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The purpose of the study was to investigate the quality and reliability of YouTube videos as a source of information in water treatments. We searched videos on YouTube ( www.youtube.com ) using the following keywords: "health resort medicine," "spa treatment," "spa therapy," "hydrotherapy," "thermal medicine," "balneology," and "balneotherapy" on June 17th, 2021. The global quality scale (GQS) was used to evaluate the quality of the videos. The assessment of reliability was evaluated using the modified DISCERN tool. Some other video parameters and sources of the videos were also recorded. One hundred twenty-one (121) videos were analyzed. The most common video source was advertisement (46.3%). GQS and modified DISCERN median scores were generally low. They were superior for "hydrotherapy" and "balneotherapy" and were also higher in videos uploaded by health-related persons or organizations (physicians, health-related professionals, and health-related websites). A statistically significant positive correlation was found between investigated parameters (like view ratio, number of likes, video power index, video length) and GQS. Only video length was correlated with modified DISCERN for investigated parameters. The median video power index scores were statistically higher for "spa therapy" and "spa treatment." The YouTube content linked with water treatments has poor quality and reliability most of time. The hydrotherapy and balneotherapy keywords have the best quality and reliability.We think that designers of water treatment videos should involve health professionals more often so that the content of their video will better explain the details of medical conditions or interventions.The scientific experts should ensure a consensus in terminology to straighten the awareness of water treatments for patients and physicians.

This paper analyses how recent trends in heat waves impact heat warning systems. We performed a retrospective analysis of the challenges faced by the French heat prevention plan since 2004. We described trends based on the environmental and health data collected each summer by the French heat warning system and prevention plan. Major evolutions of the system were tracked based on the evaluations organized each autumn with the stakeholders of the prevention plan. Excess deaths numbering 8000 were observed during heat waves between 2004 and 2019, 71% of these between 2015 and 2019. We observed major changes in the characteristics, frequency and the geographical spread of heat waves since 2015. Feedbacks led to several updates of the warning system such as the extension of the surveillance period. They also revealed that risk perception remained limited among the population and the stakeholders. The sharp increase in the number of heat warnings issued per year since 2015 challenges the acceptability of the heat warnings. Recent heat waves without historical equivalent interfere with the development of evidence-based prevention strategies. The growing public health impacts heat waves emphasize the urgent need to act to adapt the population, at different levels of intervention, from individual comportments to structural modifications. A specific attention should be given to increase the resources allocated to the evaluation and the management of heat-related risks, especially considering the needs to catch with the rapid rhythm of the changing climate. Supplementary Information The online version contains supplementary material available at 10.1007/s00484-021-02123-y.

Heat stress decreases human physical work capacity (PWC), but the extent to which solar radiation (SOLAR) compounds this response is not well understood. This study empirically quantified how SOLAR impacts PWC in the heat, considering wide, but controlled, variations in air temperature, humidity, and clothing coverage. We also provide correction equations so PWC can be quantified outdoors using heat stress indices that do not ordinarily account for SOLAR (including the Heat Stress Index, Humidex, and Wet-Bulb Temperature). Fourteen young adult males (7 donning a work coverall, 7 with shorts and trainers) walked for 1 h at a fixed heart rate of 130 beats∙min−1, in seven combinations of air temperature (25 to 45°C) and relative humidity (20 or 80%), with and without SOLAR (800 W/m2 from solar lamps). Cumulative energy expenditure in the heat, relative to the work achieved in a cool reference condition, was used to determine PWC%. Skin temperature was the primary determinant of PWC in the heat. In dry climates with exposed skin (0.3 Clo), SOLAR caused PWC to decrease exponentially with rising air temperature, whereas work coveralls (0.9 Clo) negated this effect. In humid conditions, the SOLAR-induced reduction in PWC was consistent and linear across all levels of air temperature and clothing conditions. Wet-Bulb Globe Temperature and the Universal Thermal Climate Index represented SOLAR correctly and did not require a correction factor. For the Heat Stress Index, Humidex, and Wet-Bulb Temperature, correction factors are provided enabling forecasting of heat effects on work productivity. Supplementary Information The online version contains supplementary material available at 10.1007/s00484-021-02205-x.

