Short-term impact of air pollution, noise and temperature on emergency hospital admissions in Madrid (Spain) due to liver and gallbladder diseases

BACKGROUND

Very few epidemiological studies have explored the environmental and meteorological risk factors that influence liver diseases and gallbladder disorders, and no studies have addressed the specific case of Spain.

METHODS

This is a retrospective ecological study conducted during 2013-2018. We analysed emergency admissions in the central area of the Region of Madrid for the following causes: Liver and gallbladder diseases (L&GB) (ICD-10: K70-K81); disorders of gallbladder (DGB) (ICD 10: K80-K81); liver disease (LD) (ICD 10: K70-K77); alcoholic liver disease (ALD) (ICD-10: K70); viral hepatitis (VH) (ICD10:B15-B19); and hepatic failure, not elsewhere classified (HFNS) (ICD-10: K72). Independent variables used: meteorological (maximum daily temperature (Tmax in ⁰C), minimum daily temperature (Tmin in ⁰C), and relative humidity (RH in %)); chemical air pollution (8-hO3, NO2, PM10, PM2.5 in μg/m3); and noise pollution (equivalent level of daily noise (Ld in dB(A)). Transformed variables: extreme heat in degrees (Theat); wet cold (WC); and high ozone. We fitted Poisson models, negative binomials and zero-inflated Poisson controlled for seasonality, day of the week, holidays, trend, and autoregressive trend. Based on these models, the percentage of cases attributable to statistically significant risk factors was then estimated.

RESULTS

In L&GB emergency admissions daily noise is related to 4.4% (CI95%: 0.8 7.9) of admissions; NO2 to 2.9% (CI95%: 0.1 5.7) and wet cold to 0.2% (CI95%: 0.8 7.9). Heat wave temperature was only related to ALD. In addition, the wet cold association with L&GB is also related to HFNS attributing 1.0% (CI95%: 0.3 1.8) of admissions for this cause.

CONCLUSIONS

Daily noise and NO2 are associated with more than 7% of urgent L&GB admissions. Both pollutants, are mainly emitted by road traffic. A reduction of traffic in cities would result in a reduction of emergency admissions due to this cause.

Short-term impact of extreme temperatures, relative humidity and air pollution on emergency hospital admissions due to kidney disease and kidney-related conditions in the Greater Madrid area (Spain)

While some studies report a possible association between heat waves and kidney disease and kidney-related conditions, there still is no consistent scientific consensus on the matter or on the role played by other variables, such as air pollution and relative humidity. Ecological retrospective time series study 01-01-2013 to 31-12-2018). Dependent variables: daily emergency hospitalisations due to kidney disease (KD), acute kidney injury (AKI), lithiasis (L), dysnatraemia (DY) and hypovolaemia (HPV). Independent variables: maximum and minimum daily temperature (Tmax, Tmin, °C), and daily relative humidity (RH, %). Other variables were also calculated, such as the daily temperature for risk of kidney disease (Theat, °C) and low daily hazardous relative humidity (HRH%). As variables of air pollution, we used the daily mean concentrations of PM10, PM2.5, NO2 and O3 in μg/m3. Based on these, we then calculated their daily excesses over World Health Organisation (WHO) guideline levels (hPM10, hPM2.5, hNO2 and hO3 respectively). Poisson family generalised linear models (GLMs) (link = log) were used to calculate relative risks (RRs), and attributable risks and attributable admissions. In the models, we controlled for the covariates included: seasonalities, trend, autoregressive component, day of the week, month and year. A statistically significant association was found between Theat and all the dependent variables analysed. The greatest AKI disease burden was attributable to Theat (2.2 % (1.7, 2.6) of attributable hospital admissions), followed by hNO2 (1.7 % (0.9, 3.4)) and HRH (0.8 (0.6, 1.1)). In the case of hypovolaemia and dysnatraemia, the greatest disease burden again corresponded to Theat, with 6.9 % (6.2, 7.6) and 5.7 (4.8, 6.6) of attributable hospital admissions respectively. Episodes of extreme heat exacerbate daily emergency hospital admissions due to kidney disease and kidney-related conditions; and attributable risks are likewise seen for low relative humidity and high ozone levels.

Short-term effects of tropospheric ozone and other environmental factors on emergency admissions due to pregnancy complications: A time-series analysis in the Madrid Region

Air pollution has been linked to adverse neonatal outcomes, mainly in the case of prolonged exposures. This study focuses on the short-term effects on maternal health. We conducted a retrospective ecological time-series study in the Madrid Region covering the period 2013-2018. The independent variables were mean daily concentrations of tropospheric ozone (O3), particulate matter (PM10/PM2.5) and nitrogen dioxide (NO2), as well as noise levels. The dependent variables were daily emergency hospital admissions due to complications in pregnancy, childbirth and the puerperium. Poisson generalised linear regression models were fitted to quantify the relative and attributable risks, controlling for trend, seasonality, the autoregressive nature of the series, and a number of meteorological factors. There were 318 069 emergency hospital admissions due to obstetric complications across the 2191 days of study. Of this total: 13 164 (95%CI: 9930-16 398) admissions were attributable to exposure to O3, the only pollutant to show a statistically significant (p < 0.05) association with admissions due to hypertensive disorders; and 10 575 (95%CI: 3573-17 566) admissions were attributable to daytime noise levels, while admissions due to hyperemesis gravidarum and vomiting were related to exposure to night noise. Other pollutants which also displayed statistically significant associations were: NO2 concentrations, with admissions due to vomiting and preterm labour; PM10 concentrations, with premature rupture of membranes: and PM2.5 concentrations, with total complications. Exposure to a range of air pollutants, and ozone in particular, is associated with a higher number of emergency hospital admissions due to gestational complications. Hence, surveillance of environmental effects on maternal health should be intensified, and plans and strategies to minimise these should be drawn up.

Impact of urban heat islands on morbidity and mortality in heat waves: Observational time series analysis of Spain's five cities

Urban heat islands (UHIs) have become an especially relevant phenomenon as a consequence of global warming and the growing proportion of people living in cities. The health impacts that are sometimes attributed to the rise in temperature generated in an UHI are not always adequately justified. The objective is to analyse what effect UHIs have on maximum (Tmax) and minimum daily temperatures (Tmin) recorded in urban and non-urban observatories, and quantify the impact on morbidity and mortality during heat waves in Spain's five cities. Data were collected on natural-cause daily mortality and unscheduled emergency hospital admissions (ICD-10: A00-R99) registered in these 5 cities across the period 2014-2018. We analysed daily Tmax and Tmin values at urban and non-urban observatories in these cities, and quantified the impact of Tmax and Tmin values during heat waves in each of these cities, using GLM models that included Tmax only, Tmin only, and both. We controlled for air pollution and other meteorological variables, as well as for seasonalities, trend and the autoregressive nature of the series. The UHI effect was observed in Tmin but not in Tmax, and proved to be greater in coastal cities than in inland and more densely populated cities. The UHI value in relation to the mean Tmin in the summer months ranged from 1.2 °C in Murcia to 4.1 °C in Valencia (difference between urban/non-urban observatories). The modelling process showed that, while a statistically significant association (p < 0.05) was observed in inland cities with Tmax for mortality and hospital admissions in heat waves, in coastal cities the association was obtained with Tmin, and the only impact in this case was the UHI effect on morbidity and mortality. No generalisations can be made about the impact of UHI on morbidity and mortality among the exposed population in cities. Studies on a local scale are called for, since it is local factors that determine whether the UHI effect will have a greater or lesser impact on health during heat-wave events.

Short-term impact of noise, other air pollutants and meteorological factors on emergency hospital mental health admissions in the Madrid region

BACKGROUND

A number of environmental factors, such as air pollution, noise in urbanised settings and meteorological-type variables, may give rise to important effects on human health. In recent years, many studies have confirmed the relation between various mental disorders and these factors, with a possible impact on the increase in emergency hospital admissions due to these causes. The aim of this study was to analyse the impact of a range of environmental factors on daily emergency hospital admissions due to mental disorders in the Madrid Autonomous Region (MAR), across the period 2013-2018.

METHODOLOGY

Longitudinal ecological time series study analysed by Generalised Linear Models with Poisson regression, with the dependent variable being daily Emergency Hospital Mental Health Admissions (EHMHA) in the MAR, and the independent variable being mean daily concentrations of chemical pollutants, noise levels and meteorological variables.

RESULTS

EHMHA were related statistically significantly in the short term with diurnal noise levels. Relative risks (RRs) for total admissions due to mental disorders and self-inflicted injuries, in the case of diurnal noise was RR: 1.008 95%CI (1.003 1.013). Admissions attributable to diurnal noise account for 5.5% of total admissions across the study period. There was no association between hospital admissions and chemical air pollution.

CONCLUSION

Noise is a variable that shows a statistically significant short-term association with EHMHA across all age groups in the MAR region. The results of this study may serve as a basis for drawing up public health guidelines and plans, which regard these variables as risk factors for mental disorders, especially in the case of noise, since this fundamentally depends on anthropogenic activities in highly urbanised areas with high levels of traffic density.

How heat waves, ozone and sunlight hours affect endocrine and metabolic diseases emergency admissions? A case study in the region of Madrid (Spain)

BACKGROUND

Studies which analyse the joint effect of acoustic or chemical air pollution variables and different meteorological variables on neuroendocrine disease are practically nonexistent. This study therefore sought to analyse the impact of air pollutants and environmental meteorological variables on daily unscheduled admissions due to endocrine and metabolic diseases in the Madrid Region from January 01, 2013 to December 31, 2018.

MATERIAL AND METHODS

We conducted a longitudinal, retrospective, ecological study of daily time series analysed by Poisson regression, with emergency neuroendocrine-disease admissions in the Madrid Region as the dependent variable. The independent variables were: mean daily concentrations of PM₁₀, PM_2.5, NO₂ and O₃; acoustic pollution; maximum and minimum daily temperatures; hours of sunlight; relative humidity; wind speed; and air pressure above sea level. Estimators of the statistically significant variables were used to calculate the relative risks (RRs).

RESULTS

A statistically significant association was found between the increase in temperatures in heat waves, RR: 1.123 95% CI (1.001-1.018), and the number of emergency admissions, making it the main risk factor. An association between a decrease in sunlight and an increase in hospital admissions, RR: 1.005 95% CI (1.002 1.008), was likewise observed. Similarly, ozone, in the form of mean daily concentrations in excess of 44 μg/m³, had an impact on admissions due to neuroendocrine disease, RR: 1.010 95% CI (1.007-1.035). The breakdown by sex showed that in the case of women, NO₂ was also a risk factor, RR: 1.021 95% CI (1.007-1.035).

CONCLUSION

The results obtained in this study serve to identify risk factors for this disease, such as extreme temperatures in heat waves, O₃ or NO₂. The robust association found between the decrease in sunlight and increase in hospital admissions due to neuroendocrine disease serves to spotlight an environmental factor which has received scant attention in public health until now.

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.

Does the meteorological origin of heat waves influence their impact on health? A 6-year morbidity and mortality study in Madrid (Spain)

BACKGROUND

In Spain, two synoptic-scale conditions influence heat wave formation. The first involves advection of warm and dry air masses carrying dust of Saharan origin (North African Dust (NAF) = 1). The second entails anticyclonic stagnation with high insolation and stability (NAF) = 0). Some studies show that the meteorological origin of these heat waves may affect their impact on morbidity and mortality.

OBJECTIVE

To determine whether the impact of heat waves on health outcomes in Madrid (Spain) during 2013-2018 varied by synoptic-scale condition.

METHODOLOGY

Outcome data consist of daily mortality and daily hospital emergency admissions (morbidity) for natural, circulatory, and respiratory causes. Predictors include daily maximum and minimum temperatures and daily mean concentrations of NO₂, PM₁₀, PM_2.5, NO₂, and O₃. Analyses adjust for insolation, relative humidity, and wind speed. Generalized linear models were performed with Poisson link between the variables controlling for trend, seasonality, and auto-regression in the series. Relative Risks (RR) and Attributable Risks (AR) were determined. The RRs for mortality attributable to high temperatures were similar regardless of NAF status. For hospital admissions, however, the RRs for hot days with NAF = 0 are higher than for days with NAF = 1. We also found that atmospheric pollutants worsen morbidity and mortality, especially PM₁₀ concentrations when NAF = 1 and O₃ concentrations when NAF = 0.

RESULTS

The effect of heat waves on morbidity and mortality depends on the synoptic situation. The impact is greater under anticyclonic stagnation conditions than under Saharan dust advection. Further, the health impact of pollutants such as PM₁₀ and O₃ varies according to the synoptic situation.

