International Journal of Biometeorology最新文献

In 2014 the authors published a review and meta-analysis on the effectiveness of balneotherapy in Hungary based on articles by Hungarian authors issued until 2012. Now they prepared a new review and meta-analysis based on the updated database of the Hungarian articles published after 2012. A total of 18 articles were included in the new meta-analysis; with a subset having been previously incorporated in the earlier analyses. In such a way the results became more convincing. Regarding the updated systematic review (period: 2012–2025), the number of papers was 14. Regarding the meta-analysis (period: 1989–2025), the number of papers was 18 (8 + 10 = 18). The meta-analysis showed a significant reduction of pain at rest and pain on load evaluated by visual analogue scale (VAS) score and of the quality of life evaluated by the EuroQol-5D (EQ-5D) questionnaire and indexed by the EQ-VAS and the EQ-5D index. Even accounting for the heterogeneity of the studies, which is a source of bias, based on the results we can say the Hungarian studies’ results are promising regarding the positive effect of balneotherapy, especially in the treatment of degenerative locomotor diseases.

Respiratory diseases are increasingly influenced by meteorological variability, yet few studies have applied high-resolution environmental data and advanced forecasting models to quantify this relationship in climate-sensitive regions such as southern China. This study aims to characterize how climate variability drives respiratory disease dynamics by quantifying the influence of meteorological factors and constructing predictive models for early intervention. It further seeks to advance climate-resilient health surveillance through the application of machine learning and time-series forecasting techniques. A longitudinal dataset comprising daily meteorological indicators (temperature, humidity, precipitation, wind speed, atmospheric pressure, air quality index) and annual respiratory disease incidence was analyzed. Feature engineering, dimensionality reduction via Principal Component Analysis (PCA), and temporal lags were applied. Predictive models—Random Forest, Support Vector Regression (SVR), Long Short-Term Memory (LSTM), and Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors (SARIMAX)—were evaluated using coefficient of determination (R²), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). Variable importance and Pearson correlation were used to interpret model behavior and epidemiological relevance. Respiratory incidence showed marked interannual fluctuations, with notable peaks in 2014, 2018, 2022, and 2024. Random Forest identified total precipitation (27%), average temperature (22%), and relative humidity (18%) as the most influential predictors. Air quality and wind speed also contributed to model accuracy. LSTM and SARIMAX models achieved high fidelity in forecasting both long-term and weekly trends, with low residual variance and strong temporal alignment with observed case data. This study provides strong empirical evidence that respiratory disease patterns in Baise City are closely linked to meteorological conditions. The integration of machine learning and time-series modeling establishes a scalable framework for real-time forecasting and early detection of climate-sensitive health risks. These findings advance the frontier of climate-health analytics and offer actionable pathways for embedding environmental intelligence into public health policy, resource planning, and resilience-building strategies in vulnerable regions.

The summer of 2025 has been the hottest in Spain since records began, 2022registering temperatures one tenth of a degree Celsius higher than the hottest on record to date, i.e., the summer of 2022. However, mortality attributable to heat wave temperatures in 2025 was 908 deaths fewer than in 2022. Of the many factors that may have influenced the reduction in attributable mortality in 2025 with respect to 2022, this study sought to analyse the possible impact of an improvement made to heat-wave prevention plans in the form of enhancing the geographical resolution of health alerts. Using the annual heat wave intensity registered and the annual mortality attributable to these heat waves, a linear adjustment between these two variables was performed for all Spanish provinces in the above two periods. The results indicated that whereas the increase in annual mortality for every one-degree rise in annual heat wave intensity (mean slope of the lines of fit for Spain as a whole) from 2015 to 2023 was 1.74 deaths/⁰C, in the period 2024–2025 it was 1.66 deaths/⁰C. This result translates as follows: if annual attributable mortality in Spain were calculated for 2025 using the values of the slopes for the first period, this would yield a total of 4,082 attributable deaths, but if this same attributable mortality were calculated using the values of the slope corresponding to the 2024–2025 period, this would yield a total of 3,894 deaths. In conclusion, although this analysis has not taken into account many factors that could relate heat wave intensity to temperature-attributable mortality, the activation of heat wave thresholds in prevention plans at a smaller geographical scale could lead to a reduction in attributable mortality.

