Modelação do efeito do frio extremo na saúde da população de Lisboa: contributos para um sistema de vigilância e alerta

Trabalho de projecto de mestrado, Bioestatística, Universidade de Lisboa, Faculdade de Ciências, 2016Introdução Diversos estudos já reportaram a associação entre a temperatura ambiente e a mortalidade. Poucos estudos foram realizados, no entanto, especificamente, para o frio incluindo a comparação entre diversos índices meteorológicos. O presente estudo teve como objetivo avaliar os efeitos do frio na mortalidade da população de Lisboa durante o Inverno. Métodos Foram usados modelos lineares e não lineares de desfasamento distribuído (DLNM) para investigar os efeitos do frio na mortalidade por todas as causas e por doenças respiratórias e circulatórias, em diferentes desfasagens de tempo em Lisboa, e nos períodos de inverno (novembro a março) de 2002 a 2012. Foram comparados vários modelos a fim de comparar o desempenho entre diferentes índices meteorológicos (temperatura média, temperatura média e velocidade do vento, temperatura média e humidade, e temperatura windchill ). Todos os modelos foram ajustados para os efeitos de confundimento da atividade gripal. Resultados A relação entre a mortalidade e a temperatura aproxima-se da forma U ou V na série anual. Para o período de inverno a relação linear foi a que apresentou um melhor ajustamento para ambas as causas. Os resultados mostram que o efeito do frio não é imediato e persiste até entre 23 e 30 dias, enquanto que o efeito das temperaturas elevadas é imediato. O maior Risco Relativo cumulativo foi encontrado no modelo que considerou a temperatura windchill com um valor de 1.8 (IC95%: 1.7,2.0) para a mortalidade por todas as causas, e um valor of 2.0 (IC95%: 1.8,2.3) para a mortalidade por doenças dos aparelhos circulatório e respiratório. Conclusão As temperaturas baixas parecem representar um bom preditor da mortalidade em Lisboa, tendo sido encontrada uma maior associação entre o frio e a mortalidade por doenças dos aparelhos circulatório e respiratório. A temperatura windchill parece ser um melhor preditor da mortalidade que a temperatura média.Background Several studies have already reported the association between ambient temperature and mortality. However, few studies have been developed specifically for cold, making a comparison between different meteorological indices. The present study aimed to assess the health effects of cold temperature on mortality in Lisbon population during winter time. Methods A distributed lag linear and non-linear model (DLNM) was used to investigate the cold effects on mortality by all causes as well as, particularly, by circulatory and respiratory diseases, at different lags in Lisbon, in winter time (from November to March) between 2002 and 2012. A comparison of several models was accomplished in order to compare performance between meteorological indices combinations (mean temperature, mean temperature and wind speed, mean temperature and humidity, and winchill ). All models were adjusted for the confounding effects of u activity. Results An U or V -shaped relationship between temperature and mortality was observed for annual series. For winter time, the best _t was found for a linear relation between temperature and both mortality causes under study. The results show that cold effect was delayed and persisted for about 23 to 30 days, whereas hot effect was acute and lasted only 1 day. The highest cumulative relative risk for all cause mortality was found using windchill [1.8 (CI95%: 1.7,2.0)]. For mortality by circulatory and respiratory diseases the highest cumulative relative risk was also found using windchill [2.0 (CI95%: 1.8,2.3)]. Conclusion Cold temperature seemed to be a strong predictor of mortality in Lisbon, with the strongest association found between cold temperature and circulatory and respiratory mortality. Windchill temperature seemed to be a better predictor of mortality than mean temperature

Digestibility and nutritional value of fresh and stored pollen for honey bees (Apis mellifera scutellata)

