Pub Date : 2025-09-06eCollection Date: 2025-01-01DOI: 10.1080/23328940.2025.2548137
{"title":"About the Cover.","authors":"","doi":"10.1080/23328940.2025.2548137","DOIUrl":"https://doi.org/10.1080/23328940.2025.2548137","url":null,"abstract":"","PeriodicalId":36837,"journal":{"name":"Temperature","volume":"12 3","pages":"201"},"PeriodicalIF":0.0,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-17eCollection Date: 2025-01-01DOI: 10.1080/23328940.2025.2514959
Chloe Brimicombe, Debra Jackson, Ilona M Otto
{"title":"Heat impacts on child mortality differ across seasons and countries: <b>Comment on</b>: Brimicombe C, Wieser K, Monthaler T, Jackson D, De Bont J, Chersich MF, Otto IM. Effects of ambient heat exposure on risk of all-cause mortality in children younger than 5 years in Africa: a pooled time-series analysis. Lancet Planet Health. 2024;8(9):e640-e646. doi: 10.1016/S2542-5196(24)00160-8.","authors":"Chloe Brimicombe, Debra Jackson, Ilona M Otto","doi":"10.1080/23328940.2025.2514959","DOIUrl":"https://doi.org/10.1080/23328940.2025.2514959","url":null,"abstract":"","PeriodicalId":36837,"journal":{"name":"Temperature","volume":"12 3","pages":"206-208"},"PeriodicalIF":0.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-05eCollection Date: 2025-01-01DOI: 10.1080/23328940.2025.2508534
Robin de Korver, Boris R M Kingma, George Havenith, Kalev Kuklane, Glen P Kenny, Robert D Meade, Arjan J H Frijns
Sweating is a vital thermoregulatory mechanism in humans for maintaining thermal balance during exercise and exposure to hot environments. The development of models that predict sweat rate based on body temperature has been ongoing for over half a century. Here, we compared predicted water loss rates (WLR) from these models to actual observations collected during 780 participant-exposures in three independent laboratory-based experiments. In these experiments, male participants aged 19-50 years cycled or walked at various intensities (metabolic heat productions between 200 and 970 W), in air temperatures ranging from -40°C to 50°C, relative humidities (14% to 95%), and air velocities (<0.2 to 10 m/s), while wearing different clothing ensembles (thermal insulation 0.20 to 3.75 clo). The models' performances were evaluated by the coefficient of determination (R2) and Root Mean Square Error (RMSE). Performance varied greatly with a maximum R2 value of 0.5 and RMSE values ranging from 10.4 to 4.9 g/min. Models with a lower sweat onset core temperature setpoint performed better and most models generally underestimated the water loss at higher WLR. Optimization of the core and skin temperature setpoints suggests preferred core temperature setpoints within a narrow range (36.2°C to 36.6°C). Even with optimized inputs, R2 values were around 0.5, meaning only 50% of the variance in observed WLR was explained by the models. Better model consideration of relations between body temperature and sweat rate, and the incorporation of non-thermal exercise-induced sweat promotion, may reduce model underpredictions at higher exercise intensities.
