The impact of heat waves on daily mortality in districts in Madrid: The effect of sociodemographic factors

Human adaptation to heat in the context of climate change: A conceptual framework

Climate change is causing serious damage to natural and social systems, as well as having an impact on human health. Among the direct effects of climate change is the rise in global surface temperatures and the increase in the frequency, duration, intensity and severity of heat waves. In addition, understanding of the adaptation process of the exposed population remains limited, posing a challenge in accurately estimating heat-related morbidity and mortality. In this context, this study seeks to establish a conceptual framework that would make it easier to understand and organise knowledge about human adaptation to heat and the factors that may influence this process. An inductive approach based on grounded theory was used, through the analysis of case studies connecting concepts. The proposed conceptual framework is made up of five components (climate change, vulnerability, health risks of heat, axes of inequality and health outcomes), three heat-adaptation domains (physiological, cultural and political), two levels (individual and social), and the pre-existing before a heat event. The application of this conceptual framework facilitates the assistance of decision-makers in planning and implementing effective adaptation measures. Recognizing the importance of addressing heat adaptation as a health problem that calls for political solutions and social changes. Accordingly, this requires a multidisciplinary approach that would foster the participation and collaboration of multiple actors for the purpose of proposing effective measures to address the health impact of the rise in temperature.

Spatial contrasts and temporal changes in fine-scale heat exposure and vulnerability in the Paris region

Heat is identified as a key climate risk in Europe. Vulnerability to heat can be aggravated by enhanced exposure (e.g., urban heat island), individual susceptibility (e.g., age, income), and adaptive capacity (e.g., home ownership, presence of vegetation). We investigated the spatial and temporal patterns of the environmental and social drivers of vulnerability to heat in the Paris region, France, over the 2000-2020 period, and their association with mortality (restricted to 2000-2017). Daily temperatures were modeled for the 5265 IRIS of the Paris region for 2000-2020. Annual land use and socioeconomic data were collected for each IRIS. They were used to identify a priori five classes of heat-vulnerable areas based on a cluster analysis. The temperature-mortality relationship was investigated using a time-series approach stratified by clusters of vulnerability. The Paris region exhibited a strong urban heat island effect, with a marked shift in temperature distributions after 2015. The clustering suggested that the most heat-vulnerable IRIS in the Paris region have a high or very high exposure to temperature in a highly urbanized environment with little vegetation, but are not systematically associated with social deprivation. A similar J-shape temperature-mortality relationship was observed in the five clusters. Between 2000 and 2017, around 8000 deaths were attributable to heat, 5600 of which were observed in the most vulnerable clusters. Vulnerability assessments based on geographical indicators are key tools for urban planners and decision-makers. They complement the knowledge about individual risk factors but should be further evaluated through interdisciplinary collaborations.

Net impact of air conditioning on heat-related mortality in Japanese cities

BACKGROUND

Air conditioning (AC) presents a viable means of tackling the ill-effects of heat on human health. However, AC releases additional anthropogenic heat outdoors, and this could be detrimental to human health, especially in urban communities. This study determined the excess heat-related mortality attributable to anthropogenic heat from AC use under various projected global warming scenarios in seven Japanese cities. The overall protection from AC use was also measured.

METHODS

Daily average 2-meter temperatures in the hottest month of August from 2000 to 2010 were modeled using the Weather Research and Forecasting (WRF) model with BEP+BEM (building effect parameterization and building energy model). Risk functions for heat-mortality associations were generated with and without AC use from a two-stage time series analysis. We coupled simulated August temperatures and heat-mortality risk functions to estimate averted deaths and unavoidable deaths from AC use.

RESULTS

Anthropogenic heat from AC use slightly augmented the daily urban temperatures by 0.046 °C in Augusts of 2000-2010 and up to 0.181 °C in a future with 3 °C urban warming. This temperature rise was attributable to 3.1-3.5 % of heat-related deaths in Augusts of 2000-2010 under various urban warming scenarios. About 36-47 % of heat-related deaths could be averted by air conditioning use under various urban warming scenarios.

DISCUSSION

AC has a valuable protective effect from heat despite some unavoidable mortality from anthropogenic heat release. Overall, the use of AC as a major adaptive strategy requires careful consideration.