Pollen, the main protein source for honey bees, is mixed with regurgitated nectar or honey during collection and then stored as ‘bee bread’ before its consumption, mainly by young nurse workers. It has been suggested that storage of pollen improves its nutritional value and digestibility, but there is little evidence for such changes. We fed two fresh pollen types of different protein content (aloe and sunflower), and two stored pollen types (sunflower and a mixed pollen), to young caged worker bees. We measured daily consumption of pollen and sucrose solution, and survival after 14 days. At day 14 we recorded ovarian activation and extraction efficiency, by counting empty pollen grains in the rectal contents. Extraction efficiency is a measure of pollen digestibility. Contrary to our predictions, bees did not consume more fresh sunflower pollen than fresh aloe pollen to compensate for the lower protein content of sunflower pollen. In addition, they did not consume less sucrose solution when fed stored pollen diets that are already enriched in sugar. Consumption of stored sunflower pollen resulted in a low protein to carbohydrate (P:C) intake. Survival and ovarian activation were higher on diets giving higher P:C intakes. Extraction efficiency was high (up to 99%) for all pollen diets, and comparison of fresh and stored sunflower pollen showed that storage did not make it easier to digest. Changes to pollen during storage do not confer obvious benefits to honey bees.The National Research Foundation of South Africa.http://www.elsevier.com/locate/jinsphys2019-05-01hj2018Zoology and Entomolog

Seasonality of mortality under climate change: a multicountry projection study.

BACKGROUND: Climate change can directly impact temperature-related excess deaths and might subsequently change the seasonal variation in mortality. In this study, we aimed to provide a systematic and comprehensive assessment of potential future changes in the seasonal variation, or seasonality, of mortality across different climate zones. METHODS: In this modelling study, we collected daily time series of mean temperature and mortality (all causes or non-external causes only) via the Multi-Country Multi-City Collaborative (MCC) Research Network. These data were collected during overlapping periods, spanning from Jan 1, 1969 to Dec 31, 2020. We projected daily mortality from Jan 1, 2000 to Dec 31, 2099, under four climate change scenarios corresponding to increasing emissions (Shared Socioeconomic Pathways [SSP] scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We compared the seasonality in projected mortality between decades by its shape, timings (the day-of-year) of minimum (trough) and maximum (peak) mortality, and sizes (peak-to-trough ratio and attributable fraction). Attributable fraction was used to measure the burden of seasonality of mortality. The results were summarised by climate zones. FINDINGS: The MCC dataset included 126 809 537 deaths from 707 locations within 43 countries or areas. After excluding the only two polar locations (both high-altitude locations in Peru) from climatic zone assessments, we analysed 126 766 164 deaths in 705 locations aggregated in four climate zones (tropical, arid, temperate, and continental). From the 2000s to the 2090s, our projections showed an increase in mortality during the warm seasons and a decrease in mortality during the cold seasons, albeit with mortality remaining high during the cold seasons, under all four SSP scenarios in the arid, temperate, and continental zones. The magnitude of this changing pattern was more pronounced under the high-emission scenarios (SSP3-7.0 and SSP5-8.5), substantially altering the shape of seasonality of mortality and, under the highest emission scenario (SSP5-8.5), shifting the mortality peak from cold seasons to warm seasons in arid, temperate, and continental zones, and increasing the size of seasonality in all zones except the arid zone by the end of the century. In the 2090s compared with the 2000s, the change in peak-to-trough ratio (relative scale) ranged from 0·96 to 1·11, and the change in attributable fraction ranged from 0·002% to 0·06% under the SSP5-8.5 (highest emission) scenario. INTERPRETATION: A warming climate can substantially change the seasonality of mortality in the future. Our projections suggest that health-care systems should consider preparing for a potentially increased demand during warm seasons and sustained high demand during cold seasons, particularly in regions characterised by arid, temperate, and continental climates. FUNDING: The Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan

Fluctuating risk of acute kidney injury-related mortality for four weeks after exposure to air pollution: A multi-country time-series study in 6 countries.

BACKGROUND: Recent studies have reported that air pollution is related to kidney diseases. However, the global evidence on the risk of death from acute kidney injury (AKI) owing to air pollution is limited. Therefore, we investigated the association between short-term exposure to air pollution-particulate matter ≤ 2.5 μm (PM2.5), ozone (O3), and nitrogen dioxide (NO2)-and AKI-related mortality using a multi-country dataset. METHODS: This study included 41,379 AKI-related deaths in 136 locations in six countries during 1987-2018. A novel case time-series design was applied to each air pollutant during 0-28 lag days to estimate the association between air pollution and AKI-related deaths. Moreover, we calculated AKI deaths attributable to non-compliance with the World Health Organization (WHO) air quality guidelines. RESULTS: The relative risks (95% confidence interval) of AKI-related deaths are 1.052 (1.003, 1.103), 1.022 (0.994, 1.050), and 1.022 (0.982, 1.063) for 5, 10, and 10 µg/m3 increase in lag 0-28 days of PM2.5, warm-season O3, and NO2, respectively. The lag-distributed association showed that the risk appeared immediately on the day of exposure to air pollution, gradually decreased, and then increased again reaching the peak approximately 20 days after exposure to PM2.5 and O3. We also found that 1.9%, 6.3%, and 5.2% of AKI deaths were attributed to PM2.5, warm-season O3, and NO2 concentrations above the WHO guidelines. CONCLUSIONS: This study provides evidence that public health policies to reduce air pollution may alleviate the burden of death from AKI and suggests the need to investigate the several pathways between air pollution and AKI death

