Outdoor ambient temperatures and occupational injuries and illnesses: Are there risk differences in various regions within a city?

Increased risk of occupational injuries and illnesses (OI) is associated with hot ambient temperatures. However, the existing evidence of risk estimation is limited to large regions at the city or provincial scales. For effective and localized occupational health risk management, spatio-temporal analysis should be carried out at the intra-city level to identify high-risk areas within cities. This study examined the exposure-response relationship between ambient temperatures and OI at the intra-city scale in Greater Adelaide, Australia. Vulnerable groups of workers, in terms of workers' characteristics, the nature of their work, and workplace characteristics were identified. Further, the projected risk of OI was quantified in various climate change scenarios. The temperature-OI association was estimated using a time-series study design combined with Distributed Lag Non-linear Models. Daily workers' compensation claims (2005-2018) were merged with 5 km gridded meteorological data of maximum temperature (°C) at Statistical Area Level 3 in Greater Adelaide. Region-wise subgroup analyses were conducted to identify vulnerable groups of workers. Future projections (2006-2100) were conducted using downscaled climate projections and the risk was quantified using log-linear extrapolation. The analyses were performed in R 4.1.0. The overall OI risk was 16.7% (95%CI: 10.8-23.0) at moderate heat (90th percentile) and increased to 25.0% (95%CI: 16.4-34.2) at extreme heat (99th percentile). Northern Adelaide had a higher risk of OI for all types of workers at moderate heat, while western regions had a high risk for indoor industries. Southern and eastern regions had a higher OI risk for males, older workers, and outdoor industries at extreme heat. The projected risk of OI is estimated to increase from 20.8% (95%CI: -0.2-46.3) in 2010s to 22.9% (95%CI: -8.0-64.1) by 2050s. Spatio-temporal risk assessment at the intra-city scale can help us identify high-risk areas, where targeted interventions can be efficiently employed to reduce the socio-economic burden of OI.