Temperature has been studied in relation to many health outcomes. However, few studies have explored its effect on the risk of hospital admission for rheumatoid arthritis (RA). A distributed lag non-linear model (DLNM) was used to analyze associations between mean temperature, diurnal temperature range (DTR), temperature change between neighboring days (TCN), and daily admissions for RA from 2015 to 2019 in Anqing, China. Subgroup analyses based on age, gender, rheumatoid factors, and admission route were performed. In total, 1456 patients with RA were hospitalized. Regarding the cumulative-lag effects of extreme cold temperature (5th percentile = 3℃), the risks of admissions for RA were increased and highest at lag 0–11 (RR = 2.68, 95% CI: 1.23–5.86). Exposing to low (5th percentile = 1.9℃) and high (95th percentile = 14.2℃) DTRs both had increased risks of RA admission, with highest RRs of 1.40 (95% CI: 1.03–1.91) and 1.24 (95% CI: 1.0–1.53) at lag 0 day, respectively. As for TCN, the marginal risk of admission in RA patients was found when exposed to high TCN (95th percentile = 2.9℃) with the largest single-day effect at lag 10 (RR = 1.11, 95% CI: 1.01–1.23). In subgroup analyses, females were more susceptible to extreme cold temperature, low and high DTRs, and high TCN. In regard to extreme cold temperature, significant risk of hospital admission in females only appeared at lag 2 (RR = 1.48, 95% CI: 1.02–2.15) and lag 0–2 (RR = 2.35, 95% CI: 1.11–4.95). It is clear that RA patients exposed to changing temperature may increase risks of admission. Supplementary Information The online version contains supplementary material available at 10.1007/s00484-021-02207-9.

The inter- and intra-annual variability in radial growth reflects responses to climatic variability and water shortage, especially in areas subjected to seasonal drought. However, it is unknown how this variability is related to forest productivity, which can be assessed by measuring changes in canopy greenness and cover through remote sensing products as the Normalized Difference Vegetation Index (NDVI). We combine xylogenesis with measurements of inter-annual changes in seasonal wood production (earlywood width, adjusted latewood width) and NDVI to improve the understanding of climate and drought impacts on growth and forest productivity in a Pinus teocote stand located in northern Mexico. Cambial dynamics accelerated in March and a high production of radially enlarging and thickening tracheids were observed from April to October and from June to October, respectively. Tracheid maturation was very active in October when latewood production peaked. Wet conditions in winter-spring and summer-autumn enhanced earlywood and latewood production, respectively. Earlywood and latewood were constrained by long (4–10 months) and short (2–3 months) droughts, respectively. The earlywood production depended on April soil moisture, which agrees with the peak of radially enlarging tracheid production found during that month. Aligning drought proxies at inter- and intra-annual scales by using growth and productivity measures improves our understanding of conifer forest responses to water shortage.

With the global warming, the harm of heat stress (HS) to the breeding industry has become more common, which causes the decline of animal production performance and low immunity. This study aimed to analyze the effect of HS on the intestinal immune function of Salmonella-infected chickens. Fourteen-day-old broilers were divided into the following four groups of eight replicates: control (Control), heat stress (HS), Salmonella Typhimurium (ST), and heat stress + Salmonella Typhimurium (HS+ST). The broilers were subjected to a heat stress of 35 °C from 15 to 28 days of age. Salmonella Typhimurium (ST, 14028, 109 cfu/mL) was inoculated, via oral administration at 29 days of age, into ST and HS+ST group birds. On the 4th day after Salmonella Typhimurium administration, an increase in jejunum IgA levels was observed in chickens infected with Salmonella Typhimurium. Mechanistic regulation of TLR4-NFκB-NLRP3 and TLR4-TBK1 signaling by heat stress was evaluated in Salmonella Typhimurium–infected broilers. Heat stress markedly inhibited the expression of cytokines including TNF-α, IL-6, IL-1β, NLRP3, caspase-1, NF-κB-p65, and p-NF-κB-p65, and the TLR4-TBK1 cytokines IFN-α, IFN-γ, p-IRF3, and p-TBK1 in jejunum of broilers infected with Salmonella Typhimurium. Collectively, our results demonstrate that heat stress can inhibit intestinal immune response by downregulating the expression of TLR4-NFκB-NLRP3 and TLR4-TBK1 signaling pathways in broilers infected with Salmonella Typhimurium.

