AC Ambiente Construído Ambiente Construído 1415-8876 1678-8621 Associação Nacional de Tecnologia do Ambiente Construído - ANTAC Resumo Esta pesquisa teve como objetivo, investigar os fatores que contribuem para os acidentes de trabalho em canteiros de obras na cidade de Fortaleza – CE. Foram aplicados 432 questionários junto aos trabalhadores de 10 canteiros distintos pertencentes a 6 diferentes empresas. Por meio de modelos estatísticos - Regressão Logística Binária (RLB), foi avaliada a probabilidade de ocorrência de acidentes de trabalho correlacionando-os às variáveis demográficas, ocupacionais e de gestão. Os principais resultados mostraram que os trabalhadores mais jovens são mais propensos a acidentes de trabalho que os trabalhadores os mais idosos. A etapa construtiva “Alvenaria, Contrapiso e Estrutura” têm uma probabilidade maior de ocorrer acidentes do que a etapa construtiva “Instalações, Fachadas e Acabamentos”. Esta pesquisa contribuiu para uma visão gerencial mais detalhada dos desafios locais, como também para o campo de conhecimento dedicado ao desenvolvimento da segurança do trabalhador em ambientes de alto risco. Introduction The construction industry stands out for its diverse constitution, which encompasses a variety of operating companies and construction methods. In addition, it maintains constant and collaborative interaction with various economic sectors, operating jointly and sharing experiences in various fields. This characteristic finds its maximum expression in the workforce’s ability to operate at different levels of complexity, demonstrating its versatility and ability to adapt to various demands (Varghese; Koshy, 2023). In this dynamic setting, it is common to have several teams working on different tasks and changing as the construction phases progress (Abukhashabah; Summan; Balkhyour, 2020). Therefore, this environment is characterized by working conditions that are often unhealthy, increasing the chances of accidents (Pinto; Nunes; Ribeiro, 2011) and highlighting the importance of assessing Occupational Health and Safety (OHS) risks. In this context, the increase in the number of studies aimed at assessing the risks of construction work (Junjia et al., 2023) underscores the complexity of trying to control and understand this environment. Occupational risks on construction sites stand out for having a high rate of injuries and accidents when compared to other workplaces (Abukhashabah; Summan; Balkhyour, 2020). In the Spanish construction sector, for example, small and medium-sized companies point to difficulties in preventing accidents on construction sites (Segarra Cañamares et al., 2017), a point reinforced by Bridi et al. (2013) and which may be related to unhealthy working conditions (Gomes, 2011). The literature has shown that falls from heights have been one of the main types of accidents (Hsiao; Simeonov, 2001) in countries such as Saudi Arabia (Abukhashabah; Summan; Balkhyour, 2020), China (Shao et al., 2019) and the United States of America (USA) (Waehrer et al., 2007). In Brazil, Norma Regulamentadora 18 (NR) (Regulatory Standard) plays a role in regulating and preventing accidents in the construction industry. According to this standard, construction sites with more than 20 workers are obliged to draw up a program of working conditions and environment. This program establishes occupational safety guidelines for construction companies and related activities and is valid until the work is completed. In this sense, an occupational health and safety system is not effective if the workplace does not have a solid safety culture (Kim; Park; Park, 2016). In other words, accident prevention and control measures can be affected, or even ineffective, if the workplace offers precarious conditions during the execution of tasks. Identifying the factors that are related to the likelihood of accidents occurring on construction sites is a pertinent issue that should not be neglected. Numerous studies in the field of occupational safety have developed their analysis through the application of qualitative methods, such as questionnaires and interviews (Tsurugano; Inoue; Yano, 2012; Bridi et al., 2013; Liao et al., 2018) . In addition, the body of theory studied exemplifies that studies aimed at analyzing only countries with a high level of development are limited in terms of the maturity of tools to promote health and safety at work (Bridi et al., 2013). Therefore, there is a need to expose cases from developing countries and expand the analysis to specific situations, highlighting local particularities. On the other hand, the application of inferential models adds rigor and greater reliability to the results exported. Thus, the aim of this research is to identify and analyze the factors related to the likelihood of occupational accidents