Exploratory analysis of local extreme-temperature attributable mortality in an urban city of Madrid

AIM

to assess the Heat (HW) and Cold Waves (CW) risks on health in the urban municipality of Getafe.

METHODOLOGY

time series analysis between 01/01/1999-31/10/2013.

DEPENDENT VARIABLE

daily mortality due to natural causes - (ICD-10): A99-R99-.

INDEPENDENT VARIABLES

the maximum (Tmax) and minimum (Tmin) daily temperature. The mortality-temperature relationship was analysed to determine the thresholds of HW (Thresholdheat) and CW (Thresholdcold). Using Poisson GLM (link = log), the Relative Risk (RR), Attributable Risk (AR) and Attributable Mortality (AM) were determined for each degree of the Tmax exceeding the Thresholdheat (Theat) and for each degree of Tmin under the Thresholdcold (Tcold). Finally, socioeconomic variables were analysed descriptively.

RESULTS

Thresholdheat was 36 °C while Thresholdcold was 0 °C. The RRs associated with Theat, i.e. 1.08 (1.03 1.14), are akin to those obtained for Tcold, i.e. 1.05 (1.03 1.08). There were 202 HW and 430 CW episodes. The AM to HW totalled 61 (25, 96) deaths, while that attributable to CW reached 146 (82,211) deaths. The vulnerability in Getafe seems to be lower than in surrounding similar urban and rural cities.

CONCLUSIONS

The singular urban development of the municipality may have granted it an advantage over surrounding municipalities regarding temperature extremes.

Heat-related first cardiovascular event incidence in the city of Madrid (Spain): Vulnerability assessment by demographic, socioeconomic, and health indicators

While climate change and population ageing are expected to increase the exposure and vulnerability to extreme heat events, there is emerging evidence suggesting that social inequalities would additionally magnify the projected health impacts. However, limited evidence exists on how social determinants modify heat-related cardiovascular morbidity. This study aims to explore the association between heat and the incidence of first acute cardiovascular event (CVE) in adults in Madrid between 2015 and 2018, and to assess how social context and other individual characteristics modify the estimated association. We performed a case-crossover study using the individual information collected from electronic medical records of 6514 adults aged 40-75 living in Madrid city that suffered a first CVE during summer (June-September) between 2015 and 2018. We applied conditional logistic regression with a distributed lag non-linear model to analyse the heat-CVE association. Estimates were expressed as Odds Ratio (OR) for extreme heat (at 97.5th percentile of daily maximum temperature distribution), compared to the minimum risk temperature. We performed stratified analyses by specific diagnosis, sex, age (40-64, 65-75), country of origin, area-level deprivation, and presence of comorbidities. Overall, the risk of suffering CVE increased by 15.3% (OR: 1.153 [95%CI 1.010-1.317]) during extreme heat. Males were particularly more affected (1.248, [1.059-1.471]), vs 1.039 [0.810-1.331] in females), and non-Spanish population (1.869 [1.28-2.728]), vs 1.084 [0.940-1.250] in Spanish). Similar estimates were found by age groups. We observed a dose-response pattern across deprivation levels, with larger risks in populations with higher deprivation (1.228 [1.031-1.462]) and almost null association in the lowest deprivation group (1.062 [0.836-1.349]). No clear patterns of larger vulnerability were found by presence of comorbidity. We found that heat unequally increased the risk of suffering CVE in adults in Madrid, affecting mainly males and deprived populations. Local measures should pay special attention to vulnerable populations.

Short-term effects of air pollution and noise on emergency hospital admissions in Madrid and economic assessment

INTRODUCTION

The aim of this study was to study the effect of air pollution and noise has on the population in Madrid Community (MAR) in the period 2013-2018, and its economic impact.

METHODS

Time series study analysing emergency hospital admissions in the MAR due to all causes (ICD-10: A00-R99), respiratory causes (ICD-10: J00-J99) and circulatory causes (ICD-10: I00-I99) across the period 2013-2018. The main independent variables were mean daily PM_2.5, PM₁₀, NO₂, 8-h ozone concentrations, and noise. We controlled for meteorological variables, Public Holidays, seasonality, and the trend and autoregressive nature of the series, and fitted generalised linear models with a Poisson regression link to ascertain the relative risks and attributable risks. In addition, we made an economic assessment of these hospitalisations.