{"title":"Humans exercising in the heat: A review on sweat models and a comparison to recent experimental datasets.","authors":"Robin de Korver, Boris R M Kingma, George Havenith, Kalev Kuklane, Glen P Kenny, Robert D Meade, Arjan J H Frijns","doi":"10.1080/23328940.2025.2508534","DOIUrl":"10.1080/23328940.2025.2508534","url":null,"abstract":"<p><p>Sweating is a vital thermoregulatory mechanism in humans for maintaining thermal balance during exercise and exposure to hot environments. The development of models that predict sweat rate based on body temperature has been ongoing for over half a century. Here, we compared predicted water loss rates (WLR) from these models to actual observations collected during 780 participant-exposures in three independent laboratory-based experiments. In these experiments, male participants aged 19-50 years cycled or walked at various intensities (metabolic heat productions between 200 and 970 W), in air temperatures ranging from -40°C to 50°C, relative humidities (14% to 95%), and air velocities (<0.2 to 10 m/s), while wearing different clothing ensembles (thermal insulation 0.20 to 3.75 clo). The models' performances were evaluated by the coefficient of determination (R<sup>2</sup>) and Root Mean Square Error (RMSE). Performance varied greatly with a maximum R<sup>2</sup> value of 0.5 and RMSE values ranging from 10.4 to 4.9 g/min. Models with a lower sweat onset core temperature setpoint performed better and most models generally underestimated the water loss at higher WLR. Optimization of the core and skin temperature setpoints suggests preferred core temperature setpoints within a narrow range (36.2°C to 36.6°C). Even with optimized inputs, R<sup>2</sup> values were around 0.5, meaning only 50% of the variance in observed WLR was explained by the models. Better model consideration of relations between body temperature and sweat rate, and the incorporation of non-thermal exercise-induced sweat promotion, may reduce model underpredictions at higher exercise intensities.</p>","PeriodicalId":36837,"journal":{"name":"Temperature","volume":"12 3","pages":"209-230"},"PeriodicalIF":0.0,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-03eCollection Date: 2025-01-01DOI: 10.1080/23328940.2025.2508489
Yosuke Nagashima, Teruhiko Hisaoka, Tomonori Sato, Yoshitomo Ehara, Akiko Horikawa, Akiyo Shiohara, Ayana Mitsume, Shigeru Mineo, Hiroaki Yoshida
The associated factors for exertional heat stroke among amateur golfers remain poorly understood. We conducted a case-control study to examine exertional heat exhaustion (EHE) - related symptoms among amateur golfers in Japan using a self-administered questionnaire. Retrospective case-control study design. A web-based questionnaire was administered from September to November 2024. Data were collected on basic attributes, lifestyle habits, perceived health factors, perceived playing conditions, changes in eating behavior, and EHE-related symptoms. We performed a case-control analysis using a multivariate conditional logistic regression model. The explanatory variables included lifestyle habits, health factors, playing conditions, and eating behavior; the objective variables were EHE-related symptoms. Our study included 194 participants with EHE-related symptoms and 252 control participants. The following factors were significantly associated with EHE symptoms: perceived dehydration (adjusted odds ratio [AOR], 4.65, 95% confidence intervals (CI) 3.08-7.03); sleep deprivation (AOR, 4.38, 95% CI 2.84-6.77); loss of appetite (AOR, 4.32, 95% CI 2.84-6.58); accumulated fatigue (AOR, 3.26 95% CI 1.17-1.31); mental stress (AOR, 2.71, 95% CI 1.78-4.12); average rounds of golf (AOR 1.88, 95% CI 1.14-3.13); increased sports drink consumption (AOR 2.07, 95% CI 1.20-3.56); increased consumption of salt tablets and candies (AOR 1.99, 95% CI 1.29-3.05); and increased dietary supplement intake (AOR, 1.88, 95% CI 1.14-3.11).These findings suggest that amateur golfers should assess their physical condition before play and adjust their schedules accordingly, particularly in hot weather, to minimize the risk of heat-related illnesses.
