Association between physical capacity and occupational falls among middle‐aged and older farmers in Thailand: Using the self‐check risk assessment tool in Japan

1 INTRODUCTION

Aging of the agricultural workforce is a growing concern in emerging countries in Asia.1 In Thailand, agriculture is the industry with the largest number of workers, accounting for 29.5% of the working population.2 Thailand is an emerging country with a rapidly aging population, and the percentage of the population aged 65 and over is estimated to increase from 13.0% in 2020 to 26.2% in 2040.3 Because agriculture belongs to the informal sector in Thailand, farmers do not have access to social security systems such as pensions, workers’ compensation, or unemployment insurance.4 Therefore, it is important for farmers to maintain their health and ability to work over a long period.

Declining physical capacity caused by aging, including muscle weakness and loss of balance, increases the risk of falling.5 A fall is defined as “an unexpected event in which the participant comes to rest on the ground, floor, or lower level”.6 In the United States, occupational falls are categorized into “falls on same level” and “falls to lower levels”.7 It is estimated that 28–35% of older individuals aged 65 years and over experience a fall-related accident annually, sometimes resulting in fracture, disuse syndrome, or death.8 In developed countries, the incidence of occupational falls is increasing because of the aging workforce.9, 10 Older workers are reported to be at a higher risk of serious or fatal occupational injuries than younger workers.11 To prevent occupational falls, companies have taken various measures, such as education, training, and work environment improvements.12

A variety of physical capacity measurements have been developed to assess the risk of fall-related injuries in older individuals.13-15 In Japan, the Self-Check Risk Assessment of Falls and Other Accidents in the Workplace tool was developed by the Japan Industrial Safety and Health Association in 2010.16 This tool consists of five physical measurement items and can assess lower limb strength, agility, and balance among middle-aged and older workers. After the measurement, employers can arrange tasks for the workers to match their physical capacity, and the workers can maintain and improve their physical capacity. The use of this tool is currently increasing in the Japanese manufacturing industry because it can safely measure the physical capabilities of older workers without the use of specialized measurement instruments.17, 18

The development of a program for middle-aged and older farmers to assess their risk of occupational falls would be valuable in Thailand. However, the Self-Check Risk Assessment of Falls and Other Accidents in the Workplace tool was developed on the basis of a survey of workers in secondary and tertiary industries,16 and its validity for farmers has not been assessed. Because farmers work in outdoor environments, with heavy use of their feet and legs, they may differ from other study populations.17, 18 Therefore, the purpose of the current study was to evaluate the relationship between physical capacity and experiences of occupational falls among middle-aged and older Thai farmers using the Self-Check Risk Assessment of Falls and Other Accidents in the Workplace tool.

2 SUBJECTS AND METHODS 2.1 Study design and participants

We conducted a cross-sectional survey of farmers in Nan Province, Thailand from March 22–April 5, 2021. The survey consisted of a questionnaire and physical tests. Certified Thai safety officers with expertise in ergonomics measured the physical tests (SA, TL, KK, CT, and AM). A certified senior occupational physician (TI) from Japan with experience in this field provided oversight with translating the protocol procedure16 and providing training prior to the study. Farmer–producer groups and health centers in four districts (Mueang Nan, Trung Trang, Phu Pian, and Wiang Sa) of Nan Province collaborated with the study. The group leaders contacted the member farmers and invited them to health centers or related facilities in each district of the data collection sites. The inclusion criteria were used to select individuals who (a) were aged 40 years and over, and (b) had been engaged in the same agricultural work for at least 1 year. The exclusion criteria were used to screen out individuals who (a) were not engaged full-time in agriculture, (b) had limitations that could affect physical testing (e.g., lower limb dysfunction due to hemiplegia), and (c) returned incomplete questionnaires or physical tests.

2.2 Ethics

Participation was voluntary, and all participants provided written informed consent prior to the survey. Participants received 300 THB (approximately 9.6 USD) as financial compensation. This study was approved by the Ethical Review Committee for Human Research of Mahidol University (MUPH2021-023) and the Ethics Committee of the University of Occupational and Environmental Health, Japan (R2-067).