RESULTS

The following associations were found: NO₂ with admissions due to natural (RR: 1.007, 95% CI: 1.004-1.011) and respiratory causes (RR: 1.012, 95% CI: 1.005-1.019); 8-h ozone with admissions due to natural (RR: 1.049, 95% CI: 1.014-1.046) and circulatory causes (RR: 1.088, 95% CI: 1.039-1.140); and diurnal noise (L_Aeq7-23h) with admissions due to natural (RR: 1.001, 95% CI: 1.001-1.002), respiratory (RR: 1.002, 95% CI: 1.001-1.003) and circulatory causes (RR: 1.003, 95% CI: 1.002-1.005). Every year, a total of 8246 (95% CI: 4580-11,905) natural-cause admissions are attributable to NO₂, with an estimated cost of close on €120 million and 5685 (95% CI: 2533-8835) attributed to L_Aeq7-23h with an estimated cost of close on €82 million.

CONCLUSIONS

Nitrogen dioxide, ozone and noise are the main pollutants to which a large number of hospitalisations in the MAR are attributed, and are thus responsible for a marked deterioration in population health and high related economic impact.

Heat wave adaptation paradigm and adaptation strategies of community: A qualitative phenomenological study in Iran

BACKGROUND

Heat wave adaptation is a new concept related to experiencing heat. The present study aims at investigating a conceptual definition, that is, the mental framework of heat wave adaptation and its strategies.

MATERIALS AND METHODS

A phenomenological study was performed to explain the mental concept. At the same time with the data collection process, data analysis was also performed using Colaizzi method. Semi-structured interview method and purposeful sampling with maximum variety were used. Interviews were conducted with 23 different subjects in the community. The accuracy of the data was guaranteed using Lincoln & Guba scientific accuracy criteria.

RESULTS

The two main themes of the adaptation paradigm as well as its strategies were divided into the main categories of theoretical and operational concepts, as well as personal care measures and government measures. Under the category of individual measures, we obtained "clothing, nutrition, building, place of residence and lifestyle," and under the category of governance actions, the "managerial, research, health, organizational" subcategories were obtained.

CONCLUSION

According to the results of the conceptual-operational definition, heat wave adaptation is an active process and an effort to reduce the adverse effects of heat waves on individual and social life, and striking a balance that will not only result in individual awareness and actions that will lead to lifestyle changes, but also mostly requires integrated and comprehensive planning in the community. On the one hand, heat waves could not only be regarded as a threat or danger, but can also become an opportunity for the development of a community through identification and smart measures, and for adaptation, the community must take it as a risk. The community should have a plan in advance, apply the necessary rules and training, and use the new facilities and rules where necessary. This practical concept definition includes the main features of heat wave adaptation.

Population vulnerability to extreme cold days in rural and urban municipalities in ten provinces in Spain

BACKGROUND

The objective was to analyze whether there are differences in vulnerability to Extreme Cold Days (ECD) between rural and urban populations in Spain.

METHODOLOGY

Time series analysis carried out from January 1, 2000, through December 31, 2013. Municipalities with over 10,000 inhabitants were included from 10 Spanish provinces, classified into 42 groups by isoclimate and urban/rural character as defined by Eurostat criteria. The statistical strategy was carried out in two phases. First: It was analyzed the relationship between minimum daily temperature (Tmin) (source: AEMET) and the rate of daily winter mortality due to natural causes -CIE-10: A00 - R99- (source: National Statistics Institute). Then, It was determinated the threshold of Tmin that defines the ECD and its percentile in the series of winter Tmin (Pthreshold), which is a measure of vulnerability to ECD so that the higher the percentile, the higher the vulnerability. Second: possible explanatory variables of vulnerability were explored using Mixed Generalized Models, using 13 independent variables related to meteorology, environment, socioeconomics, demographics and housing quality.

RESULTS

The average Pthreshold was 18 %. The final model indicated that for each percentage point increase in unemployment, the vulnerability to ECD increased by 0.4 (0.2, 0.6) points. Also, with each point increase in rurality index, this vulnerability decreased by -6.1 (-2.1, -10.0) points. Although less determinant, other factors that could contribute to explaining vulnerability at the province level included minimum winter daily temperatures and the percentage of housing with poor insulation.