业余高尔夫球手中暑的相关因素仍然知之甚少。我们进行了一项病例对照研究,使用自我管理的问卷调查日本业余高尔夫球手的劳累性中暑(EHE)相关症状。回顾性病例对照研究设计。在2024年9月至11月期间进行了一份基于网络的问卷调查。收集了基本属性、生活习惯、感知健康因素、感知游戏条件、饮食行为变化和ehe相关症状的数据。我们使用多变量条件逻辑回归模型进行病例对照分析。解释变量包括生活习惯、健康因素、游戏条件和饮食行为;客观变量为ehei相关症状。我们的研究包括194名有ehes相关症状的参与者和252名对照参与者。以下因素与EHE症状显著相关:感知脱水(调整优势比[AOR]为4.65,95%可信区间(CI)为3.08-7.03);睡眠剥夺(AOR, 4.38, 95% CI 2.84-6.77);食欲不振(AOR, 4.32, 95% CI 2.84-6.58);累积疲劳(AOR, 3.26, 95% CI 1.17-1.31);精神压力(AOR, 2.71, 95% CI 1.78-4.12);高尔夫球平均回合数(AOR 1.88, 95% CI 1.14-3.13);运动饮料消费量增加(AOR 2.07, 95% CI 1.20-3.56);盐片和糖果的摄入量增加(AOR 1.99, 95% CI 1.29-3.05);增加膳食补充剂的摄入量(AOR, 1.88, 95% CI 1.14-3.11)。这些发现表明,业余高尔夫球手应该在比赛前评估自己的身体状况,并相应地调整日程安排,特别是在炎热的天气,以尽量减少与热有关的疾病的风险。
{"title":"Associated factors for exertional heat exhaustion-related symptoms among amateur golfers in Japan: A retrospective case-control study.","authors":"Yosuke Nagashima, Teruhiko Hisaoka, Tomonori Sato, Yoshitomo Ehara, Akiko Horikawa, Akiyo Shiohara, Ayana Mitsume, Shigeru Mineo, Hiroaki Yoshida","doi":"10.1080/23328940.2025.2508489","DOIUrl":"10.1080/23328940.2025.2508489","url":null,"abstract":"<p><p>The associated factors for exertional heat stroke among amateur golfers remain poorly understood. We conducted a case-control study to examine exertional heat exhaustion (EHE) - related symptoms among amateur golfers in Japan using a self-administered questionnaire. Retrospective case-control study design. A web-based questionnaire was administered from September to November 2024. Data were collected on basic attributes, lifestyle habits, perceived health factors, perceived playing conditions, changes in eating behavior, and EHE-related symptoms. We performed a case-control analysis using a multivariate conditional logistic regression model. The explanatory variables included lifestyle habits, health factors, playing conditions, and eating behavior; the objective variables were EHE-related symptoms. Our study included 194 participants with EHE-related symptoms and 252 control participants. The following factors were significantly associated with EHE symptoms: perceived dehydration (adjusted odds ratio [AOR], 4.65, 95% confidence intervals (CI) 3.08-7.03); sleep deprivation (AOR, 4.38, 95% CI 2.84-6.77); loss of appetite (AOR, 4.32, 95% CI 2.84-6.58); accumulated fatigue (AOR, 3.26 95% CI 1.17-1.31); mental stress (AOR, 2.71, 95% CI 1.78-4.12); average rounds of golf (AOR 1.88, 95% CI 1.14-3.13); increased sports drink consumption (AOR 2.07, 95% CI 1.20-3.56); increased consumption of salt tablets and candies (AOR 1.99, 95% CI 1.29-3.05); and increased dietary supplement intake (AOR, 1.88, 95% CI 1.14-3.11).These findings suggest that amateur golfers should assess their physical condition before play and adjust their schedules accordingly, particularly in hot weather, to minimize the risk of heat-related illnesses.</p>","PeriodicalId":36837,"journal":{"name":"Temperature","volume":"12 3","pages":"296-311"},"PeriodicalIF":0.0,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416163/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01eCollection Date: 2025-01-01DOI: 10.1080/23328940.2025.2475420
Pradeep Guin, Nandita Bhan, Keshav Sethi
The effects of exposure to extreme heat and cold temperatures on human health have mostly been studied in high-income countries. We examined this association by exploring the effect of extreme temperatures on mortality due to heatstroke and exposure to cold in India and by states. We used temperature data from the Indian Meteorological Department (IMD) and mortality data from the National Crime Records Bureau (NCRB) to examine trends in overall, gender, and age-specific mortality. We used structural breaks analysis to observe changes in India's mortality trends during 2001-2019. We examined the time trends in the relationship between extreme temperature and mortality for 24 Indian states from 2001 to 2014. We used panel regression and spline regression models. Between 2001 and 2019, India reported 19,693 and 15,197 deaths due to heatstroke and cold exposure, respectively. Top three states with the greatest number of deaths due to heatstroke were Andhra Pradesh, Uttar Pradesh, and Punjab; for cold exposure it was Uttar Pradesh, Punjab, and Bihar. Working-age men were significantly more susceptible to heatstroke. Spline regression results indicated that mortality varied across different temperature bins for both extreme summer and winter temperatures. Our findings demonstrate an urgent need to strengthen welfare and social support systems and invest in built environment and livelihood interventions to counter the avoidable mortality from extreme temperature events.
