Abstract
Background: Self-rated health is a comprehensive measure of health status that may influence occupational accidents, particularly those involving human factors. This study aimed to examine the relationship between self-rated health and occupational accidents across various industries and occupations. We also investigated the relationship stratified by the type of accidents.
Methods: We conducted a prospective cohort study using online self-administered questionnaires targeting workers in Japan. A baseline survey was conducted in March 2022, followed by a 1-year follow-up survey. Self-rated health at baseline was categorized into 4 groups: very good/good, slightly good, slightly poor, and poor/very poor. The dependent variable was the occurrence of occupational accidents and types of occupational accidents during the follow-up period. Logistic regression analyses adjusted for covariates were used to calculate odds ratios (ORs) and 95% CIs. We also performed trend tests and calculated P for trend.
Results: The analysis included 15 744 participants, among whom 1534 experienced workplace accidents. Compared with the very good/good group, the ORs for occupational accidents were 1.37 (95% CI, 1.21-1.56) in the slightly good group, 2.41 (95% CI, 2.07-2.80) in the slightly poor group, and 3.67 (95% CI, 2.94-4.59) in the poor/very poor group. Trend tests revealed significant associations between self-rated health and injuries from falls, injuries from cutting and rubbing, and heat stroke but not with injuries from crashes or tumbles and injuries from flying or falling objects.
Conclusions: Self-rated health was significantly associated with occupational accidents, particularly those involving substantial human factors.
Keywords: occupational accidents, mental health, physical health, prospective cohort study, self-rated health, workplace
Key points
Occupational accidents are perceived as being caused by a multifaceted interplay of various factors including human factors such as physical and mental health.
Self-rated health has been shown to correlate with objective health measures such as physical and mental health, so it may serve as a comprehensive measure of health status in relation to human factors, one of the contributors to occupational accidents.
Although previous studies have reported associations between self-rated health and occupational accidents for specific occupations, such as female firefighters, there are no studies that span diverse industries and occupations, examine differences by type of occupational accident, or examine the temporal relationship between self-rated health and occupational accidents.
In this study, we observed that lower self-rated health of workers was associated with an increased likelihood of experiencing an occupational accident, particularly those primarily caused by human factors. The results of this study suggest that self-rated health could serve as a convenient risk assessment indicator for occupational accidents, and that a proactive approach to monitoring the self-rated health of workers could reduce the occurrence of occupational accidents.
1. Introduction
The prevention of occupational accidents represents a significant concern not only for corporations but also for society at large. In Japan, it was projected that approximately 50 000 full-time equivalent workers would be lost in 2021. In practice, this constitutes an immense burden on society, due to not only the decline in labor productivity among the affected workforce but also the additional financial losses incurred through litigation, compensation for property damage, and other economic detriments, including business-related losses.1
Occupational accidents are perceived as being caused by a multifaceted interplay of various factors. These contributory elements can be classified into equipment factors, such as malfunctioning machinery and tools; operational factors, such as work procedures; human factors, encompassing physical and mental capacities; and administrative factors, such as adherence to safety protocols.2 In Japan, the human factors such as health status are becoming increasingly important due to the aging population, declining physical function, and higher incidence of diseases.
Self-rated health may serve as a comprehensive measure of health status in relation to human factors, one of the contributors to occupational accidents. Despite its subjective nature, self-rated health has been demonstrated to correlate with objective health metrics. Moreover, it has been identified as an independent predictor of both mortality and morbidity.3-5 Regarding physical health, self-rated health has been linked to diminished physical function and obesity.6,7 In cases of reduced physical function, it has been shown to predict future physical impairments, even when controlling for baseline impairment levels.8 As for obesity, a higher body mass index has been associated with lower self-rated health.9 In the realm of mental health, self-rated health has been associated with depression and sleep disorders, where depression is connected to the presence or absence of depressive symptoms as well as the number of depressive symptoms.10 Additionally, self-rated health has been found to influence both sleep duration and sleep quality in relation to sleep disorders.11
Several studies have explored the relationship between self-rated health and occupational accidents, but they have several limitations. One study examining work-related injuries among female firefighters in the United States found that firefighters who reported a strong subjective sense of health experienced fewer work-related injuries, such as dislocations, sprains, and contusions.12 In another study focused on falls among African Americans, which was not limited to specific occupations, it was found that better self-rated health was associated with a lower incidence of falls, irrespective of whether the individual had previously experienced a fall. The researchers of this study proposed that the mechanism underlying this relationship was that self-rated health is linked to physical functions, such as mobility, and mental functions, such as self-efficacy, and that through these functions, the incidence of falls decreases as self-rated health improves.13 However, as these studies were cross-sectional, the temporal relationship between self-rated health and occupational accidents remains unclear, and thus a causal link has not been firmly established. Moreover, these studies were specific to gender and occupation, which limits their broader applicability.
The relationship between human factors and occupational accidents may vary according to the specific types of accidents. Injuries resulting from collisions or falls, as well as those caused by being caught or pinched, are predominantly attributed to equipment factors among the 4 major contributors to occupational accidents.14 Conversely, back pain stemming from heavy lifting or improper posture is largely associated with operational factors.15 Hence, the interplay between various factors differs based on the nature of the accident. Considering that self-rated health reflects the worker’s overall health status, which is a critical human factor, the correlation between self-rated health and occupational accidents may be more pronounced for accident types where human factors exert a greater influence. To our knowledge, no studies have examined the relationship between self-rated health and occupational accidents while differentiating between accident types.