CONCLUSIONS

The vulnerability to ECD was greater in urban zones than in rural zones. Socioeconomic status is a key to understanding how this vulnerability is distributed. These results suggest the need to implement public health prevention plans to address ECD at the state level. These plans should be based on threshold temperatures determined at the smallest scale possible.

Gender differences in adaptation to heat in Spain (1983-2018)

In Spain the average temperature has increased by 1.7 °C since pre-industrial times. There has been an increase in heat waves both in terms of frequency and intensity, with a clear impact in terms of population health. The effect of heat waves on daily mortality presents important territorial differences. Gender also affects these impacts, as a determinant that conditions social inequalities in health. There is evidence that women may be more susceptible to extreme heat than men, although there are relatively few studies that analyze differences in the vulnerability and adaptation to heat by sex. This could be related to physiological causes. On the other hand, one of the indicators used to measure vulnerability to heat in a population and its adaptation is the minimum mortality temperature (MMT) and its temporal evolution. The aim of this study was to analyze the values of MMT in men and women and its temporal evolution during the 1983-2018 period in Spain's provinces. An ecological, longitudinal retrospective study was carried out of time series data, based on maximum daily temperature and daily mortality data corresponding to the study period. Using cubic and quadratic fits between daily mortality rates and the temperature, the minimum values of these functions were determined, which allowed for determining MMT values. Furthermore, we used an improved methodology that provided for the estimation of missing MMT values when polynomial fits were inexistent. This analysis was carried out for each year. Later, based on the annual values of MMT, a linear fit was carried out to determine the rate of evolution of MMT for men and for women at the province level. Average MMT for all of Spain's provinces was 29.4 °C in the case of men and 28.7 °C in the case of women. The MMT for men was greater than that of women in 86 percent of the total provinces analyzed, which indicates greater vulnerability among women. In terms of the rate of variation in MMT during the period analyzed, that of men was 0.39 °C/decade, compared to 0.53 °C/decade for women, indicating greater adaptation to heat among women, compared to men. The differences found between men and women were statistically significant. At the province level, the results show great heterogeneity. Studies carried out at the local level are needed to provide knowledge about those factors that can explain these differences at the province level, and to allow for incorporating a gender perspective in the implementation of measures for adaptation to high temperatures.

Analysis of vulnerability to heat in rural and urban areas in Spain: What factors explain Heat's geographic behavior?

INTRODUCTION

There is currently little knowledge and few published works on the subject of vulnerability to heat in rural environments at the country level. Therefore, the objective of this study was to determine whether rural areas are more vulnerable to extreme heat than urban areas in Spain. This study aimed to analyze whether a pattern of vulnerability depends on contextual, environmental, demographic, economic and housing variables.

METHODS

An ecological, longitudinal and retrospective study was carried out based on time series data between January 01, 2000 and December 31, 2013 in 42 geographic areas in 10 provinces in Spain. We first analyzed the functional relationship between the mortality rate per million inhabitants and maximum daily temperature (Tmax). We then determined the summer temperature threshold (Pthreshold) (June-September) at which increases in mortality are produced that are attributable to heat. In a second phase, based on Pthreshold, a vulnerability variable was calculated, and its distribution was analyzed using mixed linear models from the Poisson family (link = log). In these models, the dependent variable was vulnerability, and the independent variables were exposure to high temperatures, aridity of the climate, deprivation index, percentage of people over age 65, rurality index, percentage of housing built prior to 1980 and condition of dwellings.

RESULTS

Rurality was a protective factor, and vulnerability in urban areas was six times greater. In contrast, risk factors included aridity (RR = 5.89 (2.26 15.36)), living in cool summer zones (2.69 (1.23, 5.91)), poverty (4.05 (1.91 8.59)) and the percentage of dysfunctional housing (1.13 (1.04 1.24)).

CONCLUSIONS

Rural areas are less vulnerable to extreme heat than the urban areas analyzed. Also, population groups with worse working conditions and higher percentages of dwellings in poor conditions are more vulnerable.

