Demographic Analysis of Occupational Safety in the Construction Sector: Strategies and Insights for Risk Reduction

Abstract

The construction sector is among the most dangerous industries, recognized for its significant rate of accidents with even more serious consequences, especially in developing countries. In addition to threatening the health and living conditions of workers, occupational accidents also negatively impact work productivity and sustainability. In this context, a country-by-country analysis of occupational accidents in the sector is critical to understand local demographic differences better and determine the impact of workplace safety practices. In parallel with the growing economy, the construction sector in Türkiye creates a large employment area and stands out as one of the sectors where occupational accidents occur most frequently. This study aims to analyze the interactions of occupational accidents and incapacity with demographic factors in the construction sector in Türkiye. This study analyzes the demographic factors, including age, gender, marital status, education, and work experience, of workers involved in occupational accidents within the construction industry between 2018 and 2022. As a result, it is found that young (18–27 years), male, single, and less experienced (1–10 years) workers are more prone to occupational accidents while increasing age and education level increases the risk of incapacity caused by occupational accidents. As experience increases, the probability of occupational accidents decreases; however, the recovery period is longer for workers who are exposed to heavy working conditions for a long time. The results show that the probability and severity of occupational accidents differ according to demographic characteristics. Therefore, high-risk workers should be identified, and occupational safety policies should be restructured based on this data. This study provides an important guide for policy changes and practical applications for demographically oriented restructuring of occupational safety measures in the construction industry.

1. Introduction

Economic development and sustainable growth depend on strong infrastructure and productive sectors. In this context, the construction sector is a key component for developed and developing countries. The dynamics of the sector encompass not only the construction of physical structures but also employment, capital flows, and technology transfer, which have a crucial impact on the operation of the economic system [1]. The contributions of the construction sector in economic, social, and environmental dimensions make it an indispensable element of development goals at national and global levels. In the global context, this sector not only shapes the dynamics of economic growth but also has a central importance in improving the socio-economic well-being of societies and supporting sustainable development goals [2,3].

The construction sector is essential to economic growth and stability, influencing and being influenced by various economic factors. Its contributions extend beyond construction activities, including job creation, infrastructure development, and cross-sectoral linkages that collectively enhance national economic performance. It is a key component of national economies and represents a prominent field of employment. It involves a large workforce due to its extensive scope and the diverse range of activities it encompasses [4]. The global construction sector accounts for approximately 13% of the world’s Gross Domestic Product (GDP) and offers work opportunities to more than 7% of the global workforce [5]. In addition to its role in the national economy, the construction sector faces challenges in terms of working conditions. Globally, the construction sector, especially in Europe, has the highest rates of workplace accidents. It is considered one of the most hazardous industries due to its frequent accidents and severe impacts on worker health [6]. Its unique characteristics, such as variable work areas, structural and operational challenges, physically demanding tasks, hazardous working conditions, and the extensive use of diverse equipment, contribute to frequent accidents. In addition, the sector differs significantly from others due to its complex workflows, temporary organizational frameworks, frequently changing job locations, and dynamic operational environments [7,8,9].

In the construction sector, it can lead to serious consequences when adequate and effective measures are not taken. These risks result in heavy costs, such as occupational accidents leading to death and permanent loss of limbs. In addition, neglecting the necessary precautions causes significant costs at the individual and the economic and social levels. From an economic point of view, there are adverse effects such as labor losses, disruptions in production, and increased health costs. At the social level, such accidents deeply affect workers’ families, leading to social unrest and decreased confidence in occupational safety. Therefore, effectively implementing workplace safety practices in the construction sector is very important. Even with persistent efforts to improve safety standards, the construction sector still faces a significant challenge with its high rate of accidents, which concerns both professionals and researchers [6,10]. In parallel, the construction industry persists with injury rates and associated expenses that remain notably above average [11]. Annually, about 100,000 workers die on construction sites, making up about 35% of occupational deaths globally [12]. In this respect, a greater comprehension of the underlying factors of accidents in construction is necessary to design impactful prevention strategies [13]. By identifying and addressing the root causes of accidents, stakeholders can implement targeted interventions that protect workers and improve overall project efficiency and productivity.

Literature Review

In recent years, considerable research has been carried out to determine the causes of work-related accidents. These studies highlight that such incidents typically result from unsafe worker behaviors or dangerous workplace conditions. Since human error has a greater impact on accidents than technical failures, most workplace accidents are caused by the hazardous actions of managers, engineers, and workers in different industries [14]. Findings in this field demonstrate that 80–90% of workplace accidents and incidents are linked, either directly or indirectly, to unsafe actions [15]. In the literature, unsafe behaviors and a lack of safety culture are frequently emphasized as the primary causes of workplace accidents in the construction sector [16,17]. Consequently, since worker behaviors are a primary factor in most workplace accidents, the impact of demographic characteristics on these incidents demands thorough academic attention. The construction sector is marked by highly variable working conditions, which expose workers to numerous hazards, many of which are human-related. Therefore, it is crucial to research the occupational characteristics of workers most injured in workplace accidents within this sector [18]. Numerous studies in the literature indicate that demographic factors such as age, gender, education level, and work experience significantly impact construction safety. For instance, some research shows that younger and less experienced construction workers are more prone to accidents due to their limited familiarity with safety procedures, often underestimating potential hazards and exhibiting a greater tendency to take risks [19,20]. Gender differences also significantly influence construction accidents. Male construction workers, who dominate the industry, experience more frequent injuries due to their involvement in physically demanding and high-risk tasks, while female workers may face challenges related to inadequate personal protective equipment and ergonomic risks [21,22]. Furthermore, the level of education and training is crucial, as individuals with lower levels of educational achievement may struggle to understand complex safety protocols and hazard identification, thereby increasing the likelihood of engaging in unsafe practices within the construction environment [23]. It is important to conduct research that considers demographic variables to develop suitable safety interventions and training programs in the industry.

Additional factors examined in the literature include individual and job-related characteristics, for example gender, age, education, and employment status. Numerous studies in the literature discuss the relationship between various factors related to demographic characteristics and occupational activities of workers and occupational accidents. These studies are located in different sectors [15,17,24,25,26,27,28] and especially in the construction sector [29,30,31,32,33,34,35]. In the construction sector, research has been carried out to determine the factors influencing the severity of accidents, and the severity has been modeled based on these factors [36,37,38]. Choi et al. [16] developed a forecasting model utilizing machine learning methods to determine the potential risk of fatal accidents on construction sites. Tetik et al. [39] utilized a decision tree algorithm to pinpoint the factors most strongly connected to accidents and injuries in the construction sector.

Unsafe actions and personal characteristics, covering aspects like gender, nationality, age group, marital status, educational level, and employment experience, are influential factors in workplace incidents [40]. Demographic factors, including education status, age, and ethnicity, may impact the safety culture and safety practices, which are vital for worker safety [41,42]. Risky behavior is the primary factor contributing to site accidents in the construction sector [43,44,45]. Safety management should prioritize reducing and eliminating unsafe behaviors among construction workers [46]. To design safety measures that properly address the requirements of construction workers, employers and safety managers need to gain a comprehensive understanding of workers’ situational awareness on-site [47]. Identifying workers who do not comply with occupational health and safety standards is vital. Numerous researchers have discovered that factors such as gender, training, experience, age, occupation, and education influence workers’ situational consciousness [48,49,50].

Khodabandeh et al. [51] concluded that worker characteristics and work factors can help identify different severity levels of fatal occupational accidents. Koc et al. [52] identified that workers in older age groups are more inclined to fatal accidents, indicating that age is a critical factor in risk evaluation for safety. Başağa et al. [4] highlighted the significance of considering various worker characteristics, including education level, age, and work experience, in designing occupational health and safety training programs. Han et al. [48] examined the impact of demographic factors on the safety perceptions of construction workers. Hatami et al. [53] found that young and inexperienced workers in the construction sector are at higher risk of accidents than older and experienced workers. Alizadeh et al. [54] used the Bayesian theorem to determine posterior probabilities for the severity of accidents on an individual basis within the Iranian construction industry. Their findings indicated that workers with under one year of experience had the greatest risk of injury. Villanueva and Garcia [55] found that the probability of fatal accidents in the workplace rises with age and work period and is more significant among male and temporary workers. Meng and Chan [56] highlighted the significance of safety constructs like safety awareness and safety participation behavior in improving worker safety. Park et al. [57] aimed to recognize the main fundamental causes affecting various combinations of unsafe actions and unsafe conditions in construction accidents.

The construction sector accounts for approximately 6% of the GDP and provides employment for over 1.5 million people. It plays a significant part in the economic advancement of Türkiye. When considering its direct and indirect effects on other sectors, the construction sector’s contribution to the Turkish economy reaches up to 30% [58]. In Türkiye, as in many developing countries, the construction sector is vital to economic growth and urban development. Based on data from the Social Security Institution (SSI), accidents in the construction sector are a significant problem in Türkiye, as they are all over the world. In Türkiye, 28% of fatal work accidents in 2022 occurred in this sector [59]. The analysis of unsafe acts and conditions indicated that safety management, or the absence of it, poses a major issue on Turkish construction sites [60].

The Occupational Health and Safety Law (Law No. 6331) and its associated regulations in Türkiye impose stricter requirements on employers to implement safety measures and establish effective safety management systems. However, the industry’s emphasis on worker health and safety needs to be revised, with safety measures often perceived as unnecessary expenses or additional financial burdens. Consequently, the sector is commonly seen as one of the most dangerous compared to other industrial fields [61].