The objective of this study was to explore the relationship between self-rated health and occupational accidents across diverse industries and occupations by sampling the general working population. Additionally, it aimed to elucidate this relationship stratified by the type of occupational accident.
2. Materials and methods
2.1. Study design and participants
This prospective cohort study was conducted using data in the Work, Well-being and Safety for Occupational Health Practice and Management Study (W2S-Ohpm Study). This study was collected using a self-administered online questionnaire survey and delivered by an internet survey company. Details of the study protocol have been reported elsewhere.16
The baseline survey was conducted in March 2022 among workers in Japan aged 20 years or older. We used a balanced sampling method to ensure that the sample of workers in Japan matched the general population in terms of sex, age, and region of residence. In the baseline survey, 27 693 workers were included. The follow-up survey was conducted in March 2023, 1 year after the baseline survey. In total, 16 629 participants responded to the follow-up survey (60.0% follow-up rate), and we selected the subjects as follows to fit the aim of this study. We excluded 885 participants who had angina, heart attack, stroke, or cancer and were being treated or had been treated but had discontinued treatment. This is because they are already considered to have received some work-related consideration from the company. Finally, 15 744 participants were included in the analysis.
This study was approved by the Ethics Committee of the University of Occupational and Environmental Health, Japan (approval no. R3-076). Informed consent was obtained from all participants using an online form provided by an internet survey company.
2.2. Assessment of self-rated health
To assess self-rated health, we asked, “How do you rate your current health status?” Answers were selected from the following 6 options: very good, good, slightly good, slightly poor, poor, or very poor. This method of questioning is used in the Longitudinal Survey of Middle-aged and Elderly Persons in Japan.17 We classified these into 4 groups: very good/good, slightly good, slightly poor, poor/very poor, respectively. Self-rated health in the baseline survey was used as the independent variable.
2.3. Assessment of occupational accidents in the workplace
To assess experience of occupational accidents in the workplace, we asked, “Have you visited a medical facility for a work-related injury or illness in the past year?” One answer could be selected from among the following 5 options: never; once; twice; 3 times; or 4 times or more. We then classified workers as having had no occupational accident if they had had no occupational accident at all, and as having had an occupational accident if they had had at least 1 occupational accident.
To assess types of occupational accidents, we asked workers which type of injury or illness they had experienced. If workers had experienced 4 or more injuries or illnesses, they answered 3 of the more serious ones. One answer could be selected from the following 14 options respectively: (1) injuries from crashes or tumbles, (2) injuries from falls, (3) injuries caused by flying or falling objects, (4) injuries from collapses, (5) injuries from being hit by a collision, (6) injuries from being caught or pinched, (7) injuries caused by cutting or rubbing, (8) burns or electric shock, (9) back pain from heavy lifting or poor posture, (10) dermatitis from contact with hazardous substances, (11) illness due to exposure to hazardous substances, (12) heat stroke, (13) traffic accidents, or (14) others. The occurrences of occupational accidents and occupational accidents by types in the follow-up survey were used as the dependent variables.
2.4. Covariates
Covariates comprised age, sex, industry category, working years in the same company, and sleeping hours. Age was expressed as a continuous variable. Sex was expressed as a categorical variable. Participants chose 1 of 20 options for the industry category, according to Japan’s standard industry classification: agriculture and forestry; fisheries; mining and quarrying of stone; construction; manufacturing; electricity, gas, heat supply, and water; information and communications; transport and postal services; wholesale and retail trade; finance and insurance; real estate and goods, retail and leasing; scientific research, professional and technical services; accommodation, eating and drinking services; living-related and personal services and amusement services; education and learning support; medical, health care and welfare; compound services; services (not elsewhere classified); public services (not elsewhere classified); and others.18 Working years in the same company were expressed as a continuous variable. Participants chose 1 of 7 options for the average hours of sleep per day in a month: <5 hours, ≥5 and <6 hours, ≥6 and <7 hours, ≥7 and <8 hours, ≥8 and <9 hours, ≥9 and <10 hours, and ≥10 hours.
2.5. Statistical analysis
Unpaired t test and chi-squared test were used to compare the characteristics of respondents and nonrespondents to the follow-up survey. Logistic regression analysis was used to examine associations between self-rated health and occupational accidents. We calculated the odds ratios (ORs) and 95% CIs for the occurrence of occupational accidents adjusting for covariates. First, we calculated the OR adjusted for age and sex. Second, we calculated the OR additionally adjusted for industry category, working years in the same company, and sleeping hours. We also performed a trend test by considering the independent variable, self-rated health, as a continuous variable rather than a categorical variable, and calculated P for trend.
In addition, we examined associations between self-rated health and occupational accidents by types. The major occupational accidents by types—injuries from crashes or tumbles; injuries from falls; injuries caused by flying or falling objects; injuries caused by cutting or rubbing; and heat stroke—were included in the analysis. Back pain from heavy lifting or poor posture and traffic accidents were also major occupational accidents, but they were excluded from the analysis because back pain is likely to include treatment for back pain outside an occupational accident, and traffic accidents may include commuting accidents. We calculated the OR adjusted for age, sex, industry category, working years in the same company, and sleeping hours. We also performed trend tests for each type of occupational accident.
