METHOD: A total of 328 municipal workers were enrolled in April to March 2016 were asked to recall if they experienced eleven HRI symptoms during the previous work day. Rasch Measurement Model was used to examine the unidimensional parameters and bias for gender before identifying the threshold of HRI symptoms. We determined the threshold symptom based on the person-item map distribution on a logit ruler value.
RESULTS: A total of 320 respondents were analysed. The psychometric features HRI symptoms suggested evidence of unidimensionality and free of bias for gender (DIF size =0.57; DIF t value =1.03). Based on the person-item map distribution, the thirst item was determined as the threshold item (Cut-off point = -2.17 logit) for the preventative action purposes to group the person as mild and moderate/severe HRI groups.
CONCLUSION: Thirst item is viewed as threshold symptoms between mild and moderate or severe HRI symptoms. It is a reliable symptom to initiate behavioural response to quench the thirst by adequate fluids. Failure to recognise the thirst symptom may lead to devastating unwanted health complications.
Objective: This study assessed the impact of heat on the health and productivity among maize farmers in a hot tropical country.
Methods: A cross-sectional study was conducted among 396 maize farmers, randomly selected across Gombe province, Nigeria. The wet bulb globe temperature monitor (WBGT) Model QuesTemp036 was used in determining the heat index. Health was determined using a validated questionnaire, while productivity was determined by recording work output based on the number of ridges cultivated during the working hours.
Results: The farms recorded mean heat index with standard deviation (SD) of 31.56 (2.19) and 34.08 (1.54) in the hours of 9 am to 12 pm and 12-3 pm respectively, which exceeded the threshold level set by the ACGIH. Heavy sweating (93.2%), tiredness (48.5%), dizziness (34.1%), and headache (40.4%) were experienced by the respondents almost on daily basis. The finding further showed a significant difference in the farmers' productivity during the three time duration of the work day (p < 0.001). The productivity was significantly higher between the hours of 6-9 am (p < 0.001) and 12-3 pm (p < 0.001), compared to the hours of 9 am to 12 pm (p < 0.001). The factors that significantly predict the productivity outcome include temperature (p < 0.001), gender (p < 0.001), age (p=0.033), and BMI (p=0.008).
Conclusion: The farmers were frequently experiencing heat exhaustion which decreased their productivity.