Urban air pollution can have negative short- and long-term impacts on health, including cardiovascular, neurological, immune system and developmental damage. The irritant qualities of pollutants such as ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM) can cause respiratory and cardiovascular distress, which can be heightened during physical activity and particularly so for those with respiratory conditions such as asthma. Previously, research has only examined marathon run outcomes or running under laboratory settings. This study focuses on elite 5-km athletes performing in international events at nine locations. Local meteorological and air quality data are used in conjunction with race performance metrics from the Diamond League Athletics series to determine the extent to which elite competitors are influenced during maximal sustained efforts in real-world conditions. The findings from this study suggest that local meteorological variables (temperature, wind speed and relative humidity) and air quality (ozone and particulate matter) have an impact on athletic performance. Variation between finishing times at different race locations can also be explained by the local meteorology and air quality conditions seen during races.

Weather conditions regulate the growth and yield of crops, especially in rain-fed agricultural systems. This study evaluated the use and relative importance of readily available weather data to develop yield estimation models for maize and soybean in the US central Corn Belt. Total rainfall (Rain), average air temperature (Tavg), and the difference between maximum and minimum air temperature (Tdiff) at weekly, biweekly, and monthly timescales from May to August were used to estimate county-level maize and soybean grain yields for Iowa, Illinois, Indiana, and Minnesota. Step-wise multiple linear regression (MLR), general additive (GAM), and support vector machine (SVM) models were trained with Rain, Tavg, and with/without Tdiff. For the total study area and at individual state level, SVM outperformed other models at all temporal levels for both maize and soybean. For maize, Tavg and Tdiff during July and August, and Rain during June and July, were relatively more important whereas for soybean, Tavg in June and Tdiff and Rain during August were more important. The SVM model with weekly Rain and Tavg estimated the overall maize yield with a root mean square error (RMSE) of 591 kg ha−1(4.9%nRMSE) and soybean yield with a RMSE of 205 kg ha−1(5.5%nRMSE). Inclusion of Tdiff in the model considerably improved yield estimation for both crops; however, the magnitude of improvement varied with the model and temporal level of weather data. This study shows the relative importance of weather variables and reliable yield estimation of maize and soybean from readily available weather data to develop a decision support tool in the US central Corn Belt.

One of the major sources of uncertainty in large-scale crop modeling is the lack of information capturing the spatiotemporal variability of crop sowing dates. Remote sensing can contribute to reducing such uncertainties by providing essential spatial and temporal information to crop models and improving the accuracy of yield predictions. However, little is known about the impacts of the differences in crop sowing dates estimated by using remote sensing (RS) and other established methods, the uncertainties introduced by the thresholds used in these methods, and the sensitivity of simulated crop yields to these uncertainties in crop sowing dates. In the present study, we performed a systematic sensitivity analysis using various scenarios. The LINTUL-5 crop model implemented in the SIMPLACE modeling platform was applied during the period 2001–2016 to simulate maize yields across four provinces in South Africa using previously defined scenarios of sowing dates. As expected, the selected methodology and the selected threshold considerably influenced the estimated sowing dates (up to 51 days) and resulted in differences in the long-term mean maize yield reaching up to 1.7 t ha−1 (48% of the mean yield) at the province level. Using RS-derived sowing date estimations resulted in a better representation of the yield variability in space and time since the use of RS information not only relies on precipitation but also captures the impacts of socioeconomic factors on the sowing decision, particularly for smallholder farmers. The model was not able to reproduce the observed yield anomalies in Free State (Pearson correlation coefficient: 0.16 to 0.23) and Mpumalanga (Pearson correlation coefficient: 0.11 to 0.18) in South Africa when using fixed and precipitation rule-based sowing date estimations. Further research with high-resolution climate and soil data and ground-based observations is required to better understand the sources of the uncertainties in RS information and to test whether the results presented herein can be generalized among crop models with different levels of complexity and across distinct field crops.