In all the analyses, the very good/good group was the reference category. We considered P values <.05 to indicate statistical significance. All analyses were conducted using Stata statistical software (Release 18; StataCorp LLC, College Station, TX, USA).
3. Results
Table 1 shows the characteristics of participants according to their self-rated health. Of the total 15 744 participants, 1534 had experienced occupational accidents in the workplace. The mean (SD) age of participants was 47.3 (13.0) years. As for the gender ratio, the proportion of women increased with better self-rated health. Table S1 shows the characteristics of respondents and nonrespondents to the follow-up survey. The mean age of respondents was greater than that of nonrespondents, and the proportion of male respondents was higher than that of male nonrespondents.
Table 1.
Basic characteristics of participants.
| Self-rated health | ||||
|---|---|---|---|---|
| Very good/good | Slightly good | Slightly poor | Poor/very poor | |
| Total | 6671 | 6217 | 2288 | 568 |
| Age, mean (SD) | 46.8 (13.5) | 47.9 (12.9) | 47.3 (12.1) | 45.6 (12.2) |
| Sex (men), n (%) | 3777 (56.6) | 3544 (57.0) | 1323 (57.8) | 330 (58.1) |
| Industry category, n (%) | ||||
| Agriculture and forestry | 62 (0.9) | 61 (1.0) | 21 (0.9) | 7.0 (1.2) |
| Fisheries | 4.0 (0.1) | 3.0 (0.0) | 4.0 (0.2) | 0.0 (0.0) |
| Mining and quarrying of stone | 6.0 (0.1) | 3.0 (0.0) | 1.0 (0.0) | 1.0 (0.2) |
| Construction | 329 (4.9) | 319 (5.1) | 124 (5.4) | 19 (3.3) |
| Manufacturing | 1083 (16.2) | 1020 (16.4) | 402 (17.6) | 97 (17.1) |
| Electricity, gas, heat supply, and water | 99 (1.5) | 62 (1.0) | 40 (1.7) | 9.0 (1.6) |
| Information and communications | 322 (4.8) | 327 (5.3) | 103 (4.5) | 28 (4.9) |
| Transport and postal services | 290 (4.3) | 319 (5.1) | 100 (4.4) | 24 (4.2) |
| Wholesale and retail trade | 678 (10.2) | 650 (10.5) | 237 (10.4) | 59 (10.4) |
| Finance and insurance | 303 (4.5) | 255 (4.1) | 91 (4.0) | 25 (4.4) |
| Real estate and goods, retail and leasing | 173 (2.6) | 169 (2.7) | 69 (3.0) | 17 (3.0) |
| Scientific research, professional and technical services | 194 (2.9) | 192 (3.1) | 65 (2.8) | 10 (1.8) |
| Accommodation, eating and drinking services | 217 (3.3) | 194 (3.1) | 62 (2.7) | 16 (2.8) |
| Living-related and personal services and amusement services | 170 (2.5) | 167 (2.7) | 59 (2.6) | 17 (3.0) |
| Education and learning support | 456 (6.8) | 378 (6.1) | 150 (6.6) | 24 (4.29) |
| Medical, health care, and welfare | 892 (13.4) | 825 (13.3) | 277 (12.1) | 66 (11.6) |
| Compound services | 61 (0.9) | 54 (0.9) | 22 (1.0) | 8 (1.4) |
| Services (not elsewhere classified) | 673 (10.1) | 651 (10.5) | 232 (10.1) | 68 (12.0) |
| Public services (not elsewhere classified) | 434 (6.5) | 358 (5.8) | 130 (5.7) | 37 (6.5) |
| Others | 225 (3.4) | 210 (3.4) | 99 (4.3) | 36 (6.3) |
| Working years in the same company, mean (SD) | 11.9 (10.9) | 12.1 (11.1) | 12.1 (11.1) | 11.5 (11.0) |
| Sleeping hours, n (%) | ||||
| <5 h | 370 (5.5) | 504 (8.1) | 361 (15.8) | 135 (23.8) |
| ≥5 and <6 h | 1909 (28.6) | 2206 (35.5) | 824836.0) | 179 (31.5) |
| ≥6 and <7 h | 2643 (39.6) | 2264 (36.4) | 695 (30.49) | 139 (24.5) |
| ≥7 and <8 h | 1444 (21.6) | 1029 (16.6) | 324 (14.2) | 81 (14.3) |
| ≥8 and <9 h | 266 (4.0) | 180 (2.9) | 61 (2.7) | 17 (3.0) |
| ≥9 and <10 h | 20 (0.3) | 18 (0.3) | 16 (0.7) | 10 (1.8) |
| ≥10 h | 19 (0.3) | 16 (0.3) | 7.0 (0.3) | 7.0 (1.2) |
| Occupational accidents (yes), n (%) | 476 (7.1) | 578 (9.3) | 353 (15.4) | 127 (22.4) |
Table 2 shows the association between self-rated health and occupational accidents. In the multivariate adjusted model, compared with the very good/good group, the ORs (95% CIs) of the occurrence of occupational accidents were significantly higher in the slightly good group at 1.37 (1.21-1.56), slightly poor group at 2.41 (2.07-2.80), and poor/very poor group at 3.67 (2.94-4.59). Thus, the ORs tended to be higher for the group with a worse self-rated health (P for trend <.001).
