Climatology and Long-Term Trends in Population Exposure to Urban Heat Stress Considering Variable Demographic and Thermo–Physiological Attributes

Abstract

Previous studies assessing population exposure to heat stress have focused primarily on environmental heat loads without accounting for variations in human thermo–physiological responses to heat. A novel 30-year (1991–2020) human thermal bioclimate dataset, consisting of hourly mPET (modified physiologically equivalent temperature) values for diverse populations, was employed in the present study to assist in addressing this gap. Focusing on the Athens urban area (AUA), Greece, the climatology and long-term trends in acclimatization-based strong heat stress (accliSHS) experienced by average male and female adult and senior individuals during the warm period of the year (April–October) were investigated. Results showed that an average adult (senior) in AUA experienced, on average, approximately 13 (18) additional days with at least 1 h accliSHS in 2020 compared with 1991. The increasing rates per year were particularly pronounced for days with ≥6 h accliSHS, indicating a rise in the daily duration of heat stress in AUA from 1991 to 2020. Combining the variations in climate and demographics in AUA during the examined 30-year period, the long-term trends in ≥1 h accliSHS exposure for the study population types were further examined. This analysis revealed that seniors’ exposure to ≥1 h accliSHS in AUA increased by up to +153,000 person-days $\times$ year⁻¹ from 1991 to 2020. Increasing population aging was the main driver of this outcome, highlighting the urgent need for heat–health action planning in Greece.

1. Introduction

Anthropogenic-driven global warming and the consequent intensification of weather and climate extremes induce severe impacts on humans [1]. One of the most important climate-related threats is related to the thermal environment. Population exposure to elevated heat conditions endangers human livability and survivability, as hot weather and heatwaves are associated with adverse birth outcomes [2,3], worsened mental health [4] and sleep quality [5], limited ability to exercise, play, and work [6,7,8,9], and increased morbidity and mortality, primarily due to cardiorespiratory diseases [10,11]. These heat-related issues in turn cause a substantial economic burden on healthcare systems and various labor sectors, especially those heavily relying on an outdoor workforce [12,13].

The spatiotemporal assessment of heat stress exposure patterns in the recent past [14,15,16,17,18,19,20,21,22] and future [23,24,25,26,27,28,29,30,31,32] can provide essential guidance for targeted adaptation and action aimed at alleviating the above impacts, such as the development of early warning systems. However, previous relevant studies have not accounted for exposure to heat stress within a human–biometeorological and health-related context. Single meteorological variables (e.g., air temperature [19]) or simple composite indices (e.g., heat index (HI) [31]) were primarily used in these studies, even though the comprehensive assessment of heat stress requires considering the collective impact of all heat-related environmental drivers (i.e., temperature, humidity, wind speed, and radiation loads). Most importantly, it requires solving the human energy balance equation, integrating anthropometric data (e.g., age), clothing, and activity in addition to the above environmental variables [33,34,35,36]. Thus, even with the employment of more advanced direct indices such as outdoor wet-bulb globe temperature (WBGT; e.g., [20]), the existing literature on the topic has ignored the thermo–physiological basis of the human thermal environment.

In this article, to assist in addressing this research gap, we expand the concept of heat stress exposure assessment to account for the thermo–physiological responses of different population groups. To that end, we employed a novel 30-year (1991–2020) human thermal bioclimate dataset consisting of hourly mPET (modified physiologically equivalent temperature) values to characterize heat stress levels for diverse population types [36]. The study area was the Athens urban area (AUA) in Greece, situated in the Eastern Mediterranean. Initially, we analyzed the long-term trends in acclimatization-based strong heat stress (accliSHS) experienced by average male and female adults and senior individuals in five regional units in AUA during the warm period of the year (April–October). Emphasis was placed on accliSHS duration, which is of paramount importance in relation to adverse health outcomes [37,38,39]. Then, we computed accliSHS exposure and assessed its long-term trends for each examined demographic type and regional unit by combining the mPET estimates with population data. Contributions arising from changes in climate and population sizes were determined; these are discussed, emphasizing the differences between the targeted demographic groups and regional units in AUA.

