Visits to the accident and emergency department in hot season of a city with subtropical climate: association with heat stress and related meteorological variables

Extreme Hot Weather Events and Risk of Hospitalization for Cardiovascular and Respiratory Diseases in Older People in Hong Kong in 2012-2018

BACKGROUND

The older population is more vulnerable to the impact of extreme hot weather events (EHWEs), although the impact on the frailer institutionalized older population was seldom assessed. Our objective was to assess the relationship between EHWEs and hospitalization risks among institutionalized and community-dwelling older people.

METHODS

We used territory-wide hospitalization records of Hong Kong from the year 2012 to 2018 to assess the associations between EHWEs and cardiovascular and respiratory disease hospitalizations in the population aged 65 or above. A very hot day (VHD) was defined as the daily maximum temperature ≥33 °C, and a hot night (HN) was defined as the daily minimum temperature ≥28 °C. We assessed whether prolonged exposure to high temperatures (defined as 3 consecutive VHDs (3VHD) or HNs (3HN)) was related to a higher risk of hospitalization over a lag period of 0-21 days. Time-stratified case-crossover design was used. Analyses were stratified by old age home (OAH) residence status.

RESULTS

Exposure to 3VHDs was related to a higher risk of cardiovascular disease admissions for community-dwelling older people [relative risk (RR): 1.09; 95% confidence interval (95%CI): 1.03-1.14 (lagged 4 days, ie, delayed manifestation up to 4 days)], whereas for OAH residents, the association could have a lag of 18 days (RR: 1.28; 95%CI: 1.05-1.54). For respiratory disease admissions, such relatively long-delayed relationship was not clearly observed.

CONCLUSIONS

The warming climate could increase healthcare demand in the long run. Frailer patients could present with a generally more marked and delayed onset of cardiovascular disease aggravation than the community-dwelling population.

Suitable temperature indicator for adverse health impacts in sub-tropical cities: a case study in Hong Kong from 2010-2019

Heat-health warning systems and services are important preventive actions for extreme heat, however, global evidence differs on which temperature indicator is more informative for heat-health outcomes. We comprehensively assessed temperature predictors on their summer associations with adverse health impacts in a high-density subtropical city. Maximum, mean, and minimum temperatures were examined on their associations with non-cancer mortality and hospital admissions in Hong Kong during summer seasons 2010-2019 using Generalized Additive Models and Distributed Lag Non-linear Models. In summary, mean and minimum temperatures were identified as strong indicators for mortality, with a relative risk(RR) and 95% confidence interval(CI) of 1.037 (1.006-1.069) and 1.055 (1.019-1.092), respectively, at 95th percentile vs. optimal temperature. Additionally, minimum temperatures captured the effects of hospital admissions, RR1.009 (95%CI: 1.000- 1.018). In stratified analyses, significant associations were found for older adults, female sex, and respiratory-related outcomes. For comparison, there was no association between maximum temperature and health outcomes. With climate change and projected increase of night-time warming, the findings from this comprehensive assessment method are useful to strengthen heat prevention strategies and enhance heat-health warning systems. Other locations could refer to this comprehensive method to evaluate their heat risk, especially in highly urbanized environments and subtropical cities.

Impact of heat waves on semen quality: A retrospective study in Argentina between 2005 and 2023

Heat waves, defined as periods with daily temperatures surpassing the historical average for a specific region, have become more frequent worldwide in recent years. Previous studies have reported a negative association between temperature and semen quality, but the focus has mainly been on Asian and European populations. The study included 54,926 men (18-60 years) undergoing routine semen analysis between 2005 and 2023 at CEUSA-LAEH andrology unit, in Buenos Aires, Argentina. Hourly temperature readings were provided by the Servicio Meteorológico Nacional. R programming (R Studio v2022.07.2) was used to define heat waves, calculate key characteristics, visualize results, and perform statistical tests at the IBYME laboratory. During the period studied, a total of 124 days had heat waves (defined after at least 3 consecutive days with 32.3 °C and 22 °C). Men exposed to heat waves during spermatogenesis exhibited lower sperm number (concentration and count; P < 0.0001) and decreased normal morphology (percentage of normal sperm and normal motile count; P < 0.05) compared to those not exposed. These differences were most pronounced between semen samples from years with several heat waves (2013, 2023) and none (2005, 2007, 2016), displaying 4-5 times higher fold changes (P < 0.05). Further analysis employing multiple regression revealed a significantly negative association between semen quality and heat wave length, suggesting that a prolonged exposure may be more detrimental than an acute exposure. Subsequent analysis focusing on prolonged exposure (≥6-days heat wave) during spermatogenesis revealed a negative (P < 0.05) association between early exposure (spermatocytogenesis: 64-90 days prior semen collection) and semen quality. This study underscores the negative association between early exposure to heat waves during sperm development and semen quality, raising concerns about its possible association with the worldwide declining male fertility. A comprehensive collaborative approach is crucial, involving global governmental policies, sustainable practices, and coordinated efforts across scientific, healthcare, and policy domains.