There is substantial epidemiological evidence on the associations between cold weather and adverse health effects. Meteorological alarm systems are being developed globally, and generalized protective advice is given to the public based on outdoor exposure parameters. It is not clear how these shared outdoor exposure parameters relate to the individual-level thermal exposure indoors, where the majority of time is spent. We hypothesized a priori that there are opposite correlations between indoor and outdoor temperatures in residential apartments. Apartments were classified into 3 categories according to their response to declining outdoor temperature: under-controlled apartments cool down, controlled apartments maintain constant indoor temperature level, and over-controlled apartments warm up. Outdoor and indoor temperatures were measured in 30-min intervals in 417 residential apartments in 14 buildings in Kotka, Finland, between February and April 2018 with outdoor temperatures ranging from − 20.4 °C to + 14.0 °C. Different apartment types were present in all buildings. Floor and orientation did not explain the divergence. Indoor temperatures below the limit value + 20 °C by building code occurred in 26.2%, 7.9%, and 23.6% of the under-controlled, controlled, and over-controlled apartments, some in conjunction with increasing outdoor temperatures. Indoor temperatures above the limit + 25 °C occurred but were more rare. This proof-of-concept study demonstrates that while the home environment may be a source of thermal stress during cold weather, generalized advice for adjusting the heating may lead to paradoxical exposures in some cases. More elaborate conceptualizations of everyday thermal exposures are needed to safely reduce weather-related health risks using shared meteorological alarm systems. Electronic supplementary material The online version of this article (10.1007/s00484-020-01998-7) contains supplementary material, which is available to authorized users.

Low back pain (LBP) is one of the most costly diseases in the developed world. This study aimed to investigate the effects of underwater traction therapy on chronic low back pain. The primary objective was to prove that underwater traction therapy has favorable effects on LBP. Our secondary objective was to evaluate whether it also leads to improvement in the quality of life. This is a prospective, multicenter, follow-up study. A total of 176 patients with more than 3 months of low back pain enrolled from outpatient clinics were randomized into three groups: underwater weight bath traction therapy and non-steroidal anti-inflammatory drugs (NSAIDs); weight bath; and only NSAIDs. The following parameters were measured before, right after, and 9 weeks after the 3-week therapy: levels of low back pain in rest and during activity were tested using the visual analogue scale (VAS), the Oswestry Low Back Disability Questionnaire, and the EuroQol-5D-5L Questionnaire.The VAS levels improved significantly (p Based on our results, for patients suffering from LBP pain who underwent underwater weight bath traction therapy, there were favorable impacts on the pain levels at rest or during activity. Clinical trial registration ID: NCT03488498, April 5, 2018

