Published December 20, 2011 · Estimated reading time: 16 minutes · Filed under , , ,

Social Risk Factors for Heat Wave Mortality Among the Elderly: A case study of the 2003 heat wave in Paris, France

By Marzieh Ghiasi (Dec 2011)

Heat waves are a phenomenon whereby unusually high temperatures persist over a region for days or weeks. Heat waves can have health consequences for populations and often lead to increases in mortality within exposed populations. However, unlike other natural disasters, heat waves are a silent killer even though they have been found to kill the most in developed countries as they largely affect certain vulnerable segments of the population. As global warming progresses in this century, heat waves and other extreme weather phenomena have been predicted to increase in frequency and intensity. The first step to avoiding adverse health outcomes adequately is to address how heat waves affect populations.  In this paper I examine the 2003 heat wave in France which killed nearly 15,000 individuals, a large portion of whom were the elderly. I look at explanations for the high rates of mortality, observed, particularly in Paris by looking at the physical basis, health factors, and sociological dynamics that determine who dies during a heat wave. I argue that four specific social risk factors aggravated death among the elderly in Paris, namely gender, social isolation, socioeconomic status and the paradox of vulnerability. Taking steps to reduce the impact of these factors will be an important step in reducing casualties in future heat waves.

Image source


Heat wave is considered a relative term with no universal definition. The world Meteorological Organization has defined heat waves as consisting of a consecutive period of 5 or more days with temperatures exceeding a given area’s average maximum by 5°C (Poumadère, Mays, Le Mer, & Blong, 2005). In North America, heat waves are considered to be periods of 3 or more consecutive days with temperatures exceeding 32°C, often accompanied by high humidity (Klinenberg, 2003). During a heat wave, high temperature continental (dry) tropical and maritime (moist) tropical air masses move into a region (Ackerman & Knox, 2011). This creates a stationary high pressure dome over a region that persists for days with (1) high temperatures (2) high humidity (3) light winds and (4) high solar energy reaching the surface due to clear skies (Kilbourne, 1997).

The August 2003 Heat wave in Europe, which had been worse than any so far on record in the region, since at least 1873 (Vandentorren et al., 2004)is thought to have been due to several factors. Primarily associated were Atlantic and Mediterranean Sea Surface Temperature (SST) anomalies, which in turn, have been linked to (1) remaining effects of the 2002 El Niño (2) an intense West African monsoon season in 2003 (Chase, Wolter, Pielke, & Rasool, 2006). This created a high pressure anticyclone region over Europe preventing precipitation over the area. As well, due to clear conditions, heat trapping by anthropogenic greenhouse  gases, and soil/vegetation profile of the region, highly positive sensible heat fluxes were observed (Black, Blackburn, Harrison, Hoskins, & Methven, 2004).

In Europe, 46,000 individuals died as a result of the 2003 heat wave. However, cities across the continent varied greatly in terms of exposure and population health outcomes, due to both geographical differences, and the extent to which temperatures differed from normal conditions that the population was used to. D’Ippoliti et al. (2010)found that French cities recorded the most severe differences, where in some regions temperatures were 11-12°C above the seasonal average for nine consecutive days.

In France, between August 3-14, 2003 some 60 million people were exposed to the heat wave, and 14,748 excess deaths occurred as a result of it (Toulemon & Barbieri, 2005). There was geographical variability observed in the country both with respect to temperatures and excess mortality. Interestingly, the regions in southern France with the highest number of days (>11 days) exceeding 35°C did not suffer as much mortality as more northern regions which had 9-11 days exceeding 35° (Fig 1). The population density in France is high in the South along the Mediterranean coast in and the center and North. Based on this, Toulemon et al. (2005)argue there is no correlation between temperature and mortality in France.

Fig. 1 (A) Number of days temperature of French départements exceeded 35°C between 1-20 Aug, 2003 (dark red >11 days) (B) Percent increase in excess mortality in French departments between 1-20 Aug, 2003 (dark blue>. Source: Toulemon and Barbieri (2005).

However, this map merely reflects absolute temperatures, and gives no information about the difference between the temperature observed and the average temperatures in a regular season. Average temperatures are generally higher in Southern France, and in other regions of Europe this has been shown to help populations better protect themselves against abnormally warm weather conditions (D'Ippoliti, et al., 2010). Nevertheless, specific metropolitan areas recorded some of the highest temperatures and excess mortalities when compared to surrounding rural areas. Paris had the highest excess mortalities in France at 149% in the city and 174% in the surrounding suburbs (Fouillet et al., 2006).