2.3 Outcome

The outcome of this study was experience of occupational falls on the same level or lower levels.7 We asked the following question in the questionnaire: “Have you been injured at work by a fall on the same level or lower levels in the past 12 months?” Responses were selected from “yes, one time,” “yes, two times or more,” and “no”.

2.4 Explanatory variables The Self-Check Risk Assessment of Falls and Other Accidents in the Workplace tool was used to assess participants’ physical capacity.16 This tool consists of five physical measurement items: (a) two-step test, (b) stepping test in a seated position, (c) functional reach test, (d) standing on one leg with eyes closed, and (e) standing on one leg with eyes open. We measured each of the four tests twice, except for the stepping test, and used the better of the two results.16 A brief description of each measurement method is given below. Two-step test The two-step test evaluates walking ability and muscle strength of the lower limbs. This test measures the maximum two strides without losing balance (cm) divided by self-reported body height (cm). Stepping test in a seated position The stepping test in a seated position evaluates the agility of the lower limbs. This test counts the number of steps performed by seated participants while they move their toes left and right between the floor outside and inside a 30 cm wide line in 20 s. Functional reach test The functional reach test evaluates dynamic balance. This test measures the distance reached with fingertips extended (cm) as far forward as possible while participants maintain their balance without moving their feet. Standing on one leg with eyes closed Standing on one leg with eyes closed evaluates static balance. This test was conducted while standing on one leg with eyes closed, and measures maximum holding time until both feet touch the ground (sec). The measurement was stopped at 120 s. Standing on one leg with eyes open

Standing on one leg with eyes open also evaluates static balance. This test was conducted using the same procedure described above but with eyes open. The measurement was stopped at 180 s.

2.5 Covariates

The covariates were selected on the basis of relevant studies of farmers or older community-dwelling adults.19-21 The questionnaire collected information about participants’ sex,19 age,19, 20 marital status,19 education,19, 20 agricultural product,20 working hours,20 height and weight,21 and underlying diseases with medication use.20 Information about agricultural products was obtained in descriptive form, and then categorized into rice, vegetables, flowers, fruit, and rubber trees. Body mass index was calculated by self-reported height and weight.

2.6 Statistical analysis

To dichotomize the outcome variable of experience of occupational falls, we combined responses of “yes, one time” and “yes, two times or more” into “yes”. Measured values were categorized into “good,” “normal,” and “bad,” based on the tertile distribution of the sample for each item of physical tests. Chi-square tests (univariate model) and multiple logistic regression (adjusted model) were conducted to assess the association between each physical capacity of the five physical tests and experience of occupational falls. The multivariate model was adjusted for sex, age, marital status, education, agricultural product, working hours, body mass index, and underlying diseases with medication use. Goodness of fit was assessed using the Hosmer–Lemeshow test. Receiver operating characteristic (ROC) curves were calculated to assess the relationship between continuous values of the five physical tests and experience of occupational falls. Area under the ROC curves (AUCs) were also calculated. We also performed the same analyses for participants aged 50 years and over to evaluate the results in older individuals separately. Statistical significance was defined as p value <0.05. Stata/SE 16.1 (StataCorp) was used for the statistical analysis.

3 RESULTS

Table 1 presents the characteristics of the study participants. A total of 442 participants volunteered to take part in the present study. Because 23 participants met the exclusion criteria, 419 were eligible for analysis. Participants’ average age was 58.0 years (range: 40–80 years); 224 participants (53.5%) were women and 271 (64.1%) had no educational background or had only graduated from elementary school. The most common agricultural product was rice (69.9%), followed by vegetables (29.8%) and flowers (13.6%). The average score of the stepping test was 22.0 steps per 20 s. The average score of the standing on one leg test was 10.5 s with eyes closed, and 82.1 s with eyes open. In addition, 25.5% of participants had experienced occupational falls in the past 12 months.