2. Materials and Methods

2.1. Study Urban Area

AUA is situated in south Greece (Figure 1), characterized by a Mediterranean climate with hot summers. It consists of five regional units, namely North Athens, West Athens; Central Athens, Piraeus, and South Athens (Figure 1), which accommodate around three million inhabitants in total [40]. Central and West Athens feature compact built-up areas characterized by narrow streets and flat-roofed, light-colored buildings. These areas are also marked by a lack of green spaces. This urban setting description holds for much of Piraeus as well, whereas regions with a more dispersed built-up environment and an abundance of greenery are primarily located in South and North Athens [40,41]. These urban characteristics contribute to the development of prominent overheating, particularly in Central and West Athens and Piraeus [41]. The urban heat island (UHI) effect in these areas is particularly intense during the night (>4 °C; [42]), while high spatial variability characterizes the entire AUA in terms of responsiveness to heat stress [40].

Moreover, in recent decades, the climatic features of AUA have been significantly altered due to anthropogenic climate change. Specifically, increasing trends in the duration, frequency, and intensity of heat extremes have been evident, notably since 1990 [43,44,45,46], with a lengthening of the “hot extremes season” also apparent [43,45]. These changes contribute to the establishment of more stressful human bioclimatic conditions in the area [44,45,47,48,49]. Thus, significant challenges in relation to public health arise in AUA, especially when considering that the population exposed to these stressful conditions is increasingly aging [50].

2.2. Human Bioclimate and Population Data

The human bioclimate data used in the current study consisted of hourly, population-weighted mPET index values for average male and female adult and senior individuals. They spanned from 1991 to 2020 in the five regional units in AUA and focused on the warm period (April–October).

Briefly, mPET is an advanced human-biometeorological index that is intimately related to human thermal perception and stress. It is computed based on human energy balance modeling that incorporates both the environmental (air and radiant temperature, humidity, and wind speed) and personal/thermo–physiological (sex, age, height, weight, metabolic activity, and clothing coverage) factors that affect the human thermal environment [51,52]. Furthermore, the mPET thermoregulation model can be applied for different demographic and thermo-physiological attributes that correspond to the characteristics of average individuals within population sub-groups. Thus, compared with other thermal stress metrics, mPET assesses heat stress in a thermo–physiologically significant way while allowing consideration of population-wide variability in heat stress [36,39]. This means that given the same environmental conditions in each AUA regional unit, different mPET values and corresponding heat stress levels were estimated for each average individual within each targeted population type. The dataset used to extract the mPET data for the study area and populations is publicly available (https://zenodo.org/records/10893914; accessed on 1 September 2024) and has been described in more detail by Giannaros et al. [36].

The population data for each AUA regional unit were retrieved from the Hellenic Statistical Authority and Eurostat. They correspond to the 1991, 2001, 2011, and 2021 censuses, grouped by sex and age. Thus, to estimate group-specific populations for each day from 1 January 1991 to 31 December 2020, linear interpolation was applied to the censuses population counts for each targeted demographic group and AUA regional unit. Considering the relatively limited data points and the impact of the immigration outflow following the 2009 financial crisis in Greece, linear interpolation was considered to provide more robust and reliable estimates than alternative methods such as exponential or multivariate approaches [53]

2.3. Exposure Estimations and Trend Analysis

The methods used in the existing literature to define heat stress exposure are characterized by significant diversity. For example, Tuholske et al. used fixed thresholds to identify extreme heat episodes [17], whereas Dong et al. applied percentile-based criteria to define humid heatwaves [22]. Here, we focused on days with strong heat stress (SHS), following previous epidemiological (e.g., [39,54,55]) and thermo–physiological (e.g., [56,57]) evidence showing that heat-related health risks are associated with SHS exposure.