Various studies have tried to account for the environmental factors that contributed to high death counts in Paris and other cities. An important factor, seen in earlier heat waves, was modified climates in cities due to urbanization. The urban heat island effect leads to higher temperatures in cities than outlying areas. This modified urban energy balance profile is primarily caused by the presence of building materials such as asphalt, which have low albedo and high heat capacity. Another important contributor to the heat island effect is the absence of vegetation in urban areas, which cool surroundings by evapotranspiration, converting what would normally become sensible heat and contribute to temperature rise to latent heat through the phase change process of water (Ebi & Meehl, 2007). The urban heat island effect was found to have increased heat exposure to residents of Paris and suburbs by 35%  (Rey et al., 2009). Additionally, Severe heat island effects have been recorded around the homes and neighbourhoods where many heat wave victims resided (Vandentorren et al., 2006).


Persistent heat wave conditions can have severe health effects and endanger lives, particularly those of the most vulnerable segments in society. Directly, heat overexposure can lead to heat cramps, heat syncope, heat exhaustion, and heat stroke. Heat cramps, caused by the loss of fluids and electrolyte imbalance in the body, lead to muscle spasms and nausea. Heat syncope refers to the loss of consciousness as a result of exposure to heat. Heat exhaustion leads to rapid breathing, dizziness, and excessive sweating as the body tries to lose energy. This can be a precursor to more severe condition of heat stroke, which is a medical emergency. During a heat stroke, sweating ceases, pulse accelerates, and the body becomes hyperthermic as it loses its ability to cool down, leading to death if not treated (Kilbourne, 1997).  However, mortality from heatstroke represented only a portion of deaths in the French heat wave. A matched case-control study of excess  mortalities in Paris and two other French cities found that while 35% of causes of deaths involved heat directly, another 37% were due to cardiovascular causes, and the rest respiratory, neurological and ill-defined causes (Fouillet, et al., 2006).

Heat wave mortality is also associated with aggravation of underlying medical conditions such as nephritis and diabetes that are not normally associated with heat (Kilbourne, 1997). As well, while some conditions may not lead to death, they may cause severe disability. For example, in the case of heatstroke victims surviving the 1995 Chicago heat wave, one third of the individuals had not shown any recovery after one year (Ebi & Meehl, 2007).

The overall excess mortality in France (55%) and urban Paris (149%) recorded between Aug 1-20th shows that while excess deaths were recorded across all segments of the population, certain segments were far more likely to incur mortality (Fouillet, et al., 2006). Living in urban areas, as described earlier, is considered by most literature to be a major environmental vulnerability factor (D'Ippoliti, et al., 2010). The dominant population vulnerability factor in heat waves is age. With the exception of the very young, excess mortality rates increased with age with 90% of the victims in Paris being over the age of 65. Paris also has the highest share of individuals over 80 than the rest of France, which may have contributed to skewed mortality (Cadot, Rodwin, & Spira, 2007). Gender was another factor correlated with population vulnerability, as women represented 65% of deaths, and men 35% (Toulemon & Barbieri, 2005).

2 (A) Daily excess mortality from Jul-Sep 2003 in the France, numbers shown for Aug 4, 8, 12 and 16 (solid line: daily Tmax, dotted line: daily Tmin). Source: Fouillet et al.(2005). (B) Daily excess mortality in Aug 2003 in France separated into male and female components. Source: Poumadere et al. (2005).

One of the concerns in analyzing mortality data, especially those that show excess deaths predominantly among the elderly, is the potential for disregarding harvesting effect. It is thought that heat waves can lead to a short-term forward shift in mortality, where vulnerable individuals, due to die shortly, will die due to heat stress. Consequently, if the harvesting effect has taken place, one should observe an overall decrease in mortality rate following a heat wave. After the August 2003 heat wave, the French daily excess mortality returned to baseline and in the weeks following there appeared to be no mortality deficit (Fig. 2A). However, in 2004, a mortality deficit of 20,000 deaths was observed in the country, which was attributed to harvesting effects of the heat wave in the previous summer (Fouillet et al., 2008). Toulemon et al. (2005)tested whether the 2003 French heat wave killed only the frailest individuals with little time left to live, or people who would have, without the heat wave, survived to a normal life expectancy. Calculating life expectancies, they found that only 2000 of the victims would have been expected to die before 2004. As well, the mortality deficit in 2004 could further be explained by the lack of a flu pandemic in that year, and severe measures against alcohol implemented in the same year.


In the following section four social risk factors which render the elderly particularly vulnerable to heat waves, and can confound mortality data from heat waves, are considered. These include (1) gender (2) social isolation (3) socioeconomic status (4) health status.


