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Background: The objective of this study was to compare differences in lifestyle diseases, musculoskeletal pain, psychosocial stress, and self-health awareness according to gender in Korean farmers. Methods: The study population comprised 436 farmers residing in rural areas in Korea. A self-administered questionnaire was used to survey demographic characteristics, health-related behaviors, and musculoskeletal pain. The psychosocial well-being index short form (PWI-SF) was used to survey psychosocial stress, and the 12-item short form health survey (SF-12) was used to survey self-health awareness. In addition, a clinical examination was performed for each participant, and lifestyle diseases were identified through a health checkup. Results: Among lifestyle diseases, females showed a significantly higher proportion than males for metabolic syndrome (OR: 4.57 [95% CI, 1.67–12.51]). For musculoskeletal pain, females again showed significantly higher proportion than males for hand pain (OR: 16.79 [95% CI, 3.09–91.30]), and pain in at least one body part (OR: 2.34 [95% CI, 1.16–4.70]). For psychosocial stress, females showed a significantly higher proportion than males for high-risk stress (OR: 3.10 [95% CI, 1.17–8.24]). Among the items in self-health awareness, females showed significantly higher proportion than males for mental component score (MCS) (OR: 3.10 [95% CI, 1.52–6.31]) and total score (OR: 2.34 [95% CI, 1.11–4.90]). Conclusions: For all items that showed significant differences, females showed higher proportion than males, which indicates that female farmers tended to have poorer overall health than male farmers. Therefore, specialized programs will have to be developed to improve the health of female farmers. Keywords: Farmer, Gender, Health status, Lifestyle diseases, Musculoskeletal pain, Psychosocial stress, Self-health awareness Background financial situation is also unstable . In Korea, occupa- The rural population of Korea has declined sharply, tional injuries within the farming sector have from 10.8 million in 1980 to 2.4 million in 2017. During higher-than-average accident rates reported than other this time, young people from rural areas had relocated occupations [5, 6]. In addition, the basic living condi- to urban areas, creating an aging society in rural regions. tions of Korean farmers are much poorer than those liv- This phenomenon has created a shortage of labor in ing in urban areas due to excessive physical labor, younger age groups, while increasing the intensity of increase in the number of female farmers, lack of educa- labor for elderly and female farmers [1, 2]. tion, poor hygienic environment, apathy towards health, Farming, which is known to be a dangerous occupa- and low socioeconomic status. They also experience dif- tion for both males and females, has unique characteris- ficulties in the utilization of healthcare facilities. Further- tics that are different from other occupations due to the more, they must also participate in other outdoor and characteristics and behaviors of farmers, their working household work due to a shortage of labor in farming environment, and organizational structure . Moreover, areas. The physical and mental functions of farmers tend farmers do not properly apply the safety rules, and their to deteriorate as a consequence [7–9]. A study in 2009 compared the proportion of musculo- * Correspondence: email@example.com skeletal and chronic diseases between Korean farmers Department of Occupational and Environmental Medicine, Soonchunhyang and other occupational groups; it found that both male University Gumi Hospital, 179, 1gongdan-ro, Gumi, Gyeongsangbuk-do, Republic of Korea © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Lee et al. Annals of Occupational and Environmental Medicine (2019) 31:7 Page 2 of 9 and female farmers showed a higher proportion of mus- million won, 25–49 million won, and ≥ 50 million won, culoskeletal disease, while female farmers showed a sig- and housework was categorized as 0, < 2, and ≥ 2 h/day. nificantly higher proportion of hypertension than other Alcohol drinking, smoking, and exercise status were occupational groups . In a study conducted in 2016 surveyed as health-related behaviors. Alcohol drinking on the proportion of musculoskeletal pain and the char- status was categorized as nondrinker, once/week, and acteristics of Korean farmers, female farmers showed a two or more times/week. Smoking status was catego- significantly higher risk of pain in the shoulders, hands, rized as nonsmoker, ex-smoker, and current smoker. lower back, and legs compared to male farmers . A Exercise status was categorized as “Yes,” if the subjects study in 2015 examined the health status and related performed moderate to vigorous exercise or walking at factors of farmers, using the 12-item short form health least 5 days a week and “No,” if otherwise. survey (SF-12) to evaluate self-health awareness; the re- A clinical examination was performed on each partici- sults showed that females had a lower mental compo- pant through a health checkup to measure height, nent score (MCS) than males . weight, waist circumference, body mass index (BMI), As shown, studies have compared differences in the blood pressure, hemoglobin, fasting blood glucose (FBS), risk or proportion of specific diseases between male and serum lipids, and serum liver enzymes. Obesity was de- female farmers or differences in disease proportion be- fined based using BMI, with BMI < 25 kg/m as normal tween farmers and other occupational groups. However, and ≥ 25 kg/m as obese . Blood pressure, there have been no studies that systematically compare hemoglobin, FBS, serum lipids, and serum liver enzymes the physical and mental state of farmers according to were defined as abnormal when a disease was suspected gender. Accordingly, this study aimed to compare differ- or diagnosed based on the standards of the NHIS in ences in lifestyle diseases, musculoskeletal pain, psycho- Korea. The details are as follows. Hypertension was social stress, and self-health awareness of Korean defined as systolic pressure ≥ 140 mmHg or diastolic pres- farmers according to gender. sure ≥ 90 mmHg during blood pressure measurement, or being treated for hypertension. Diabetes mellitus was de- Methods fined as FBS ≥126 mg/dL, or being treated for diabetes Subjects mellitus. Dyslipidemia was defined as total cholesterol The study area was set as rural areas in Gyeongsangbuk-do ≥240 mg/dL, triglyceride ≥200 mg/dL, high-density lipo- Province in Korea. The study population consisted of protein cholesterol (HDL-C) < 40 mg/dL, low-density lipo- farmers residing in a total of 11 areas: 3 areas in protein cholesterol (LDL-C) ≥160 mg/dL, or being treated 2015, 4 in 2016, and 4 in 2017. Among the 458 for dyslipidemia. Anemia was defined as hemoglobin < 13 people who participated in both a questionnaire sur- mg/dL for males and < 12 mg/dL for females. For serum vey and health checkup conducted by the National liver enzymes, aspartate aminotransferase (AST), alanine Health Insurance Service (NHIS), 436 people were in- aminotransferase (ALT), and gamma-glutamyltransferase cluded in the final study population, after excluding (γ-GTP) levels were measured, and AST ≥50 IU/L, ALT 22 people who did not work in farming or provided ≥45 IU/L, or γ-GTP ≥78 IU/L for males and ≥ 46 IU/L for incomplete responses to the questionnaire. females were considered abnormal . For metabolic syndrome, the National Cholesterol Survey content Education Program’s Adult Treatment Panel III (NCEP A self-administered questionnaire was used to survey ATP III) was applied for metabolic syndrome, along with demographic characteristics, health-related behaviors, the International Diabetes Federation (IDF) definition in and musculoskeletal pain. The specific details were as 2009 for waist circumference. Those who satisfied 3 or follows: more of the following conditions were considered to have metabolic syndrome: systolic blood pressure ≥ 130 mmHg, Demographic characteristics, health-related behaviors, and diastolic blood pressure ≥ 85 mmHg, or being treated for clinical examination hypertension; FBS ≥100 mg/dL or being treated for dia- The demographic characteristics of the subjects in- betes mellitus; waist circumference ≥ 90 cm for males cluded: gender, age, working duration, main crops, pres- and ≥ 80 cm for females; triglyceride ≥150 mg/dL; and ence of family members other than the spouse, spouse, HDL-C < 40 mg/dL for males and < 50 mg/dL for females income, and housework time. Main crops were catego- [15–17]. rized as grains, vegetables, fruits, livestock, and other. Lifestyle diseases were identified based on these re- Spouse was categorized as “Yes” or “No” (single, di- sults. Lifestyle diseases refer to a disease group with on- vorced, or widowed), and presence of family members set and progression affected by lifestyle, including diet, other than the spouse was categorized as “Yes” or “No”. exercise, smoking, and drinking . In this study, life- Income was categorized as < 10 million won, 10–24 style disease was defined as a suspected or confirmed Lee et al. Annals of Occupational and Environmental Medicine (2019) 31:7 Page 3 of 9 disease in the health checkup or diagnosis with meta- was performed to investigate the differences in life- bolic syndrome. Specifically, hypertension, diabetes mel- style disease, musculoskeletal pain, psychosocial stress, litus, dyslipidemia, anemia, abnormal serum liver and self-health awareness between male and female enzymes, and metabolic syndrome were checked as life- farmers. For psychosocial stress, healthy and potential style diseases. stress of PWI-SF was set as low risk and used as the reference. For self-health awareness, the results were Musculoskeletal pain assessment divided into high and low based on the median value To evaluate musculoskeletal pain symptoms, this study of SF-12 scores, with the higher score group set as used the questionnaire “Guidelines for surveys of harm- the reference. The adjustment variables included in ful factors in tasks involving musculoskeletal loads” multiple logistic regression analysis were age, spouse, from the Korea Occupational Safety and Health Agency income, housework time, alcohol drinking, smoking, (KOSHA) CODE H-9-2016 . Items included in the exercise; they were included in the analysis because questionnaire were: six specific body parts (neck, shoul- showed p-value < 0.15 in univariate analysis. We also der, arm, hand, lower back, and leg), duration of pain, included several other variables (i.e., work duration, severity of pain, and frequency of symptoms in the last main crops, presence of family members other than year. Based on the results, musculoskeletal pain was de- the spouse) associated with lifestyle disease, musculo- fined as moderate-to-severe pain in one or more areas skeletal pain, psychosocial stress, and self-health that persists for at least one week or occurs more than awareness in previous study [26–30]. All statistical once in a month, in accordance with Standard 2 of the analyses were performed using SPSS version 14.0 National Institute for Occupational Safety and Health (SPSS,Inc.,Chicago,IL, USA). (NIOSH) . Psychosocial stress assessment Results The psychosocial well-being index short form (PWI-SF) Among demographic characteristics, the mean ages of was used as the tool for assessing psychosocial stress. males and females were 62.7 ± 9.21 and 60.9 ± 9.67 years, The form comprised questions about physical and men- respectively. The proportion of males and females with- tal state in the past few weeks, with the total score ran- out a spouse was 8.8 and 19.0%, respectively. The pro- ging between 0 and 54 points. Higher scores indicated a portion of males and females who did no housework higher level of psychosocial stress, with ≤8, 9–26, and ≥ was 49.0 and 1.3%, respectively, while 37.3% of males 27 points defined as healthy, potential stress, and and 36.6% of females spent < 2 h/day on housework, and high-risk stress, respectively [21, 22]. 13.7% of males and 62.1% of females spent ≥2 h/per day on housework. There were no differences in working Self-health awareness assessment duration, main crops, presence of family members other The 12-item short form health survey (SF-12) was used than the spouse, and income between males and as the tool for assessing self-health awareness. SF-12 is females. an abridged version of SF-36, which can be used to Among health-related behaviors, the proportion of measure physical component score (PCS) and sub-items, male and female nondrinkers was 38.2 and 81.0%, re- mental component score (MCS) and sub-items, and the spectively, while 16.7% of males and 12.9% of females total score. Sub-items under PCS included physical func- drank once a week, and 45.1% of males and 6.0% of fe- tioning (PF), role physical (RP), bodily pain (BP), and males drank two or more times a week. The proportion general health (GH); sub-items under MCS included of male and female nonsmokers was 36.3 and 97.4%, re- mental health (MH), role emotional (RE), social func- spectively, while 31.9% of males and 1.7% of females tioning (SF), and vitality (VT). A higher score in each were ex-smokers, and 31.9% of males and 0.9% of fe- item indicated better-perceived health status for that males were current smokers. There was no difference in item [23–25]. exercise level between males and females (p < 0.05) (Table 1). Statistical analysis When comparing lifestyle diseases between males and In this study, t-test and chi-square test were performed to in- females, proportion of diabetes mellitus was significantly vestigate the differences in demographic characteristics, lower in females (9.1%) than in males (17.2%); anemia health-related behaviors, clinical examination, musculoskeletal was significantly higher in females (15.5%) than in males pain, and self-health awareness between male and female (6.4%); abnormal serum liver enzymes were significantly farmers. A linear-by-linear association test was per- lower in females (7.8%) than in males (23.5%); and meta- formed to investigate differences in psychosocial bolic syndrome was significantly higher in females stress. In addition, multiple logistic regression analysis (32.6%) than in males (21.6%). Meanwhile, there were no Lee et al. Annals of Occupational and Environmental Medicine (2019) 31:7 Page 4 of 9 Table 1 Baseline characteristics of the study subjects according to gender Variables Male Female p- value n (%) or Mean ± SD n (%) or Mean ± SD Demographic variables Age (years) 62.7 ± 9.21 60.9 ± 9.67 0.048 Work duration (years) 29.2 ± 18.5 29.1 ± 16.8 0.950 Main crops 0.952 Grains 34 (16.7) 42 (18.1) Vegetables 54 (26.5) 65 (28.0) Fruits 106 (52.0) 115 (49.6) Livestock 8 (3.9) 7 (3.0) Other 2 (1.0) 3 (1.3) Spouse 0.002 No 18 (8.8) 44 (19.0) Yes 186 (91.2) 187 (81.0) Presence of family members other than the spouse 0.903 No 66 (32.4) 76 (32.9) Yes 138 (67.6) 155 (67.1) Income (million KRW) 0.133 < 10 60 (32.8) 89 (41.8) 10–24 38 (20.8) 47 (22.1) 25–49 64 (35.0) 53 (24.9) ≥ 50 21 (11.5) 24 (11.3) Housework time (hours/day) 0.000 0 100 (49.0) 3 (1.3) < 2 76 (37.3) 85 (36.6) ≥ 2 28 (13.7) 144 (62.1) Health-related behaviors Alcohol drinking 0.000 Nondrinker 78 (38.2) 188 (81.0) 1/week 34 (16.7) 30 (12.9) More than 2/week 92 (45.1) 14 (6.0) Smoking 0.000 Nonsmoker 74 (36.3) 225 (97.4) Ex-smoker 65 (31.9) 4 (1.7) Current smoker 65 (31.9) 2 (0.9) Exercise 0.124 No 110 (53.9) 142 (61.2) Yes 94 (46.1) 90 (38.8) KRW South Korean won. *p-value by t-test or Chi-square test Mean ± SD N (%) differences in hypertension, dyslipidemia, and obesity 19.0% of females had hand pain; 24.8% of males and between males and females (p < 0.05) (Table 2). 40.1% of females had lower back pain; and 25.7% of When comparing the complaint rate of males and fe- males and 37.9% of females had leg pain. These results males experiencing musculoskeletal pain, 5.4% of males show a significantly higher proportion of females hav- and 12.1% of females had neck pain; 4.0% of males and ing neck, hand, lower back, and leg pain. Moreover, Lee et al. Annals of Occupational and Environmental Medicine (2019) 31:7 Page 5 of 9 Table 2 Comparison of lifestyle diseases according to gender Table 3 Comparison of musculoskeletal pain according to body parts according to gender Variables Male Female p- value Variables Male Female p- n (%) n (%) value n = 202 (46.5%) n = 232 (53.5%) Hypertension 0.843 Neck 0.016 No 125 (61.3) 140 (60.3) No 191 (94.6) 204 (87.9) Yes 79 (38.7) 92 (39.7) Yes 11 (5.4) 28 (12.1) Diabetes mellitus 0.012 Shoulder 0.066 No 169 (82.8) 211 (90.9) No 160 (79.2) 166 (71.6) Yes 35 (17.2) 21 (9.1) Yes 42 (20.8) 66 (28.4) Dyslipidemia 0.952 Arm 0.397 No 119 (58.3) 136 (58.6) No 178 (88.1) 198 (85.3) Yes 85 (41.7) 96 (41.4) Yes 24 (11.9) 34 (14.7) Anemia 0.003 Hand 0.000 No 191 (93.6) 196 (84.5) No 194 (96.0) 188 (81.0) Yes 13 (6.37) 36 (15.5) Yes 8 (4.0) 44 (19.0) Abnormal serum liver enzymes 0.001 Back 0.001 No 156 (76.5) 206 (88.8) No 152 (75.2) 139 (59.9) Yes 48 (23.5) 26 (11.2) Yes 50 (24.8) 93 (40.1) Obesity 0.703 Leg 0.007 No 125 (61.3) 138 (59.5) No 150 (74.3) 144 (62.1) Yes 79 (38.7) 94 (40.5) Yes 52 (25.7) 88 (37.9) Metabolic syndrome 0.025 Pain in at least one body part 0.000 No 120 (78.4) 120 (67.4) No 107 (53.0) 76 (32.8) Yes 33 (21.6) 58 (32.6) Yes 95 (47.0) 156 (67.2) *p-value by Chi-square test *p-value by Chi-square test the proportion of those with pain in at least one body part was significantly higher in females (67.2%) than diseases, the risk for metabolic syndrome was signifi- in males (47.0%). Meanwhile, there were no differ- cantly higher in females than males (OR: 4.57 [95% CI, ences in the shoulder and arm pain between males 1.67–12.51]). For musculoskeletal pain, females showed and females (p < 0.05) (Table 3). significantly higher risk than males for hand pain (OR: When comparing psychosocial stress between males 16.79 [95% CI, 3.09–91.30]), and pain in at least one and females using the PWI-SF, 27.1% of males and 16.7% bodypart(OR:2.34[95% CI,1.16–4.70]). For psycho- of females belonged to the healthy group; 60.3% of males social stress, females had a significantly higher risk for and 58.1% of females belonged to the potential stress high-risk stress than males (OR: 3.10 [95% CI, 1.17– group; and 12.6% of males and 25.2% of females belonged 8.24]). Among the items in self-health awareness, fe- to the high-risk stress group (p < 0.05) (Table 4). males showed significantly higher risk than males for When comparing self-health awareness between males MCS (OR: 3.10 [95% CI, 1.52–6.31]) and total score and females using the SF-12, PCS was 68.6 ± 23.5 in males (OR: 2.34 [95% CI, 1.11–4.90]) (Table 6). and 58.3 ± 26.0 in females. MCS was 77.5 ± 18.8 in males and 67.8 ± 22.5 in females. The total score was 73.1 ± 18.9 in males and 63.1 ± 22.6 in females. Females showed sig- Table 4 Comparison of psychosocial stress according to gender nificantly lower PCS, MCS, individual sub-item (PF, RP, Variables Male Female p- BP, GH, MH, RE, SF, or VT) scores, and total score in the value n (%) n (%) SF-12, compared to males (p <0.05) (Table 5). Group 0.000 Multiple logistic regression analysis was performed to in- Healthy 54 (27.1) 37 (16.7) vestigate the differences in lifestyle diseases, musculoskel- Potential stress 120 (60.3) 129 (58.1) etal pain, psychosocial stress, and self-health awareness High-risk stress 25 (12.6) 56 (25.2) between males and females, after adjusting for demographic characteristics and health-related behaviors. Among lifestyle *p-value of linear-by-linear association Lee et al. Annals of Occupational and Environmental Medicine (2019) 31:7 Page 6 of 9 Table 5 Comparison of self-health awareness according to Table 6 Adjusted odds ratio of lifestyle diseases, musculoskeletal gender pain, psychosocial stress, and self-health awareness according to gender Variables Male Female p- value Variables Female 95% CI Mean ± SD Mean ± SD OR PCS 68.6 ± 23.5 58.3 ± 26.0 0.000 Lifestyle disease PF 71.8 ± 33.7 60.2 ± 35.8 0.001 Hypertension 1.42 0.70–2.87 RP 75.3 ± 31.5 63.8 ± 35.4 0.000 Diabetes mellitus 0.53 0.21–1.36 BP 81.1 ± 24.5 70.8 ± 30.5 0.000 Dyslipidemia 1.24 0.62–2.45 GH 46.4 ± 25.0 38.4 ± 24.7 0.001 Anemia 1.54 0.50–4.71 MCS 77.5 ± 18.8 67.8 ± 22.5 0.000 Abnormal serum liver enzymes 1.40 0.52–3.75 MH 76.1 ± 23.3 66.5 ± 26.1 0.000 Obesity 2.05 1.02–4.13 RE 82.6 ± 26.6 73.2 ± 29.8 0.001 Metabolic syndrome 4.57 1.67–12.51 SF 89.4 ± 22.9 80.7 ± 29.3 0.001 Musculoskeletal pain VT 62.1 ± 33.2 50.8 ± 34.2 0.001 Neck 0.90 0.25–3.28 Total score 73.1 ± 18.9 63.1 ± 22.6 0.000 Shoulder 0.75 0.34–1.65 PCS physical component score, PF physical functioning, RP role physical, BP bodily pain, GH general health, MCS mental component score, MH mental Arm 0.67 0.25–1.80 health, RE role emotional, SF social functioning, VT vitality. *p-value by t-test Hand 16.79 3.09–91.30 Lower back 2.12 0.99–4.56 Discussion Leg 1.42 0.67–3.03 In this study, the proportion of metabolic syndrome was Pain in at least one body part 2.34 1.16–4.70 significantly higher in females (32.6%) than in males Psychosocial stress (21.6%), and the risk of metabolic syndrome in females High-risk stress 3.10 1.17–8.24 was 4.57 [95% CI, 1.67–12.51] times higher than in males. In a study that followed up 1095 rural residents Self-health awareness for 5 years to measure the proportion of metabolic syn- PCS 1.52 0.75–3.11 drome, females showed a significantly higher proportion MCS 3.10 1.52–6.31 of 46.4/1000 person-years, compared to 30.0/1000 Total score 2.34 1.11–4.90 person-years for males, which is consistent with the PCS physical component score, MCS mental component score. present study . A previous study of 91 farmers found Adjusted for age, working duration, main crops, presence of family members that the proportion of metabolic syndrome was lower in other than the spouse, spouse, income, housework time, alcohol drinking, smoking, exercise. females (42.9%) than in males (51.4%), which is contra- OR of male: 1.00. dictory to the present study . The previous study did Odds ratio and 95% confidence interval by multiple logistic regression analysis. not include people being treated for hypertension and diabetes mellitus in the criteria for metabolic syndrome. This is postulated to be the reason for the difference have influenced the results. Second, previous studies have from the present study. Another study that followed up reported a statistically significant positive correlation be- 460 rural residents for 5 years also found the proportion tween BMI and risk of metabolic syndrome [37, 38], and of metabolic syndrome to be 37.9/1000 person-years in other studies have presented obesity as the most sensitive males and 18.9/1000 person-years in females . The indicator of metabolic syndrome [39, 40]. It is presumed present study included only farmers, whereas the previ- that females having significantly higher risk of obesity than ous study included all rural residents; it is presumed that males in in the present study may have influenced the the different findings may be attributable to 47.4% of the results. subjects in the previous study being unemployed. The Chi-square test results for musculoskeletal pain showed reason why females showed a higher risk of metabolic that a significantly higher proportion of females had neck, syndrome in the present study may be attributed to hand, lower back, and leg pain compared to males. Mul- several factors. First, pregnancy and childbirth have been tiple logistic regression analysis results also showed that reported to cause metabolic disorders accompanied by females had a higher risk of pain than males; specifically, weight gain, increased abdominal obesity, and postpartum the odds ratios were 16.79 [95% CI, 3.09–91.30] for hand depression [34–36]. Since the females who participated in pain, and 2.34 [95% CI, 1.16–4.70] for pain in at least one the present study had an average age in their 60s, the fact body part. A previous study that investigated the risk and that most have experienced pregnancy and childbirth may characteristics of musculoskeletal pain in 1013 Korean Lee et al. Annals of Occupational and Environmental Medicine (2019) 31:7 Page 7 of 9 farmers found that females had a significantly higher risk PCS, MCS, total score, and 8 sub-items, indicating that of pain than males, with odds ratios of 1.77 [95% CI, females tended to perceive their health to be poor com- 1.18–2.64] for shoulder pain, 3.88 [95% CI, 2.35–6.42] for pared to males. Previous studies also showed similar re- hand pain, 2.13 [95% CI, 1.39–3.24] for lower back pain, sults, where females showed lower perception of their and 1.92 [95% CI, 1.29–2.86] for leg pain . The higher overall self-health than males did [25, 46, 47]. Nettleton overall risk of pain in females shown in the previous study explained that performing the dual task of work and is similar to the present study, but the pain areas were dif- housework has a negative effect on the health of females ferent. This difference is postulated to be due to the . Meanwhile, MacIntyre explained that symptoms present study applying NIOSH Standard 2, whereas the are more readily noticed in females since they tend to be previous study applied NIOSH Standard 1. In a study of well aware of their own health, whereas males do not musculoskeletal pain in 220 Indian rice farmers, the risk accept the fact that they may be ill and perceive their of pain in females was significantly higher than that of health to be better than it actually is . In such cases, males for shoulder, hand, lower back, and knee pain . males may show relatively better scores than their actual For the farmers in the present study, fruits were the main health status, which may be the reason for the lower crop, while the main crop in the previous study was rice. perception of their self-health in females than males. In Farming different crops is predicted to lead to differences other words, itis presumed that the responses to the in posture while farming, which would, in turn, lead to questions might contain over- or under-estimations. differences in the location of pain. In the present study, fe- The present study has several limitations. First, the male farmers showed higher risk than males for hand study population consisted of people from 11 rural areas pain. This may be because female Korean farmers often in Gyeongsangbuk-do Province but, because of the small perform tasks that require repetitive use of the hands and sample size from each area, it is difficult to generalize fingers [27, 28]. Moreover, females in the present study the findings for all farmers. Second, there was no investi- showed significantly higher time spent on housework than gation of the life expectancy of male and female farmers males and, as a result, the working time, including house- in Korea. The life expectancy of females in the general work, may be higher in female farmers than in male population in Korea was found to be 85.6 years in 2017, farmers. In a study that investigated the difference in mus- which was longer than the 79.5 years for males . In a culoskeletal disorders according to gender among 358 Ko- previous study conducted in the United States, the life rean farmers, the average daily working time for female expectancy of females in rural areas in 2005–2009 was farmers (9.6 h) was longer than that of male farmers (9.2 79.7 years, which was longer than that of males aged h). Since the female farmers also tended to be solely re- 74.1 years . In the present study, the health status of sponsible for housework, they had a greater burden [27, female farmers was poorer than was that of males, but 28]. It is postulated that female farmers showed a higher we could not confirm if they had a longer life expectancy risk of hand pain than males because housework mostly than did males despite their poorer health status. involves the use of the hands. Despite these limitations, this study was able to com- For psychosocial stress assessed using the PWI-SF, the pare lifestyle diseases, musculoskeletal pain, psychosocial chi-square tests results showed that a higher proportion stress, and self-health awareness to identify differences of females had potential stress and high-risk stress than in the physical and mental health status of farmers ac- males. Further, females had a higher risk for high-risk cording to gender. It also demonstrated that female stress than males (OR: 3.10 [95% CI, 1.17–8.24]). In a farmers had higher health risks than male farmers, indi- 2017 study that used the PWI-SF to analyze psychosocial cating that female farmers tend to have poorer health stress factors in 3631 rural residents, females had a signifi- than male farmers. In addition, this study is significant cantly higher risk for high-risk stress than males (OR: 2.34 in recognizing these differences and thus it can be used [95% CI, 1.88–2.92]), which is similar to the present study as basic data for the development of a specialized health . In a 2011 study on 1737 rural residents, psychosocial promotion program for female farmers. stress was significantly higher in females than in males, which was also similar to the present study . These re- Conclusions sults are postulated to reflect the characteristics associated While there have been many studies on the specific with cultural differences regarding gender roles in Korean health issues of farmers, there have been almost no stud- society and the patriarchal characteristics of Korean rural ies to date that have examined the overall difference in areas [44, 45]. The relatively longer working hours for fe- the health of farmers according to gender. This study male farmers are also presumed to act as a burden, result- was conducted to investigate the differences in health ing in increased stress . status between male and female farmers. The items that For self-health awareness assessed using the SF-12, fe- showed differences in the health status of farmers ac- males showed significantly lower scores than males for cording to gender were metabolic syndrome, Lee et al. 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Cha ES, Kong KA, Moon EK, Lee WJ. Prevalence and changes in chronic III: National Cholesterol Education Program’s Adult Treatment Panel III; diseases among south Korean farmers: 1998 to 2005. BMC Public Health. NHIS: National Health Insurance Service; NIOSH: National Institute for 2009;9:268. Occupational Safety and Health; OR: Odds ratio; PCS: Physical 11. Min D, Baek SR, Park HW, Lee SA, Moon JY, Yang JE, et al. Prevalence and component score; PF: Physical functioning; PWI-SF: Psychosocial well- characteristics of musculoskeletal pain in Korean farmers. Ann Rehabil Med. being index short form; RE: Role emotional; RP: Role physical; SF: Social 2016;40(1):1–13. functioning; SF-12: 12-item short form health survey; γ-GTP: Gamma- 12. Park KG, Roh SY, Lee JH, Kwon SC, Jeong MH, Lee SJ. Health status and glutamyltransferase related factors in farmers by SF-12. Ann Occup Environ Med. 2015;27:2. 13. 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