Specifically, we considered accliSHS days to account for population- and location-specific short-term acclimatization effects. The definition of accliSHS was based on variable mPET thresholds derived from adjusting the fixed SHS mPET threshold (i.e., 35 °C; [58]) according to the thermal stress conditions prevailing in the 30 days previous, specific to each population and regional unit. This was carried out through the application of a Gaussian filter with 30 significant weights, reflecting a thermo–physiologically relevant short-term (30 days) adaptation to SHS exposure [39]. This process used a formula based on the HeRATE (Health-Related Assessment of the Thermal Environment) approach [59], applied to the population-and location-specific mPET estimates (see Section 2.2). Further details, including the applied formula, can be found in Giannaros et al. [39]. Accounting for different exposure hours within a given day, we computed the annual number of days when population- and location-specific mPET values exceeded the accliSHS mPET thresholds for at least 1 h and 6 h during the warm period of the year (April–October), for each year from 1991 to 2020. Following previous studies [17,41], long-term (1991–2020) trends in the annual number of days with ≥1 h and ≥6 accliSHS for each examined population type and regional unit were assessed using an ordinary least squares (OLS) regression model. The statistical significance of trends was computed based on Student’s t-test at 95% significance level (p-value ≤ 0.05) [45,60]. Further, changes in population- and location-based multi-year numbers of days with ≥1 h and ≥ 6 accliSHS were computed. Concerning accliSHS exposure, the location- and population-specific ≥ 1 h accliSHS exposure per year was quantified in person-days $\times$ year⁻¹, based on Tuholske et al. [17]. In particular, for each year between 1991 and 2020 and for each AUA regional unit, we multiplied the annual number of days with ≥1 h accliSHS and the population size of each targeted demographic type. We then applied OLS regression to assess the long-term (1991–2020) trends in population- and location-specific ≥1 h accliSHS exposure. Finally, we referred to Tuholske et al. [17] to estimate the relative contribution shares (%) in the exposure trends arising from climate- and demographic-related changes. In more detail, the climate-related contributions were assessed in person-days $\times$ year⁻¹ by multiplying the annual number of days with ≥1 h accliSHS by the corresponding population size fixed in 1991, while the contributions of demographics were assessed in person-days $\times$ year⁻¹ by multiplying the annual number of days with ≥1h accliSHS by the corresponding annual population change since 1991. The rates of changes in these contributions were estimated by applying OLS regression. These rates were subsequently used to compute an index ([−1, 1]) indicating the relative shares (%) of the ≥1 h accliSHS exposure trends from changes in climate and population size from 1991 to 2020 (100% dominated by climate-related changes versus 100% dominated by demographic-related changes) [17].

3. Results

3.1. Trends in Annual accliSHS Days

Figure 2 illustrates the rate of change in numbers of days annually with at least one 1 h accliSHS, expressed in days $\times$ year⁻¹, for each examined population type in AUA from 1991 to 2020. Overall, an increasing trend was evident, ranging from +0.22 (for an average male adult in West Athens) to +0.78 (for an average male senior in South Athens) days $\times$ year⁻¹ with ≥1 h accliSHS, across AUA. These results were statistically significant at a 95% confidence level in all regional units, expect for the average male and female adult individuals in West Athens. For all population types, South and Central Athens demonstrated the highest increasing trends (>+0.5 days $\times$ year⁻¹), while North Athens and Piraeus were characterized by increasing trends that spanned from +0.37 to +0.55 days $\times$ year⁻¹ (Figure 2).

Regarding age-related differences, the average seniors were characterized by overall higher increasing trends in the number of days per year with ≥1 h accliSHS compared with average adults, throughout AUA. For example, the increasing trend for the average male adult in South Athens was equal to +0.67 days $\times$ year⁻¹, whereas it was equal to +0.78 days $\times$ year⁻¹ for the average male senior in the same regional unit. Similarly, the average female senior in North Athens (+0.55 days $\times$ year⁻¹) experienced a higher increase in ≥1 h accliSHS compared with the average female adult (+0.42 days $\times$ year⁻¹) by +0.13 days/year⁻¹. Sex-related differences were less evident, as the trends in increase were approximately the same for the average male and female individuals, both adults and seniors, in all AUA regional units (Figure 2).

The trends described above denote that, on average, the annual days with ≥1 h accliSHS for an average adult and senior in AUA increased by ~13 and ~18 days, respectively, within the 30-year study period (1991–2020). Specifically, the increase in the average annual number of days with ≥1 h accliSHS from early 1990s to late 2020s ranged from 4 days for an average female adult in West Athens to 12 days for the same population type in South Athens, as shown in

Table 1. Five-year average numbers of days with ≥1 h accliSHS for the examined population types in AUA regional units in early 1990s (1999–1995) and late 2010s (2016–2020).