on construction sites for vertical buildings in Fortaleza, the capital of the state of Ceará (CE), in northeastern Brazil. The construction sites were visited between January and April 2022. Such factors include demographic variables, occupational variables and variables related to organizational management. To this end, a questionnaire was administered to 432 construction workers working on ten construction sites in six different companies. Descriptive techniques included measures of central tendency and dispersion, presented in graphs and tables. The binary logistic regression model was developed to show the odds ratios of the phenomena evaluated. Finally, this research contributes to the body of OHS literature by applying inferential models to assess the chances of accidents occurring on construction sites of vertical buildings in the city of Fortaleza (CE), implying the addition of technological innovation tools. Backgrounds The construction industry is among the sectors with the highest number of occupational accidents (Trillo Cabello et al., 2021). Multiple studies describe the environment as volatile and dynamic, involving various agents and equipment. These factors complicate the application of an adequate safety management system that promotes the full safety of workers (Im et al., 2009). In Brazil, this scenario is no different, where a considerable proportion of workers still face challenges regarding workplace safety (DRUCK, 2011). In this context, the construction industry is impacted by its own multifaceted nature, although it has undergone regulatory advances and efforts by on the part of various organizations (SESI, 2015; CBIC, 2016) and companies (Silva; Mello, 2021) to improve safety conditions. This diversity of agents involved creates a complex chain of responsibilities, making it difficult to coordinate and implement safety practices. Between 2012 and 2022, for example, the Observatório de Segurança e Saúde no Trabalho (OSST) (Occupational Health and Safety Observatory) (Brasil, 2023b) reported that the building construction sector is the fifth most reported economic sector for accidents. During this period, accidents related to falls from height stood out as the predominant type, mainly affecting the occupation of Servants. Moreover, 2022 data shows that Fortaleza leads in the number of workplace accidents among the population with formal employment ties in the state of Ceará, accounting for approximately 50% of cases, while ranking 13th nationally. Researchers have sought to understand occupational accidents through causal models and analysis of contributing factors (Trillo Cabello et al., 2021). However, in a world of constant political and economic change, the growing demand for productivity (Forteza; Carretero-Gómez; Sesé, 2017) and competitiveness contrasts with increasing demands for social justice, universalization of labor rights and reduction of occupational risks (Chagas et al., 2011). At this point, regulatory requirements must aim for complete physical and mental well-being, focusing on improving the work environment, not just on minimizing exposure to unhealthy agents. For example, by simplifying processes, the Lean Construction model contributes to a more efficient organization of the construction site, reducing waiting times, unnecessary movements and eliminating activities that do not add value to the final product (Koskela, 1992). This not only increases productivity but also creates a safer working environment. In this way, it is possible to establish a relationship between the Lean philosophy and occupational safety, insofar as simplifying processes and eliminating redundant or risky activities reduces workers’ exposure to dangerous situations. Furthermore, by promoting and correcting potential sources of danger, it contributes to a stronger safety culture within the team (Aslam; Gao; Smith, 2020). This is fundamental not only for protecting staff but also for reducing the costs associated with accidents and injuries in the workplace. Finally, numerous researchers design various questionnaires using different methods to capture the possible reasons that explain the causes of accidents or unsafe worker behavior (Im et al., 2009; Fang; Zhao; Zhang, 2016). The consequences of accidents can encompass various aspects, such as physical, psychological and financial, affecting both companies and injured workers (Forteza; Carretero-Gómez; Sesé, 2017; Betsis et al., 2019). Based on a literature review on studies related to safety culture and management in the workplace, there has been disagreement over a universal approach to measuring performance and evaluating the effectiveness of occupational safety management (Dejoy, 2005; Fang; Zhao; Zhang, 2016). However, such divergences may be linked to the continuous need for companies and