The correlation between excess mortality and gender has been drawn in many studies of heat waves. A general reason offered for this has been greater longevity among women which means within older age groups, a larger portion of the population will be female. That is, age is thought to confound the correlation between gender and heat wave mortality (Fouillet, et al., 2006). Two factors, however, bring into question whether the sex differences in mortality were in fact due to differential age structures in the French populations.

First, although women in Europe and the US live longer than men, in Europe more elderly women die in heat waves, while in the US more men do (Ebi & Meehl, 2007; Klinenberg, 2003). Second, looking at the data from Paris in 2003, controlling for age reduces sex differences in mortality only slightly (-5%), with women still representing 60% of excess deaths (Toulemon & Barbieri, 2005)(Fig. 2B). Similarly, studies of other European cities have shown that despite controlling for and stratifying age groups, women still remain a vulnerable group (D'Ippoliti, et al., 2010). While some have suggested that women may have underlying physiological vulnerabilities, such as reduced sweating capacity (D'Ippoliti, et al., 2010), the greater susceptibility of men in the US context suggests that gendered sociological factors in each region may play a more prominent role than any biological factors.

In the 1995 Chicago heat wave, it was found that elderly men were twice as likely to die as women of the same age. Klinenberg (2003)attributed this to greater loss of social relationships and isolation after retirement among men. In Paris 66% of elderly women live alone, a higher proportion than the rest of France, at 50%. However, immigrant Paris-dwelling elder women, many of whom live in multi-generational families with high social contact, were not found to face similar mortality risks (Cadot, et al., 2007). This suggests that similar to the US, social isolation may be contributing to the skewed sex ratio of heat wave mortality in France.

Social isolation

Social isolation, or living alone, has been identified by multiple studies as the most significant risk factor for death during heat waves (Cadot, et al., 2007; Kilbourne, 1997). In France, it was found that the absence of social activities led to a sixfold increase in risk of death during a heat wave among the elderly (Vandentorren, et al., 2006). As well, mortality risks were much greater for those living at home (+74%) than those in public hospitals (+45%), where they were frequently checked on (Fouillet, et al., 2006). Differential mortality risks in different regions of Europe, and between Northern and Southern France, as well as between ethnic minorities versus ethnic French have been attributed to different levels of integration of elderly family member in family life. In those communities where the elderly are more integrated, they have reduced risk of mortality due to heat waves (D'Ippoliti, et al., 2010).

Socioeconomic status

Low socioeconomic status (SES) has been shown by studies to be a risk factor for heat wave mortality across Europe. The causes for this increased risk are speculated to be differences in housing and neighbourhoods, as well as confounding factors such as health status which correlated with SES in many places (Ebi & Meehl, 2007). Individuals of lower socioeconomic status often live in areas where crime and a lack of investment lead to insecurity and social isolation (Klinenberg, 2003). Low SES groups also tend to live in areas with low air quality which can contribute to acute respiratory diseases during a heat wave (Fouillet, et al., 2006).

Areas of concentrated poverty also have been shown to have magnified urban heat island effects due to fewer open spaces and less vegetation (Ebi & Meehl, 2007). The location of rooms in which elderly with low SES resided were found to be very important in determining the death risk in the 2003 Paris heat wave, with rooms having poor insulation, no air conditioning, and located on the top most floor contributing to worse health outcomes (Vandentorren, et al., 2006).

Nevertheless, studies drawing a correlation between SES and mortality among elderly in the heat wave in Paris are not conclusive. One study in particular cites higher mortality in Southeastern portions of the city compared to the poorest neighbourhoods (Cadot, et al., 2007). The study cites social networks among low-SES immigrants as a confounding factor. Another study however finds, in comparing Parisian neighbourhoods, that the most deprived neighbourhoods had twofold higher excess mortality than the least deprived neighbourhoods (Rey, et al., 2009).

The paradox of vulnerability

Lack of mobility and various underlying health issues among the elderly have been associated with increased risk of death during heat waves (Vandentorren, et al., 2006). In a notable paradox in France, however, the most disabled elderly had better survival rates in nursing homes compared to less disabled elderly, respectively with a +3.1 versus +8.3 increase in risk of mortality compared to normal. Analysis, controlling for age and sex, showed that these differential outcomes were a result of institutional staff paying special attention to those most vulnerable as opposed to carefully monitoring all patients (Holstein, Canouï-Poitrine, Neumann, Lepage, & Spira, 2005).