	Demographic Type
AUA Regional Unit	Male Adult	Male Senior	Female Adult	Female Senior
North Athens	early 1990s: 94 late 2020s: 103	early 1990s: 77 late 2020s: 87	early 1990s: 99 late 2020s: 107	early 1990s: 79 late 2020s: 90
West Athens	early 1990s: 121 late 2020s: 125	early 1990s: 104 late 2020s: 112	early 1990s: 124 late 2020s: 128	early 1990s: 106 late 2020s: 114
Central Athens	early 1990s: 109 late 2020s: 119	early 1990s: 90 late 2020s: 105	early 1990s: 112 late 2020s: 122	early 1990s: 93 late 2020s: 107
Piraeus	early 1990s: 100 late 2020s: 107	early 1990s: 83 late 2020s: 94	early 1990s: 105 late 2020s: 111	early 1990s: 85 late 2020s: 95
South Athens	early 1990s: 97 late 2020s: 111	early 1990s: 81 late 2020s: 98	early 1990s: 102 late 2020s: 114	early 1990s: 83 late 2020s: 99

, corresponding to percentage increases ranging from 3.2% to 11.8%. Similar findings were evident for an average male adult, whereas the average number of days per year with accliSHS for at least 1 h increased by 7.7% (7.6%) for an average male (female) senior in West Athens and by 21% (19.2%) in South Athens from the early 1990s to the late 2010s (Table 1).

The patterns of increase in the trends outlined earlier (Figure 1) were similarly observed when focusing on annual days with ≥6 h accliSHS, as shown in Figure A1. As such, a significant contribution to the rise in the annual number of days with ≥1 h accliSHS seems to have arisen from the increased numbers of days with more than 6 h accliSHS. This indicates that AUA experienced an increase in the daily duration of accliSHS, in addition to the increase in the number of annual days with at least 1 h accliSHS, during the examined 30-year period (1991–2020). The related evidence of this became more apparent when comparing the percentage increases in the average numbers of days with ≥1 h and ≥6 h accliSHS, as shown in Table 1 and

Table A1. Five-year average numbers of days with ≥6 h accliSHS for the examined population types in AUA regional units in early 1990s (1999–1995) and late 2010s (2016–2020).

	Demographic Type
AUA Regional Unit	Male Adult	Male Senior	Female Adult	Female Senior
North Athens	early 1990s: 20 late 2020s: 23	early 1990s: 11 late 2020s: 16	early 1990s: 22 late 2020s: 27	early 1990s: 12 late 2020s: 17
West Athens	early 1990s: 33 late 2020s: 38	early 1990s: 19 late 2020s: 27	early 1990s: 38 late 2020s: 41	early 1990s: 20 late 2020s: 28
Central Athens	early 1990s: 27 late 2020s: 33	early 1990s: 15 late 2020s: 23	early 1990s: 30 late 2020s: 35	early 1990s: 16 late 2020s: 25
Piraeus	early 1990s: 23 late 2020s: 34	early 1990s: 11 late 2020s: 21	early 1990s: 26 late 2020s: 37	early 1990s: 13 late 2020s: 22
South Athens	early 1990s: 21 late 2020s: 34	early 1990s: 13 late 2020s: 21	early 1990s: 24 late 2020s: 37	early 1990s: 13 late 2020s: 21

, respectively. Indicatively, these increases ranged from 5.7% (female adult) to 13.2% (male senior) for ≥1 h accliSHS in Pireaus, whereas they ranged from 42.3% (average female adult) to 87.7% (average male senior) for ≥6 h accliSHS in the same regional unit (Table 1 and Table A1).

3.2. Trends in Annual accliSHS Exposure

Figure 3, Figure 4, Figure A2 and Figure A3 show the 1991–2020 trends in ≥1 h accliSHS exposure and in climate- and demographic-related changes for the examined demographic types in the five AUA regional units. The warming referenced in the first column of plots refers to the increasing trend in annual ≥ 1 h accliSHS person-days $\times$ year⁻¹, similar to the growing numbers of annual ≥ 1 h accliSHS days per year documented in Section 3.1. The population sizes stated in the second column of plots may be associated with an increasing or decreasing trend, expressed in person-days $\times$ year⁻¹ (Figure 3, Figure 4, Figure A2 and Figure A3). The warming and population size trends both contribute to the population- and location-specific ≥ 1 h accliSHS exposure trends, illustrated in person-days $\times$ year⁻¹ in the third column of plots in Figure 3, Figure 4, Figure A2 and Figure A3. For adults (Figure 3 and Figure A2), the demographic changes exhibit parabolic shapes due to the population increase from 1991 to 2000 and the subsequent population decrease since 2000, which was particularly pronounced after 2010. As such, the population size trends in Figure 3 and Figure A2 indicate the general direction of the demographic shifts from 1991 to 2020, indicating an overall decrease in the AUA adult population, except in North Athens, during the examined 30-year period. This overall decreasing trajectory in population size was more noticeable in Central Athens, as indicated by the steeper trend slopes (−462,000 person-days $\times$ year⁻¹ for male adults and −620,000 person-days $\times$ year⁻¹ for female adults). As a result, the ≥1 h accliSHS exposure of adults in this regional unit was reduced (−253,000 person-days $\times$ year⁻¹ for male adults and −396,000 person-days $\times$ year⁻¹ for female adults), despite the significant warming the Central Athens experienced (+209,000 person-days $\times$ year⁻¹ for male adults and +224,000 person-days $\times$ year⁻¹ for female adults). On the other hand, the overall decline in the adult population in the other AUA regional units after 2000 was less evident. This fact, combined with warming in these areas (see also Section 3.1), resulted primarily in increases in ≥1 h accliSHS exposure for adults, ranging from +21,000 person-days $\times$ year⁻¹ (West Athens) to +139,000 person-days $\times$ year⁻¹ (North Athens) for female adults and from +23,000 person-days $\times$ year⁻¹ (Piraeus) to +75,000 person-days $\times$ year⁻¹ (North Athens) for male adults (Figure 3 and Figure A2).