Table 2.
Relationship between self-rated health and occupational accidents.
| Self-rated health | Age, sex-adjusted | Multivariate adjusted a | |||||||
|---|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | P value | OR | 95% CI | P value | P for trend | |||
| Very good/good | Reference | Reference | <.001 | ||||||
| Slightly good | 1.38 | 1.22 | 1.57 | <.001 | 1.37 | 1.21 | 1.56 | <.001 | |
| Slightly poor | 2.45 | 2.11 | 2.84 | <.001 | 2.41 | 2.07 | 2.80 | <.001 | |
| Poor/very poor | 3.72 | 2.98 | 4.63 | <.001 | 3.67 | 2.94 | 4.59 | <.001 | |
Abbreviation: OR, odds ratio.
Multivariate adjusted for age, sex, industry category, working years in the same company, and sleeping hours.
Table 3 shows the number of occupational accidents by types. The total number of occupational accidents was 1861: injuries from falls were 344 (18.5%), injuries caused by cutting or rubbing were 158 (8.49%), injuries from crashes or tumbles were 80 (4.30%), injuries caused by flying or falling objects were 67 (3.60%), and heat stroke was 61 (3.28%).
Table 3.
Types of occupational accidents.
| Type of occupational accident | Occupational accidents | |
|---|---|---|
| n | % | |
| Injuries from crashes or tumbles | 80 | 0.5 |
| Injuries from falls | 344 | 2.2 |
| Injuries caused by flying or falling objects | 67 | 0.4 |
| Injuries from collapses | 38 | 0.2 |
| Injuries from being hit by a collision | 56 | 0.4 |
| Injuries from being caught or pinched | 54 | 0.3 |
| Injuries caused by cutting or rubbing | 158 | 1.0 |
| Burns or electric shock | 34 | 0.2 |
| Back pain from heavy lifting or poor posture | 189 | 1.2 |
| Dermatitis from contact with hazardous substances | 14 | 0.1 |
| Illness due to exposure to hazardous substances | 4 | 0.0 |
| Heat stroke | 61 | 0.4 |
| Traffic accidents | 62 | 0.4 |
| Others | 700 | 4.4 |
Table 4 shows the association between self-rated health and occupational accidents by types. In the multivariate model, compared with the very good/good group, the OR (95% CI) of the occurrence of injuries from falls was significantly higher in the slightly poor group at 1.80 (1.34-2.42), and in the poor/very poor group at 2.07 (1.30-3.30). The OR (95% CI) of injuries caused by cutting or rubbing also was significantly higher in the slightly poor group at 1.58 (1.03-2.45) and in the poor/very poor group at 2.90 (1.64-5.12); and the OR (95% CI) of heat stroke was significantly higher in the poor/very poor group at 4.49 (1.95-10.3). Trend tests also showed that injuries from falls, injuries caused by cutting and rubbing, and heat stroke were associated with self-rated health, whereas injuries from crashes or tumbles and injuries caused by flying or falling objects were not significantly associated with self-rated health.
Table 4.
Relationship between self-rated health and occupational accidents by causes and types.
| Self-rated health | Type of injuries/illness | Multivariate adjusted a | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | P value | P for trend | |||
| Injuries from crashes or tumbles | ||||||
| Very good/good | reference | .679 | ||||
| Slightly good | 0.94 | 0.57 | 1.55 | .811 | ||
| Slightly poor | 1.24 | 0.66 | 2.33 | .504 | ||
| Poor/very poor | 1.03 | 0.31 | 3.37 | .964 | ||
| Injuries from falls | ||||||
| Very good/good | reference | <.001 | ||||
| Slightly good | 1.16 | 0.90 | 1.50 | .249 | ||
| Slightly poor | 1.80 | 1.34 | 2.42 | <.001 | ||
| Poor/very poor | 2.07 | 1.30 | 3.30 | .002 | ||
| Injuries caused by flying or falling objects | ||||||
| Very good/good | reference | .557 | ||||
| Slightly good | 0.89 | 0.51 | 1.56 | .682 | ||
| Slightly poor | 1.51 | 0.79 | 2.90 | .213 | ||
| Poor/very poor | 0.79 | 0.19 | 3.38 | .756 | ||
| Injuries caused by cutting or rubbing | ||||||
| Very good/good | reference | .001 | ||||
| Slightly good | 0.94 | 0.64 | 1.38 | .75 | ||
| Slightly poor | 1.58 | 1.03 | 2.45 | .038 | ||
| Poor/very poor | 2.89 | 1.63 | 5.12 | <.001 | ||
| Heat stroke | ||||||
| Very good/good | reference | .003 | ||||
| Slightly good | 1.17 | 0.63 | 2.15 | .617 | ||
| Slightly poor | 1.59 | 0.75 | 3.34 | .223 | ||
| Poor/very poor | 4.48 | 1.95 | 10.30 | <.001 | ||
Multivariate adjusted for age, sex, industry category, working years in the same company, and sleeping hours.
