The compensatory reserve index (CRI), derived from machine learning algorithms from peripherally obtained photoplethysmography signals, provides a non-invasive assessment of cardiovascular stability, that may be useful clinically. Briefly, the CRI device provides a value between 0 and 1, with 1 reflecting full compensable capabilities and 0 reflecting little to no compensable capabilities. However, the CRI algorithm was developed in younger to middle aged adults, such that it is unknown if older age modulates CRI responses to cardiovascular challenges. In young and older subjects, we compared CRI responses to normothermic and hyperthermic progressive lower body negative pressure (LBNP), and volume loading with saline infusion. Eleven younger (20-36 years) and 10 older (61-75 years) healthy participants underwent (1) graded normothermic LBNP up to 30 mmHg, (2) graded hyperthermic (1.5°C increase in blood temperature) LBNP up to 30 mmHg, and (3) infusion of 15 mL/kg saline (volume loading) with hyperthermia maintained. CRI was obtained throughout each procedure. CRI at 30 mmHg LBNP was 0.18 and 0.24 units greater in the older group during normothermic and hyperthermic LBNP, respectively. However, CRI was not different between age groups at any other LBNP stage, nor did CRI change with volume loading regardless of age. In response to passive hyperthermia alone, regression analyses showed that heart rate was the strongest predictor of CRI. Blood temperature, rate pressure product, and stroke volume were also predictive of CRI but to a lesser extent. In conclusion, age attenuates the reduction in CRI during progressive normothermic and hyperthermic LBNP, but only at 30 mmHg. Second, the CRI was unchanged during volume loading in all subjects. Future studies should determine whether the age differences in CRI reflect age differences in LBNP tolerance.

BACKGROUND: Climate change increasingly impacts health, particularly of rural populations in sub-Saharan Africa due to their limited resources for adaptation. Understanding these impacts remains a challenge, as continuous monitoring of vital signs in such populations is limited. Wearable devices (wearables) present a viable approach to studying these impacts on human health in real time.
OBJECTIVE: The aim of this study was to assess the feasibility and effectiveness of consumer-grade wearables in measuring the health impacts of weather exposure on physiological responses (including activity, heart rate, body shell temperature, and sleep) of rural populations in western Kenya and to identify the health impacts associated with the weather exposures.
METHODS: We conducted an observational case study in western Kenya by utilizing wearables over a 3-week period to continuously monitor various health metrics such as step count, sleep patterns, heart rate, and body shell temperature. Additionally, a local weather station provided detailed data on environmental conditions such as rainfall and heat, with measurements taken every 15 minutes.
RESULTS: Our cohort comprised 83 participants (42 women and 41 men), with an average age of 33 years. We observed a positive correlation between step count and maximum wet bulb globe temperature (estimate 0.06, SE 0.02; P=.008). Although there was a negative correlation between minimum nighttime temperatures and heat index with sleep duration, these were not statistically significant. No significant correlations were found in other applied models. A cautionary heat index level was recorded on 194 (95.1%) of 204 days. Heavy rainfall (>20 mm/day) occurred on 16 (7.8%) out of 204 days. Despite 10 (21%) out of 47 devices failing, data completeness was high for sleep and step count (mean 82.6%, SD 21.3% and mean 86.1%, SD 18.9%, respectively), but low for heart rate (mean 7%, SD 14%), with adult women showing significantly higher data completeness for heart rate than men (2-sided t test: P=.003; Mann-Whitney U test: P=.001). Body shell temperature data achieved 36.2% (SD 24.5%) completeness.
CONCLUSIONS: Our study provides a nuanced understanding of the health impacts of weather exposures in rural Kenya. Our study\'s application of wearables reveals a significant correlation between physical activity levels and high temperature stress, contrasting with other studies suggesting decreased activity in hotter conditions. This discrepancy invites further investigation into the unique socioenvironmental dynamics at play, particularly in sub-Saharan African contexts. Moreover, the nonsignificant trends observed in sleep disruption due to heat expose the need for localized climate change mitigation strategies, considering the vital role of sleep in health. These findings emphasize the need for context-specific research to inform policy and practice in regions susceptible to the adverse health effects of climate change.