Temporal variations in the short-term effects of ambient air pollution on cardiovascular and respiratory mortality: a pooled analysis of 380 urban areas over a 22-year period

BACKGROUND: Ambient air pollution, including particulate matter (PM) with diameters ≤10 µm (PM10) or ≤2·5 µm (PM2·5) and nitrogen dioxide (NO2), has been linked to mortality. It is unclear whether populations’ vulnerability to these pollutants has changed over time, and studies lack multi-country analyses. We therefore evaluated whether changes in exposure were associated with changes in mortality effect estimates over time. METHODS: We examined over 21·6 million cardiovascular and 7·7 million respiratory deaths in 380 cities across 24 countries between 1995 and 2016. We applied a two-stage approach to analyze the short-term effects of NO2, PM10, and PM2·5 on cause-specific mortality using city-specific time series regression analyses and multilevel random-effects meta-analysis. We assessed changes over time using a longitudinal meta-regression with time as a linear fixed term and explored potential sources of heterogeneity and two-pollutant models. FINDINGS: All three air pollutants showed decreasing concentrations over time. The pooled results suggested no significant temporal change in the effect estimates per unit exposure of PM10, PM2·5, or NO2 and mortality. However, the risk of cardiovascular mortality increased from 0·37% (95%CI: -0·05% to 0·80%) in 1998 to 0·85% (95%CI: 0·55% to 1·16%) in 2012 with a 10 µg/m3 increase in PM2·5. Two-pollutant models generally showed comparable results for PM fractions and indicated temporal differences for NO2. INTERPRETATION: Although air pollution levels have decreased, the effect sizes per unit increase have not changed. This might be due to the composition and toxicity, air pollution sources, but also other factors, such as socioeconomic determinants, or changes in population distribution and susceptibility

Air pollution mixture complexity and its effect on PM2.5-related mortality: a multi-country time-series study in 264 cities

Background: Fine particulate matter (PM2.5) occurs within a mixture of other pollutant gases that interact and impact its composition and toxicity. To characterise the local toxicity of PM2.5, it is useful to have an index that accounts for the whole pollutant mix, including gaseous pollutants. We consider a recently proposed pollutant mixture complexity index (PMCI) to evaluate to which extent it relates to PM2.5 toxicity. Methods: The PMCI is constructed as an index spanning seven different pollutant, relative to the PM2.5 levels. We consider a standard two-stage analysis using data from 264 cities in the Northern Hemisphere. The first-stage estimates the city-specific relative risks between daily PM2.5 and all-cause mortality, which are then pooled into a second-stage meta-regression model with which we estimate the effect modification from the PMCI. Results: We estimate a relative excess risk of 1.0042 (95%CI: 1.0023 - 1.0061) for an IQR increase (from 1.09 to 1.95) of the PMCI. The PMCI predicts a substantial part of within country relative risk heterogeneity with much less between-country heterogeneity explained. The AIC and BIC of the main model are lower than those of alternative meta-regression models considering the oxidative capacity of PM2.5 or its composition. Conclusions: The PMCI represents an efficient and simple predictor of local PM2.5-related mortality, providing evidence that PM2.5 toxicity depends on the surrounding gesous pollutant mix. With the advent of remote sensing for pollutants, the PMCI can provide a useful index to track air quality

The LoCALL App: learning to “read” the world while playing with linguistic landscapes

No abstract available.publishe

Whole-genome sequencing as a tool for studying the microevolution of drug-resistant serial Mycobacterium tuberculosis isolates