4. Discussion
The study prospectively investigated the association between workers’ self-rated health and the occurrence of occupational accidents. A lower self-rated health status was associated with an increased likelihood of experiencing an occupational accident. This finding aligns with a previous study of female firefighters, which reported that those with higher self-rated health were less likely to experience occupational accidents.12 The present study suggests that a similar relationship may exist within the broader workforce. When trend analyses were conducted by accident type, injuries resulting from falls, injuries caused by cutting or friction, and heat stroke exhibited a significant association with self-rated health, whereas injuries caused by collisions, tumbles, or by flying or falling objects showed no significant correlation with self-rated health. The finding that falls were associated with self-rated health is consistent with earlier research.13 However, certain types of occupational accidents, such as those caused by flying or falling objects, did not show an association with self-rated health. In other words, the results imply that the impact of self-rated health on the incidence of occupational accidents may vary depending on the primary factors contributing to different types of occupational accidents.
The relationship between self-rated health and occupational accidents may be mediated by both the physical and mental health of workers, which are human factors. In terms of physical health, previous research suggests that self-rated health impacts physical functioning, with a decline potentially leading to dysfunction and triggering work-related musculoskeletal disorders.6,8,19 Additionally, self-rated health has been identified as an independent contributor to morbidity, particularly in relation to cardiovascular disease, diabetes, and chronic kidney disease.20,21 Self-rated health has also been linked to obesity, with an increased body mass index being inversely correlated with self-rated health. This relationship is evident, as obesity is a known risk factor for cardiovascular disease, diabetes, and chronic kidney disease. However, this association persists even when controlling for the presence of chronic conditions such as hypertension and diabetes.7,9 These physical health issues are believed to heighten the likelihood of occupational accidents by inducing symptoms like headaches, dizziness, hypoglycemia, anemia, dehydration, paralysis, and fatigue, which may lead to accidents in the workplace. On the other hand, self-rated health has also been strongly linked to mental health. Studies have demonstrated an association between self-rated health and depression, indicating that poorer self-rated health correlates with the severity and number of depressive symptoms.10 Regarding sleep disturbances, self-rated health has been shown to be related to both sleep duration and quality, with the perception of poor health potentially leading to anxiety and worry, which in turn disrupt sleep patterns. Moreover, self-rated health has been found to predict sleep quality over a 3-year period.11,22 In terms of fatigue, there is evidence that self-rated health is associated with both mental and physical exhaustion. A decline in self-rated health has been shown to trigger increases in inflammatory markers such as interleukin 6 and C-reactive protein, as well as heightened physiological stress responses, ultimately leading to greater fatigue due to these biological processes.23-25 Furthermore, prior research on occupational accidents suggests that treatment for depression, sleep deprivation, and chronic fatigue is significantly associated with the occurrence of such incidents.26
This hypothesis that the physical and mental health of workers mediates the relationship between self-rated health and occupational accidents can be seen from the results of analysis by types of occupational accidents. Injuries resulting from falls, cutting, and friction are occupational accidents associated with workers’ movements. In addition to work-related factors such as uneven flooring and confined workspaces, human factors, including declines in physical function and unintentional behaviors, are considered significant contributors. The main causes of heat stroke also include work-related factors, such as hot environments, but human factors like illness, fatigue, and sleep deprivation are similarly deemed critical. Conversely, injuries from crashes, tumbles, and those caused by flying or falling objects are thought to be more heavily influenced by equipment factors, such as deficiencies in machinery design, inadequate inspection and maintenance, and work-related factors like poor lighting, as well as by management factors, including compliance with safety regulations, rather than by human factors. These distinctions may explain the variability in the association between self-rated health and different types of occupational accidents. Collectively, these findings indicate that a deterioration in self-rated health, impacting both physical and mental well-being, may contribute to a rise in occupational accidents, particularly those primarily driven by human factors.
In this study, 9.7% of participants experienced at least 1 occupational accident within a year. Occupational accidents are often underreported due to organizational factors such as lack of organizational responsiveness and organizational safety climate, as well as individual factors such as fear of reprisals or loss of benefits.27 The high occurrence of occupational accidents observed in this study is consistent with a previous study of occupational accidents across diverse industries and occupations in Japan.28 However, the 9.7% reported here is nearly double the 5.0% identified in earlier studies. This discrepancy likely arises from differences in the definition of occupational accidents. Whereas the previous study examined only injuries as occupational accidents, this study included diseases based on the definition of the Ministry of Health, Labour and Welfare.29 Additionally, the prevalence of COVID-19 infections may have significantly contributed to the higher occurrence of occupational accidents. In Japan, COVID-19 infection in the workplace is recognized as an occupational accident.30 During the study period in 2022, a substantial number of COVID-19 cases were recorded, leading to an approximate 2-fold increase in reported occupational accidents compared with 2021.31,32 Based on the above, we believe that the occurrence of occupational accidents has increased compared with previous studies in Japan.