Following the 2003 heat wave in France, many French officials were quick to blame the crises on the fragmented French family structure, as the Health Minister of the country stated that the event was a “brutal revelation of a social fracture, of the solitude and isolation of the aged.” (Crumley, 2003). While these broad social trends are important to take note of, the role of public health intervention in avoiding health disasters such as that of the 2003 European heat wave cannot be underemphasized. Some of the lessons learnt, including greater awareness and better prevention efforts were actually used in the 2006 French heat wave which had 2100 excess deaths, 4400 deaths less than anticipated by epidemiological models (Fouillet, et al., 2008).

As global warming increases the probability of catastrophic weather events including heat waves across the planet, it is critical to concentrate efforts on preparation and minimization of human casualties to the furthest extent. To do so, heat waves must be looked beyond the scope of climatological phenomena and understood in terms of physical and environmental conditions that exacerbate their adverse effects, as well as health and sociological factors that contribute to their mortalities.


Ackerman, S. A., & Knox, J. (2011). Meteorology : understanding the atmosphere. Sudbury, Mass.: Jones & Bartlett Learning.

Black, E., Blackburn, M., Harrison, G., Hoskins, B., & Methven, J. (2004). Factors contributing to the summer 2003 European heatwave. Weather, 59(8), 217-223.

Cadot, E., Rodwin, V., & Spira, A. (2007). In the Heat of the Summer. Journal of Urban Health, 84(4), 466-468.

Chase, T. N., Wolter, K., Pielke, R. A., Sr., & Rasool, I. (2006). Was the 2003 European summer heat wave unusual in a global context? Geophys. Res. Lett., 33(23), L23709.

Crumley, B. (2003). Elder Careless. Time. Retrieved from,8816,477899,00.html

D'Ippoliti, D., Michelozzi, P., Marino, C., de'Donato, F., Menne, B., Katsouyanni, K., et al. (2010). The impact of heat waves on mortality in 9 European cities: results from the EuroHEAT project. Environmental Health, 9(1), 37.

Ebi, K., & Meehl, J. (2007). The heat is on: climate change and heatwaves in the Midwest. Arlington, VA: Pew Center for Climate Change.

Fouillet, Rey, G., Laurent, F., Pavillon, G., Bellec, S., Guihenneuc-Jouyaux, C., et al. (2006). Excess mortality related to the August 2003 heat wave in France. International Archives of Occupational and Environmental Health, 80(1), 16-24.

Fouillet, Rey, G., Wagner, V., Laaidi, K., Empereur-Bissonnet, P., Le Tertre, A., et al. (2008). Has the impact of heat waves on mortality changed in France since the European heat wave of summer 2003? A study of the 2006 heat wave. International Journal of Epidemiology, 37(2), 309-317.

Holstein, J., Canouï-Poitrine, F., Neumann, A., Lepage, E., & Spira, A. (2005). Were less disabled patients the most affected by 2003 heat wave in nursing homes in Paris, France? Journal of Public Health, 27(4), 359-365.

Kilbourne, E. M. (1997). Heat Waves and Hot Environments. In E. K. Noji (Ed.), The public health consequences of disasters. New York: Oxford University Press.

Klinenberg, E. (2003). Heat wave : a social autopsy of disaster in Chicago. Chicago; London: Univ. of Chicago Press.

Poumadère, M., Mays, C., Le Mer, S., & Blong, R. (2005). The 2003 Heat Wave in France: Dangerous Climate Change Here and Now. Risk Analysis, 25(6), 1483-1494.

Rey, G., Fouillet, A., Bessemoulin, P., Frayssinet, P., Dufour, A., Jougla, E., et al. (2009). Heat exposure and socio-economic vulnerability as synergistic factors in heat-wave-related mortality. European Journal of Epidemiology, 24(9), 495-502.

Toulemon, L., & Barbieri, M. (2005). The Mortality Impact of the August 2003 Heat Wave in France. Paper presented at the XXV International Population Conference.

Vandentorren, Bretin, P., Zeghnoun, A., Mandereau-Bruno, L., Croisier, A., Cochet, C., et al. (2006). August 2003 Heat Wave in France: Risk Factors for Death of Elderly People Living at Home. The European Journal of Public Health, 16(6), 583-591.

Vandentorren, Suzan, F., Medina, S., Pascal, M., Maulpoix, A., Cohen, J.-C., et al. (2004). Mortality in 13 French Cities During the August 2003 Heat Wave. American Journal of Public Health, 94(9), 1518-1520.

Print / Share this post:
  • Print
  • Twitter
Permanent linkMarzieh Ghiasi

No responses yet

You should share your thoughts: