Korea’s agriculture plays a major role in the food production industry and concern for farmer’s health is increasing. Especially, farmers tend to be more elderly compared to any other industry. Understanding farmers’ health status is basically an important step. In this study, marriage status, smoking, regular exercise, monthly day off and pesticide protective device wearing were significant variables in farmers’ health status.
SF-12 score of the subjects was 52.66 out of 100. The study of Cha BS et al (1998) which showed the assessment of workers’ health status by SF-36 showed 69.61, manufacturer male employees’ assessment by SF-36 (Kim SA et al, 2006) was 78.44, and Lee SM (2010)’s study of large workplace employees in Daejeoun and Chungchung health status assessment by SF-12 showed 75.75 [11,14,15]. All of the above studies showed higher scores than this study. It may be because the farmers were older or there were more number of females or had less education or lower economic level than in the other workplace. In Jun JY’s study which evaluated elderly in a rural area by SF-36 revealed 56.15. It was higher than this study. Such study included subjects who were all elderly in an area regardless of farming. But it was difficult to compare because the number of subjects was too small [16].
On the mental component score, the females’ score was lower than the males’. It corresponded with previous studies which showed that the females generally had a lower health status than males [12,15,17-19]. There are some points to be considered. Nettleton (1995) explained that women work double hours at home and at work which causes negative effect on health. On the other hand, MacIntyre (1993) said that women tend to know more about their health status, and men exaggerate their health [20,21].
This study did not show significant difference in health status according to age. It does not follow previous studies which explains that health status decreases with age [12,17,18,22-24]. But some studies in elderly subjects showed that health status does not have correlation with age [25]. And the average age of the subjects was 64.1 which was high and many of them were more than their 60’s in this study. Therefore, it may not appropriate to compare.
Health status in married group was higher than in single group. Previous studies showed similar results. Existing spouse is helpful in physical health management and psychological stability [14,16,26,27].
Smokers’ health status score was higher than nonsmokers’ score. It was similar to previous studies [28,29]. However, there are many reports which explain that smoking has negative health effect and stop smoking in old age is helpful in improvement of health and quality of life [30]. And smoking can be a confounding factor. Alcohol did not have any significant correlation. The regular exercise group had a higher health status score. It corresponded with other studies [28,31,32].
Pesticide exposure did not show any significant relation. Long time pesticide exposure group tended to have low scores, but was not significant after revision. Meanwhile pesticide protective device wearing had a positive effect, especially the mental component. People who made efforts to wear protective device tended to have more concern about health. It was meaningful that there were few previous studies concerning the association of protective device and health. Longer monthly day off group had higher physical component scores. There were some similar results about the association between working day and health [33-35].
There are some limitations in this study. First of all, this study was carried out targeting 9 provinces in the country, but the sampling count per each town was too small. Therefore, it cannot be generalized among all farmers. And there were many differences in working conditions by crop. A close investigation was needed further. Secondly, this study was a cross-sectional research. The association of variables was found to exist, but the order of time was not clear. Lastly, there were omitted variable bias. The subjects were old age, but a questionnaire was used. BMI, income level, education level and sleeping hours which are related to health were omitted [25,36].