Current and projected heatwave-attributable occupational injuries, illnesses, and associated economic burden in Australia

The cumulative effects of consecutive days of prolonged, physical work or activity on heat strain and physical performance: a systematic review

With climate warming, there is an urgent need to understand the health effects of occupational heat exposure. This systematic review examined the cumulative effects of consecutive days of prolonged physical work or activity on heat strain and physical performance. Electronic databases MEDLINE, SPORTDiscus, PsychInfo, and Academic Search Complete were searched until July 2024 with terms related to work, consecutive days, and heat. Studies were included if they involved ≥4 h of physical work/activity on ≥2 consecutive days, and included a measure of heat strain (e.g., core temperature) or physical performance (e.g., repetitions). After removing duplicates, 6030 studies were screened (title and abstract), 133 progressed to full-text screening, and 33 met the inclusion criteria with risk of bias assessed. However, only five studies used standardized environmental and work conditions across days. Synthesis of the cumulative effects (without meta-analysis) was therefore restricted to these studies. None observed a cumulative impact on heat strain, as indexed by a higher core temperature or heart rate compared to day 1. None reported a reduction in physical task performance across days. These findings indicate that the cumulative effects of occupational heat exposure on heat strain and physical task performance were minimal, although evidence supporting this conclusion is sparse. PROSPERO registration: CRD42023452936.

The use of machine and deep learning to model the relationship between discomfort temperature and labor productivity loss among petrochemical workers

BACKGROUND

Workplace may not only increase the risk of heat-related illnesses and injuries but also compromise work efficiency, particularly in a warming climate. This study aimed to utilize machine learning (ML) and deep learning (DL) algorithms to quantify the impact of temperature discomfort on productivity loss among petrochemical workers and to identify key influencing factors.

METHODS

A cross-sectional face-to-face questionnaire survey was conducted among petrochemical workers between May and September 2023 in Fujian Province, China. Initial feature selection was performed using Lasso regression. The dataset was divided into training (70%), validation (20%), and testing (10%) sets. Six predictive models were evaluated: support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), Gaussian Naive Bayes (GNB), multilayer perceptron (MLP), and logistic regression (LR). The most effective model was further analyzed with SHapley Additive exPlanations (SHAP).

RESULTS

Among the 2393 workers surveyed, 58.4% (1,747) reported productivity loss when working in high temperatures. Lasso regression identified twenty-seven predictive factors such as educational level and smoking. All six models displayed strong prediction accuracy (SVM = 0.775, RF = 0.760, XGBoost = 0.727, GNB = 0.863, MLP = 0.738, LR = 0.680). GNB model showed the best performance, with a cutoff of 0.869, accuracy of 0.863, precision of 0.897, sensitivity of 0.918, specificity of 0.715, and an F1-score of 0.642, indicating its efficacy as a predictive tool. SHAP analysis showed that occupational health training (SHAP value: -3.56), protective measures (-2.61), and less physically demanding jobs (-1.75) were negatively associated with heat-attributed productivity loss, whereas lack of air conditioning (1.92), noise (2.64), vibration (1.15), and dust (0.95) increased the risk of heat-induced productivity loss.

CONCLUSIONS

Temperature discomfort significantly undermined labor productivity in the petrochemical sector, and this impact may worsen in a warming climate if adaptation and prevention measures are insufficient. To effectively reduce heat-related productivity loss, there is a need to strengthen occupational health training and implement strict controls for occupational hazards, minimizing the potential combined effects of heat with other exposures.

Outdoor thermal performance of urban development patterns in Greater Adelaide since the late 19th century

Extreme heat events have become more common and more severe during summer than ever before as a result of the warming climate in Australia. The impact of urban morphology and green coverage on outdoor thermal comfort has been the subject of extensive research, however, their link to suburban developments of different historic periods is still underexplored. This paper investigates and compares the outdoor thermal performance of ten suburban areas constructed since the late nineteenth century in Greater Adelaide, which were built to different planning ideals and concepts of their time. Microclimate models of two precedents for five development eras were constructed in ENVI-met, validated with site data related to a recent heatwave event in 2023, and then used to facilitate further investigation of the impact of development patterns on outdoor thermal comfort. This study examines how these urban patterns perform in scenarios of varying development intensity and greenery ratio. In these case studies, the distance between buildings, streets' spatial ratio and green coverage has a significant impact on the thermal environment. The results underline the impact of solar exposure on outdoor thermal performance even in lower-density suburban areas. Some of the outcomes of the study are counter-intuitive to conventional assumptions about urban design typologies. In this comparison, for example, one of the "green" model garden city developments did not perform as well as denser 19th-century suburbs. The results can support better decision-making for future urban planning in Australia and other regions with similar climate conditions. The study shows that real performance does not always align with stated green ambitions and, urban design should consider and evaluate heat mitigation through evidence-based testing to achieve real green development.

Preparing for a hotter climate: A systematic review and meta-analysis of heatwaves and ambulance callouts in Australia

OBJECTIVE

The objective of this study was to quantify the impact of heatwaves on likelihood of ambulance callouts for Australia.

METHODS

A systematic review and meta-analysis was conducted to retrieve and synthesise evidence published from 1 January 2011 to 31 May 2023 about the association between heatwaves and the likelihood of ambulance callouts in Australia. Different heatwave definitions were used ranging from excess heat factor to heatwave defined as a continuous period with temperatures above certain defined thresholds (which varied based on study locations).

RESULTS

We included nine papers which met the inclusion criteria for the review. Eight were eligible for the meta-analyses. The multilevel meta-analyses revealed that the likelihood of ambulance callouts for all causes and for cardiovascular diseases increased by 10% (95% confidence interval: 8%, 13%) and 5% (95% confidence interval: 1%, 3%), respectively, during heatwave days.

CONCLUSIONS

Exposure to heatwaves is associated with an increased likelihood of ambulance callouts, and there is a dose-response association between heatwave severity and the likelihood of ambulance callouts.

IMPLICATIONS FOR PUBLIC HEALTH

The number of heatwave days are going to increase, and this will mean an increase in the likelihood of ambulance callouts, thereby, spotlighting the real burden that heatwaves place on our already stressed healthcare system. The findings of this study underscore the critical need for proactive measures, including the establishment of research initiatives and holistic heat health awareness campaigns, spanning from the individual and community levels to the healthcare system, in order to create a more resilient Australia in the face of heatwave-related challenges.