{"title":"Mortality due to heatstroke and exposure to cold: Evidence from India.","authors":"Pradeep Guin, Nandita Bhan, Keshav Sethi","doi":"10.1080/23328940.2025.2475420","DOIUrl":"10.1080/23328940.2025.2475420","url":null,"abstract":"<p><p>The effects of exposure to extreme heat and cold temperatures on human health have mostly been studied in high-income countries. We examined this association by exploring the effect of extreme temperatures on mortality due to heatstroke and exposure to cold in India and by states. We used temperature data from the Indian Meteorological Department (IMD) and mortality data from the National Crime Records Bureau (NCRB) to examine trends in overall, gender, and age-specific mortality. We used structural breaks analysis to observe changes in India's mortality trends during 2001-2019. We examined the time trends in the relationship between extreme temperature and mortality for 24 Indian states from 2001 to 2014. We used panel regression and spline regression models. Between 2001 and 2019, India reported 19,693 and 15,197 deaths due to heatstroke and cold exposure, respectively. Top three states with the greatest number of deaths due to heatstroke were Andhra Pradesh, Uttar Pradesh, and Punjab; for cold exposure it was Uttar Pradesh, Punjab, and Bihar. Working-age men were significantly more susceptible to heatstroke. Spline regression results indicated that mortality varied across different temperature bins for both extreme summer and winter temperatures. Our findings demonstrate an urgent need to strengthen welfare and social support systems and invest in built environment and livelihood interventions to counter the avoidable mortality from extreme temperature events.</p>","PeriodicalId":36837,"journal":{"name":"Temperature","volume":"12 2","pages":"179-199"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12051615/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144040397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-27eCollection Date: 2025-01-01DOI: 10.1080/23328940.2025.2493460
Essi K Ahokas, Heikki Kyröläinen, Johanna K Ihalainen, Helen G Hanstock
Heat exposure after exercise may enhance recovery of physical performance but can also impose additional physiological stress on athletes. This study investigated the effects of post-exercise infrared sauna (IRS) on adrenal and autonomic nervous system (ANS) responses and examined how these responses adapt over time during a 6-week training intervention. Forty female team-sport athletes were pair-matched into an IRS-group and a control group (CON). Participants completed jumping exercises followed by IRS (10 min, 50 °C) or passive recovery and physiological assessments during two experimental trials: in the first (EX1) and in the last (EX2) week of the training intervention. The ANS responses were assessed by nocturnal heart rate (HR) and heart rate variability recorded before and after exercise session. Saliva cortisol concentrations, muscle soreness, and perceived recovery were assessed in the morning, before and after the exercise sessions. Cortisol increased by 5.1 ± 8.6 nmol/l the morning after EX1 in the IRS-group (p = 0.017), but not in the CON-group. Furthermore, a greater pre-post change in cortisol concentration was observed following EX1 (4.6 ± 10.4 nmol/l) compared to EX2 (-1.8 ± 7.6 nmol/l). The IRS-group showed a higher post-session HR in EX1 compared to the CON-group (61 ± 8 bpm vs. 55 ± 6 bpm; p = 0.019). Increased muscle soreness was observed at EX1 post36h only in the CON-group. Post-exercise IRS initially elevated physiological stress responses in female athletes. After six weeks of regular IRS use, athletes' ANS balance and cortisol response adapted, suggesting effective physiological adjustment to the heat intervention within six weeks.
