摘要Objective:This study assessed heat exposure,physiological responses,and the risk of chronic kidney disease among outdoor agricultural workers in Pak Chong,Thailand,and developed a predictive model for Wet Bulb Globe Temperature(WBGT).Methods:A cross-sectional study was conducted among 170 agricultural workers.Field WBGT was measured at 33 locations in April and July and corrected for Clothing Adjustment Factor to determine effective WBGT.Core temperature,skin temperature,heart rate,blood pressure,and body weight were monitored before,during,and after work shifts.Urine dipstick and microalbumin tests were performed to evaluate dehydration and kidney disorder.Workloads were classified according to American Conference of Governmental Industrial Hygienists(ACGIH)metabolic rate categories.Meteorological data were used to train machine learning models—including linear regression,decision tree,random forest,and extreme gradient boosting—to predict WBGT values.Results:Effective WBGT at fruit gardens and field crops sites frequently exceeded ACGIH limits for moderate-to-heavy work.Workers' systolic/diastolic blood pressure and heart rate increased during work(transient car-diovascular strain)while body temperature remained stable.Post-shift,34.7％showed moderate dehydration;microalbumin screening was positive in 31/170(18.2％)suggesting possible early renal involvement but not chronic kidney disease diagnosis.Among the predictive models,extreme gradient boosting achieved the best per-formance(root mean square error=0.798 ℃,mean absolute error=0.576 ℃,R2=0.81).The most influential predictors were air temperature,sunshine duration,and site-specific factors.Conclusions:Agricultural workers in Pak Chong are frequently exposed to heat stress that exceeds ACGIH stan-dards,predisposing them to dehydration and kidney impairment.The findings support evidence-based preventive strategies such as regulated work-rest cycles,hydration management,and medical surveillance.Moreover,the validated WBGT prediction tool offers a practical approach for real-time monitoring and proactive climate adap-tation to protect outdoor workers in heat-prone environments.