-based time–series studies show an effect in adult age groups, with the effect larger among people 65 years or older versus other ages.14 Comparison of numbers of elderly in 65–69, 70–74, 75+ between two periods might be interesting. Another factor is the relatively high percentage of people with illnesses and disabilities within the elderly population. Also, people with lower socioeconomic status may be more vulnerable to heat-related mortality because of poorer-quality housing and a lack of air-conditioning.15 The populations in more deprived areas within a city are also more likely to have other risk factors for heat-related death.16
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Intervention measures |
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The elderly are most vulnerable to heat-related mortality. When older people live alone, they may not receive the care they need during a heat wave and they are also less likely to call for medical attention, and therefore may die at home without being admitted to hospital.17 After the 2003 Europe heat wave, in order to prevent the consequences of a new heat wave, the Health Department of France set up a National Heat Wave Plan to prevent the risks related to heat stress, including the setting-up of a system for real-time surveillance of health data, compilation of scientific recommendations on the prevention and treatment of heat-related disease, air-conditioning equipment for hospitals and retirement homes, drawing up of emergency plans for retirement homes, city-scale censuses of the isolated and vulnerable, visits to those people during the heat periods, and set-up of a warning system, etc. Though, it is hard to assess the effectiveness of these intervention measures, it can be believed that these can be at least partially responsible for the lower mortality levels observed during the heat wave of 2006 than that in 2003. It is worth mentioning here, that air conditioning can allow people to continue to work effectively in hot weather and undoubtedly lessens heat stress, thus protecting susceptible sections of the population throughout a heat wave. Furthermore, larger living areas can result in better ventilation throughout a home, creating a more comfortable indoor environment.
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References |
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16 Martinez BF, Annest JL, Kilbourne EM, et al. Geographic distribution of heat-related deaths among elderly persons. Use of county-level dot maps for injury surveillance and epidemiologic research, JAMA (1989) 262:2246–50.
17 Semenza JC, McCullough JE, Flanders WD, McGeehin MA, Lumpkin JR. Excess hospital admissions during July 1995 heat wave in Chicago. Am J Prev Med (1999) 16:269–77.[CrossRef][Web of Science][Medline]
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