TABLE 1. General characteristics of the study participants. Total Occupational falls Yes No n = 419 n = 107 n = 312 Sex, n (%) Women 224 (53.5) 43 (40.2) 181 (58.0) Men 195 (46.5) 64 (59.8) 131 (42.0) Age (years), n (%) 40–49 69 (16.4) 24 (22.4) 45 (14.4) 50–59 175 (41.8) 44 (41.2) 131 (42.0) 60–69 140 (33.4) 32 (29.9) 108 (34.6) 70–80 35 (8.4) 7 (6.5) 28 (9.0) Marital status, n (%) Marriage 344 (82.5) 95 (88.8) 249 (80.3) Single/Divorced/Widowed 73 (17.5) 12 (11.2) 61 (19.7) Education, n (%) None, or elementary school 271 (64.7) 67 (62.6) 204 (65.4) Junior high school or above 148 (35.3) 40 (37.4) 108 (34.6) Agricultural product (multiple selections allowed), n (%) Rice 293 (69.9) 69 (64.5) 224 (71.8) Vegetables 125 (29.8) 38 (35.5) 87 (27.9) Flowers 57 (13.6) 10 (9.3) 47 (15.1) Fruit 52 (12.4) 22 (20.6) 30 (9.6) Rubber trees 44 (10.5) 9 (8.4) 35 (11.2) Working hours (hours/day), n (%) 6.0–7.9 146 (35.0) 30 (28.3) 116 (37.3) 8.0–8.9 218 (52.3) 60 (56.6) 158 (50.8) ≥9.0 53 (12.7) 16 (15.1) 37 (11.9) Body mass index (kg/m2), mean (SD) 23.7 (3.7) 24.4 (3.8) 23.5 (3.7) Underlying disease with medication use, n (%) 147 (35.5) 34 (31.8) 113 (36.8) Two-step test (widest two-step stride [cm]/body height [cm]), mean (SD) 1.27 (0.16) 1.28 (0.16) 1.26 (0.16) Stepping test in a seated position (steps/20 s), mean (SD) 22.0 (5.2) 22.3 (4.7) 21.9 (5.4) Functional reach test (cm), mean (SD) 25.9 (7.3) 27.4 (7.3) 25.4 (7.2) Standing on one leg with eyes closed (sec), mean (SD) 10.5 (16.1) 9.7 (13.7) 10.9 (16.8) Standing on one leg with eyes open (sec), mean (SD) 82.1 (69.1) 81.5 (68.1) 82.4 (69.5)

Table 2 shows the associations between physical capacity and occupational falls. In each of the five physical test components, there were no significant associations between normal or bad physical capacity and experience of occupational falls compared with good physical capacity for participants aged 40 years and over. The Hosmer–Lemeshow test confirmed the goodness of fit of the adjusted model: the lowest p value was 0.397 for the “standing on one leg with eyes open” and the highest p value was 0.792 for the “two-step test.” When the analysis was limited to participants aged 50 years and over (n = 350), no significant differences were observed (data not shown).

TABLE 2. Associations between physical capacity and occupational falls using the Self-Check Risk Assessment of Falls and Other Accidents in the Workplace tool Participants Occupational falls Univariate Adjusteda n n (%) OR 95% CI p value OR (95% CI) p value Two-step test (widest two-step stride [cm]/body height [cm]) Good (1.33–1.82) 139 43 (30.9) 1.00 — — 1.00 — — Normal (1.21–1.32) 140 32 (22.9) 0.66 0.39–1.13 0.128 0.67 0.38–1.21 0.184 Bad (0.66–1.20) 140 32 (22.9) 0.66 0.39–1.13 0.128 0.90 0.49–1.65 0.737 Stepping test in the seated position (steps/20 s) Good (24–43) 151 40 (26.5) 1.00 — — 1.00 — — Normal (20–23) 143 36 (25.2) 0.93 0.55–1.58 0.797 1.10 0.61–1.96 0.758 Bad (10–19) 125 31 (24.8) 0.92 0.53–1.58 0.749 1.14 0.62–2.13 0.672 Functional reach test (cm) Good (30–49) 140 42 (30.0) 1.00 — — 1.00 — — Normal (24–29) 123 29 (23.6) 0.72 0.42–1.25 0.242 0.78 0.43–1.44 0.426 Bad (7–23) 156 36 (23.1) 0.70 0.42–1.18 0.177 0.97 0.54–1.74 0.909 Standing on one leg with eyes closed (seconds) Good (8.7–120.0) 140 37 (26.4) 1.00 — — 1.00 — — Normal (3.4–8.6) 139 31 (22.3) 0.80 0.46–1.38 0.422 0.67 0.37–1.24 0.200 Bad (0.0–3.3) 140 39 (27.9) 1.08 0.64–1.82 0.788 1.26 0.69–2.33 0.452 Standing on one leg with eyes open (seconds) Good (114–180) 140 34 (24.3) 1.00 — — 1.00 — — Normal (30–113) 140 39 (27.9) 1.20 0.71–2.06 0.496 1.22 0.68–2.19 0.497 Bad (0–29) 139 34 (24.5) 1.01 0.58–1.74 0.973 1.19 0.63–2.26 0.597 Note Abbreviations: CI, confidence intervalOR, odds ratio. a Adjusted for sex, age, marital status, education, agricultural product, working hours, body mass index, and underlying diseases with medication use.