Previous research has revealed that occupational accidents in the construction industry are primarily related to hazardous working conditions and unsafe worker behaviors. In particular, many studies have focused on determining the frequency of construction accidents and the underlying causes of these accidents [36,62,63,64,65,66,67,68,69,70,71]. However, studies on the relationship between occupational accidents and demographic factors are generally narrow in scope, focusing only on specific variables and neglecting the interaction of different demographic groups and multivariate analysis [72,73,74].

Studies examining the impact of demographic characteristics on safety behaviors [42,48,56,75,76,77] and studies analyzing factors contributing to the occurrence of accidents [78,79,80,81,82] are generally based on surveys. Such studies are open to subjective assessments and biases, making it difficult to assess the factors that cause accidents objectively. The strength of this study is that it analyzes the data of the workers directly involved in the accident; that is, it analyzes the concrete findings obtained from actual incidents. Thus, the impact of demographic variables on occupational accidents was evaluated through an objective database, and the interactions between multiple variables were taken into consideration, making a difference in the literature. In addition, the integration of lost workday and incapacity for work analysis into the study allows for the evaluation of not only the probability of occurrence of occupational accidents but also their economic and operational impact on the sector. This comprehensive approach provides an essential framework for developing more effective occupational safety policies in the construction industry, providing critical insights into identifying high-risk worker groups and developing demographically tailored safety interventions.

This study aims to analyze the demographic characteristics of construction workers in Türkiye between 2018 and 2022 and determine the profile of workers in the sector. In addition, the demographic characteristics of those with occupational accidents in the sector were determined, and the probability of occupational accidents was calculated. In this study, demographic groups were comparatively considered to calculate the probability of work accidents, which offers a different perspective than previous studies. The effect of demographic factors on incapacity for work was determined by logistic regression analysis. Finally, the change in the duration of lost workdays according to demographic characteristics was analyzed. This study adopts a unique approach by simultaneously examining the demographic distribution of the general construction workforce and those who have experienced workplace accidents, calculating accident probabilities based on demographic factors, and modeling disability outcomes using logistic regression analysis.

2. Materials and Methods

The construction sector significantly impacts the Turkish economy, both in terms of its employment generation capacity and the economic mobility it provides to other sectors. Building projects, infrastructure investments, and large-scale public projects are the main factors that support the sector. In particular, the increasing rate of urbanization, urban transformation projects, and the growing population keep the demand in the sector constantly alive. Despite these positive aspects, it is also a sector with significant risks regarding occupational health and safety. In particular, the sector’s rapid growth, infrastructure projects, and urban transformation work create conditions that may increase the frequency and seriousness of work-related accidents.

Based on Social Security Institution statistics [59], the state of the construction sector in Türkiye is summarized in

Table 1. Trends in occupational injuries [59].

Year	Workers	Occupational Injuries		Fatal Occupational Injuries
		Numbers	Injury Rate *	Numbers	Fatality Rate **
2018	1,601,184	77,157	48	591	37
2019	1,294,788	47,701	37	368	28
2020	1,587,666	44,304	28	347	22
2021	1,630,678	58,107	36	386	24
2022	1,808,486	64,184	35	422	23

* Number of occupational accidents per 1000 workers. ** Number of occupational accidents per 100,000 workers.

. Table 1 presents data on the number of workers, occupational injuries, and fatal injuries in the Turkish construction industry from 2018 to 2022. In 2018, the number of workers was 1.6 million, increasing by 13% to 1.8 million by 2022. This increase indicates that the sector is growing or the demand for labor is increasing. The rates of incidents and fatalities in the construction industry have significantly fallen from 2019 to 2020. The year 2020 saw the lowest injury and fatality rates, likely influenced by disruptions in construction activities during the COVID-19 pandemic. Fatal work accidents decreased from 591 in 2018 to 422 in 2022. The fatality rate decreased from 37 to 23 per 100,000 workers. This decline shows that while there has been progress in reducing fatal risks, the fact that one in three people killed in fatal work accidents in Türkiye is in the construction sector shows that it still needs attention [83].

There are notable disparities in the education levels, economic and living conditions, perceptions, and behaviors of construction sector workers in Türkiye. The Social Security Institution (SSI) was formally requested to provide data for academic research, and the requested data was subsequently obtained. This study uses SSI data from 2018 to 2022, focusing on construction workers. In this study, all construction accidents that occurred in Turkey between 2018 and 2022 were analyzed. The analysis follows two stages. First, the situation of all workers in the sector (all workers with and without accidents) was analyzed. To better understand the general structure of the sector, the distribution of workers according to gender, age, marital status, and professional experience was evaluated. According to demographic characteristics, the probability of having an occupational accident was calculated. In the second stage, only the cases of workers who had occupational accidents were analyzed. In these workers, the effect of demographic characteristics on incapacity for work was determined by logistic regression analysis, and how the loss of workday varies according to demographic factors was analyzed (Figure 1).

In this study, logistic regression analysis was utilized to assess the impact of demographic characteristics, such as age, education level, work experience, marital status, and gender on the probability of work incapacity using SPSS version 30.0. Logistic regression was selected for its effectiveness in modeling the relationships between categorically dependent variables and multiple independent variables. Moreover, descriptive statistical methods, including frequency distributions and percentages, were employed to summarize the data set, offering a comprehensive understanding of the data distribution.

3. Results and Discussion

3.1. Analysis of Workers in the Construction Sector

The distribution of 1,037,510 people working in the sector between 2018 and 2022 was determined according to demographic data on gender, age, marital status, and experience. Then, according to these variables, occupational accidents were analyzed, and workers’ accident probabilities were calculated.

3.1.1. Impact of Gender in Construction Sector

• Worker Profile

In Türkiye, 99% of construction workers are male, and 1% are female (Figure 2). There are also similar studies in the literature that support this gender inequality in the construction workforce [84,85,86]. One of the main reasons for the high number of male workers in the sector is that it has hazardous working conditions that require physical strength and endurance. Risky activities such as heavy lifting, working at heights, and using dangerous machinery in construction work led to a higher concentration of male workers.

• Workforce Profile Affected by Occupational Accidents

The formulation used to calculate the probability of occupational accidents is shown in Equation (1).

$$Probability of work accident {\displaystyle \frac{Number of male workers with occupational accidents}{Number of male workers in the sector}}\ast 100$$

(1)

Each variable group was analyzed within itself. When the probability of having an occupational accident by gender was analyzed, it was determined that 32.1% of male and 1.5% of female workers were likely to have an occupational accident (Figure 3). Similarly, male workers were at a higher risk of experiencing workplace accidents compared to female workers [21,87]. This can be attributed to the fact that males are employed in more risky jobs due to the hazardous and difficult working conditions in the construction sector, whereas female workers are usually employed in low-hazard jobs such as office or service occupations.

3.1.2. Impact of Marital Status in Construction Sector

• Worker Profile

When the distribution of workers in the sector by marital status is analyzed, divorced workers are in the first place, and married workers are in the second place. The fact that divorced workers are in the first place indicates that the heavy and dangerous working conditions of the sector may have adverse effects on family life. In particular, intense working hours and physical hardships make it difficult for workers to balance their social and family lives [88,89]. Therefore, it can be said that divorces are high in this sector (Figure 4).

• Workforce Profile Affected by Occupational Accidents

The effect of marital status on the probability of having an occupational accident in the sector was also analyzed. Regarding the probability of a workplace injury in the sector, single workers are in the first place, with a significant difference of 83.4%. Married workers, with 39%, follow this (Figure 5). Although divorced workers have the highest employment rate in the sector, their probability of having a work accident is 2.2%. This situation reveals that the probability of a workplace injury in the sector differs significantly according to marital status. Since single workers have the highest probability of a workplace injury, the experience data of these workers were analyzed, and it was found that 84% of these workers have less experience.

The fact that married workers are in second place, with 39%, indicates that they are also exposed to occupational accidents but not at a rate as high as single workers. This situation may reflect the fact that married individuals generally feel more responsible and, therefore, tend to be more careful.

Although divorced workers have the highest employment rate in the sector, the fact that the probability of occupational accidents remains at a low level of 2.2% indicates that there are a high number of individuals working in experienced and safe positions within this group. After analyzing the data set, 66% of divorced individuals consist of workers with 15 years or more work experience.

The low probability of occupational accidents, especially among divorced and widowed workers, suggests that these workers work more carefully. Divorced and widowed individuals generally have more life experience and maturity, which leads them to be more careful and conscious about occupational safety issues. The lower probability of occupational accidents among divorced and widowed workers in the construction sector can be attributed to their heightened life commitment and stronger work motivation, which may be influenced by the trauma associated with divorce and widowhood. These life events may contribute to a more disciplined, focused, and cautious approach to work, enhancing safety awareness and reducing the risk of accidents. This factor should be carefully considered when developing occupational safety and worker health strategies.

3.1.3. Effect of Age in the Construction Sector

• Worker Profile

It is observed that the highest employment rate in the construction sector is among young workers between the ages of 18 and 27 and that the employment rate in the sector gradually decreases with increasing age. This conclusion suggests that the construction sector demands a younger workforce and that jobs that require physical endurance and energy are more common among young workers due to the nature of the sector. The declining percentage of the elderly labor force in the sector can be explained by factors such as occupational attrition or the shift to alternative sectors. This finding makes an important contribution to understanding labor force dynamics in the construction sector on an age-based basis (Figure 6).

• Workforce Profile Affected by Occupational Accidents

Young workers in the construction sector are found to be at high risk of occupational accidents. This finding was consistent with previous studies [90,91]. In particular, 86.6% of workers in the 18–27 age group are more vulnerable to occupational accidents, indicating that workers in this age group are more vulnerable in terms of occupational safety (Figure 7). Although the probability of occupational accidents is in line with the distribution of employment, the exceptionally high rate among young workers points to some critical factors. Young workers often lack experience, making them unfamiliar with safety rules and less careful in managing work processes. In addition, the fact that the young workforce is generally involved in heavier and riskier jobs in the sector may make them more vulnerable to the risk of accidents. Young workers may be unable to anticipate hazards adequately due to a lack of experience and may be more prone to risk taking. In addition, younger workers may need to pay more attention to safety precautions to work faster or prove themselves in a competitive workplace. This situation can lead to an increase in accident rates. As a result, the fact that the probability of occupational accidents is so high among young workers reveals that occupational safety measures should be implemented more carefully, especially in this age group. This high rate indicates that occupational safety measures should be handled differently according to age groups and that young workers, in particular, should be supported more in terms of training and supervision.

3.1.4. Impact of Work Experience in the Construction Sector

• Worker Profile

The number of workers with 11–20 years of work experience in the sector ranks first with a rate of 32%. This finding shows that workers with a medium level of experience dominate the sector. Workers with 1–10 and 21–30 years of experience are similarly distributed. However, the percentage of those with over 30 years decreases, likely due to the sector’s physical demands (Figure 8). The nature of the sector, demanding long-term physical stamina and performance, leads to a decline in this workforce at older ages.

• Workforce Profile Affected by Occupational Accidents

The distribution of workers according to their work experience and accident probabilities reveals the strong influence of experience on occupational safety. According to the probability of occupational accidents, the highest rate is observed among workers with 1–10 years of experience, at 38.4%. This finding shows that inexperience and lack of complete knowledge of safety rules increase the risk of occupational accidents. The fact that the probability of occupational accidents decreases as experience increases confirms the positive effect of experience on occupational safety. Especially for workers with 11–20 years of experience, the probability of accidents decreased by half to 19.1%, indicating that experience reinforces safe working habits. These findings suggest that experience directly impacts occupational safety (Figure 9). Similarly, inexperience is considered a factor affecting unsafe behavior in construction [92,93]. Previous studies have also found that inexperienced workers have higher accident rates, as in this study [79,82].

3.2. Analyses of Workers Affected by Occupational Accidents in Construction Industry

In the second stage of this study, analyses were conducted only for workers who had an occupational accident. In this context, logistic regression analysis was performed to determine how effective demographic characteristics are in the event of incapacity for work. Then, it was analyzed how lost workdays differ according to demographic characteristics.

3.2.1. Analysis of Incapacity for Work Status with Logistic Regression

Logistic regression is applied to determine the likelihood of an event (dependent variable) from independent variables. Unlike linear models, logistic regression assumes a logit function, making it ideal for binary outcomes, such as determining incapacity for work. The general form of the logistic regression Equation (2) is shown below:

Pi = (Y|X) = e ^{(β0 + β1X1+…+βnXn)}/(1 + e^{(β0+β1X1+…+βnXn)})

(2)

The fundamental principle of logistic regression is to analyze the relationship between dependent and independent variables to predict the likelihood of an event occurring. This method aims to develop a model that accurately represents this relationship while utilizing the fewest possible variables [94,95]. It accounts for varying subpopulation variances and captures nonlinear relationships, making it superior to linear regression for analyzing occupational injury data [96]. Logistic regression effectively models binary outcomes such as workplace accidents by accommodating both continuous and categorical explanatory variables. It provides clear odds ratios for risk assessment [97]. Logistic regression analysis has been preferred in many studies in the literature in the analysis of occupational accidents [60,98,99,100].

According to Law No. 5510 on Social Insurance and General Health Insurance [101], incapacity for work is the inability of the insured to fulfill work capacity due to a work accident or occupational disease. In this case, the insured is paid incapacity benefit. Incapacity benefit is financial support provided to compensate for the loss of income when the insured person cannot continue working due to his/her health condition. Incapacity for work can cause economic and social damage to a country. Effects such as loss of income, reduced productivity, and increased health expenditures can slow the economy’s growth rate and burden public finances. Therefore, managing and preventing incapacity can help safeguard economic and social well-being for individuals and society. In this context, to analyze the effect of demographic characteristics on occupational accident severity, logistic regression was used to examine how factors such as age, education, gender, experience, and marital status impact incapacity.

In the data set of 252,664 work accidents, 47,004 work accidents resulted in incapacity for work, and 205,660 work accidents did not result in incapacity for work. In other words, according to the data set, approximately 80% of the accidents did not result in incapacity for work. In this case, when incapacity is modeled, the prediction percentage is 81%, but this result will be misleading due to this imbalance in the data distribution. Therefore, 47,004 data were randomly selected from the data set without incapacity, and the data set was balanced. As a result, 94,008 accident data were analyzed by binary logistic regression analysis in terms of incapacity, experience, education, age, marital status, and gender variables (

Table 2. Distribution of demographic factors.

Dependent Variable (Y)	Independent Variable (X)	Subcategory of Independent Variable	Frequency	Distribution of Subcategories (%)
Incapacity for Work	Age	18–27	29,554	31.4
		28–37	25,965	27.6
		38–47	21,980	23.4
		48–57	13,611	14.5
		58 and above	2898	3.1
	Experience	0–5 year	21,288	22.6
		6–10 year	19,411	20.6
		11–15 year	16,351	17.4
		16–20 year	10,352	11.0
		20 years above	26,606	28.3
	Education status	Literate	15,154	16.1
		Primary school	26,031	27.7
		Secondary school	26,741	28.4
		High school	20,807	22.1
		University	5275	5.6
	Marital status	Single	32,218	34.3
		Divorced	3435	3.7
		Widow	231	0.2
		Married	58,124	61.8
	Gender	Female	1302	1.4
		Male	92,706	98.6

). The analysis results are showed in

Table 3. Logistic regression analysis results.

		B	S.E.	Wald	df	Sig.	Exp (B)	95% C.I. for EXP (B)
								Lower	Upper
Step 1 a	Experience (0–5 year)			163.871	4	0.000
	Experience 1 (6–10 year)	0.026	0.023	1.325	1	0.250	1.026	0.982	1.073
	Experience 2 (11–15 year)	−0.133	0.030	19.604	1	0.000	0.875	0.825	0.928
	Experience 3 (16–20 year)	−0.130	0.034	14.961	1	0.000	0.878	0.822	0.938
	Experience 4 (20+ year)	−0.343	0.033	105.995	1	0.000	0.710	0.665	0.758
	Marital status (Single)			144.956	3	0.000
	Marital status 1 (Divorced)	−0.015	0.040	0.144	1	0.705	0.985	0.910	1.066
	Marital status 2 (Widow)	0.306	0.138	4.926	1	0.026	1.358	1.036	1.780
	Marital status 3 (Married)	0.218	0.021	111.032	1	0.000	1.243	1.194	1.294
	Age (18–27)			704.792	4	0.000
	Age 1 (28–37)	0.453	0.026	298.438	1	0.000	1.574	1.495	1.657
	Age 2 (38–47)	0.782	0.032	587.525	1	0.000	2.186	2.052	2.328
	Age 3 (48–57)	0.932	0.037	651.514	1	0.000	2.539	2.364	2.727
	Age 4 (58 and above)	0.874	0.050	306.246	1	0.000	2.398	2.174	2.644
	Education status (Literate)			2661.633	4	0.000
	Education status 1 (Primary school)	0.482	0.021	506.629	1	0.000	1.619	1.552	1.688
	Education status 2 (Secondary school)	0.640	0.021	904.907	1	0.000	1.896	1.818	1.977
	Education status 3 (High school)	0.977	0.022	1893.599	1	0.000	2.657	2.543	2.777
	Education status 4 (University)	1.419	0.035	1628.009	1	0.000	4.131	3.856	4.426
	Gender 1 (Female)	−579	0.064	82.756	1	0.000	0.560	0.495	0.635
	Constant	−517	0.067	60.353	1	0.000	0.596

a. Variable(s) entered in step 1: experience, marital status, age, education status, gender. First subcategory of independent variables selected as reference category. Hosmer and Lemeshow Chi-Square Test = X² (8) = 27.792, p = 0.053. B: beta coefficient, S.E: standard error, Wald: Wald Chi-Square Test, df: degrees of freedom, Sig: significance value or p-value, Exp (B): odds ratio, 95% C.I. for Exp(B): 95% confidence interval for odds ratio.

. The model achieved a predictability rate of 59.6%.

Table 3 shows the various demographic factors affecting incapacity for work. Experience level significantly affects the likelihood of incapacity; workers with more experience have a lower risk. Married workers have a higher likelihood of incapacity compared to single workers. The risk of incapacity increases with age, especially for those aged 58 and over. Educational attainment also substantially impacts incapacity, with those with higher levels of education having a higher risk of incapacity. In terms of gender, females are less likely to be incapacitated than males. These findings emphasize the importance of considering demographic variables in the development of labor policies.

Equation (3) is obtained as a result of logistic regression analysis. This equation can help estimate the probability of a construction worker becoming incapacitated due to an accident.

$$\begin{gathered} Y=-0.517+0.026X_{experience1}-0.133X_{experience2}-0.130X_{ecperience3}-0.343X_{experience4} \\ -0.015X_{marital status1}+0.306X_{marital status2}+0.218X_{marital status3}+0.453X_{age1} \\ +0.782X_{age2}+0.932X_{age3}+0.874X_{age4}+0.482X_{education status1}+0.640X_{education status2} \\ +0.977X_{education status3}+1.419X_{education status4}-0.579X_{gender1} \end{gathered}$$

(3)

3.2.2. Demographic Differences in Lost Workdays

Lost workdays are defined as the total number of days a worker cannot work due to an occupational accident, disease, or other reasons. Lost workdays are not only an individual problem but also create severe costs for employers and the general economy. The importance of this concept in occupational safety analysis is that it increases the effectiveness of risk assessments and reveals the necessity of preventive measures. Measuring lost workdays during analyses helps to understand the severity of potential hazards and to prioritize the safety measures that need to be taken. In addition, reducing lost workdays contributes to both the sustainability of businesses and worker satisfaction by increasing labor productivity. Therefore, considering lost workday data in occupational safety analyses is critical in developing a safe workplace and preventing work-related accidents.

The average lost workdays of workers who had an occupational accident in the construction sector between 2018 and 2022 was determined to be 7.5 days. The number of lost workdays of the subcategories of each demographic characteristic in this study was analyzed to determine whether they were below or above the average value (7.5 days).

As seen in Figure 10a, although the average number of lost workdays in construction work accidents is 7.5, this value is found to be 17 for married workers, which explains that married workers are more affected by accidents and their recovery processes take longer.

For the education level, it is seen that university graduates are in the priority risk group with a loss of 12 workdays (Figure 10b). When the data of university graduates are analyzed, it is determined that those with 6–10 years of experience are in the first place with a rate of 37%. A total of 6–10 years of experience includes a period in which workers start to take on tasks such as “middle management” or “field responsibility”. At this point, the increase in technical responsibilities and managerial burdens may reduce the focus on security practices in the field. The negligent behavior and weakened risk perception that come with experience and self-confidence can lead to more serious accidents for this group of workers.

As the age variable increases, the severity of accidents in the sector also increases. In particular, it was determined that workers in the 48–57 age group experienced accidents with a high number of lost workdays (Figure 10c). This finding is similar to some studies in the literature [74,102]. As the age of workers increases, their physical endurance and recovery capacity generally decreases. In individuals working in physically demanding jobs such as construction, musculoskeletal problems, joint pain, or chronic injuries may become more familiar with age. This fact can lead to a more extended recovery period after an accident and, therefore, an increase in lost working days.

For construction workers with 20 years or more of experience, the main reasons for the average number of lost days being 38 days, 5 times higher than all accidents, are physical wear and tear, prolonged recovery period due to age, and weakened risk perception based on experience (Figure 10d). Exposure to heavy working conditions for many years leads to musculoskeletal problems and chronic health problems, which increase the impact of accidents and prolong the recovery period. In addition, self-confidence and habits based on experience can lead to neglect of safety precautions. The severity of accidents is often higher for workers involved in more complex and risky tasks. Regular health screenings, safety training, and ergonomic working conditions are essential for experienced workers.

Figure 10e shows that in work accidents in the construction sector, females experience accidents with an average of 9 lost workdays. This value is above the average value. The construction sector is generally a male-dominated sector, which can lead to the risks faced by women in the workplace being overlooked and safety measures being inadequate. Working environments and equipment designed for the male workforce may not be suitable for female workers, which may increase accidents. The main reasons why females are more likely to be affected by a work accident in the construction sector are physiological, ergonomic, and sectoral factors. The physical structure of women differs from that of men, especially in terms of muscle strength, bone density, and endurance. In the event of an accident of the same severity, women are more likely to suffer bone fractures or soft tissue damage and may take longer to recover.

4. Conclusions

Analysis of occupational accidents in the construction sector in Türkiye shows that occupational safety measures in the sector are inadequate. One out of every three people killed in work accidents in Türkiye works in the construction sector [7]. In addition, this sector ranks third in Türkiye in terms of the rate of occupational accidents per capita [103]. This study establishes the demographic profile of construction sector workers in Türkiye and analyzes in detail the characteristics of workers who have suffered occupational accidents.

The findings reveal that demographic characteristics play an essential role in the frequency and consequences of occupational accidents. Gender, age, marital status, education level, and work experience affect the probability of exposure to occupational accidents and recovery times differently.

Gender differences represent a critical dimension in addressing occupational accidents. In this study, male workers exhibited a significantly higher incidence of occupational accidents (32%) than female workers (1%). This observation aligns with findings from previous studies [87,104]. However, on average, female workers experienced a longer recovery following accidents, losing 9 working days compared to 7 days for male workers. This finding supports the conclusions of Lakhani [105]. These findings underscore the need to redesign existing workplace safety measures to account for female workers’ physiological and ergonomic requirements. Implementing gender-sensitive safety strategies has the potential to mitigate the differential impacts of occupational accidents across genders, thereby enhancing overall workplace safety and inclusivity.

Analysis of the age variable revealed that young workers (86.6%) represent the most vulnerable group concerning occupational accident risk. This finding is consistent with the study by Idrees et al. [106], which highlighted similar concerns. The heightened risk among young workers can be attributed to inexperience, limited hazard anticipation skills, and a greater propensity for risk-taking behaviors. Pairing young workers with experienced mentors and providing field-specific guidance may help mitigate this vulnerability. Conversely, while the frequency of accidents tends to decline with increasing age, the recovery process is observed to be more prolonged. This trend aligns with the conclusions of Fontaneda et al. [107]. This can be attributed to the fact that the physical endurance of older workers decreases, and chronic health problems prolong the recovery period. Ergonomic adjustments and proactive health screenings for older workers may be beneficial.

Differences were observed in accident results depending on education status. When the relationship between education status and the risk of occupational accidents was analyzed, it was found that workers with higher levels of education were less likely to have occupational accidents. However, high school and university graduates were involved in more complex and technical tasks, which resulted in longer periods of incapacity as a result of accidents. This finding suggests that safety training should be performed continuously for workers with increased technical responsibilities.

The experience factor has a critical role in reducing occupational accidents. In this study, workers with 1–10 years of experience had the highest risk of occupational accidents (38.4%). The risk of occupational accidents decreases significantly with increasing experience, but experienced workers (over 20 years) were found to require more extended recovery periods due to physical wear and tear and chronic health problems. Job rotation for experienced workers may contribute to reducing the physical burden.

Marital status stands out as an essential factor in the probability of occupational accidents. Although single workers are 83.4% more likely to be exposed to accidents, divorced and widowed workers are less likely. This can be explained by life experience and more cautious work behavior. These results suggest that safety measures should be focused on young and single workers.

In addition, logistic regression analysis was performed to determine the effect of demographic characteristics on incapacity for work. A model based on demographic variables was developed and, through this model, the probability of a worker experiencing an occupational accident resulting in incapacity for work could be predicted. As a result of the analysis, it was determined that the worker’s age and higher education level are important factors that increase this probability.

When all these results are evaluated, it reveals the importance of targeted interventions based on demographic characteristics to prevent occupational accidents in the construction industry. This study’s findings show that effective occupational safety strategies should consider the “demographic characteristics of workers.” It also draws attention to the difference between measures to reduce occupational accidents and measures to reduce accident severity in the sector. Mandatory safety training for young and inexperienced workers, ergonomic adjustments for middle-aged and experienced workers, and gender-appropriate designs can improve the sector’s safety performance.

This is one of the rare studies that analyzes the impact of demographic factors on occupational accidents in the Turkish construction industry. The results provide an essential guide for restructuring safety policies in the sector. Although this study was conducted within the context of Türkiye, its findings have significant implications on a global scale. The methodological framework, which integrates demographic analysis, logistic regression modeling, and lost workday dynamics, can be adapted to diverse construction industry settings worldwide. By identifying high-risk demographic groups and factors contributing to workplace accidents, this study provides a universal model to inform safety policies and practices across different cultural, economic, and regulatory environments. The insights from this research serve as a foundation for developing globally relevant preventive measures, enabling industries in various regions to prioritize safety interventions more effectively and foster a safer working environment for all construction workers. The emphasis on the importance of training programs, especially for young and inexperienced workers, could be integrated into international safety standards. By demonstrating the impact of demographic factors on occupational accidents, this study provides a guide that can lead to restructuring safety policies for high-risk sectors in Türkiye and worldwide.

This study has limitations in terms of the scope of the research because only one country’s data is analyzed, and this data is available for a certain period. In this study, only the effects of demographic characteristics of workers on occupational accidents were analyzed, and risk perception, safety culture, and environmental factors were excluded from the evaluation. Future studies can investigate the effect of demographic characteristics and safety behaviors such as risk perception, safety culture, and worker motivation. In this way, the probability of occupational accidents will be comprehensively evaluated in all aspects. In addition, comparative studies can be conducted to examine the Turkish construction industry in other countries.