OBJECTIVE: Few studies used thermal quantitative sensory testing to assess the effects of repeated capsaicin gel administration in the oral cavity. This study aimed to investigate thermal sensory and pain thresholds before and after repeated capsaicin gel administration.
METHODS: Ten healthy females (22 ± 2 years) applied a capsaicin gel on the gingival mucosa twice daily for 14 days, and heat pain threshold, warm detection threshold, cold pain threshold, and cold detection threshold were assessed on the oral mucosa. Measurements were performed before and after the 14 days and were compared to a control sample (n = 10, all females, 23 ± 3 years).
RESULTS: Capsaicin increased heat pain threshold in the anterior maxilla by 2.9°C (95% CI: 1.6-4.2) (p < 0.001) and in the anterior mandible by 2.2°C (95% CI: 1.0-3.4) (p = 0.001), similar to warm detection threshold that increased by Δ1.1°C (95% CI: 0.3-1.9) (p = 0.009). No significant changes were found in the controls.
CONCLUSIONS: These findings encourage the use of thermal quantitative sensory testing in the oral cavity to assess thermal sensation, which might be useful for assessing the effects of therapies aimed at reducing pain.

Global climate change increases the likelihood of co-occurrence of hot and dry spells with increased intensity, frequency, and duration. Studying the impact of the two stresses provide a better understanding of tolerance mechanisms in wheat, and our study was focused on revealing plant stress responses to different severities of combined stress at two phenophases in old and modern wheat genotypes. During the stem elongation and anthesis stages, plants were exposed to four treatments: control, deficit irrigation, combined heat, and deficit irrigation at 31 °C (HD31) and 37 °C (HD37). The modern genotypes were less affected by deficit irrigation at stem elongation as they maintained higher photosynthesis, stomatal conductance, and leaf cooling than old genotypes. When the HD37 stress was imposed during anthesis, the modern genotypes exhibited superior performance compared to the old, which was due to their higher photosynthetic rates resulting from improved biochemical regulation and a higher chlorophyll content. The plant responses varied during two phenophases under the combined stress exposure. Genotypes subjected to HD37 stress during stem elongation, photosynthesis was mainly controlled by stomatal regulation, whereas at anthesis it was predominated by biochemical regulation. These findings contribute to a deeper comprehension of plant tolerance mechanisms in response to different intensities of co-occurring hot and dry weather conditions.

BACKGROUND: Some studies have found hot temperatures to be associated with exacerbations of schizophrenia, namely psychoses. As climate changes faster in Northern countries, our understanding of the association between temperature and hospital admissions (HA) for psychosis needs to be deepened.
OBJECTIVE: 1) Among adults diagnosed with schizophrenia, measure the relationship between mean temperatures and HAs for psychosis during summer. 2) Determine the influence of individual and ecological characteristics on this relationship.
METHODS: A cohort of adults diagnosed with schizophrenia (n = 30,649) was assembled using Quebec\'s Integrated Chronic Disease Surveillance System (QICDSS). The follow-up spanned summers from 2001 to 2019, using hospital data from the QICDSS and meteorological data from the National Aeronautics and Space Administration\'s (NASA) Daymet database. In four geographic regions of the province of Quebec, a conditional logistic regression was used for the case-crossover analysis of the relationship between mean temperatures (at lags up to 6 days) and HAs for psychosis using a distributed lag non-linear model (DLNM). The analyses were adjusted for relative humidity, stratified according to individual (age, sex, and comorbidities) and ecological (material and social deprivation index and exposure to green space) factors, and then pooled through a meta-regression.
RESULTS: The statistical analyses revealed a statistically significant increase in HAs three days (lag 3) after elevated mean temperatures corresponding to the 90th percentile relative to a minimum morbidity temperature (MMT) (OR 1.040; 95% CI 1.008-1.074), while the cumulative effect over six days was not statistically significant (OR 1.052; 95% IC 0.993-1.114). Stratified analyses revealed non statistically significant gradients of increasing HAs relative to increasing material deprivation and decreasing green space levels.
CONCLUSIONS: The statistical analyses conducted in this project showed the pattern of admissions for psychosis after hot days. This finding could be useful to better plan health services in a rapidly changing climate.

