INTRODUCTION AND OBJECTIVES: Some atmospheric features have been linked to the triggering of myocardial infarction. Because data from the Temperate-Mediterranean is scarce, we sought to study whether meteorological parameters influence the incidence of ST-elevation myocardial infarction (STEMI) as confirmed by primary percutaneous intervention in a city with temperate weather (Porto, Portugal). METHODS: Retrospective analysis of a series of STEMI-patients from January 2010 to December 2017. Temperature (T), relative humidity (RH), precipitation, and atmospheric pressure were obtained from a government-led institute. We utilized a generalized linear model (GLM) with a Poisson distribution, where a series of models with multivariable analysis were computed. The effects (GLM coefficients) are presented as excess relative risk (ERR). RESULTS: One thousand and four consecutive STEMI-patients were included. The most important predictors of STEMI were Tmin two days before (for 1°C drop ERR=1.9%, p=0.009) and a 1% increase in RH three days before (EER=0.7%, p=0.006). Conversely, the same increase in RH the day before reduced the relative risk (EER=-0.6%, p=0.023). Temperature range, atmospheric pressure and precipitation had no impact on STEMI incidence. CONCLUSION: In a Temperate-Mediterranean city hot or cold temperature extremes, temperature drop and relative humidity had a significant impact on the occurrence of STEMI.
Mycobacterium avium subsp. paratuberculosis (MAP) may play a role in the pathology of human inflammatory bowel disease (IBD). Previously, we found a high frequency (98% in patients with active disease) of MAP DNA detection in the blood of Portuguese Crohn’s Disease patients, suggesting this cohort has high exposure to MAP organisms. Water is an important route for MAP dissemination, in this study we therefore aimed to assess MAP contamination within water sources in Porto area (the residential area of our IBD study cohort). Water and biofilms were collected in a wide variety of locations within the Porto area, including taps connected to domestic water sources and from municipal water distribution systems. Baseline samples were collected in early autumn plus further domestic water samples in early winter, to assess the effect of winter rainfall. DNA was extracted from all 131 samples and IS900-based nested PCR used to assess the frequency of MAP presence. Our results show high MAP positivity in municipal water sources (20.7% of water samples and 41.4% of biofilm samples) and even higher amongst domestic sources (30.8% of water samples and 50% of biofilm samples). MAP positivity in biofilms correlated with positivity in water samples from the same sources. A significantly higher frequency of MAP-positivity was observed during winter rains as compared with samples collected in autumn prior to the winter rainfall period (61.9% versus 30.8%). We conclude that domestic and municipal water sources of Porto region have a high burden of MAP contamination and this prevalence increases with rainfall. We hypothesize that human exposure to MAP from local water supplies is commonplace and represents a major route for MAP transmission and challenge which, if positively linked to disease pathology, may contribute to the observed high prevalence of IBD in Porto district.
The far-reaching impact of the Sun on Earth’s climate and on people’s health and well-being is a poorly understood and non-consensual scientific issue, with empirical literature stressing the need to expand the knowledge of such relationships. Here, the interplay between solar activity (SA) and climate, and its likely cascading effects on all-cause mortality, were examined at several time scales. To this end, the parish records of Braga (1700-1880) and Torre de Moncorvo (1700-1850), in two different geographical locations of northern Portugal (Iberia, SW Europe), were used. Crude mortality rate (CMR) and winter-summer ratio (W/S) values were computed to characterize mortality patterns/trends and couple them with potential relevant drivers: total solar irradiance (TSI) as a proxy of SA, the North Atlantic Oscillation (NAO), and key historical events. What emerged, albeit incomplete, was a complex picture of death deeply embedded in people’s physical and socioeconomic environments, at a time when ubiquitous poverty (and co-morbid malnutrition) was the most inveterate cause of ill health. After identifying the positive mortality episodes in both municipalities, their incidence was found to be higher in periods of weakened SA (normal/grand minima). Standard inference statistics were used to estimate the significance of the observations. The highest CMR peaks matched not only with wars but also with known wide-ranging mortality crises, which seem to have been triggered by major agricultural production shortfalls, followed by substantial increases in food prices, driven, in turn, by climate deterioration, including extreme weather occurrences. The outcome was social unrest, famines, and outbreaks of infectious diseases, heightening the death toll. The influence of prominent solar/climate variations was investigated using wavelet transform coherence analysis (WTC). The results showed (multi)decadal oscillations in both (TSI and NAO) somehow regulating mortality. But the WTC analysis also estimated SA signals in low-frequency mortality dynamics disguised by time-varying determinants, where distinct players of space weather might have been implicated.
Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays. The main goal of this work is to assess the impact of the exposure to air pollutants on the number of daily hospital admissions due to respiratory causes in 58 spatial locations of Portugal mainland, during the period 2005-2017. To this end, INteger Generalised AutoRegressive Conditional Heteroskedastic (INGARCH)-based models are extensively used. This family of models has proven to be very useful in the analysis of serially dependent count data. Such models include information on the past history of the time series, as well as the effect of external covariates. In particular, daily hospitalisation counts, air quality and temperature data are endowed within INGARCH models of optimal orders, where the automatic inclusion of the most significant covariates is carried out through a new block-forward procedure. The INGARCH approach is adequate to model the outcome variable (respiratory hospital admissions) and the covariates, which advocates for the use of count time series approaches in this setting. Results show that the past history of the count process carries very relevant information and that temperature is the most determinant covariate, among the analysed, for daily hospital respiratory admissions. It is important to stress that, despite the small variability explained by air quality, all models include on average, approximately two air pollutants covariates besides temperature. Further analysis shows that the one-step-ahead forecasts distributions are well separated into two clusters: one cluster includes locations exclusively in the Lisbon area (exhibiting higher number of one-step-ahead hospital admissions forecasts), while the other contains the remaining locations. This results highlights that special attention must be given to air quality in Lisbon metropolitan area in order to decrease the number of hospital admissions.