The findings of this study underscore the necessity of comprehensively understanding workers’ health status within the framework of human factors for the effective management of occupational accidents. Furthermore, previous research has demonstrated that self-rated health possesses the capability to holistically evaluate health conditions pertinent to human factors, which are significant contributors to occupational accidents. Notably, self-rated health can serve as a straightforward risk assessment tool for occupational hazards due to its simplicity and ease of response. It may be feasible to mitigate the occurrence of occupational accidents by evaluating the self-rated health of workers and refraining from assigning them to hazardous tasks if they report poor health. Regarding heat stroke, one of the occupational accidents, previous studies have shown that even in workers without underlying diseases and who are usually healthy, health conditions such as insufficient sleep, the presence of a hangover, skipping breakfast, diarrhea, or fever are associated with the onset of heat stroke.33 Based on these risk factors, the domestic heat stroke guide for workers recommends that, prior to starting work, employers should check not only whether workers had adequate sleep the previous night, the presence of a hangover, and breakfast intake, but also their overall health condition (good/poor), which can be considered substitutable by self-rated health.34 Focusing on the results of this study, it is suggested that, compared with the group reporting very good/good health, the risk of occupational accidents may also increase in those reporting slightly good health. This suggests that the 2-step assessment of health conditions (good/poor) recommended in the heat stroke guide may be insufficient to adequately evaluate the risk of heat stroke. Rather, assessing workers’ health conditions using multiple categories, such as 4 to 6 levels, may enable a more precise risk evaluation. Furthermore, the results of this study indicate that monitoring workers’ health status is critically important not only for the prevention of heat stroke but also for reducing the incidence of other occupational accidents.
The strength of this study lies in its longitudinal design, which, unlike prior research, demonstrates a robust association between workers’ self-rated health and occupational accidents. This indicates that self-rated health may correlate with both the physical and mental well-being of workers, suggesting a potential risk for injury. Furthermore, when analyzing the various types of occupational accidents, those characterized by a significant human factor component exhibited a relationship with self-rated health, whereas accidents not predominantly influenced by human factors did not, implying that the nature of the association may vary according to the specific determinants of the occupational incidents.
However, this study has several limitations. First, it did not assess the physical functioning and mental health of the workers. In this study, we examined the relationship between self-rated health and occupational accidents, which may be mediated by both the physical and mental health of workers. However, since we did not objectively evaluate workers’ physical function or mental health, we cannot rule out the possibility of an indirect relationship mediated by other factors. Future studies should evaluate both physical and mental health of workers together to verify the relationship more clearly between self-rated health and occupational accidents. Second, the range of occupational accident types examined was limited, and the severity of injuries was not evaluated. Future research is warranted to further validate these findings by exploring the relationship between self-rated health and a broader spectrum of occupational accidents, along with their severity. Third, the response rate to the questionnaire was relatively low (60.0%). Table S1 shows that, compared with nonrespondents, respondents had a higher average age and a higher percentage of men. Previous studies of self-rated health suggest that older age is associated with lower self-rated health.35 Additionally, a survey on the occurrence of occupational accidents in Japan indicates that men experience occupational accidents at a higher rate than women, and that the elderly experience occupational accidents at a rate 2 to 4 times higher than the young.36 Therefore, it is possible that participants with lower self-rated health and a higher likelihood of occupational accidents may have been selected, and that the association between self-rated health and occupational accidents may have been overestimated.
5. Conclusion
This study demonstrated that the self-rated health of workers was associated with the incidence of occupational accidents, particularly those characterized by a substantial human factor component. It further posits that self-rated health might serve as a convenient risk assessment indicator for occupational accidents, and that a proactive approach to monitoring self-rated health of workers could mitigate the occurrence of occupational accidents.
Supplementary Material
Acknowledgments
We presented the same topic at ICOH2024, Morocco. The abstract from this conference presentation has been published in Occupational Medicine (https://academic.oup.com/occmed/article/74/Supplement_1/0/7707437).
The current members of the W2S-Ohpm Study, in alphabetical order, are as follows: Aki Tomizawa, Akiko Matsuyama, Asumi Yama, Ayaka Yamamoto, Ayana Ogasawara, Chihiro Kinugawa, Haruna Hirosato, Hideki Fujiwara, Junta Naka, Kakeru Tsutsumi, Kazufumi Matsuyama, Kenta Moriya, Kiminori Odagami, Koji Mori, Kosuke Sakai, Madoka Miyashita, Mako Masuda, Masahiro Tanaka, Masako Nagata, Megumi Kawashima, Miho Omori, Mika Kawasumi, Misako Uetsuki, Mizuho Inagaki, Naoto Ito, Natsumi Shinzato, Nuri Purwito Adi, Osamu Une, Rina Minohara, Shigeki Morioka, Shunsuke Inoue, Suo Taira, Takahiro Jinnouchi, Takahiro Mori, Tatsuhiko Hara, Tomohisa Nagata (present chairperson of the study group), Tomoko Sawajima, Yuki Hino, Yuto Fukui. All members are affiliated with the University of Occupational and Environmental Health, Japan.
The study was approved by the Ethics Committee of the University of Occupational and Environmental Health, Japan (R3-076). Informed consent was obtained from all participants via the survey form on the website.
Contributor Information
Yuto Fukui, Department of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu, Japan.
Tomohisa Nagata, Department of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu, Japan.
Kiminori Odagami, Department of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu, Japan.
Koji Mori, Department of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu, Japan.
Author contributions
T.N., K.O., and K.M. conceived the study idea; T.N., K.O., and K.M. collected the data; Y.F. designed the analysis, analyzed the data, and wrote the draft of the manuscript. All authors have advised on the data interpretation and have reviewed, edited, and approved the final manuscript.
Supplementary material
Supplementary material is available at Journal of Occupational Health online.