运动后的热暴露可以促进身体机能的恢复,但也会给运动员带来额外的生理压力。本研究调查了运动后红外线桑拿(IRS)对肾上腺和自主神经系统(ANS)反应的影响,并研究了这些反应在为期6周的训练干预中是如何随时间变化的。40名女性团队运动运动员被配对成irs组和对照组(CON)。在训练干预的第一周(EX1)和最后一周(EX2)进行的两次实验中,参与者完成了跳跃练习,然后进行IRS(10分钟,50°C)或被动恢复和生理评估。通过记录运动前后的夜间心率(HR)和心率变异性来评估ANS反应。唾液皮质醇浓度、肌肉酸痛和感知恢复在早晨、运动前和运动后进行评估。皮质醇在EX1后早晨升高5.1±8.6 nmol/l (p = 0.017), con组无升高。此外,与EX2(-1.8±7.6 nmol/l)相比,EX1后皮质醇浓度的前后变化更大(4.6±10.4 nmol/l)。与con组相比,irs组在EX1的治疗后HR更高(61±8 bpm vs 55±6 bpm; p = 0.019)。仅con组在36小时后EX1时观察到肌肉酸痛增加。运动后IRS最初提高了女性运动员的生理应激反应。在常规IRS使用六周后,运动员的ANS平衡和皮质醇反应适应,表明六周内对热干预进行了有效的生理调整。
{"title":"Salivary cortisol response to post-exercise infrared sauna declines over time.","authors":"Essi K Ahokas, Heikki Kyröläinen, Johanna K Ihalainen, Helen G Hanstock","doi":"10.1080/23328940.2025.2493460","DOIUrl":"10.1080/23328940.2025.2493460","url":null,"abstract":"<p><p>Heat exposure after exercise may enhance recovery of physical performance but can also impose additional physiological stress on athletes. This study investigated the effects of post-exercise infrared sauna (IRS) on adrenal and autonomic nervous system (ANS) responses and examined how these responses adapt over time during a 6-week training intervention. Forty female team-sport athletes were pair-matched into an IRS-group and a control group (CON). Participants completed jumping exercises followed by IRS (10 min, 50 °C) or passive recovery and physiological assessments during two experimental trials: in the first (EX1) and in the last (EX2) week of the training intervention. The ANS responses were assessed by nocturnal heart rate (HR) and heart rate variability recorded before and after exercise session. Saliva cortisol concentrations, muscle soreness, and perceived recovery were assessed in the morning, before and after the exercise sessions. Cortisol increased by 5.1 ± 8.6 nmol/l the morning after EX1 in the IRS-group (<i>p</i> = 0.017), but not in the CON-group. Furthermore, a greater pre-post change in cortisol concentration was observed following EX1 (4.6 ± 10.4 nmol/l) compared to EX2 (-1.8 ± 7.6 nmol/l). The IRS-group showed a higher post-session HR in EX1 compared to the CON-group (61 ± 8 bpm vs. 55 ± 6 bpm; <i>p</i> = 0.019). Increased muscle soreness was observed at EX1 post36h only in the CON-group. Post-exercise IRS initially elevated physiological stress responses in female athletes. After six weeks of regular IRS use, athletes' ANS balance and cortisol response adapted, suggesting effective physiological adjustment to the heat intervention within six weeks.</p>","PeriodicalId":36837,"journal":{"name":"Temperature","volume":"12 3","pages":"281-295"},"PeriodicalIF":0.0,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416168/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-23eCollection Date: 2025-01-01DOI: 10.1080/23328940.2025.2484499
Marie Gombert-Labedens, Kristine Vesterdorf, Andrea Fuller, Shane K Maloney, Fiona C Baker
Changes in thermoregulation, notably the emergence of hot flashes, occur during the menopause transition in association with reproductive hormonal changes. Hot flashes constitute the most characteristic symptom of menopause (prevalence of 50-80%), and have a substantial negative effect on quality of life. Here, we review the endocrine changes associated with menopause and the thermoregulatory system and its sensitivity to female sex hormones. We then review current knowledge on the underlying neural mechanisms of hot flashes and how the reproductive and thermoregulatory systems interact in females. We consider the kisspeptin-neurokinin B-dynorphin (KNDy) neuron complex, which becomes hyperactive when estradiol levels decrease. KNDy neurons project from the arcuate nucleus to thermoregulatory areas within the hypothalamic preoptic area, where heat loss mechanisms are triggered, including cutaneous vasodilation and sweating - characteristics of the hot flash. We describe the physiology and measurement of hot flashes and discuss the mixed research findings about thresholds for sweating in symptomatic individuals. We consider the unique situation of hot flashes that arise during sleep, and discuss the relationships between the environment, exercise, and body mass index with hot flashes. We also discuss the unique situation of surgical menopause (with oophorectomy) and cancer therapy, conditions that are associated with frequent, severe, hot flashes. We then provide an overview of treatments of hot flashes, including hormone therapy and targeted neurokinin B-antagonists, recently developed to target the neural mechanism of hot flashes. Finally, we highlight gaps in knowledge about menopausal thermoregulation and hot flashes and suggest future directions for research.