Uncontrolled wildfires have a substantial impact on the environment, the economy and local populations. According to the European Forest Fire Information System (EFFIS), between 2000 and 2013 wildfires burned up to 740 000 ha of land annually in the south of Europe, Portugal being the country with the highest percentage of burned area per square kilometre. However, there is still a lack of knowledge regarding the impacts of the wildfire-related pollutants on the mortality of the country’s population. All wildfires occurring during the fire season (June-July-AugustSeptember) from 2001 and 2016 were identified, and those with a burned area above 1000 ha (large fires) were considered for the study. During the studied period (2001-2016), more than 2 million ha of forest (929 766 ha from June to September alone) were burned in mainland Portugal. Although large fires only represent less than 1% of the number of total fires, in terms of burned area their contribution is 46% (53% from June to September). To assess the spatial impact of the wildfires, burned areas in each region of Portugal were correlated with PM10 concentrations measured at nearby background air quality monitoring stations. Associations between PM10 and all-cause (excluding injuries, poisoning and external causes) and cause-specific mortality (circulatory and respiratory) were studied for the affected populations using Poisson regression models. A significant positive correlation between burned area and PM10 was found in some regions of Portugal, as well as a significant association between PM10 concentrations and mortality, these being apparently related to large wildfires in some of the regions. The north, centre and inland of Portugal are the most affected areas. The high temperatures and long episodes of drought expected in the future will increase the probabilities of extreme events and therefore the occurrence of wildfires.
Epidemiological studies on the impact of determining environmental factors on human health have proved that temperature extremes and variability constitute mortality risk factors. However, few studies focus specifically on susceptible individuals living in Portuguese urban areas. This study aimed to estimate and assess the health burden of temperature-attributable mortality among age groups (0-64 years; 65-74 years; 75-84 years; and 85+ years) in Lisbon Metropolitan Area, from 1986-2015. Non-linear and delayed exposure-lag-response relationships between temperature and mortality were fitted with a distributed lag non-linear model (DLNM). In general, the adverse effects of cold and hot temperatures on mortality were greater in the older age groups, presenting a higher risk during the winter season. We found that, for all ages, 10.7% (95% CI: 9.3-12.1%) deaths were attributed to cold temperatures in the winter, and mostly due to moderately cold temperatures, 7.0% (95% CI: 6.2-7.8%), against extremely cold temperatures, 1.4% (95% CI: 0.9-1.8%). When stratified by age, people aged 85+ years were more burdened by cold temperatures (13.8%, 95% CI: 11.5-16.0%). However, for all ages, 5.6% of deaths (95% CI: 2.7-8.4%) can be attributed to hot temperatures. It was observed that the proportion of deaths attributed to exposure to extreme heat is higher than moderate heat. As with cold temperatures, people aged 85+ years are the most vulnerable age group to heat, 8.4% (95% CI: 3.9%, 2.7%), and mostly due to extreme heat, 1.3% (95% CI: 0.8-1.8%). These results provide new evidence on the health burdens associated with alert thresholds, and they can be used in early warning systems and adaptation plans.
Aedes albopictus is an invasive mosquito that has colonized several European countries as well as Portugal, where it was detected for the first time in 2017. To increase the knowledge of Ae. albopictus population dynamics, a survey was carried out in the municipality of Loulé, Algarve, a Southern temperate region of Portugal, throughout 2019, with Biogents Sentinel traps (BGS traps) and ovitraps. More than 19,000 eggs and 400 adults were identified from May 9 (week 19) and December 16 (week 50). A positive correlation between the number of females captured in the BGS traps and the number of eggs collected in ovitraps was found. The start of activity of A. albopictus in May corresponded to an average minimum temperature above 13.0 °C and an average maximum temperature of 26.2 °C. The abundance peak of this A. albopictus population was identified from September to November. The positive effect of temperature on the seasonal activity of the adult population observed highlight the importance of climate change in affecting the occurrence, abundance, and distribution patterns of this species. The continuously monitoring activities currently ongoing point to an established population of A. albopictus in Loulé, Algarve, in a dispersion process to other regions of Portugal and raises concern for future outbreaks of mosquito-borne diseases associated with this invasive mosquito species.
Previous studies have consistently analyzed the impact that extreme temperatures will have on human health. However, there are very few data on temperature-related mortality burden considering future demographic changes in a context of climate change in Portugal. This study aims to quantify the impact of climate change on heat-, cold-, and net change mortality burdens, taking into account the future demographic changes in Lisbon Metropolitan Area, Portugal. We applied a time-series generalized linear model with a quasi-Poisson model via a distributed lag nonlinear model to project temperature-related mortality burden for two climatological scenarios: a present (or reference, 1986-2005) scenario and a future scenario (2046-2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that the total attributable fraction due to temperature, extreme and moderate cold, is statistically significant in the historical period and the future projected scenarios, while extreme and moderate heat were only significant in the projected future summer period. Net differences were attributed to moderate cold in the future winter months. Projections show a consistent and significant increase in future heat-related mortality burden. The attributable fraction due to heat in the future period, compared to the historical period, ranges from 0 to 1.5% for moderate heat and from 0 to 0.5% for extreme heat. Adaptation should be implemented at the local level, so as to prevent and diminish the effects on citizens and healthcare services, in a context of climate change.