organizations to adapt. Age profile of accidents It is challenging to define a single approach to workplace safety effective in all circumstances (Bridi et al., 2013). The performance of safety management varies and depends on the context in which it is applied. Thus, some studies analyze factors such as behavioral causes and working conditions as factors that directly influence safety during activity execution (Dejoy, 2005; Satish Mohan; Wesley, 2005; Fang; Zhao; Zhang, 2016), arguing that such factors can distract workers from their environment (Xiang et al., 2023). Research indicates that younger workers are more prone to unsafe behavior due to their lack of experience and awareness of occupational risks (Santana et al., 2009; Miranda et al., 2012), which can lead to accidents during task execution. This observation is supported by Ling, Liu and Woo (2009), who note that construction fatalities in Singapore and the USA often involve young and relatively inexperienced workers who may not be able to identify surrounding dangers. However, it is equally valid to consider that older workers, despite their experience, may have a relatively higher frequency of accidents, as pointed out by Suárez-Cebador, Rubio-Romero and López-Arquillos (2014). Several lines of discussion are possible, but the observations by Ling, Liu and Woo (2009) are relevant; they suggest that very experienced workers may become complacent and their alertness may decrease with advanced age – considered in their study to be between 46 and 57 years. The literature suggests strong enough evidence to consider that younger groups tend to have more frequent accidents. Thus, the discussion has two ramifications. The first involves theories such as Planned Behavior, which can explain how knowledge linked to safety practices relates to the occurrence of accidents (Koo et al., 2014). The second assesses the demographic of formal construction workers in Fortaleza, showing the predominance of younger groups, 18 – 24 years and 25 – 29 years, Ministério do Trabalho e Emprego (MTE) (Ministry of Labor and Employment) (Brasil, 2023a). Based on the literature presented and the information provided by OSST (Brasil, 2023b) and MTE (BRASIL, 2023a), which highlights the significant concentration of young workers in the formal construction industry in Fortaleza, the first research hypothesis can be posited: Hypothesis 1 (H1). The probability of accidents occurring in older age groups is lower than in younger age groups. Construction phases and occupational accident risks: approach to work at height Another important and underexplored factor is the analysis of accidents throughout the construction phases (Amorosino, 2014), which can provide a deeper understanding of working practices and the specific conditions at each stage. This approach can not only identify causal factors, but delves into the unique nature of each stage of the work (Trillo Cabello et al., 2021). Understanding, at least in part, the variables surrounding incidents makes it possible to anticipate risk situations and target specific preventive strategies for each construction phase. Regarding regulatory compliance, Brazilian construction relies on NRs to establish criteria, guidelines, and specifications ensuring process safety and quality. However, compared to companies in other sectors, most construction firms take considerable time to fully assimilate and adhere to these standards, if not only partially. Despite these efforts, the industry still reports significant safety incidents (Loosemore; Malouf, 2019; Brasil, 2023b). Following this logic, it is essential to recognize that changing safety behavior takes time. Workers need continuous exposure to absorb, adapt and apply safety practices to their specific work context (Koo et al., 2014; Loosemore; Malouf, 2019). Such questions can enable more precise planning, adapted to the safety demands of each construction phase, considering the size of the project (López Arquillos; Rubio Romero; Gibb, 2012). For example, when it comes to falls from heights on construction sites in Brazil, we are faced with one of the main types of fatalities reported in the analyzed literature (Satish Mohan; Wesley, 2005; Betsis et al., 2019; Abukhashabah; Summan; Balkhyour, 2020) — workers need to assimilate and constantly apply the safety measures contained in NR 18 and NR 35. Thus, introducing basic safety knowledge on the first day of work, a common procedure in most sectors, becomes a challenge when it comes to making significant behavioral changes in environments where there are a variety of dynamic and uncontrollable factors. Finally, when accidents at heights are discussed, a critical safety issue at work is being addressed, especially in urban environments such as Fortaleza, where construction and other activities involving