CONCLUSIONS

Based on these findings, we strongly recommend prevention plans to include data on the meteorological situation originating the heat wave, on a synoptic-scale, as well as comprehensive preventive measures against the compounding effect of high temperatures and pollution.

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.

Temporal evolution of threshold temperatures for extremely cold days in Spain

In contrast to research on heat waves, there are no studies in recent years that analyze the temporal evolution of threshold temperatures (Tthreshold) for extremely cold days (ECD). It is unknown whether threshold temperatures have increased more quickly than the minimum daily temperature (Tmin) in recent years. The objective of this study was to analyze the temporal evolution of the minimum daily temperature (Tmin) in a group of Spanish provinces and compare it with the evolution of threshold temperatures. An ecological, retrospective time series study was carried out using daily observations between January 1, 1983 and December 31, 2018 (36 years) in 10 provinces that are representative of the different climate territories in Spain. For each representative observatory in each province, the values of Tmin were obtained for the winter months (November-March). The value of Tthreshold was determined for each province and each year, using dispersion diagrams for the pre-whitened series, with daily mortality due to natural causes displayed on the Y axis (CIEX: A00-R99) and Tmin grouped by 10 degree intervals on the X axis. To determine the temporal evolution of Tmin and Tthreshold for each province, linear models were fitted, with time as the independent variable. During the winter months, Tmin increased at an average rate of 0.2 °C/decade (IC95: 0.1-0.3), while Tthreshold remained practically constant during the period, at 0.1 °C/decade (IC95% -0.1 0.3). These values are much lower than those obtained in the case of heat, both in terms of the evolution of maximum daily temperature and that of Tthreshold. In conclusion, the fact that this trend has been maintained across time in a scenario of climate change, with a slow increase in minimum daily temperatures and constant values of Threshold, suggests a decrease in the number of ECD.

Effects of local factors on adaptation to heat in Spain (1983-2018)

The European Union is currently immersed in policy development to address the effects of climate change around the world. Key plans and processes for facilitating adaptation to high temperatures and for reducing the adverse effects on health are among the most urgent measures. Therefore, it is necessary to understand those factors that influence adaptation. The aim of this study was to provide knowledge related to the social, climate and economic factors that are related to the evolution of minimum mortality temperatures (MMT) in Spain in the rural and urban contexts, during the 1983-2018 time period. For this purpose, local factors were studied regarding their relationship to levels of adaptation to heat. MMT is an indicator that allows for establishing a relationship to between mortality and temperature, and is a valid indicator to assess the capacity of adaptation to heat of a certain population. MMT is obtained through the maximum daily temperature and daily mortality of the study period. The evolution of MMT values for Spain was established in a previous paper. An ecological, longitudinal and retrospective study was carried out. Generalized linear models (GLM) were performed to identify the variables that appeared to be related to adaptation. The adaptation was calculated as the difference in variation in MMT based on the average increase in maximum daily temperatures. In terms of adaptation to heat, urban populations have adapted more than non-urban populations. Seventy-nine percent (n = 11) of urban provinces have adapted to heat, compared to twenty-one percent (n = 3) of rural provinces that have not adapted. In terms of urban zones, income level and habituation to heat (values over the 95th percentile) were variables shown to be related to adaptation. In contrast, among non-urban provinces, a greater number of housing rehabilitation licenses and a greater number of health professionals were variables associated with higher increases in MMT, and therefore, with adaptation. These results highlight the need to carry out studies that allow for identifying the local factors that are most relevant and influential in population adaptation. More studies carried out at a small scale are needed.

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.

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

Backgraund

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.

Methods

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, 2013. 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 &gt;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 (Tthresold) 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.

Results

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 &gt;64 years of age and living in the metropolitan area were found to be risk factors.

Conclusions

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.

Key messages

Heat waves affect urban and rural areas differently. So results and conclusions from urban areas should not be extrapolated to rural population. Socioeconomic status and ageing are important variables which explain the different behavior of heat waves in different areas.

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

Background

Although there is significant scientific evidence on the impact of heat waves, there are few studies that analyze the effects of sociodemographic factors on the impact of heat waves below the municipal level.

