*p < .10.* **Table 2.**

*Occupational Wellbeing*

**Variables VIF β Std.** 

**Survey year (reference category: 2008)**

**Gender (reference category: female)**

**Level of education (reference category: university)**

**Marital status (reference category: single)**

**Work schedule (reference category: part time)**

**General health status (reference category: poor)**

**Occupation (reference category: manager)**

**Age (reference category: 15–24)**

Did not finish school/illiterate

Professional occupational group worker

Service employee and sale representative

Qualified agricultural worker

Facility and machinery operator

worker

Non-qualified job

**Error**

 1.67 −0.195 0.122 0.111 0.823 0.648 1.046 2.09 −0.128 0.104 0.219 0.880 0.717 1.079 1.9 −0.261 0.114 0,022b 0.770 0.615 0.964 1.85 −0.246 0.121 0,042b 0.782 0.617 0.991

Male 1.2 0.809 0.107 0.000a 2.246 1.822 2.769

25–34 3.25 −0.229 0.134 0.088c 0.795 0.611 1.035 35–44 3.90 −0.509 0.148 0.001a 0.601 0.450 0.803 45–54 3.39 −0.721 0.160 0.000a 0.486 0.355 0.665 55–64 2.19 −1.202 0.215 0.000a 0.300 0.197 0.458 65+ 1.56 −1.217 0.308 0.000a 0.296 0.162 0.542

Primary school 3.25 0.539 0.179 0.003a 1.714 1.208 2.434 Secondary school 2.16 0.441 0.182 0.016b 1.554 1.087 2.222 High school 2.00 0.477 0.168 0.004a 1.612 1.160 2.238

Married 1.53 0.079 0.109 0.467 1.082 0.875 1.339

Full time 1.06 0.072 0.168 0.669 1.074 0.773 1.494

Technician 1.91 0.697 0.252 0.006a 2.008 1.225 3.292 Office worker 1.76 −0.007 0.313 0.982 0.993 0.538 1.833

Artist 2.78 1.452 0.218 0.000a 4.270 2.786 6.542

Very good 4.97 −0.650 0.154 0.000a 0.522 0.386 0.706

1.89 0.339 0.230 0.141 1.404 0.894 2.204

2.87 0.440 0.267 0.100 1.553 0.920 2.624

2.87 0.614 0.225 0.006a 1.848 1.189 2.875

3.15 1.109 0.233 0.000a 3.031 1.922 4.781

2.11 1.020 0.228 0.000a 2.774 1.773 4.340

2.65 1.241 0.224 0.000a 3.459 2.228 5.370

**P OR 95% CI**

**Low. Up.**

**138**

*Binary logistic regression estimation results of socio-demographic and economic factors that affect whether individuals experience work accidents.*

95% CI = 2.786–6.542), plant-machine operators/assemblers (OR = 2.774; 95% CI = 1.773–4.340), and those who work in jobs that do not require qualification (OR = 3.459; 95% CI = 2.228–5.370) have higher odds of having a work accident than managers. When general health status is examined, the odds ratio of experiencing work accident of those with very good health (OR = 0.522; 95% CI = 0.386–0.706) is lower than those with poor health status. People who receive psycho-social support/ are depressed (OR = 1.641; 95% CI = 1.246–2.160) had higher odds of having a work accident than others. Finally, the odds ratio of experiencing work accidents for participants who used alcohol (OR = 1.331; 95% CI = 1.130–1.568) was higher than for those who did not.

#### **3.3 Average direct elasticity**

Average direct elasticities and standard errors in the socio-demographic and economic factors that influence whether individuals experience work accidents resulting in injuries in Turkey are provided in **Table 3**.

For marginal effects, the probability of experiencing work accidents was lower in other years compared to 2008. In terms of gender, the probability of men experiencing work accidents was 78.9% higher than women. Also, as age increased compared to the age range of 15–24, the probability of work accidents decreased. The probability of individuals within the age groups of 25–34, 35–44, 45–54, 55–64, and 65+ are 22%, 49%, 69,6%, 116,8% and 118,2%, respectively, lower than the 15–24 age range.