Figure 1 shows the ROC curves for each of the five physical test components to assess the experience of occupational falls. All AUCs were less than 0.60, with a maximum value of 0.57 for the functional reach test. A similar trend was observed when the analysis was limited to participants aged 50 years and over (data not shown).

image

Receiver operating characteristic (ROC) curves of five physical tests to assess experience of occupational falls in the past 12 months: (a) two-step test, (b) stepping test in a seated position, (c) functional reach test, (d) standing on one leg with eyes closed, and (e) standing on one leg with eyes open.

4 DISCUSSION

The present study evaluated the relationship between physical capacity and the experience of occupational falls among middle-aged and older farmers using the Self-Check Risk Assessment of Falls and Other Accidents in the Workplace. The results revealed that 25.5% of farmers had experienced occupational falls in the past 12 months. We found no significant associations between physical capacity at each physical test component of this tool and experience of occupational falls. The trend was not changed at different cut-off age points and categorical or continuous assessment. These findings suggest that this tool may not be useful for a program to assess occupational fall risk among older farmers.

There are several possible reasons for the lack of association between physical capacity and experience of occupational falls. The current findings are in agreement with two replication studies of the Self-Check Risk Assessment of Falls and Other Accidents in the Workplace.17, 18 These two replication studies were conducted among manufacturing workers under the age of 65, suggesting that the relatively younger age and work environment safety may have attenuated the results.17, 18 In contrast, the current study included workers up to 80 years old and working in an outdoor environment but still found no association. Therefore, we considered that the relationship between physical capacity and occupational falls among older workers may be complex. First, the “healthy worker effect” should be considered, because the prediction accuracy of physical capacity for future fall injuries may differ between older workers and community-dwelling older individuals.22-24 Second, employers may have arranged work with a low risk of occupational injuries for older farmers in the current study population.25 Third, occupational falls may be strongly influenced by factors other than physical function, such as work content and the work environment.26 Therefore, we believe that multiple intervention approaches may be necessary for preventing occupational falls among older farmers.

Importantly, the current study revealed the present status of occupational falls in middle-aged and older farmers. The results revealed that 25.5% of older farmers had experienced occupational falls, which is a relatively high proportion compared with similar studies in the manufacturing industry (6.2–14.2%).16, 17 The agricultural sector involves a high risk of injury,4 such as slipping because of rain or tripping in the dark. For example, because rice cultivation involves running water, work environments typically contain many slippery surfaces.27 Another study in Nepal reported that 35.1% of farmers experienced occupational injuries three times a year, particularly during the rainy season.28 In contrast, a study in United States reported that agriculture did not involve a higher frequency of occupational falls than other industries.9 As agriculture becomes more automated in developed countries, the number of occupational accidents tends to decrease.29 These findings suggest that the high frequency of occupational falls in the agricultural sector depends on a variety of factors, including the type of agricultural product, climate, and automation. Because farming is included in the informal sector in emerging countries, there are no national statistics regarding workers’ compensation. The current results suggest the importance of fall prevention in Asian agriculture.