Extreme high-altitude environments pose significant challenges to both physiological adaptation and mental health. This study aimed to characterize the dynamic relationship between Acute Mountain Sickness (AMS) and psychological health, identifying symptom-level drivers of psychological distress in mountaineers. Fifteen mountaineers participating in three expeditions were assessed one week before ascent, upon arrival at high altitude, immediately post-climb, and one week after. The expeditions covered a maximum altitude range of 5276 m to 6621 m (Erfeng of Siguniang Mountain: 5276 m, 4 days; Mount Wukuchu: 5526 m, 6 days; Mount Geladandong: 6621 m, 9 days). Linear Mixed Models (LMM) were employed to isolate the effects of AMS status from environmental confounders, and Generalized Estimating Equations (GEE) were used to identify specific symptom-level predictors of psychological outcomes. LMM analysis revealed that AMS-positive status significantly impaired overall mental health (p = 0.009). Specifically, AMS led to significant elevations in somatization, obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, and hostility (all p < 0.05). Notably, AMS specifically exacerbated mental fatigue (p = 0.022) but had no significant impact on physical fatigue or general affect. GEE scanning further identified symptom-specific drivers: headache was a pervasive predictor of somatization and interpersonal sensitivity, while dizziness emerged as the most robust predictor of physical fatigue (p = 0.002). AMS primarily drives specific pathological psychological distress and mental exhaustion rather than generalized mood fluctuations. These findings underscore the necessity of symptom-specific psychological monitoring during high-altitude adaptation.

This study aimed to describe the skin phototypes of the sampled population in a region of the Brazilian Amazon using the Fitzpatrick scale, as well as to investigate sun exposure habits and associate photoprotection practices with socioeconomic vulnerability conditions. Data were obtained from a household survey conducted in 2022 by Community Health Agents of three Municipal Health Departments, covering 1,442 urban adults. Descriptive statistics, Pearson’s Chi-squared test with Yates’ correction, and Odds Ratios were applied to assess associations between socioeconomic vulnerability and photoprotection practices. Results showed a predominance of melano-protected phototypes (V and VI, 49.2%), followed by melano-competent (III and IV, 43.9%) and melano-compromised (I and II, 7%). While lighter phototypes often adopt sun protection, darker phototypes face greater exposure linked to work and culture. Sunscreen adherence was low across all phototypes, with alternative methods, such as wearing hats and clothing, being more common. Socioeconomic vulnerability increased the likelihood of not adopting photoprotection practices by 2.28 times. These findings highlight that low sunscreen adherence, combined with socioeconomic vulnerability, substantially increases the risk of inadequate photoprotection in the Brazilian Amazon.

Air pollution, primarily resulting from industrial activities and the combustion of fossil fuels, poses a significant health risk in Arak due to elevated levels of PM_2.5 and ozone. This study aims to quantify the health impacts of these pollutants and assess the potential benefits that could be realized through a reduction in their concentrations. The study employs the World Health Organization (WHO) AirQ⁺ and the Environmental Protection Agency’s BenMAP-CE models to estimate the number of premature deaths and illnesses associated with exposure to PM_2.5 and O₃ in Arak from 2017 to 2019. Data from air quality monitoring stations were analyzed, and health impact functions were used to assess the mortality rates linked to each pollutant. During 2017–2019, PM_2.5 concentrations exceeding WHO guidelines were associated with an estimated 729 (95% CI: 499–947), 654 (95% CI: 447–851), and 460 (95% CI: 313–602) premature deaths in 2017, 2018, and 2019, respectively, among adults aged ≥ 30 years (approximately 294,000–298,000 individuals). Achieving the WHO annual PM_2.5 guideline (10 µg/m³) could prevent an average of 614 premature deaths per year in this population, while a uniform 30% reduction in O₃ concentrations over the study period could avert approximately 145 additional deaths. The AirQ + and BenMAP-CE models produced comparable results, confirming their effectiveness in health impact assessments. These findings underscore the urgent need for the implementation of effective air quality management policies in Arak and highlight the health impacts associated with air pollution.

Various methods, including balneotherapy, are employed in the management of patients with chronic pain. This research investigated the effect of the predominance of central sensitization on responses to balneotherapy applied together with conventional physical therapy in patients with chronic low back and knee pain. This prospective study included 75 patients with chronic low back or knee pain, classified as having predominant central sensitization (n = 35) or not (n = 40). All participants received a three-week course of whole-body balneotherapy combined with conventional physical therapy, including transcutaneous electrical nerve stimulation, hot pack, and therapeutic ultrasound. Pain intensity, as the primary outcome, was assessed using the visual analogue scale (VAS), while quality of life and emotional status were evaluated using the Short Form-12 (SF-12) and the Hospital Anxiety and Depression Scale (HADS), respectively. Disability associated with chronic pain was evaluated using the Roland Morris Disability Questionnaire in patients with low back pain and the Knee Injury and Osteoarthritis Outcome Score (KOOS) in those with knee pain. Changes in outcomes over time and between groups were analyzed using linear mixed-effects models. Improvement in the VAS, SF-12 Physical and Mental Component, HADS-Depression, and HADS-Anxiety scores was observed in both groups post-treatment (between p < 0.01 and p = 0.015). Also, post-treatment improvement in disability scores was observed in both groups (between p < 0.01 and 0.021). Group × time interaction was observed only for the SF-12 mental component score, in favor of the predominant central sensitization group (ΔΔ = 5.95, 95% CI 1.31 to 10.59, p = 0.013). No significant group × time interaction was observed for other outcomes (range: 0.10–0.97). Applied together with physical therapy agents with balneotherapy can reduces pain severity and disability levels, and increases their quality of life in patients with chronic pain with and without predominant central sensitization. Improvements in mental health–related quality of life were more pronounced in patients with predominant central sensitization.