To investigate the effect of balneotherapy on body mass index, adipokine levels, sleep disturbances, and quality of life in women with morbid obesity. Fifty-four women with morbid obesity were included in the study. The body mass indexes (BMI) and waist/hip ratios (WHR) of the women were calculated. Subcutaneous fat thickness was measured using a *skinfold meter, and the percentage of adipose tissue was calculated. The *Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality, and the Nottingham Health Profile (NHP) was used to assess quality of life. In addition to routine biochemical tests, leptin, adipokine, visfatin from blood, and cortisol from saliva samples were studied. Participants were given 15 sessions of balneotherapy for 20 min each. After treatment, the laboratory and clinical parameters of the participants were *reevaluated. There was no statistically significant difference of BMI, WHR, and percentage of adipose tissue between before and after treatment measurements (p ˃ 0.05).There was a statistically significant improvement in PSQI and NSP scores (p ˂ 0.001). The levels of blood glucose, leptin, and visfatin were significantly decreased, and adiponectin was significantly increased after treatment (p = 0.047, p ˂ 0.001, p ˂ 0.001, and p ˂ 0.001, respectively).There was no statistically significant changes in salivary cortisol levels (p = 0.848). Patients with diabetes showed a statistically significant decrease in glucose levels after treatment (p = 0.017).There was a statistically significant decrease in low-density lipoprotein cholesterol levels in patients with dyslipidemia compared with pre-treatment (p = 0.018). Balneotherapy improves sleep and quality of life of women with morbid obesity. After balneotherapy, glucose, leptin, adiponectin, and visfatin levels may change positively. © 2020, ISB.

The aim of this paper is to analyze the relationship between North Atlantic Oscillation (NAO), meteorological variables, air pollutants, and hospital admissions due to diseases of circulatory systems in Lisbon (Portugal) during winter months (2003–2012). This paper is one of the few studies analyzing the impact of NAO on health through its influence on thermal stress and air pollution and is the first to be conducted in Lisbon. This study uses meteorological data (synthetized into a thermal comfort index), air pollutant metrics, and the NAO index (all clustered in 10-day cycles to overcome daily variability of the NAO index). The relationship between morbidity, thermal comfort index, NAO index, and air pollutants was explored through several linear models adjusted to seasonality through a periodic function. The possible indirect effect between the NAO index and hospital admissions was tested, assuming that NAO (independent variable) is affecting hospital admissions (outcome variable) through thermal discomfort and/or pollution levels (tested as individual mediators). This test was conducted through causal mediation analysis and adjusted for seasonal variation. The results from this study suggest a possible indirect relationship between NAO index and hospital admissions. Although NAO is not significantly associated with hospital admissions, it is significantly associated with CO, PM2.5, NO, and SO2 levels, which in turn increase the probability of hospitalization. The discomfort index (built with temperature and relative humidity) is significantly associated with hospital admissions, but its variability is not explained by the NAO index. This study highlights the impacts of the atmospheric circulation patterns on health. Furthermore, understanding the influence of the atmospheric circulation patterns can support the improvement of the existing contingency plans. info:eu-repo/semantics/publishedVersion

Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future. Here, we present a new method for creating realistic climate forcing for manipulation experiments and apply it to the UHasselt Ecotron experiment. The new methodology uses data derived from the best available regional climate model projection and consists of generating climate forcing along a gradient representative of increasingly high global mean air temperature anomalies. We first identified the best-performing regional climate model simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European domain (EURO-CORDEX) ensemble based on two criteria: (i) highest skill compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. The time window is subsequently selected from the model projection for each ecotron unit based on the global mean air temperature of the driving global climate model. The ecotron units are forced with 3-hourly output from the projections of the 5-year period in which the global mean air temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The presented methodology can also be applied to other manipulation experiments, aiming at investigating ecosystem responses to realistic future climate change., International Journal of Biometeorology, 64, ISSN:0020-7128, ISSN:1432-1254

In this study, we addressed potential biases which can occur when sensorial scores of temperature, wetness and discomfort are repeatedly reported, in transient exercise conditions. We pointed out that, when repeatedly reported, previous sensorial scores can be set by the participants as reference values and the subsequent score may be given based on the previous point of reference, the latter phenomenon leading to a bias which we defined as 'anchoring bias'. Indeed, the findings shown that subsequent sensorial scores are prone to anchoring biases and that the bias consisted in a systematically higher magnitude of sensation as compared to when reported a single time only. As such, the study allowed recognition, quantification and mitigation of the identified bias which can improve the methodological rigour of research studies involving assessments of sensorial data in transient conditions.