Importantly, the current study also provided information about the basic physical capabilities of Thai farmers. We observed a gap between standard evaluation values and the measurements in the current study.16 For example, the average score on the stepping test was 22.0 steps in the current study, which is lower than the normal range of 29–43 steps in the original rating chart. Similarly, the average score for standing on one leg with eyes open was 10.5 s, which was also relatively low (normal range in the original rating chart: 17.1–55.0 s). This trend was consistent with a previous study using other physical tests among older Thai adults.30 In that study, Thaweewannakij et al. proposed that one reason for this result is that older Thai adults tend to be relatively small in stature, indicating little muscle mass compared with populations in other countries.30 These results suggest that agility and balance in older Thai farmers are relatively poor, potentially affecting their risk of health issues beyond occupational falls.31

The current study involved several limitations. Because of the cross-sectional design, it was difficult to derive causal relationships between physical capacity and experience of occupational falls. For example, participants who had experienced severe occupational falls may not have been able to join the study. Future studies should be conducted using a cohort design. However, a history of falls in the past year is known to act as a strong predictor of future fall risk; the evidence supports our findings.32 Second, selection bias may have affected the current study. For example, it is possible that participants who were concerned about their health were more likely to participate in this study, potentially influencing the results. To overcome this limitation, participants should be selected randomly. Third, the relationship between the physical examination and occupational falls may not have been clarified because of the relatively low and narrow range of physical capacity of the participants in this study. Therefore, the development of a physical examination with a wider range of values for the older population in Thailand may yield different results. Further research is warranted in this field.

In conclusion, the present study revealed the current status of occupational falls and physical capacity among middle-aged and older Thai farmers using the Self-Check Risk Assessment of Falls and Other Accidents in the Workplace tool. However, the results revealed no associations between physical capacity and experiences of occupational falls. Because the mechanisms underlying occupational falls are complex, multiple intervention approaches may be valuable for preventing accidents.

ACKNOWLEDGMENTS

This study was supported by JSPS KAKENHI Grant Number 20K23244. The funders had no role in the study design, the data collection and analysis, the decision to publish, or the preparation of the manuscript. The authors gratefully acknowledge Ms. Kotchakorn Santiwang for managing the research project and data collection.

DISCLOSURE

Approval of the research protocol: This study was approved by the Ethical Review Committee for Human Research of Mahidol University (MUPH2021-023) and the Ethics Committee of the University of Occupational and Environmental Health, Japan (R2-067). Informed Consent: All participants provided written informed consent prior to the survey. Registry and the Registration No. of the study/trial: N/A. Animal Studies: N/A. Conflict of Interest: N/A.

AUTHOR CONTRIBUTIONS

S.A. conceived the ideas. S.A, T.L, C.T., K.K., and A.M. collected the data. T.L. contributed data entry. T.I. contributed data analysis. T.I. drafted the initial manuscript with S.A. and K.H. All the authors read and approved the final manuscript.

No additional data are available.

REFERENCES

1Rigg J, Phongsiri M, Promphakping B, Salamanca A, Sripun M. Who will tend the farm? Interrogating the ageing Asian farmer. J Peasant Stud. 2020; 47: 306- 325. 2 Thailand Office of National Economic and Social Development Council. Thai Economic Performance in Q1 and Outlook for 2021. Published 2021. https://www.nesdc.go.th/nesdb_en/article_attach/article_file_20210528141639.pdf. Accessed July 1, 2021. 3 statista. Share of population older than 65 in Thailand from 2015 to 2020 with a forecast to 2100. Published 2021. https://www.statista.com/statistics/713667/thailand-forecast-aging-population/. Accessed July 1, 2021. 4Yogyorn D, Slatin C, Siriruttanapruk S, et al. Estimating of the costs of nonfatal occupational injuries and illnesses in agricultural works in Thailand. J Public Health Policy. 2021; 42: 71- 85. 5Rubenstein LZ. Falls in older people: epidemiology, risk factors and strategies for prevention. Age Ageing. 2006; 35(suppl_2): ii37- ii41. 6Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2012; 2012: CD007146. 7 United States Department of Labor Bureau of Labor Statistics. Occupational Injury and Illness Classification Manual Version 2.01. Published 2012.

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