Treatment of drug-resistant tuberculosis requires extended use of more toxic and less effective drugs and may result in retreatment cases due to failure, abandonment or disease recurrence. It is therefore important to understand the evolutionary process of drug resistance in Mycobacterium tuberculosis. We here in describe the microevolution of drug resistance in serial isolates from six previously treated patients. Drug resistance was initially investigated through phenotypic methods, followed by genotypic approaches. The use of whole-genome sequencing allowed the identification of mutations in the katG, rpsL and rpoB genes associated with drug resistance, including the detection of rare mutations in katG and mixed populations of strains. Molecular docking simulation studies of the impact of observed mutations on isoniazid binding were also performed. Whole-genome sequencing detected 266 single nucleotide polymorphisms between two isolates obtained from one patient, suggesting a case of exogenous reinfection. In conclusion, sequencing technologies can detect rare mutations related to drug resistance, identify subpopulations of resistant strains, and identify diverse populations of strains due to exogenous reinfection, thus improving tuberculosis control by guiding early implementation of appropriate clinical and therapeutic interventions.JLCGD was a Fellow of Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), PEAS is a Fellow of Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) productivity. The study had financial support by Project CNPq/Universal (401963/2016–0), CAPES (PVE-CAPES, 88881.064961/2014–01) and Fundação para a Ciência e Tecnologia (FCT), Portugal [UID/DTP/04138/2019]. This work was carried out with the support of the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) to working mission within the scope of the Capes-Print Program, Financing Code 001". JP was supported by FCT through Estímulo Individual ao Emprego Científico [CEECIND/00394/2017]. JEP is funded by a Newton Institutional Links Grant (British Council, no. 261868591). TGC is funded by the Medical Research Council UK (Grant no. MR/M01360X/1, MR/N010469/1, MR/R025576/1, and MR/R020973/1) and BBSRC (Grant no. BB/R013063/1). SC is funded by Medical Research Council UK grants (ref. MR/M01360X/1, MR/R025576/1, and MR/R020973/1). AP is funded by a faculty baseline fund (BAS/1/1020-01-01) from KAUST.info:eu-repo/semantics/publishedVersio

Ozone-related acute excess mortality projected to increase in the absence of climate and air quality controls consistent with the Paris Agreement

DATA AND CODE AVAILABILITY : The projected data on temperature and ozone concentration can be obtained from the CMIP6 database (https://esgf-node.llnl.gov/search/cmip6/). The projected population data can be obtained from the Socioeconomic Data and Applications Center, Global 1-km Downscaled Population Base Year and Projection Grids Based on the SSPs, v1.01 (2000 – 2100): https://doi.org/10.7927/ q7z9-9r69. The historical baseline mortality and population data can be obtained from the United Nations’ World Population Prospects 2019 Report (https://population.un.org/wpp/Download/Standard/MostUsed/). Code used to generate the results are publicly available on Github (https://github. com/CHENlab-Yale/MCC_FutureO3). Any additional information required for reanalyzing the data reported in this paper is available from the lead contact upon reasonable request.Short-term exposure to ground-level ozone in cities is associated with increased mortality and is expected to worsen with climate and emission changes. However, no study has yet comprehensively assessed future ozone-related acute mortality across diverse geographic areas, various climate scenarios, and using CMIP6 multi-model ensembles, limiting our knowledge on future changes in global ozone-related acute mortality and our ability to design targeted health policies. Here, we combine CMIP6 simulations and epidemiological data from 406 cities in 20 countries or regions. We find that ozone-related deaths in 406 cities will increase by 45 to 6,200 deaths/year between 2010 and 2014 and between 2050 and 2054, with attributable fractions increasing in all climate scenarios (from 0.17% to 0.22% total deaths), except the single scenario consistent with the Paris Climate Agreement (declines from 0.17% to 0.15% total deaths). These findings stress the need for more stringent air quality regulations, as current standards in many countries are inadequate.The Swiss National Science Foundation, the Yale Planetary Solutions Project seed grant, the National Heart, Lung, and Blood Institute of the National Institutes of Health, the European Union’s Horizon 2020 Project Exhaustion and the Fundacao para a Ciencia e a Tecnologia.https://www.cell.com/one-earth/home2025-01-23hj2024Geography, Geoinformatics and MeteorologySDG-11:Sustainable cities and communitie