Allergenic ragweed (Ambrosia spp.) pollen grains, after being released from anthers, can be dispersed by air masses far from their source. However, the action of air temperature, humidity and solar radiation on pollen grains in the atmosphere could impact on the ability of long distance transported (LDT) pollen to maintain allergenic potency. Here, we report that the major allergen of Ambrosia artemisiifolia pollen (Amb a 1) collected in ambient air during episodes of LDT still have immunoreactive properties. The amount of Amb a 1 found in LDT ragweed pollen grains was not constant and varied between episodes. In addition to allergens in pollen sized particles, we detected reactive Amb a 1 in subpollen sized respirable particles. These findings suggest that ragweed pollen grains have the potential to cause allergic reactions, not only in the heavily infested areas but, due to LDT episodes, also in the regions unaffected by ragweed populations. Electronic supplementary material The online version of this article (doi:10.1007/s00484-016-1139-6) contains supplementary material, which is available to authorized users.

A birch pollen emission model is described and its main features are discussed. The development of the model is based on a double-threshold temperature sum model that describes the propagation of the flowering season and naturally links to the thermal time models to predict the onset and duration of flowering. For the flowering season, the emission model considers ambient humidity and precipitation rate, both of which suppress the pollen release, as well as wind speed and turbulence intensity, which promote it. These dependencies are qualitatively evaluated using the aerobiological observations. Reflecting the probabilistic character of the flowering of an individual tree in a population, the model introduces relaxation functions at the start and end of the season. The physical basis of the suggested birch pollen emission model is compared with another comprehensive emission module reported in literature. The emission model has been implemented in the SILAM dispersion modelling system, the results of which are evaluated in a companion paper.

The main goal of this paper is to estimate how the observed and predicted climate changes may affect the development rates and emergence of the codling moth in the southern part of the Wielkopolska region in Poland. In order to simulate the future climate conditions one of the most frequently used A1B SRES scenarios and two different IPCC climate models (HadCM3 and GISS modelE) are considered. A daily weather generator (WGENK) was used to generate temperature values for present and future climate conditions (time horizons 2020-2040 and 2040-2060). Based on the generated data set, the degree-days values were then calculated and the emergence dates of the codling moth at key stages were estimated basing on the defined thresholds. Our analyses showed that the average air surface temperature in the Wielkopolska region may increase from 2.8°C (according to GISS modelE) even up to 3.3°C (HadCM3) in the period of 2040-2060. With the warming climate conditions the cumulated degree-days values may increase at a rate of about 142 DD per decade when the low temperature threshold (T(low)) of 0°C is considered and 91 DD per decade when T(low) = 10°C. The key developmental stages of the codling moth may occur much earlier in the future climate conditions than currently, at a rate of about 3.8-6.8 days per decade, depending on the considered GCM model and the pest developmental stage. The fastest changes may be observed in the emergence dates of 95% of larvae of the second codling moth generation. This could increase the emergence probability of the pest third generation that has not currently occurred in Poland.

An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission module parameterisation and to the meteorological input data. The most important parameters are highlighted. The reference year considered for the analysis is 2006. It is shown that the model is capable of predicting about two-thirds of allergenic alerts, with the odds ratio exceeding 12 for the best setup. Several other statistics corroborate with these estimations. Low-pollen concentration days are also predicted correctly in more than two-thirds of cases. The model experiences certain difficulties only with intermediate pollen concentrations. It is demonstrated that the most important input parameter is the near-surface temperature, the bias of which can easily jeopardise the results. The model sensitivity to random fluctuations of temperature is much lower. Other parameters important at various stages of pollen development, release, and dispersion are precipitation and ambient humidity, as well as wind direction.