{"title":"Effects of menopause on temperature regulation.","authors":"Marie Gombert-Labedens, Kristine Vesterdorf, Andrea Fuller, Shane K Maloney, Fiona C Baker","doi":"10.1080/23328940.2025.2484499","DOIUrl":"https://doi.org/10.1080/23328940.2025.2484499","url":null,"abstract":"<p><p>Changes in thermoregulation, notably the emergence of hot flashes, occur during the menopause transition in association with reproductive hormonal changes. Hot flashes constitute the most characteristic symptom of menopause (prevalence of 50-80%), and have a substantial negative effect on quality of life. Here, we review the endocrine changes associated with menopause and the thermoregulatory system and its sensitivity to female sex hormones. We then review current knowledge on the underlying neural mechanisms of hot flashes and how the reproductive and thermoregulatory systems interact in females. We consider the kisspeptin-neurokinin B-dynorphin (KNDy) neuron complex, which becomes hyperactive when estradiol levels decrease. KNDy neurons project from the arcuate nucleus to thermoregulatory areas within the hypothalamic preoptic area, where heat loss mechanisms are triggered, including cutaneous vasodilation and sweating - characteristics of the hot flash. We describe the physiology and measurement of hot flashes and discuss the mixed research findings about thresholds for sweating in symptomatic individuals. We consider the unique situation of hot flashes that arise during sleep, and discuss the relationships between the environment, exercise, and body mass index with hot flashes. We also discuss the unique situation of surgical menopause (with oophorectomy) and cancer therapy, conditions that are associated with frequent, severe, hot flashes. We then provide an overview of treatments of hot flashes, including hormone therapy and targeted neurokinin B-antagonists, recently developed to target the neural mechanism of hot flashes. Finally, we highlight gaps in knowledge about menopausal thermoregulation and hot flashes and suggest future directions for research.</p>","PeriodicalId":36837,"journal":{"name":"Temperature","volume":"12 2","pages":"92-132"},"PeriodicalIF":0.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12051537/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144000162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-20eCollection Date: 2025-01-01DOI: 10.1080/23328940.2025.2493456
Kevin C Miller, Rachel M Koldenhoven, Erin M Lally
A heat tolerance test (HTT) can aid in return-to-play decision making following exertional heat stroke (EHS). The HTT uses rectal temperature (TREC, >38.5°C) and heart rate thresholds (HR; >150 bpm) to identify "heat intolerance." Unfortunately, TREC is prohibited in some clinical settings (e.g. secondary schools), making a standard HTT unusable. Recently, gait sensors were used to identify heat illness, but have never been correlated with TREC during a HTT. No research has compared gait or noninvasive body temperature sites to TREC to determine their surrogacy for TREC during a HTT. Eighteen subjects underwent a standard HTT (12 men, 6 women; age: 22 ± 2y; height: 168.3 ± 8.5 cm; mass: 76.6 ± 14.8 kg). Rectal, oral, aural, forehead, and axillary temperatures, gait metrics, and HR were measured every 5 minutes during a HTT. Temperature sites were invalid if bias (i.e. difference from TREC) was >±0.27°C. Spearman correlations examined the relationship between TREC and gait variables. Mean aural, oral, axillary, and forehead bias were -0.19 ± 0.56°C, 0.70 ± 0.53°C, 0.85 ± 0.45°C, and 1.38 ± 0.69°C, respectively (F2,35 = 42.3, p < 0.001). Aural, oral, forehead, and axillary measurements exceeded our validity threshold 48 ± 30% (169 of 353), 87 ± 16% (307 of 353), 91 ± 15% (321 of 353), and 93 ± 10% (328 of 353) of the time, respectively. TREC was significantly negatively correlated to shock (r =-0.28, p < 0.001), impact g (r =-0.28, p < 0.001), and braking g (r=-0.24, p < 0.001), and positively correlated with pronation excursion (r = 0.30, p < 0.001). Clinicians should use TREC during an HTT as no alternative, valid temperature site was found. Some gait variables showed promise for tracking TREC during a HTT, but more research is necessary.
