**2.2 Measures and variables**

*Occupational Wellbeing*

thus avoiding loss of lives [17].

**2. Material and method**

**2.1 Data**

during the process after work accidents [16]. Although organizational safety is the responsibility of the employer, employees also have great responsibilities; they need to be careful and act consciously to prevent work accidents [14]. In this context, it is of great importance that employees use the protective gear prepared for them correctly, that they perform the emergency procedures that must be carried out in the event of an accident completely, and inform the proper authorities immediately–

Work accidents and diseases affect the whole country economically, socially and, psychologically. Work accidents constitute many cost elements such as lost working days, decrease in production, recruitment and training of new workers, compensation payments, and health expenditures. This situation causes state and company policies to be disrupted and sometimes not realized. In addition, the loss of human capital and the high budget share of social aid provided to the victims hinder new investments. From the perspective of the worker, the individual's loss of welfare, the psychological pressure, and loss of status that he and his family experience cause workers to feel as if they are a burden. In addition, accidents in the workplace also negatively affect other employees [6]. The aim of this study was to determine the socio-demographic and economic factors that are critical in individuals experiencing work accidents that result in injuries in Turkey. For this purpose, 10 factors were selected, and the impact of these factors on the probability of experiencing work accidents was examined. In this study, the Turkey Health Survey data made by the Turkish Statistical Institute (TSI) were employed.

The micro data set obtained from the Turkey Health Survey carried out by the TSI in 2008, 2010, 2012, 2014, and 2016 were used in this study. The Turkey Health Survey, which was first carried out in 2008, had been conducted every two years. The Turkey Health Survey was last conducted in 2016. With this survey, the aim is to minimize the information gap in the current structure by obtaining information for the health indicators that have a large share in the development indicators that show a country's level of development. In addition to being a survey that reflects the whole country, it is also important in enabling both international comparisons and shedding light on national needs. The scope of this survey is households that are located in all settlements within the borders of Turkey. Institutions including soldiers and permanent residents of dormitories, prison, nursing homes, hospitals, etc. are out of this survey's scope as well as locations (i.e. small villages, settlements of nomads, etc.) that are thought to be inadequate in terms of sample size (the

This survey was designed to give a total estimate for Turkey. A stratified twostage cluster sampling method was used to obtain the data. The first stage sampling unit was randomly selected blocks from the clusters (blocks) containing an average of 100 household addresses with a proportionate stratification, and the second stage sampling unit was the household addresses systematically and randomly

In this study, the data from a total of 35,019 employees over 15 years old were employed, including 5473 people who participated in the Turkey Health Survey in 2008, 5238 people who participated in this survey in 2010, 10,436 people who participated in 2012, 7415 people who participated in 2014, and 6457 people who

number of population less than 20) have been excluded.

selected from each selected cluster [18–22].

**134**

participated in 2016.

The dependent variable of this study was a work accident of an individual measured by the question, "Have you had an accident that caused injury in the past 12 months?" The dependent variable was a binary variable. In the established binary logistic regression model, the dependent variable was categorized as 1 if the individual had had a work accident and 0 if not.

The independent variables are survey year (2008, 2010, 2012, 2014, 2016), gender (male, female), age group (15–24, 25–34, 35–44, 45–54, 55–64, 65+), education level (did not finish school/illiterate, primary school, secondary school, high school, university), marital status (single, married), work schedule (part-time, full time), profession (managers, professional occupational groups, technicians/ assistant professional occupational groups, staff working in offices, service/sales staff, qualified agricultural/forestry/aquaculture workers, craftsmen/craft-related jobs, plant-machine operators/installers and those who work in jobs that do not require qualification), general health (very good/good, moderate, bad/very bad), psycho-social support/being depressed (no, yes), and alcohol use (no, yes). Ordinal and nominal variables were defined as dummy variables in order to observe the effects of the categories of all variables to be included in binary logistic regression model [23].

#### **2.3 Research methodology**

Survey statistics in Stata 15 (Stata Corporation) were used to account for the complex sampling design and weights. Weighted analysis was performed. First, frequency analyses of the variables in the model were performed. Then, chi-square independence tests were performed in order to detect the relationship between whether individuals had experienced a work accident and socio-economic and demographical factors. Last, factors which influenced the work accident experience of individuals were determined with binary logistic regression analysis.