Methods

The objective of this study was to analyze the role of income level, percent of the population over age 65, existence of air conditioning units and hectares (Ha) of green zones in districts in Madrid, in the impact of heat on daily mortality between January 1, 2010 and December 31, 2013. Seventeen districts were analyzed, and Generalized Linear (GLM) Poisson Regression Models were used to calculate relative risks (RR) and attributable risks (RA) for the impact of heat waves on mortality due to natural causes (CIEX:A00-R99). The pattern of risks obtained was analyzed using GLM univariates and multivariates of the binomial family (link logit), introducing the socioeconomic and demographic variables mentioned above.

Results

The results indicate that heat wave had an impact in only three of the districts analyzed. In the univariate models, all of the variables were statistically significant, but Ha of green zones lost significance in the multivariate model. Income level, existence of air conditioning units, and percent of the population over age 65 in the district remained as variables that modulate the impact of heat wave on daily mortality in the municipality of Madrid. Income level was the key variable that explained this behavior.

Conclusions

The results obtained in this study show that there are factors below the municipal level (district level) that should be considered as focus areas for health policy in order to decrease the impact of heat and promote the process of adaptation to heat in the context of climate change.

Key messages

There are factors below the municipal level which should be considered for health policy in order to decrease health heat impacts. Privation hamper isolation of ageing people from extreme outdoor temperatures. Therefore, in some cases poverty could become the key risk factor that explain the vulnerability to heat waves.

Cold spell effect on daily mortality in districts in Madrid considering sociodemographic variables

Background

While there is much research that focuses on the association between cold spell and their impacts on daily mortality at the city level, we analyze the impact related to social context and demographic variables at levels lower than the municipal.

Methods

The objective of this study was to determine the role of the percentage of people over age 65, income level and percentage of homes without heating in the analysis of the impact of cold waves on daily mortality between January 1, 2010 and December 31, 2013 in different districts of the municipality of Madrid. We calculated Relative Risks (RR) and Attributable Risks (RA) for each of 17 districts to determine correlations between the effect of cold waves and daily mortality due to natural causes (CIEX: A00-R99) using Generalized Linear Models (GLM) of the Poisson family (link log). The pattern of risks obtained by district was analyzed using binomial family models (link logit), considering socioeconomic and demographic variables.

Results

In terms of results, an impact of cold on mortality was detected in 9 of the 17 districts analyzed. The analysis of risk patterns revealed that the probability of detecting an impact in a district increases in a statistically significant way (p-value &lt;0.05) with a higher percentage of homes without heating systems and a higher percentage of population over age 65.

Conclusions

The results obtained identify the factors that should be considered in public health policies that target the district level to reduce the impact of cold waves.

Key messages

Ageing and the absence of heating systems are key variables which explain vulnerability to cold spell. Cold spell related mortality risks can be reduced by applying prevention health public plans.

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.

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.

The effect of cold waves on daily mortality in districts in Madrid considering sociodemographic variables

While there is much research that focuses on the association between cold waves and their impacts on daily mortality at the city level, few analyze the impact related to social context and demographic variables at levels lower than the municipal. The objective of this study was to determine the role of the percentage of people over age 65, income level and percentage of homes without heating in the analysis of the impact of cold waves on daily mortality between January 1, 2010 and December 31, 2013 in different districts of the municipality of Madrid. We calculated Relative Risks (RR) and Attributable Risks (RA) for each of 17 districts to determine correlations between the effect of cold waves and daily mortality due to natural causes (CIEX: A00-R99) using Generalized Linear Models (GLM) of the Poisson family (link log). The pattern of risks obtained by district was analyzed using binomial family models (link logit), considering socioeconomic and demographic variables. In terms of results, an impact of cold on mortality was detected in 9 of the 17 districts analyzed. The analysis of risk patterns revealed that the probability of detecting an impact in a district increases in a statistically significant way (p-value <0.05) with a higher percentage of homes without heating systems and a higher percentage of population over age 65. The results obtained identify the factors that should be considered in public health policies that target the district level to reduce the impact of cold waves.