Funding
This study was supported and partly funded by a research grant from the University of Occupational and Environmental Health, Japan (no grant number); Japanese Ministry of Health, Labour and Welfare ( 210401-01, 23EA1003, 23CA2033, and 23JA1005); JSPS KAKENHI ( JP22K10543 and JP19K19471); Japan Agency for Medical Research and Development ( 24rea522102s0203); Collabo-Health study group (no grant number), Hitachi Systems, Ltd (no grant number), and DAIDO LIFE INSURANCE COMPANY (no grant number). The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of the article, or the decision to submit it for publication.
Conflicts of interest
T.N. reports personal fees from BackTech Inc, EWEL Inc, and Sompo Health Support Inc, outside the submitted work. K.M. reports personal fees from BackTech Inc and Sompo Health Support Inc, outside the submitted work. All authors including T.N. and K.M. declare no conflicts of interest associated with this manuscript.
Data availability
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
References
- 1.Ministry of Health, Labour and Welfare of Japan . Issues for the 14th Industrial Injury Prevention Plan. Article in Japanese. https://www.mhlw.go.jp/content/11201250/000994095.pdf [cited 2025 October 5].
- 2.Ministry of Land, Infrastructure, Transport and Tourism, Japan Transport Safety Board . How accident investigations help prevent recurrence. Article in Japanese. https://jtsb.mlit.go.jp/fukuchiyama/kensyou/fu04-finalreport-part2-2.pdf [cited 2025 October 5].
- 3.Inoue Y, Nakata A, Kurioka S, Nagata T, Mori K. Association of self-rated health with inflammatory markers among nursing home employees. Article in Japanese. Sangyo Eiseigaku Zasshi. 2021;63(4):117-128. 10.1539/sangyoeisei.2020-020-B [DOI] [PubMed] [Google Scholar]
- 4.Okado J, Bin A, Tomoyama G, Hoshi T. A follow-up study on the relationship between subjective health and mortality among the elderly people. Article in Japanese. Jpn J Health Educ Promot. 2003;11:31-38. 10.11260/kenkokyoiku1993.11.31 [DOI] [Google Scholar]
- 5.Shankar A, Wang JJ, Rochtchina E, Mitchell P. Association between self-rated health and incident severe hypertension among men: a population-based cohort study. Singapore Med J. 2008;49(11):860-867 [PubMed] [Google Scholar]
- 6.Hillen T, Davies S, Rudd AG, Kieselbach T, Wolfe CD. Self ratings of health predict functional outcome and recurrence free survival after stroke. J Epidemiol Community Health. 2003;57(12):960-966. 10.1136/jech.57.12.960 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Okosun IS, Choi S, Matamoros T, Dever GE. Obesity is associated with reduced self-rated general health status: evidence from a representative sample of white, black, and Hispanic Americans. Prev Med. 2001;32(5):429-436. 10.1006/pmed.2001.0840 [DOI] [PubMed] [Google Scholar]
- 8.Reuben DB, Rubenstein LV, Hirsch SH, Hays RD. Value of functional status as a predictor of mortality: results of a prospective study. Am J Med. 1992;93(6):663-669. 10.1016/0002-9343(92)90200-U [DOI] [PubMed] [Google Scholar]
- 9.Hastings JF. Comparing the self-rated health effects of obesity on the health of African Americans and Caribbean blacks. Soc Work Public Health. 2019;34(5):383-394. 10.1080/19371918.2019.1613277 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Mulsant BH, Ganguli M, Seaberg EC. The relationship between self-rated health and depressive symptoms in an epidemiological sample of community-dwelling older adults. J Am Geriatr Soc. 1997;45(8):954-958. 10.1111/j.1532-5415.1997.tb02966.x [DOI] [PubMed] [Google Scholar]
- 11.Nordin M, Sundström A, Hakelind C, Nordin S. Self-rated health and its bidirectional relationship with burnout, sleep quality and somatic symptoms in a general adult population. BMC Public Health. 2024;24(1):2094. 10.1186/s12889-024-19325-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Hollerbach BS, Kaipust CM, Poston WSC, Haddock CK, Heinrich KM, Jahnke SA. Injury correlates among a national sample of women in the US fire service. J Occup Environ Med. 2020;62(8):634-640. 10.1097/JOM.0000000000001918 [DOI] [PubMed] [Google Scholar]
- 13.Tiernan C, Lysack C, Neufeld S, Goldberg A, Lichtenberg PA. Falls efficacy and self-rated health in older African American adults. Arch Gerontol Geriatr. 2014;58(1):88-94. 10.1016/j.archger.2013.08.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Watanabe J. Consideration on occupational accidents caused by aging machinery—“drawn into a machine” occupational accidents by inadequate protection measures. Article in Japanese. J Japan Soc Saf Eng. 2021;60:255-262. 10.18943/safety.60.4_255 [DOI] [Google Scholar]
- 15.Kurihara A. Current status and prospects of occupational low back pain. Article in Japanese. J Jpn Soc Lumbar Spine Disord. 2002;8:10-15. 10.3753/yotsu.8.10 [DOI] [Google Scholar]
- 16.Nagata T, Odagami K, Nagata M, Adi NP, Mori K. Protocol of a study to benchmark occupational health and safety in Japan: W2S-Ohpm study. Front Public Health. 2023;11:1191882. 10.3389/fpubh.2023.1191882 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Ministry of Health, Labor and Welfare . The longitudinal survey of middle-aged and elderly persons. Article in Japanese. https://www.mhlw.go.jp/toukei/list/29-6.html [cited 2025 October 5].