working at heights are common. These types of accidents can occur in a variety of situations, from constructions work to infrastructure maintenance, and can involve falls from scaffolding, roofs, ladders or even higher structures such as buildings and towers (Shao et al., 2019; Waehrer et al., 2007). Moreover, it is essential to promote a culture of safety in the workplace, where safety is prioritized in all stages of work at height, from planning to execution. Therefore, there is logic in associating the construction phases with the probability of accidents occurring, especially in a city like Fortaleza, which is highly verticalized, associating the probability of accidents occurring at height with construction phases that involve workers in activities such as cladding and finishing external facades. Given this context, this paper proposes the second research hypothesis: Hypothesis 2 (H2). Among the construction phase groups, the “Installations, facades and finishes” group has the highest odds ratio for accidents. Database and methods The Survey questionnaire This study is based on the analysis of data obtained through a printed questionnaire addressed to professionals working in the construction industry in Fortaleza, Ceará, Brazil. The sample consisted of all workers involved in large-scale projects, such as commercial, residential and hospital buildings, including engineers, trainees and various other professionals. These workers were distributed on construction sites belonging to six different companies, covering different construction phases. The methodology for administering the questionnaires was as follows: personal presentation and presentation of the research project; signing of the Informed Consent Form; and application of the questionnaire. Data collection was carried out meticulously, considering the wide variety of roles and responsibilities assumed by the professionals involved. The aim was to achieve a comprehensive understanding of the challenges faced in these work environments, highlighting the unique complexity of this specific context by listing possible factors related to the accidents suffered by workers (Bridi et al., 2013). During the visits to the six construction sites, 54 different functions were identified, which highlights the diversity of activities present in this scenario under study. The questionnaires were administered according to the company’s schedule, during employees’ working hours (7am to 5pm), including breakfast and lunch times. The questionnaires were administered in the canteens and workplaces. In all cases, a chair, clipboard and pen were provided so that the worker could answer the questions listed in Table 1, with a total of 33 questions. The average application time was 8 minutes, except for the cases in which some workers took the questionnaire home, as a way of reading it calmly and if any doubts arose, they would be answered the next day. Table 1 Research variables collected ID VARIABLES CATEGORIES CLASSIFICATION 1 Construction phase Construction of retaining walls and excavationConstruction of foundation blocks and excavationMasonry, screed and structureInstallations, facade and finishes Polychotomous ordinal qualitative 2 Gender FemaleMale Dichotomous nominal qualitative 3 Age range ≤ 2425 - 44≥ 45 Polychotomous ordinal qualitative 4 Marital status SingleMarriedSeparated/DivorcedWidowed Polychotomous nominal qualitative 5 Level of education Literate + IlliterateElementaryHigh schoolGraduated Polychotomous ordinal qualitative 6 Main career occupation 11 occupation categories Polychotomous nominal qualitative 7 Employment status SalariedOutsourcedTrainee Polychotomous nominal qualitative 8 Working shift Full-timeMorningAfternoonEveningFull-time/ Evening Polychotomous nominal qualitative 9 Years of experience Scalar variable Continuous quantitative 10 Weekly hours worked Scalar variable Continuous quantitative 11 Activities on theconstruction site 11 activity categories Polychotomous nominal qualitative 12 Role on site Electrical servicesBlacksmith/carpenterAssemblers/weldersMachine operatorsTechnical Room/administration/StorekeeperRough service WorkersOthers Polychotomous nominal qualitative 13 Have you ever had an accident in your career? YesNo Dichotomous nominal qualitative 14 Have you ever had an accident at work on this site? YesNo Dichotomous nominal qualitative 15 Did the accident occur during the week or at the weekend? WeekWeekend Dichotomous nominal qualitative 16 On which shift the accident occurred MorningAfternoonEvening Polychotomous nominal qualitative 17 What was the causative agent in the last accident? 