Knowledge, perception and practice on protection of heat-related stress affecting health and productivity among maize farmers in Gombe, Nigeria
Heat stress disorders and subsequent productivity reduction output have been a rising concern for agricultural workers, working under direct sunlight for an extended number of hours. The study was conducted to assess the knowledge, perception and practice on protection of heat-related stress affecti...
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| Format: | Thesis |
| Language: | English |
| Published: |
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/70917/1/FPSK%28M%29%202017%208%20-%20IR.pdf http://psasir.upm.edu.my/id/eprint/70917/ |
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| Summary: | Heat stress disorders and subsequent productivity reduction output have been a rising concern for agricultural workers, working under direct sunlight for an extended number of hours. The study was conducted to assess the knowledge, perception and practice on protection of heat-related stress affecting health and productivity among maize farmers in Gombe, Nigeria. A cross-sectional study was conducted among 396 maize farmers. Simple random sampling technique was used to determine the; knowledge, perception, and practice of heat stress, experience on impact of heat stress, self-reported heat stress related symptoms, the relationship between knowledge scores of workers and health practices, and the self-reported heat stress related symptoms. The validated self-administered questionnaire was used as the instrument for the data collection. The relationship between physiological body changes and exposed heat, and their difference was determined in the different time of the day during farming operation. The difference in productivity within the different time of the day was also determined. The relationship of temperature, BMI, age, and gender on the productivity were also determined. Anthropometric data was measured using a weighing scale and tape height instrument. Data on physiological body changes for blood pressure and heart rate were measured using digital blood pressure monitor, while body temperature was measured using a digital thermometer. The productivity of workers was determined using the productivity data sheet that keeps a record of the number of ridges tilled per hectare within the three different time of the farming operation. The wet bulb globe temperature monitor (WBGT) QuestTemp°36 model was used in determining the heat index. The study showed that the majority of the respondents got high scores on knowledge of the basic factors that cause heat stress (87.9%), and moderate score on the early heat stress related illnesses or symptoms (68.4%). Heat stress is perceived by about 66% as a determining factor for causing health disorder and productivity decrease. Common safe working practices for protection against heat stress were embraced almost every day by about 90.0% of the farmers. Over 50% reported heat stress as a factor to the loss of productivity based on their experience. Heavy sweating (93.2%), tiredness (48.5%), dizziness (34.1) and headache (40.4) were experienced by the respondents almost on daily basis. There was a significant positive correlation between knowledge and health practices of heat stress, as well as inverse relationship between knowledge and reported HRI and symptoms. There was a significant difference in practice score between knowledge groups. The total mean heat stress index of the farms was 30.26°C exceeding the threshold level set by ACGIH. There was a direct significant correlations between respondents’ body temperature before, during and after working hours and the environmental temperature, (p <0.001). Systolic blood pressure during work and the environmental temperature showed a direct significant correlations, (p <0.001). A direct significant correlation between respondents’ heart rate and environmental temperature was seen during and after working hours (p < 0.001). Both systolic and diastolic blood pressure, heart rate and body temperature showed a significant difference before, during and after working hours (p <0.001). There was a significant regression for all the variables tested on productivity; temperature (p < 0.001), gender (p < 0.001), age (p = 0.033) and BMI (p = 0.008). The finding further showed significant differences in the productivity between the hours of 6am-9am, 9am-12pm, and 12-3pm (p <0.001). The farmers were frequently found experiencing heat exhaustion which decreased their productivity. |
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