For seniors, the results of the present analysis are clearer. All AUA regional units experienced warming (see also Section 3.1). Additionally, all examined areas were characterized by an increasingly elderly population, including both males and females, although this increase was less evident in Central Athens. Combined, these trends led to significant increases in seniors’ exposure to ≥1 h accliSHS across the AUA. These values ranged from +64,000 person-days $\times$ year⁻¹ (Piraeus) to +109,000 person-days $\times$ year⁻¹ (North Athens) for male seniors, while the highest increase in exposure was evident for female seniors, surpassing +100,000 person-days $\times$ year⁻¹ in most regional units and reaching up to +153,000 person-days $\times$ year⁻¹ in North Athens. This outcome was primarily driven by greater increases in the elderly female population compared with elderly males. Indicatively, the exposure of female and male adults in South Athens to at least 1 h accliSHS grew by +136,000 person-days $\times$ year⁻¹ and +97,000 person-days $\times$ year−1, respectively. Warming contributed almost equally to these trends for both sexes (+19,000 person-days $\times$ year⁻¹ for females and +25,000 person-days $\times$ year⁻¹ for males), whereas population size changes contributed by +111,000 person-days $\times$ year⁻¹ and +78,000 person-days $\times$ year⁻¹ for females and males, respectively (Figure 4 and Figure A3).

The above contributions are summarized in Figure 5, which illustrates the relative contribution shares (%) in the 30-year (1991–2020) trends in exposure to ≥1 h accliSHS for the examined populations in AUA. Specifically, the decreasing trends in exposure for male and female adults in Central Athens (Figure 3 and Figure A2) were driven by the population decline by ~37.7% and ~46.9%, respectively (Figure 5a,c). In contrast, the increase in exposure for male adults in North and South Athens and Piraeus and for female adults in North, West, and South Athens was attributed primarily to warming (Figure 3 and Figure A2), with relative contribution shares ranging from ~20.9% in Piraeus to ~92.2% in North Athens for female adults and from ~8.1% in North Athens to ~78.3% in South Athens for male adults (Figure 5a,c). For seniors, the increase in the size of their population contributed more than 60% to the exposure of both males and females in North, West, and South Athens and Piraeus to at least 1 h accliSHS. The highest value in these relative contribution shares (~82.9%) was found for female seniors in West Athens (Figure 4, Figure 5b,d, and Figure A3). On the other hand, warming primarily drove the exposure of seniors in Central Athens to ≥1 h accliSHS (Figure 5b,d), as an outcome of the less pronounced increase in the elderly population in this area (Figure 4 and Figure A3). Indicatively, warming contributed by ~28.8% to the increase in ≥1 h accliSHS exposure for male seniors in Central Athens (Figure 5b,d).

4. Discussion

In the present study, we assessed the climatology and long-term (1991–2020) trends in population exposure to heat stress, considering population-wide variability in heat stress and short-term acclimatization effects. This was achieved by employing a novel human thermal bioclimate dataset containing hourly values of an advanced human-biometeorological index, namely mPET, for diverse demographic types [36]. We specifically focused on acclimatization-based SHS experienced by average male and female adult and senior individuals living in AUA, Greece, which is of particular interest with respect to heat-related issues due to the dangerous confluence of accelerated warming [61] and increased population ageing [50] in the region. The definition of aclliSHS was based on variable mPET thresholds, thus accounting for population- and location-specific short-term thermo–physiological adaptation to heat, which is critical with respect to the occurrence of heat-related health effects [39].