Ice slurry ingestion during prolonged exercises may improve performance in hot environments; however, the ideal amount and timing of ingestion are still uncertain. We determined whether ad libitum ice slurry ingestion influences physiological and perceptual variables and half-marathon performance while comparing the effects of the amount and moment of ingestion between ice slurry and water at 37 °C. Ten trained participants (28 ± 2 years; mean and SD) were required to run two half marathons while consuming either ice slurry (-1 °C; Ad-1) or water (37 °C; 37 CE) ad libitum. They then performed two other half marathons where, during one, they were required to ingest an amount of water equivalent to the amount consumed during the Ad-1 trial (Pro37), and in the other, to ingest ice slurry in the amount consumed during the 37 CE trial (Pro-1). During the half marathons, dry-bulb temperature and relative humidity were controlled at 33.1 ± 0.3 °C and 60 ± 3%, respectively. Ad-1 ingestion (349.6 ± 58.5 g) was 45% less than 37 CE ingestion (635.5 ± 135.8 g). Physical performance, heart rate, perceived exertion, body temperatures, and thermal perception were not influenced by the temperature or amount of beverage ingestion. However, a secondary analysis suggested that lower beverage ingestion was associated with improved performance (Ad-1 + Pro37 vs. 37 CE + Pro-1: -4.0 min, Cohen\'s d = 0.39), with a significant relationship between lower beverage ingestion and faster running time (b = 0.02, t = 4.01, p < 0.001). In conclusion, ice slurry ingestion does not affect performance or physiological or perceptual variables during a half marathon in a hot environment. Preliminary evidence suggests that lower beverage ingestion (ice slurry or warm water) is associated with improved performance compared to higher ingestion.

Nighttime heat is an important factor in heat-health outcomes, though nighttime heat exposure and its impacts are poorly understood. We assessed overnight heat in indoor (n = 12) and outdoor (n = 3) living spaces in Knoxville, Tennessee, using iButton Hygrochrons in August 2021. Indoor sleep spaces, all of which were air conditioned, reported a variety of overnight conditions. Indoor sleep spaces were both warmer and cooler than outdoor temperatures overnight, and some participants noted having physical health effects of overnight heat in their homes. Downtown outdoor sleep spaces, including a park and encampment, exhibited an urban heat island signal, staying warmer than other outdoor areas. Future research should focus on the intensity and length of the overnight recovery period for individuals and how that affects heat-health outcomes, especially after being exposed to daytime heat. Specifically, do homes reach a cool enough temperature for recovery, and do outdoor sleeping spaces offer a long enough and cool enough period for recovery? We provide some recommendations for such future studies, including (1) focus on purposeful sampling, (2) use deliberate sensor placement for representative results, (3) prepare for participant drop-off due to non-compliance and technological problems, and (4) strategically gather demographic information.

UNASSIGNED: Daily time-series regression models are commonly used to estimate the lagged nonlinear relation between temperature and mortality. A major impediment to this type of analysis is the restricted access to daily health records. The use of weekly and monthly data represents a possible solution unexplored to date.
UNASSIGNED: We temporally aggregated daily temperatures and mortality records from 147 contiguous regions in 16 European countries, representing their entire population of over 400 million people. We estimated temperature-lag-mortality relationships by using standard time-series quasi-Poisson regression models applied to daily data, and compared the results with those obtained with different degrees of temporal aggregation.
UNASSIGNED: We observed progressively larger differences in the epidemiological estimates with the degree of temporal data aggregation. The daily data model estimated an annual cold and heat-related mortality of 290,104 (213,745-359,636) and 39,434 (30,782-47,084) deaths, respectively, and the weekly model underestimated these numbers by 8.56% and 21.56%. Importantly, differences were systematically smaller during extreme cold and heat periods, such as the summer of 2003, with an underestimation of only 4.62% in the weekly data model. We applied this framework to infer that the heat-related mortality burden during the year 2022 in Europe may have exceeded the 70,000 deaths.
UNASSIGNED: The present work represents a first reference study validating the use of weekly time series as an approximation to the short-term effects of cold and heat on human mortality. This approach can be adopted to complement access-restricted data networks, and facilitate data access for research, translation and policy-making.
UNASSIGNED: The study was supported by the ERC Consolidator Grant EARLY-ADAPT (https://www.early-adapt.eu/), and the ERC Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.