The climatic conditions of northeastern Brazil can induce heat stress, reducing the weight, production, and reproductive rates of sheep. This study aimed to analyze the dynamics of abiotic factors, comfort indices on the seminal quality of Dorper sheep under normal local meteorological conditions and adiabatic evaporative cooling. The study involved 20 rams aged 18 ± 2 months, weighing an average of 70 ± 3 kg, raised in a semiarid region of Brazil from April to June 2023. The animals were kept in an open pen for 22 days and for 43 days under the influence of an adiabatic evaporative cooling system (AECS). Air temperature (AT, ºC), relative humidity (RH, %), and black globe temperature (BGT, ºC) were monitored every 15 min daily, with semen collected and analyzed every three weeks, totaling four collections. Thermal characterization of the pen was determined by temperature and humidity indices, black globe temperature and humidity, and specific enthalpy (kJ kg-1). Semen characteristics were analyzed using a completely randomized design with two treatments and 20 replicates, with means compared using the t-test (p ≤ 0.05). Meteorological variables and comfort indices underwent descriptive statistical analysis. Principal Component Analysis (PCA) was applied to these variables and seminal characteristics. During the driest periods, AECS increased pen RH by 8% and reduced AT by 1.24 °C, maintaining THI values below critical levels. The PCA revealed that only sperm plasma membrane integrity (PMI) significantly responded to environmental changes, increasing by 16% during AECS operation, allowing a regression model with R² greater than 0.72 for estimating PMI.

Climate change is rapidly reshaping species distributions and threatening ecosystem services, yet continent-wide forecasts for Neotropical hoverflies are virtually absent. Here, we present the first large-scale ecological niche modeling assessment for Dioprosopa clavata (Fabricius, 1794), a key syrphid with dual ecological roles in pollination and aphid control. Using 1,214 curated occurrences and an ensemble of MaxEnt, DOMAIN, and GLM, we combined climatic and physiographic predictors (elevation, compound topographic index, profile curvature) to project suitability under SSP2–4.5 (intermediate) and SSP5–8.5 (high-end) scenarios for 2021–2040 and 2081–2100. Models showed excellent predictive performance, with climate explaining ~ 71% of model contribution and physiography ~ 29%, highlighting the buffering role of topographic heterogeneity. Near-term projections retained most of the current range (≈ 88–89% stability), but late-century forecasts revealed dramatic contractions, up to 43.5% habitat loss under SSP5–8.5, particularly in tropical lowlands of northern South America and Central America. These losses were accompanied by increased spatial fragmentation and modest poleward and upslope gains, suggesting climate-driven range shifts toward cooler, higher-elevation refugia. Our findings indicate that D. clavata habitats will decline most severely where pollination and pest control services are most needed, agricultural regions of tropical South America, potentially reducing local ecosystem service provision. By identifying priority areas for connectivity and microclimatic refugia, this study offers a mechanical aware forecast and actionable hypotheses to guide field validation, monitoring programs, and climate-smart conservation strategies for an understudied yet functionally crucial pollinator group.

The Universal Thermal Climate Index (UTCI) was used to estimate thermal stress for humans in the South Shetland Islands (West Antarctica), the region in Antarctica with the highest number of scientific stations and visiting tourists. This was done to analyze the duration of comfortable weather conditions, which are crucial for conducting fieldwork and other outdoor tasks. The UTCI is one of the most commonly used climate thermal indices, but it had not previously been calculated for any region in Antarctica. The research was based on hourly data (air temperature, humidity, global solar radiation and wind speed) derived from the Henryk Arctowski Polish Antarctic Station between 2013 and 2023. The range of hourly UTCI values indicates conditions ranging from no thermal stress to extreme cold stress, with predominant strong cold stress (–26.9 to − 13.0 °C; 40.5% of cases) and very strong cold stress (–39.9 to − 27.0 °C; 25.3% of cases). In such conditions, it is recommended that physical activity is increased and that the extremities and face are protected from the cold while working outside, as well as increasing the thermo-isolation properties of clothing. The same thermal stress class remains for more than one day sporadically. The most favourable conditions for spending time outside (without thermal stress or with slight cold stress), which lasted 7–9 consecutive hours, occurred rarely and only from December to March. Due to high wind speed, some UTCI values fall outside the thermal stress scale; nevertheless, the authors classified these as extreme cold stress and suggest developing the UTCI formula to make it more applicable in regions where very high wind speed occur.