Association between ambient temperature and economic burden of unintentional injury in Tianjin: a case-crossover study

OBJECTIVE

Unintentional injuries constitute a significant global public health issue with significant social and economic costs. Previous evidence suggests ambient temperatures are associated with unintentional injury occurrences. However, the impacts of ambient temperature on unintentional injury economic burden have received little research attention. The objective of the study was to examine the association between ambient temperature and economic burden of unintentional injury.

DESIGN

Time-stratified case-crossover study.

SETTING

This study was performed at Tianjin Hospital, the largest trauma centre in Tianjin, by applying a hospital-based time-stratified case-crossover study.

PARTICIPANTS

The 12 241 patients admitted with unintentional injuries and meteorological data were collected in Tianjin, China in 2021.

PRIMARY AND SECONDARY OUTCOME

The association between ambient temperature and unintentional injury hospitalisation was evaluated with a distributed lag non-linear model, further temperature-attributable economic burden of unintentional injuries was quantified, and adjusted for demographic characteristics, injury mechanism and injury location of injury.

RESULTS

The temperatures below 11.5°C were significantly associated with the increased risk of unintentional injury hospitalisation in Tianjin, in 2021. The effect was maximised on the current day. The relatively low temperature was responsible for 25.44% (95% CI 13.74, 33.09) of unintentional injury patients, and was associated with the number of unintentional injury patients (3114, 95% CI 1608, 4036). The relatively low temperature was associated with the excess economic burden for unintentional injury (¥197.52 million, 95% CI 102.00, 256.00; about 27.10 million dollars), accounting for 26.49% of the total economic burden. The cold temperatures generally had greater impacts on males (¥136.46 million, 95% CI 83.28, 172.42; about 18.67 million dollars) and the elderly (¥74.35 million, 95% CI 14.87, 102.14; about 10.24 million dollars).

CONCLUSION

The temperature was associated with approximately 3000 unintentional injury patients and ¥200 million (27 million dollars), accounting for 26% of the total economic burden in Tianjin, 2021.

The role of older adult-focused social vulnerability on the relationship between temperature and emergency department attendance in a subtropical Asian city

PURPOSE

Older adults exhibit a wide range of capabilities and vulnerabilities that affect their capacity to respond to heat. This study analysed the associations between hot temperatures and Accident & Emergency (A&E) attendance taking into account older adult-focused social vulnerability.

METHODS

Daily A&E attendance data of Young-old (65-74) and Old-old (75+) was obtained for Hong Kong 2010-2019 hot seasons and stratified into three Social Vulnerability Index (SVI) groups (Low, Moderate, High). Mean temperature (lag 0-2) was analysed on A&E attendance at each SVI using Generalized Additive Models and Distributed Lag Non-linear Models.

RESULTS

High temperatures were associated with increased same-day (lag 0) relative risk (RR) of A&E attendance for Young-old and Old-old in High SVI districts, with RR being 1.024 (95 % CI: 1.011, 1.037) and 1.036 (95 % CI: 1.018, 1.053), respectively. The Old-old living in Moderate and Low SVI districts also demonstrated increased RR of 1.037 (95 % CI: 1.028, 1.047) and 1.022 (95 % CI: 1.009, 1.036), respectively. Fewer emergency visits were found on the subsequent day (lag 1) of hot temperatures.

CONCLUSIONS

Older adults, both young-old and old-old, living in districts with higher social vulnerability tended to have increased risk of A&E attendance associated with same-day high temperature. With climate change and rapidly aging population, cities should prepare to meet needs of more vulnerable older adults in extreme heat.

