0322 The usefulness of compensation statistics to detect heat-related health outcomes in a temperate climate: the experience of Quebec0322 The usefulness of compensation statistics to detect heat-related health outcomes in a temperate climate: the experience of Quebec
研究利用魁北克1998-2010年工人补偿数据，发现夏季高温与热相关疾病补偿数正相关，每升高1°C发病率增加41%，且63%病例发生在30°C以下，表明补偿统计可识别高危行业。
<h3>Objectives</h3> To explore relationships between summer outdoor temperatures in Quebec (Canada) and occupational compensation statistics for heat-related illnesses. <h3>Method</h3> Daily compensation counts of heat-related illnesses (heat strain, heatstroke, loss of consciousness, etc.), occurring between May and September, were obtained from the workers’ compensation board of Quebec for each health region between 1998 and 2010. Regional daily maximum outdoor temperatures were obtained from Environment Canada. Associations between daily compensation counts and temperature were estimated using negative binomial or Poisson regression models for each region and were adjusted for relative humidity and temporal trends. Pooled effect sizes for Quebec (all health regions combined) were obtained using a fixed effect model for meta-analysis. <h3>Results</h3> In an average population of 3.7 million workers, 259 illnesses classified as heat-related were compensated between 1998 and 2010, giving an average annual rate of 0.11 case per 100 000 workers per summer month. During the study period, 63.0% of heat-related outcomes occurred on days with a maximum daily average temperature below 30<sup>o</sup>C. Occupations with the largest number of compensations were those of labourers (32%), firefighters (11%) and truck drivers (4%). The pooled incidence rate ratio (IRR) was 1.41 (95% CI 1.35–1.46) per 1<sup>o</sup>C increase in daily maximum temperature. Effects of barometric pressure and lag will be explored. <h3>Conclusions</h3> Heat-related illnesses do occur in temperate climates. Our results suggest that compensation statistics, albeit crude indicators of health effects, can be useful to identify industry sectors and occupations that would benefit from preventive interventions aimed at high risk workers.