- 18.Ministry of Internal Affairs and Communications . Japan’s standard industry classification. Article in Japanese. https://www.soumu.go.jp/main_content/000890407.pdf [cited 2025 October 5].
- 19.Idler EL, Russell LB, Davis D. Davis D. Survival, functional limitations, and self-rated health in the NHANES I epidemiologic follow-up study, 1992. First National Health and Nutrition Examination Survey. Am J Epidemiol. 2000;152(9):874-883. 10.1093/aje/152.9.874 [DOI] [PubMed] [Google Scholar]
- 20.Galenkamp H, Deeg DJ, Huisman M, Hervonen A, Braam AW, Jylhä M. Is self-rated health still sensitive for changes in disease and functioning among nonagenarians? J Gerontol B Psychol Sci Soc Sci. 2013;68(5):848-858. 10.1093/geronb/gbt066 [DOI] [PubMed] [Google Scholar]
- 21.Ko HL, Min HK, Lee SW. Self-rated health and the risk of incident chronic kidney disease: a community-based Korean study. J Nephrol. 2023;36(3):745-753. 10.1007/s40620-022-01518-3 [DOI] [PubMed] [Google Scholar]
- 22.Shankar A, Charumathi S, Kalidindi S. Sleep duration and self-rated health: the national health interview survey 2008. Sleep. 2011;34(9):1173-1177. 10.5665/SLEEP.1232 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Hirsch S, Stephens AR, Crane PB. Fatigue, depression, cardiovascular risk, and self-rated health: comparing a community sample of adults to those with a history of myocardial infarction. Clin Nurs Res. 2022;31(2):174-182. 10.1177/10547738211055570 [DOI] [PubMed] [Google Scholar]
- 24.Gelauff JM, Kingma EM, Kalkman JS, et al. Fatigue, not self-rated motor symptom severity, affects quality of life in functional motor disorders. J Neurol. 2018;265(8):1803-1809. 10.1007/s00415-018-8915-7 [DOI] [PubMed] [Google Scholar]
- 25.Engberg I, Segerstedt J, Waller G, Wennberg P, Eliasson M. Fatigue in the general population—associations to age, sex, socioeconomic status, physical activity, sitting time and self-rated health: the northern Sweden MONICA study 2014. BMC Public Health. 2017;17(1):654. 10.1186/s12889-017-4623-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.McAninch J, Greene C, Sorkin JD, Lavoie MC, Smith GS. Higher psychological distress is associated with unintentional injuries in US adults. Inj Prev. 2014;20(4):258-265. 10.1136/injuryprev-2013-040958 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Probst TM, Estrada AX. Accident under-reporting among employees: testing the moderating influence of psychological safety climate and supervisor enforcement of safety practices. Accid Anal Prev. 2010;42(5):1438-1444. 10.1016/j.aap.2009.06.027 [DOI] [PubMed] [Google Scholar]
- 28.Yamauchi T, Sasaki T, Takahashi K, et al. Long working hours, sleep-related problems, and near-misses/injuries in industrial settings using a nationally representative sample of workers in Japan. PLoS One. 2019;14(7):e0219657. 10.1371/journal.pone.0219657 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ministry of Health, Labour and Welfare of Japan . 2023 survey on industrial accidents. Article in Japanese. https://www.mhlw.go.jp/toukei/itiran/roudou/saigai/23/ [cited 2025 October 5].
- 30.Ministry of Health, Labour and Welfare of Japan . To persons infected with COVID-19 at work. https://www.mhlw.go.jp/content/000743364.pdf [cited 2025 October 5].
- 31.Japan Industrial Safety and Health Association . Change in number of fatal & non fatal injuries with work absence of 4 days or more in all industries (1996-2022). https://www.jisha.or.jp/english/statistics/detail.html?pdid=1678#f02 [cited 2025 October 5].
- 32.Mori T, Nagata T, Odagami K, Nagata M, Adi NP, Mori K. A prospective cohort study of perceived organizational support and occupational accidents and near-miss events among Japanese workers. J Saf Res. 2024;89(8):19-25. 10.1016/j.jsr.2024.01.002 [DOI] [PubMed] [Google Scholar]
- 33.Kawanami S. Current status and prevention of occupational heat stroke. Article in Japanese. Occup Health Rev. 2022;35(2):91-107. 10.34354/ohpfrev.35.2_91 [DOI] [Google Scholar]
- 34.Ministry of Health, Labour and Welfare of Japan . practical heat stroke guide for workers. Article in Japanese. https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000116133_00001.html [cited 2025 October 5].
- 35.Miyahara H, Oda T. Relationships among subjective view of health, motor ability, functional capacity, lifestyle, and social attributes in old age. Rigakuryoho Kagaku. 2007;22(3):391-396. 10.1589/rika.22.391 [DOI] [Google Scholar]
- 36.Ministry of Health, Labour and Welfare of Japan . The state of the occupational accidents and diseases in Japan. Article in Japanese. 2019. https://www.mhlw.go.jp/content/11302000/000633584.pdf [cited 2025 October 5].
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.