Sensitivities of heat-wave mortality projections: Moving towards stochastic model assumptions

This paper analyses the probabilistic future behaviour of heat-waves (HWs) in the city of Madrid in the twenty-first century, using maximum daily temperatures from twenty-one climate circulation models under two representative concentration pathways (RCP 8.5 & RCP 4.5). HWs are modelled considering three factors: number per annum, duration and intensity, characterised by three stochastic processes: Poisson, Gamma and truncated Gaussian, respectively. Potential correlations between these processes are also considered. The probabilistic temperature behaviour is combined with an epidemiological model with stochastic mortality risk following a generalized extreme value distribution (gev). The objective of this study is to obtain probability distributions of mortality and risk measures such as the mean value of the 5% of worst cases in the 21st century, in particular from 2025 to 2100. Estimates from stochastic models for characterising HWs and epidemiological impacts on human health can vary from one climate model to another, so relying on a single climate model can be problematic. For this reason, the calculations are carried out for 21 models and the average of the results is obtained. A sensitivity adaptation analysis is also performed. Under RCP 8.5 for 2100 for Madrid city a mean excess of 3.6 °C over the 38 °C temperature threshold is expected as the average of all models, with an expected attributable mortality of 1614 people, but these figures may be substantially exceeded in some cases if the highest-risk cases occur.

Temporal trends of the association between temperature variation and hospitalizations for schizophrenia in Hefei, China from 2005 to 2019: a time-varying distribution lag nonlinear model

Along with climate change, unstable weather patterns are becoming more frequent. However, the temporal trend associated with the effect of temperature variation on schizophrenia (SCZ) is not clear. Daily time-series data on SCZ and meteorological factors for 15-year between January 1, 2005 and December 31, 2019 were collected. And we used the Poisson regression model combined with the time-varying distribution lag nonlinear model (DLNM) to explore the temporal trend of the association between three temperature variation indicators (diurnal temperature range, DTR; temperature variability, TV; temperature change between neighboring days, TCN) and SCZ hospitalizations, respectively. Meanwhile, we also explore the temporal trend of the interaction between temperature and temperature variation. Stratified analyses were performed in different gender, age, and season. Across the whole population, we found a decreasing trend in the risk of SCZ hospitalizations associated with high DTR (from 1.721 to 1.029), TCN (from 1.642 to 1.066), and TV (TV0-1, from 1.034 to 0.994; TV0-2, from 1.041 to 0.994, TV0-3, from 1.044 to 0.992, TV0-4, from 1.049 to 0.992, TV0-5, from 1.055 to 0.993, TV0-6, from 1.059 to 0.991, TV0-7, from 1.059 to 0.990), but an increasing trend in low DTR (from 0.589 to 0.752). Subgroup analysis results further revealed different susceptible groups. Besides, the interactive effect suggests that temperature variation may cause greater harm under low-temperature conditions. There was a synergy between TCN and temperature on the addition and multiplication scales, which were 1.068 (1.007, 1.133) and 0.067 (0.009, 0.122), respectively. Our findings highlight public health interventions to mitigate temperature variation effects needed to focus not only on high temperature variations but also moderately low temperature variations. Future hospitalizations for SCZ associated with temperature variation may be more severely affected by temperature variability from low temperature environments. The temporal trend is associated with the effect of temperature variation on schizophrenia (SCZ).

Evolution of the minimum mortality temperature (1983-2018): Is Spain adapting to heat?

The objective of this study was to analyze at the level of Spain's 52 provinces province level the temporal evolution of minimum mortality temperatures (MMT) from 1983 to 2018, in order to determine whether the increase in MMT would be sufficient to compensate for the increase in environmental temperatures in Spain for the period. It also aimed to analyze whether the rate of evolution of MMT would be sufficient, were it to remain constant, to compensate for the predicted increase in temperatures in an unfavorable (RCP 8.5) emissions scenario for the time horizon 2051-2100. The independent variable was made up of maximum daily temperature data (Tmax) for the summer months in the reference observatories of each province for the 1983-2018 period. The dependent variable was daily mortality rate due to natural causes (ICD 10: A00-R99). For each year and province, MMT was determined using a quadratic or cubic fit (p < 0.05). Based on the annual MMT values, a linear fit was carried out that allowed for determining the time evolution of MMT. These values were compared with the evolution of Tmax registered in each observatory during the 1983-2018 analyzed period and with the predicted values of Tmax obtained for an RCP8.5 scenario for the period 2051-2100. The rate of global variance in Tmax in the summer months in Spain during the 1983-2018 period was 0.41 °C/decade, while MMT across the whole country increased at a rate of 0.64 °C/decade. Variations in the provinces were heterogeneous. For the 2051-2100 time horizon, there was predicted increase in Tmax values of 0.66 °C/decade, with marked geographical differences. Although at the global level it is possible to speak of adaptation, the heterogeneities among the provinces suggest that the local level measures are needed in order to facilitate adaptation in those areas where it is not occurring.