The evolution of minimum mortality temperatures as an indicator of heat adaptation: The cases of Madrid and Seville (Spain)

The increase in the frequency and intensity of heat waves is one of the most unquestionable effects of climate change. Therefore, the progressive increase in maximum temperatures will have a clear incidence on the increase in mortality, especially in countries that are vulnerable due to geographical location or their socioeconomic characteristics. Different research studies show that the mortality attributable to heat is decreasing globally, and research is centred on future scenarios. One way of detecting the existence of a lesser impact of heat is through the increase in the so-called temperature of minimum mortality (TMM). The objective of this study is to determine the temporal evolution of TMM in two Spanish provinces (Seville and Madrid) during the 1983-2018 period and to evaluate whether the rate of adaptation to heat is appropriate. We used the gross rate of daily mortality due to natural causes (CIEX: A00-R99) and the maximum daily temperature (°C) to determine the quinquennial TMM using dispersion diagrams and realizing fit using quadratic and cubic curvilinear estimation. The same analysis was carried out at the annual level, by fitting an equation to the line of TMM for each province, whose slope, if significant (p < 0.05) represents the annual rate of variation in TMM. The results observed in this quinquennial analysis showed that the TMM is higher in Seville than in Madrid and that it is higher among men than women in the two provinces. Furthermore, there was an increase in TMM in all of the quinquennium and a clear decrease in the final period. At the annual level, the linear fit was significant for Madrid for the whole population and corresponds to an increase in the TMM of 0.58 °C per decade. For Seville the linear fits were significant and the slopes of the fitted lines was 1.1 °C/decade. Both Madrid and Seville are adapting to the increase in temperatures observed over the past 36 years, and women are the group that is more susceptible to heat, compared to men. The implementation of improvements and evaluation of prevention plans to address the impact of heat waves should continue in order to ensure adequate adaptation in the future.

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

Although there is significant scientific evidence on the impact of heat waves, there are few studies that analyze the effects of sociodemographic factors on the impact of heat waves below the municipal level. The objective of this study was to analyze the role of income level, percent of the population over age 65, existence of air conditioning units and hectares (Ha) of green zones in districts in Madrid, in the impact of heat on daily mortality between January 1, 2010 and December 31, 2013. Seventeen districts were analyzed, and Generalized Linear (GLM) Poisson Regression Models were used to calculate relative risks (RR) and attributable risks (RA) for the impact of heat waves on mortality due to natural causes (CIEX:A00-R99). The pattern of risks obtained was analyzed using GLM univariates and multivariates of the binomial family (link logit), introducing the socioeconomic and demographic variables mentioned above. The results indicate that heat wave had an impact in only three of the districts analyzed. In the univariate models, all of the variables were statistically significant, but Ha of green zones lost significance in the multivariate model. Income level, existence of air conditioning units, and percent of the population over age 65 in the district remained as variables that modulate the impact of heat wave on daily mortality in the municipality of Madrid. Income level was the key variable that explained this behavior. The results obtained in this study show that there are factors at levels below the municipal level (district level) that should be considered as focus areas for health policy in order to decrease the impact of heat and promote the process of adaptation to heat in the context of climate change.

Short-term effects of traffic noise on suicides and emergency hospital admissions due to anxiety and depression in Madrid (Spain)

Studies show a relationship between some mental illnesses and suicides and different environmental variables such as air pollution, characterized by stress at the neuropsychological level. Despite the fact that traffic noise is also a powerful neurological stressor, studies that relate traffic noise to these mental disorders are practically non-existent. The objective is to analyze the short-term impact that chemical air pollution, traffic noise and thermal extremes have on emergency hospital admissions due to anxiety, dementia and suicides in the city of Madrid. This ecological, longitudinal study uses generalized linear models with Poisson link to analyze the short-term impact of the average daily concentrations of chemical pollutants (NO₂, PM₁₀, PM_2.5, O₃), noise pollution indicators (Leq_day, Leq_night and Leq_24h) and temperatures during heat waves (T_heat) and cold waves (T_cold) on daily admissions to emergency services in the city of Madrid from 2010 to 2013 due to anxiety (ICD-10: F32), depression (ICD-10: F40-F42) and suicide (ICD-10: X60-X84). The results show no association between any of the chemical pollutants considered and the dependent variables studied. On the contrary, the values of Leq_day are associated with the three variables analyzed in lag 0 for the cases of anxiety and depression and in lag 1 for suicides, with RR: 1.20 (IC95% 1.14 1.26), RR: 1.11 (IC95% 1.06 1.16) and RR: 1.17 (IC95% 1.05 1.30), respectively, for increases of 1 dB(A) in the values of Leq_day. An association was also found between T_cold and admissions for anxiety in lag 9 with RR: 1.62 (IC95% 1.18 2.22) for increases of 1 °C in the values of T_cold. Traffic noise can be considered an important risk factor related to the illnesses and anxiety and depression and for suicides in the city of Madrid, although new studies are needed to support the findings shown here.

