Association between thermal stress and cardiovascular mortality in the subtropics.

Hazardous thermal conditions resulting from climate change may play a role in cardiovascular disease development. We chose the Universal Thermal Climate Index (UTCI) as the exposure metric to evaluate the relationship between thermal conditions and cardiovascular mortality in Shenzhen, China. We applied quasi-Poisson regression non-linear distributed lag models to evaluate the exposure-response associations. The findings suggest that cardiovascular mortality risks were significantly increased under heat and cold stress, and the adverse effects of cold stress were stronger than heat stress. Referencing the 50th percentile of UTCI (25.4°C), the cumulative risk of cardiovascular mortality was 75% (RRlag0-21 =1.75, 95%CI: 1.32, 2.32) higher in the 1st percentile (3.5°C), and 40% (RRlag0-21=1.40, 95%CI: 1.09, 1.80) higher in the 99th percentile (34.1°C). We observed that individuals older than 65 years were more vulnerable to both cold and heat stress, and females were identified as more susceptible to heat stress than males. Moreover, increased mortality risks of hypertensive disease and cerebrovascular disease were observed under cold stress, while heat stress was related to higher risks of mortality for hypertensive disease and ischemic heart disease. We also observed a stronger relationship between cold stress and ischemic heart disease mortality during the cold season, as well as a significant impact of heat stress on cerebrovascular disease mortality in the warm season when compared to the analysis of the entire year. These results confirm the significant relationship between thermal stress and cardiovascular mortality, with age and sex as potential effect modifiers of this association. Providing affordable air conditioning equipment, increasing the amount of vegetation, and establishing comprehensive early warning systems that take human thermoregulation into account could all help to safeguard the well-being of the public, particularly vulnerable populations, in the event of future extreme weather.

Short-term effects of temperature-related indices on emergency ambulance dispatches due to mental and behavioral disorders in Shenzhen, China.

Introduction: The precise associations between temperature-related indices and mental and behavioral disorders (MBDs) have yet to be fully elucidated. Our study aims to ascertain the most effective temperature-related index and assess its immediate impact on emergency ambulance dispatches (EADs) due to MBDs in Shenzhen, China. Methods: EADs data and meteorological data from January 1, 2013, to December 31, 2020, in Shenzhen were collected. Distributed lag non-linear models (DLNMs) were utilized to examine the non-linear and lagged effects of temperature-related indices on EADs due to MBDs. The Quasi Akaike Information criterion (QAIC) was used to determine the optimal index after standardizing temperature-related indices. After adjusting for confounding factors in the model, we estimated the immediate and cumulative effects of temperature on EADs due to MBDs. Results: The analysis of short-term temperature effects on EADs due to MBDs revealed Humidex as the most suitable index. Referring to the optimal Humidex (3.2th percentile, 12.00°C), we observed a significant effect of Humidex over the threshold (34.6th percentile, 26.80°C) on EADs due to MBDs at lag 0-5. The cumulative relative risks for high temperature (90th percentile, 41.90°C) and extreme high temperature (99th percentile, 44.20°C) at lag 0-5 were 1.318 (95% CI: 1.159-1.499) and 1.338 (95% CI: 1.153-1.553), respectively. No significant cold effect was observed on EADs due to MBDs. Conclusion: High Humidex was associated with more EADs due to MBDs in subtropical regions. Health authorities should implement effective measures to raise public awareness of risks related to high temperature and protect vulnerable populations.

Increased emergency cases for out-of-hospital cardiac arrest due to cold spells in Shenzhen, China.

Cold spells have been associated with specific diseases. However, there is insufficient scientific evidence on the effects of cold spells on out-of-hospital cardiac arrest (OHCA). Data on OHCA cases and on meteorological factors and air pollutants were collected between 2013 and 2020. We adopted a quasi-Poisson generalized additive model with a distributed lag nonlinear model (DLNM) to estimate the effect of cold spells on daily OHCA incidence. Backward attributable risk within the DLNM framework was calculated to quantify the disease burden. We compared the effects and OHCA burden of cold spells using nine definitions. The risks of different cold spells on OHCA increased at higher intensities and longer durations. Based on Akaike's information criterion for the quasi-Poisson regression model and the attributable risk, the optimal cold spell was defined as a period in the cold month when the daily mean temperature was below the 10th percentile of the temperature distribution in the study period for at least 2 days. The single-day effect of the optimal cold spell on OHCA occurred immediately and lasted for approximately 1 week. The maximum single-day effect was 1.052 (95% CI: 1.018-1.087) at lag0, while the maximum cumulative effect was 1.433 (95% CI:1.148-1.788) after a 14-day lag. Men were more susceptible to cold spells. Young and middle-aged people were affected by cold spells similar to the elderly. Cold spells can increase the risk of OHCA with an approximately 1-week lag effect. Health regulators should take more targeted measures to protect susceptible populations during cold weather.

Evaluating the predictive ability of temperature-related indices on the stroke morbidity in Shenzhen, China: Under cross-validation methods framework.

BACKGROUND: Composite temperature-related indices have been utilized to comprehensively reflect the impact of multiple meteorological factors on health. We aimed to evaluate the predictive ability of temperature-related indices, choose the best predictor of stroke morbidity, and explore the association between them. METHODS: We built distributed lag nonlinear models to estimate the associations between temperature-related indices and stroke morbidity and then applied two types of cross-validation (CV) methods to choose the best predictor. The effects of this index on overall stroke, intracerebral hemorrhage (ICH), and ischemic stroke (IS) morbidity were explored and we explained how this index worked using heatmaps. Stratified analyses were conducted to identify vulnerable populations. RESULTS: Among 12 temperature-related indices, the alternative temperature-humidity index (THIa) had the best overall performance in terms of root mean square error when combining the results from two CVs. With the median value of THIa (25.70 °C) as the reference, the relative risks (RRs) of low THIa (10th percentile) reached a maximum at lag 0-10, with RRs of 1.20 (95%CI:1.10-1.31), 1.49 (95%CI:1.29-1.73) and 1.12 (95%CI:1.03-1.23) for total stroke, ICH and IS, respectively. According to the THIa formula, we matched the effects of THIa on stroke under various combinations of temperature and relative humidity. We found that, although the low temperature (<20 °C) had the greatest adverse effect, the modification effect of humidity on it was not evident. In contrast, lower humidity could reverse the protective effect of temperature into a harmful effect at the moderate-high temperature (24 °C-27 °C). Stratification analyses showed that the female was more vulnerable to low THIa in IS. CONCLUSIONS: THIa is the best temperature-related predictor of stroke morbidity. In addition to the most dangerous cold weather, the government should pay more attention to days with moderate-high temperature and low humidity, which have been overlooked in the past.