热耐受性测试(HTT)可以帮助在劳累性中暑(EHS)后做出回归比赛的决策。HTT使用直肠温度(TREC, >38.5°C)和心率阈值(HR, >150 bpm)来识别“热不耐受”。不幸的是,TREC在一些临床环境(如中学)是被禁止的,这使得标准HTT无法使用。最近,步态传感器被用于识别热疾病,但从未与高温试验期间的TREC相关。没有研究将步态或无创体温位点与TREC进行比较,以确定其在HTT期间TREC的替代位置。18例患者接受了标准HTT检查(男性12例,女性6例,年龄22±2y,身高168.3±8.5 cm,体重76.6±14.8 kg)。在HTT期间,每5分钟测量一次直肠、口腔、耳部、前额和腋窝温度、步态指标和心率。如果偏置(即与TREC的差异)为bb0±0.27°C,温度位点无效。Spearman相关性检验TREC和步态变量之间的关系。耳部、口腔、腋窝和前额的平均偏倚分别为-0.19±0.56°C、0.70±0.53°C、0.85±0.45°C和1.38±0.69°C (F2,35 = 42.3, p REC与休克显著负相关(r =-0.28, p r= -0.28, p r=-0.24, p r= 0.30, HTT期间p REC没有可选的有效温度位点)。一些步态变量显示了在HTT过程中跟踪TREC的希望,但还需要更多的研究。
{"title":"Validity of common body temperature sites and gait parameters during a heat tolerance test.","authors":"Kevin C Miller, Rachel M Koldenhoven, Erin M Lally","doi":"10.1080/23328940.2025.2493456","DOIUrl":"https://doi.org/10.1080/23328940.2025.2493456","url":null,"abstract":"<p><p>A heat tolerance test (HTT) can aid in return-to-play decision making following exertional heat stroke (EHS). The HTT uses rectal temperature (T<sub>REC</sub>, >38.5°C) and heart rate thresholds (HR; >150 bpm) to identify \"heat intolerance.\" Unfortunately, T<sub>REC</sub> is prohibited in some clinical settings (e.g. secondary schools), making a standard HTT unusable. Recently, gait sensors were used to identify heat illness, but have never been correlated with T<sub>REC</sub> during a HTT. No research has compared gait or noninvasive body temperature sites to T<sub>REC</sub> to determine their surrogacy for T<sub>REC</sub> during a HTT. Eighteen subjects underwent a standard HTT (12 men, 6 women; age: 22 ± 2y; height: 168.3 ± 8.5 cm; mass: 76.6 ± 14.8 kg). Rectal, oral, aural, forehead, and axillary temperatures, gait metrics, and HR were measured every 5 minutes during a HTT. Temperature sites were invalid if bias (i.e. difference from T<sub>REC</sub>) was >±0.27°C. Spearman correlations examined the relationship between T<sub>REC</sub> and gait variables. Mean aural, oral, axillary, and forehead bias were -0.19 ± 0.56°C, 0.70 ± 0.53°C, 0.85 ± 0.45°C, and 1.38 ± 0.69°C, respectively (F<sub>2,35</sub> = 42.3, <i>p</i> < 0.001). Aural, oral, forehead, and axillary measurements exceeded our validity threshold 48 ± 30% (169 of 353), 87 ± 16% (307 of 353), 91 ± 15% (321 of 353), and 93 ± 10% (328 of 353) of the time, respectively. T<sub>REC</sub> was significantly negatively correlated to shock (<i>r</i> =-0.28, <i>p</i> < 0.001), impact g (<i>r</i> =-0.28, <i>p</i> < 0.001), and braking g (<i>r</i>=-0.24, <i>p</i> < 0.001), and positively correlated with pronation excursion (<i>r</i> = 0.30, <i>p</i> < 0.001). Clinicians should use T<sub>REC</sub> during an HTT as no alternative, valid temperature site was found. Some gait variables showed promise for tracking T<sub>REC</sub> during a HTT, but more research is necessary.</p>","PeriodicalId":36837,"journal":{"name":"Temperature","volume":"12 3","pages":"231-244"},"PeriodicalIF":0.0,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416179/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}