Will there be cold-related mortality in Spain over the 2021-2050 and 2051-2100 time horizons despite the increase in temperatures as a consequence of climate change?

INTRODUCTION

Global warming is resulting in an increase in temperatures which is set to become more marked by the end of the century and depends on the accelerating pace of greenhouse gas emissions into the atmosphere. Yet even in this scenario, so-called "cold waves" will continue to be generated and have an impact on health.

OBJECTIVES

This study sought to analyse the impact of cold waves on daily mortality at a provincial level in Spain over the 2021-2050 and 2051-2100 time horizons under RCP4.5 and RCP 8.5 emission scenarios, on the basis of two hypotheses: (1) that the cold-wave definition temperature (T _threshold) would not vary over time; and, (2) that there would be a variation in T _threshold.

MATERIAL AND METHODS

The results of a retrospective study undertaken for Spain as a whole across the period 2000-2009 enabled us to ascertain the cold-wave definition temperature at a provincial level and its impact on health, measured by reference to population attributable risk (PAR). The minimum daily temperatures projected for each provincial capital considering the above time horizons and emission scenarios were provided by the State Meteorological Agency. On the basis of the T _threshold definition values and minimum daily temperatures projected for each province, we calculated the expected impact of low temperatures on mortality under the above two hypotheses. Keeping the PAR values constant, it was assumed that the mortality rate would vary in accordance with the available data.

RESULTS

If T _threshold remained constant over the above time horizons under both emission scenarios, there would be no cold-related mortality. If T _threshold were assumed to vary over time, however, then cold-related mortality would not disappear: it would instead remain practically constant over time and give rise to an estimated overall figure of around 250 deaths per year, equivalent to close on a quarter of Spain's current annual cold-related mortality and entailing a cost of approximately €1000 million per year.

CONCLUSION

Given that cold waves are not going to disappear and that their impact on mortality is far from negligible and is likely to remain so, public health prevention measures must be implemented to minimise these effects as far as possible.

Differences in the impact of heat waves according to urban and peri-urban factors in Madrid

Aside from climatic factors, the impact of heat waves on mortality depends on the demographic and socio-economic structure of the population as well as variables relating to local housing. Hence, this study's main aim was to ascertain whether there might be a differential impact of heat waves on daily mortality by area of residence. The study is a time-series analysis (2000-2009) of daily mortality and minimum and maximum daily temperatures (°C) in five geographical areas of the Madrid region. The impact of such waves on heat-related mortality due to natural causes (ICD-10: A00- R99), circulatory causes (ICD-10: I00-I99) and respiratory causes (ICD-10: J00-J99) was obtained by calculating the relative risk (RR) and attributable risk (AR), using GLM models with the Poisson link and controlling for trend, seasonalities and the autoregressive nature of the series. Furthermore, we also evaluated other external variables, such as the percentage of the population aged over 65 years and the percentage of old housing. No heat-related mortality threshold temperature with statistical significance was detected in the northern and eastern areas. While the threshold temperatures in the central and southern areas were very similar and close to the 90th percentile, the threshold in the western area corresponded to the 97th percentile. Attributable mortality proved to be highest in the central area with 85 heat wave-related deaths per annum. External factors found to influence the impact of heat on mortality in Madrid were the size of the population aged over 65 years and the age of residential housing. Demographic structure and the percentage of old housing play a key role in modulating the impact of heat waves. This study concludes that the areas in which heat acts earliest are those having a higher degree of population ageing.

GEOSEQ: a Pascal program to calculate statistical geometry parameters of aligned nucleic acid sequences

Statistical geometry in sequence space is a statistical method used mainly to determine the topology of the divergence (i.e. tree, bundle or net) of a set of aligned sequences by combining horizontal and vertical positional information. GEOSEQ is a documented program written in Pascal that calculates the statistical geometry parameters necessary to choose between phylogenetic topologies. The input file is an optimal alignment of nucleic acid sequences in PHYLIP format (v. 3.3) with a first line containing information regarding sequences as well as some options. In order to check the randomization level associated with the obtained topology, the program has been implemented with a random generator of sequences under specified set conditions.