Extreme weather and asthma: a systematic review and meta-analysis

BACKGROUND

Climate change's influence on extreme weather events poses a significant threat to the morbidity and mortality of asthma patients. The aim of this study was to examine associations between extreme weather events and asthma-related outcomes.

METHODS

A systematic literature search for relevant studies was performed using the PubMed, EMBASE, Web of Science and ProQuest databases. Fixed-effects and random-effects models were applied to estimate the effects of extreme weather events on asthma-related outcomes.

RESULTS

We observed that extreme weather events were associated with increasing risks of general asthma outcomes with relative risks of 1.18-fold for asthma events (95% CI 1.13-1.24), 1.10-fold for asthma symptoms (95% CI 1.03-1.18) and 1.09-fold for asthma diagnoses (95% CI 1.00-1.19). Extreme weather events were associated with increased risks of acute asthma exacerbation with risk ratios of asthma emergency department visits of 1.25-fold (95% CI 1.14-1.37), of asthma hospital admissions of 1.10-fold (95% CI 1.04-1.17), of asthma outpatient visits of 1.19-fold (95% CI 1.06-1.34) and of asthma mortality of 2.10-fold (95% CI 1.35-3.27). Additionally, an increase in extreme weather events increased risk ratios of asthma events by 1.19-fold in children and 1.29-fold in females (95% CI 1.08-1.32 and 95% CI 0.98-1.69, respectively). Thunderstorms increased the risk ratio of asthma events by 1.24-fold (95% CI 1.13-1.36).

CONCLUSIONS

Our study showed that extreme weather events more prominently increased the risk of asthma morbidity and mortality in children and females. Climate change is a critical concern for asthma control.

Perception of extreme hot weather and the corresponding adaptations among older adults and service providers-A qualitative study in Hong Kong

Background

Extreme hot weather events are happening with increasing frequency, intensity and duration in Hong Kong. Heat stress is related to higher risk of mortality and morbidity, with older adults being particularly vulnerable. It is not clear whether and how the older adults perceive the increasingly hot weather as a health threat, and whether community service providers are aware and prepared for such future climate scenario.

Methods

We conducted semi-structure interviews with 46 older adults, 18 staff members of community service providers and two district councilors of Tai Po, a north-eastern residential district of Hong Kong. Transcribed data were analyzed using thematic analysis until data saturation was reached.

Results

It was agreed upon among the older adult participants that the weather in recent years has become increasingly hot and this led to some health and social problems for them, although some participants perceived that hot weather did not have any impact in their daily lives and they were not vulnerable. The community service providers and district councilors reported that there is a lack of relevant services in the community to support the older adults in hot weather; and there is generally a lack of public education regarding the heat-health issue.

Conclusions

Heatwaves are affecting older adults' health in Hong Kong. Yet, discussions and education effort regarding the heat-health issue in the public domain remain scarce. Multilateral efforts are urgently needed to co-create a heat action plan to improve community awareness and resilience.

Predicting Emergency Department Utilization among Older Hong Kong Population in Hot Season: A Machine Learning Approach

Previous evidence suggests that temperature is associated with the number of emergency department (ED) visits. A predictive system for ED visits, which takes local temperature into account, is therefore needed. This study aimed to compare the predictive performance of various machine learning methods with traditional statistical methods based on temperature variables and develop a daily ED attendance rate predictive model for Hong Kong. We analyzed ED utilization among Hong Kong older adults in May to September from 2000 to 2016. A total of 103 potential predictors were derived from 1- to 14-day lag of ED attendance rate and meteorological and air quality indicators and 0-day lag of holiday indicator and month and day of week indicators. LASSO regression was used to identify the most predictive temperature variables. Decision tree regressor, support vector machine (SVM) regressor, and random forest regressor were trained on the selected optimal predictor combination. Deep neural network (DNN) and gated recurrent unit (GRU) models were performed on the extended predictor combination for the previous 14-day horizon. Maximum ambient temperature was identified as a better predictor in its own value than as an indicator defined by the cutoff. GRU achieved the best predictive accuracy. Deep learning methods, especially the GRU model, outperformed conventional machine learning methods and traditional statistical methods.