Evolution of the minimum mortality temperature (1983-2018): Is Spain adapting to heat?

The objective of this study was to analyze at the level of Spain's 52 provinces province level the temporal evolution of minimum mortality temperatures (MMT) from 1983 to 2018, in order to determine whether the increase in MMT would be sufficient to compensate for the increase in environmental temperatures in Spain for the period. It also aimed to analyze whether the rate of evolution of MMT would be sufficient, were it to remain constant, to compensate for the predicted increase in temperatures in an unfavorable (RCP 8.5) emissions scenario for the time horizon 2051-2100. The independent variable was made up of maximum daily temperature data (Tmax) for the summer months in the reference observatories of each province for the 1983-2018 period. The dependent variable was daily mortality rate due to natural causes (ICD 10: A00-R99). For each year and province, MMT was determined using a quadratic or cubic fit (p < 0.05). Based on the annual MMT values, a linear fit was carried out that allowed for determining the time evolution of MMT. These values were compared with the evolution of Tmax registered in each observatory during the 1983-2018 analyzed period and with the predicted values of Tmax obtained for an RCP8.5 scenario for the period 2051-2100. The rate of global variance in Tmax in the summer months in Spain during the 1983-2018 period was 0.41 °C/decade, while MMT across the whole country increased at a rate of 0.64 °C/decade. Variations in the provinces were heterogeneous. For the 2051-2100 time horizon, there was predicted increase in Tmax values of 0.66 °C/decade, with marked geographical differences. Although at the global level it is possible to speak of adaptation, the heterogeneities among the provinces suggest that the local level measures are needed in order to facilitate adaptation in those areas where it is not occurring.

Heat-related mortality under climate change and the impact of adaptation through air conditioning: A case study from Thessaloniki, Greece

Climate change is expected to increase heat-related mortality across the world. Health Impact Assessment (HIA) studies are used to quantify the impact of higher temperatures, taking into account the effect of population adaptation. Although air-conditioning (AC) is one of the main drivers of technological adaptation to heat, the health impacts associated with AC-induced air pollution have not been examined in detail. This study uses the city of Thessaloniki, Greece as a case study and aims to estimate the future heat-related mortality, the residential cooling demand, and the adaptation trade-off between averted heat-related and increased air pollution cardiorespiratory mortality. Using temperature and population projections under different Coupled Model Intercomparison Project Phase 6 (CIMP6) Shared Socioeconomic Pathways scenarios (SSPs), a HIA model was developed for the future heat and air pollution cardiorespiratory mortality. Counterfactual scenarios of either black carbon (BC) or natural gas (NG) being the fuel source for electricity generation were included in the HIA. The results indicate that the heat-related cardiorespiratory mortality in Thessaloniki will increase and the excess of annual heat-related deaths in 2080-2099 will range from 2.4 (95% CI: 0.0-20.9) under SSP1-2.6 to 433.7 (95% CI: 66.9-1070) under SSP5-8.5. Population adaptation will attenuate the heat-related mortality, although the latter may be counterbalanced by the higher air pollution-related mortality due to increased AC, especially under moderate SSP scenarios and coal-fired power plants. Future studies examining the health effects of warmer temperatures need to account for the impact of both adaptation and increased penetration and use of AC.

Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death

The geographical distribution of mortality has frequently been studied. Nevertheless, those studies often consider isolated causes of death. In this work, we aim to study the geographical distribution of mortality in urban areas, in particular, in 26 Spanish cities. We perform an overall study of 16 causes of death, considering that their geographical patterns could be dependent and estimating the dependence between the causes of death. We study the deaths in these 26 cities during the period 1996-2015 at the census tract level. A multivariate disease mapping model is used in order to solve the potential small area estimation problems that these data could show. We find that most of the geographical patterns found show positive correlations. This suggests the existence of a transversal geographical pattern, common to most causes of deaths, which determines those patterns to a higher/lower extent depending on each disease. The causes of death that exhibit that underlying pattern in a more prominent manner are chronic obstructive pulmonary disease (COPD), lung cancer, and cirrhosis for men and cardiovascular diseases and dementias for women. Such findings are quite consistent for most of the cities in the study. The high positive correlation found between geographical patterns reflects the existence of both high and low-risk areas in urban settings, in general terms for nearly all the causes of death. Moreover, the high-risk areas found often coincide with neighborhoods known for their high deprivation. Our results suggest that dependence among causes of death is a key aspect to be taken into account when mapping mortality, at least in urban contexts.

Analysis of the impact of heat waves on daily mortality in urban and rural areas in Madrid

The objective of this study was to analyze and compare the effect of high temperatures on daily mortality in the urban and rural populations in Madrid. Data were analyzed from municipalities in Madrid with a population of over 10,000 inhabitants during the period from January 1, 2000 to December 31, 2020. Four groups were generated: Urban Metropolitan Center, Rural Northern Mountains, Rural Center, and Southern Rural. The dependent variable used was the rate of daily mortality due to natural causes per million inhabitants (CIE-X: A00-R99) between the months of June and September for the period. The primary independent variable was maximum daily temperature. Social and demographic "context variables" were included: population >64 years of age (%), deprivation index and housing indicators. The analysis was carried out in three phases: 1) determination of the threshold definition temperature of a heat wave (Tumbral) for each study group; 2) determination of relative risks (RR) attributable to heat for each group using Poisson linear regression (GLM), and 3) calculation of odds ratios (OR) using binomial family GLM for the frequency of the appearance of heat waves associated with context variables. The resulting percentiles (for the series of maximum daily temperatures for the summer months) corresponding to Tthreshold were: 74th percentile for Urban Metropolitan Center, 76th percentile for Southern Rural, 83rd for Rural Northern Mountains and 98th percentile for Center Rural (98). Greater vulnerability was found for the first two. In terms of context variables that explained the appearance of heat waves, deprivation index level, population >64 years of age and living in the metropolitan area were found to be risk factors. Rural and urban areas behaved differently, and socioeconomic inequality and the composition of the population over age 64 were found to best explain the vulnerability of the Rural Center and Southern Rural zones.

Analysis on Effectiveness of Impact Based Heatwave Warning Considering Severity and Likelihood of Health Impacts in Seoul, Korea

Many countries are operating a heatwave warning system (HWWS) to mitigate the impact of heatwaves on human health. The level of heatwave warning is normally determined by using the threshold temperature of heat-related morbidity or mortality. However, morbidity and mortality threshold temperatures have not been used together to account for the severity of health impacts. In this study, we developed a heatwave warning system with two different warning levels: Level-1 and Level-2, by analyzing the severity and likelihood of heat-related morbidity and mortality using the generalized additive model. The study particularly focuses on the cases in Seoul, South Korea, between 2011 and 2018. The study found that the threshold temperature for heat-related morbidity and mortality are 30 °C and 33 °C, respectively. Approximately 73.1% of heat-related patients visited hospitals when temperature was between 30 °C and 33 °C. We validated the developed HWWS by using both the threshold temperatures of morbidity and mortality. The area under curves (AUCs) of the proposed model were 0.74 and 0.86 at Level-1 and Level-2, respectively. On the other hand, the AUCs of the model using only the mortality threshold were 0.60 and 0.86 at Level-1 and Level-2, respectively. The AUCs of the model using only the morbidity threshold were 0.73 and 0.78 at Level-1 and Level-2, respectively. The results suggest that the updated HWWS can help to reduce the impact of heatwaves, particularly on vulnerable groups, by providing the customized information. This also indicates that the HWWS could effectively mitigate the risk of morbidity and mortality.