When the education levels are analyzed, primary school graduates, secondary school graduates, and high school graduates are 52.4%, 42.9%, and 46.5% more likely to have a work accident than university graduates, respectively.

When looking at the occupational groups, the probability of technicians, service/sales staff, qualified agricultural workers, craftsmen, plant/machine operators, and those who do not work in qualified jobs is, respectively, 68.5, 60.4, 108.4, 141, 99.9, and 121.1% higher than managers.

When the general health status is examined, those with very good general health status are 62.4% less likely to have a work accident than those who have poor health. In addition, those who receive psycho-social support/are depressed are 47.6% more likely to have a work accident than other individuals. Those who use alcohol are 27.6% more likely to have a work accident than those who do not.


#### **Table 3.**

*Elasticity estimates for socio-demographic and economic factors that influence whether individuals experience work accidents.*

**141**

*Modeling the Factors That Affect Work Accidents with Binary Logistic Regression…*

Work accidents remain important worldwide. Work accidents and diseases influence the whole country economically, socially, and psychologically. 286.068 work accidents occurred in Turkey in 2016. 1405 people died in these work accidents [9]. The loss of these people exerted great pressure on the country, both socially and economically. In addition, even if these accidents did not result in loss of life, the workers being unable to work as a result of their injuries, their inability to continue their work for a long time, or scars they have because of these accidents psychologically depress individuals, apart from economic problems. For this reason, it is of great importance to determine the causes of work accidents and to try to prevent

The aim of this study was to investigate the factors affecting work accidents of individuals that resulted in injuries in the last 12 months in which the survey was conducted in Turkey. As a result of the analysis, the variables of gender, age, education, occupation, health, psycho-social support/depression, and alcohol use were

According to study findings, men have more work accidents than women. Similar results can be found in many studies in the literature [26, 27]. In addition, it was detected in some studies that men are more likely to experience fatal work accidents [28]. This situation can be explained with the fact that men work more in

According to the results of the analysis, it was found that the age range that had the most work accidents was 25–34, while the age range that had the least accidents was 65+. Although the physical activity of workers decreased as they get older, their increased experience was effective in decreasing work accidents with age. In this context, there are many studies showing that work accidents are most common in the 25–44 age range and least common in the 65+ age range [12, 13, 29–31]. In some studies, the 16–24 age range was found to be the age group where work accidents occurred most frequently [26, 32]. There are also studies indicating that the 35–45 age range is the age group that most frequently experiences fatal work accidents [28]. It was detected that the probability of having a work accident decreases with an increase in the level of education. This may be due to the fact that workers who have a low level of education work in low-profile and risky jobs, or it may be due to individuals having an incomplete understanding risk factors due to a lack of education [31, 33, 34]. In addition, individuals who had not received vocational training were more likely to experience work accidents. Therefore, individuals should undergo specific training before starting to work, and, basic work-related safety measures should be taught [35]. In addition, the fact that individuals did not have sufficient work-related training increased the risk of fatal accidents. One out of every five deaths in construction workers and 95% of the deceased workers were uneducated people [28]. Workers receiving professional training to improve their job competencies and increase their job-related knowledge had an important role in preventing work accidents. In addition, developing a safety culture with training activities and the integration of these activities into corporate culture will make safety a reality at each level [36]. Also, as job safety and health training become more appealing, individuals will receive three times more information, thus considerably reducing work accidents. Applied, student-centered, and participatory training activities should be therefore put into practice [37]. It was detected that individuals working in lower level jobs were more exposed to work accidents. This may arise from the risk and safety awareness of the employees. It is expected that this result arises from the fact that those who work in jobs requiring more strength have generally received less education and people who work in upper-level positions, such as managers, will have a certain awareness, due to

*DOI: http://dx.doi.org/10.5772/intechopen.93872*

these accidents by concentrating on their causes [6].

dangerous jobs that require physical power than women.

detected statistically significant.

**4. Discussion**

*Modeling the Factors That Affect Work Accidents with Binary Logistic Regression… DOI: http://dx.doi.org/10.5772/intechopen.93872*