UNASSIGNED: The seasonal fluctuation in mortality and hospital admissions from respiratory diseases, with a winter peak and a summer trough, is widely recognized in extratropical countries. However, little is known about the seasonality of inpatient mortality and the role of ambient temperature remains uncertain. We aimed to analyse the association between ambient temperature and in-hospital mortality from respiratory diseases in the provinces of Madrid and Barcelona, Spain.
UNASSIGNED: We used data on daily hospitalisations, weather (ie, temperature and relative humidity) and air pollutants (ie, PM2.5, PM10, NO2 and O3) for the Spanish provinces of Madrid and Barcelona during 2006-2019. We applied a daily time-series quasi-Poisson regression in combination with distributed lag non-linear models (DLNM) to assess, on the one hand, the seasonal variation in fatal hospitalisations and the contribution of ambient temperature, and on the other hand, the day-to-day association between temperature and fatal hospital admissions. The analyses were stratified by sex, age and primary diagnostic of hospitalisation.
UNASSIGNED: The study analysed 1 710 012 emergency hospital admissions for respiratory diseases (mean [SD] age, 60.4 [31.0] years; 44.2% women), from which 103 845 resulted in in-hospital death (81.4 [12.3] years; 45.1%). We found a strong seasonal fluctuation in in-hospital mortality from respiratory diseases. While hospital admissions were higher during the cold season, the maximum incidence of inpatient mortality was during the summer and was strongly related to high temperatures. When analysing the day-to-day association between temperature and in-hospital mortality, we only found an effect for high temperatures. The relative risk (RR) of fatal hospitalisation at the 99th percentile of the distribution of daily temperatures vs the minimum mortality temperature (MMT) was 1.395 (95% eCI: 1.211-1.606) in Madrid and 1.612 (1.379-1.885) in Barcelona. In terms of attributable burden, summer temperatures (June-September) were responsible for 16.2% (8.8-23.3) and 22.3% (15.4-29.2) of overall fatal hospitalisations from respiratory diseases in Madrid and Barcelona, respectively. Women were more vulnerable to heat than men, whereas the results by diagnostic of admission showed heat effects for acute bronchitis and bronchiolitis, pneumonia and respiratory failure.
UNASSIGNED: Unless effective adaptation measures are taken in hospital facilities, climate warming could exacerbate the burden of inpatient mortality from respiratory diseases during the warm season.
UNASSIGNED: European Research Council Consolidator Grant EARLY-ADAPT, European Research Council Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.

OBJECTIVE: To investigate the association between ambient temperature and preterm birth (PTB) and to estimate the population attributable fraction (PAF) of PTBs due to low and high temperatures.
METHODS: Time-stratified case-crossover design.
METHODS: Japan (46 prefectures, excluding Okinawa), 2011-2020.
METHODS: 214 050 PTBs registered in the Japan Perinatal Registry Network database among 1 908 168 singleton live births.
METHODS: A quasi-Poisson regression model with a distributed lag nonlinear model was employed to assess the associations between daily mean temperature and PTBs for a lag of 0-27 days in each prefecture. A random effects meta-analysis was conducted by combining effect estimates from the 46 prefectures to estimate pooled relative risks (RRs). The PAFs of the PTBs due to below or above the mean of the 46 median temperatures (16.0°C) were calculated.
METHODS: Preterm singleton live births.
RESULTS: The association between daily mean temperature and PTB risk exhibited a U-shaped curve. The adjusted RRs were 1.15 (95% confidence interval [CI] 1.05-1.25) at the mean of the 1st percentiles (0.8°C) and 1.08 (95% CI 1.00-1.17) at the mean of the 99th percentiles (30.2°C) of 46 prefectures, with 16.0°C as the reference temperature. Approximately 2.3% (95% CI 0.6-4.0) of PTBs were attributable to low temperatures.
CONCLUSIONS: Both low and possibly high temperatures were associated with an increased risk of PTBs. These findings may help to inform preventive measures for pregnant women.