The first-stage climatological analysis showed that days with at least 1 h aclliSHS constitute a common feature during the warm period of the year (April–October) in the study area. This was expected because of the hot summers in the Mediterranean climate of AUA [40]. An average adult in particular, may have been exposed to around 100 days with ≥1 h accliSHS in the early 1990s (Table 1). For an average senior, the number of days with ≥1 h accliSHS were lower overall (~85 in early 1990s; Table 1), because of the reduced physical activity assumed in the mPET computations for this population [36,39], consistent with the metabolic activity rates of elderly people under hot environmental conditions [62,63]. However, it is interesting that higher increasing trends (1991–2020) in days with ≥1 h accliSHS were documented for the average senior compared with the average adult across AUA (Figure 1). Given the significant warming and other thermal-related changes between 1991 and 2020 in the greater study area (e.g., [45,46,64,65]), this outcome indicates that thermo–physiologically it is more difficult for seniors to cope with the increasing heat stress conditions induced by climate change. Indeed, the human body’s capacity to dissipate heat decreases as age increases [62].

Overall, the upward trends observed in our study in relation to the annual numbers of days with at least 1 h accliSHS in AUA are in accordance with previous similar studies in the area [43,47,48,49]. Regional differences in these trends are driven by geomorphological features and background atmospheric circulations that affect the thermal environment in AUA [40]. Furthermore, high rates of increase were particularly evident for days when mPET values for the examined demographic types exceeded the accliSHS threshold by more than 6 h, indicating a rise from 1991 to 2020 in the daily duration of heat stress in AUA, in agreement with previous research [49]. We focused on ≥ 6 h accliSHS because prolonged exposure to strong heat stress during the day is an important determinant for adverse health outcomes [39]. Thus, the increase greater than 8% in the average annual number of days with ≥6 h accliSHS (over 40% for an average senior; Table A1) is a particularly concerning outcome.

The significance of this outcome is heightened when it is considered alongside the increase in the elderly population from 1991 to 2020 (Figure 3, Figure 4, Figure A2 and Figure A3). This combination resulted in increases in seniors’ exposure to ≥1 h accliSHS across AUA that reached up to +153,000 person-days $\times$ year⁻¹ for female seniors in North Athens (Figure A3). The relevant outcomes for adults were more varied (Figure 3 and Figure 4), driven by population decline in Central Athens and primarily by warming in the rest of the examined AUA regional units (Figure 5). These varying contributions to the trends in ≥1 h accliSHS exposure reflect the urban and population expansion in suburban areas, particularly in North Athens [41], as well as the immigration wave associated with the outbreak of the financial crisis in Greece in 2009 [66].

5. Concluding Remarks

In this study, we expanded on existing heat stress exposure research by incorporating thermo–physiological principles through the use of an advanced human-biometeorological index, namely mPET. This approach allowed us to account for the variability in human thermoregulation responses, including those related to short-term acclimatization. As a result, we were able to provide a more nuanced and realistic assessment of the heat stress experienced by different population sub-groups. We demonstrated this novel technique in AUA, Greece, focusing on accliSHS. This research revealed increases in annual accliSHS days in the study area from 1991 to 2020 (i.e., warming). These trends, which were particularly pronounced for prolonged accliSHS exposure exceeding 6 h, pose significant thermo–physiological challenges for senior individuals. Furthermore, combined with the increase in size of the elderly population in AUA, these trends have led to a substantial and concerning increase in seniors’ accliSHS exposure over the past 30 years (1991–2020). Changes in population size linked to socioeconomic factors, such as urban expansion in northern AUA suburbs and the 2009 financial crisis in Greece, also contributed to the accliSHS exposure trends for adults, which showed both increases and decreases from 1991 to 2020. These findings underscore the multi-faceted nature of heat stress exposure, influenced by both climate change and demographic shifts [15,17,19,21,22]. Given the significant health risks associated with heat stress exposure, the current study’s findings also underscore the urgent need for heat–health action planning [67,68,69], as it is likely that continuation or intensification of the presented increasing trends in accliSHS in AUA, particularly for seniors, will amplify the burden on Greece’s healthcare system.