9 categories of causative agent Polychotomous nominal qualitative 18 Nature of the last injury 6 categories nature of the injury Polychotomous nominal qualitative 19 With work absence? YesNo Dichotomous nominal qualitative 20 Days of absence Scalar variable Continuous quantitative 21 How many construction sites have you worked on in your career? Scalar variable Continuous quantitative 22 Have you had any occupational safety training while working in your career? Yes No Dichotomous nominal qualitative 23 Have you had any occupational safety training while working on this site? Yes No Dichotomous nominal qualitative 24 If yes, which one(s)? Safety instruction Do not rememberNo trainingRegulatory standardsOthers Polychotomous nominal qualitative 25 How many hours of training? Scalar variable Continuous quantitative 26 Do you use EPI in your workplace? Yes NoSometimes Polychotomous nominal qualitative 27 Have you been or are you a member of CIPA? Yes No Dichotomous nominal qualitative 28 Are accidents that happen here reported? Yes NoUnsure Polychotomous nominal qualitative 29 Do you consider your workplace organized? Likert scale - 0 to 10 Discrete quantitative 30 At this construction site, is the company interested in your opinions on safety? Likert scale - 0 to 10 Discrete quantitative 31 How much do you consider the company’s management to be committed to safety? Likert scale - 0 to 10 Discrete quantitative 32 Are the safety procedures adopted by the company strict regarding risk? Likert scale - 0 to 10 Discrete quantitative 33 How useful do you consider the safety instructions? Likert scale - 0 to 10 Discrete quantitative Note: CIPA is the “Comissão Interna de Prevenção de Acidentes” (Internal Accident Prevention Committee). Some workers had little schooling or were illiterate. In these cases, the interviewer used didactics to clarify the purpose of the survey and some of the questions, which required more time from the researcher. At no point did the researcher answer the questionnaire for these workers. During the visits to the six construction sites, 54 different functions were identified, which highlights the diversity of activities present in this scenario under study. The analysis process was structured in six main phases, in the following order: literature review; questionnaire development; CEP approval; questionnaire administration/fieldwork; data tabulation; and statistical analysis. In this way, it was possible to collect a total of 33 research variables, including the binary dependent variable (DV), accident occurrence as shown in Table 1. Table 1 shows all 33 research variables collected during the site visits, highlighting the type of variable, its categories and how they were measured. Furthermore, Table 2 summarizes the above arguments by showing the construction phase, the companies responsible, the type of construction and the number of workers interviewed, the number of accidents per site and the types of accidents per site. Table 2 General characteristics of the sites visited Constructive phases Company Type of building Interviewed workers Accidents on site Types of Accidents on site Installations, Facade and Finishes A Hospital 84 13 9 - (T); 4 - (OD) Installations, Facade and Finishes B Residential 64 1 1 - (T) Masonry, Subfloor and Structure C Residential 42 2 2 - (T) Installations, Facade e Finishes C Residential 48 7 1 - (T); 1 - (RTA); 5 - (OD) Construction of retaining walls and excavation D Residential 28 3 2 - (T); 1 - (RTA) Masonry, Subfloor and Structure D Residential 55 2 1 - (T); 1 - (RTA) Construction of retaining walls and excavation E Residential 25 1 1 - (T) Execution of foundation blocks and excavation F Residential 45 2 2 - (T) Construction of retaining walls and excavation F Commercial 20 - - Construction of retaining walls and excavation F Residential 21 - - Sum 432 31 31 Note: Typical (T); Road Traffic Accidents (RTA); and Occupational Disease (OD). The documentary analysis of the types of accidents reported will be based on descriptive statistics showing absolute and relative numbers. The data collection application and analysis process was structured in six main phases, in the following order: literature review; questionnaire development; CEP approval; questionnaire administration/fieldwork; data tabulation; and statistical analysis. In this way, it was possible to collect a total of 33 research variables, including the binary dependent variable (DV), accident occurrence. Finally, all the steps taken here comply with Resolution 466/2012 (Brasil, 2012), which stipulates that all research projects involving human beings must be assessed by the Comitê de Ética em Pesquisa (CEP) (Research Ethics Committee), evaluated in accordance with the Certificate of Presentation of Ethical Appreciation nº 51755721.4.0000.0018. The database Table 3 summarizes the main categories obtained in the survey, offering a clear and concise summary of the sample obtained from the participants. Table 3 Main categories obtained in the survey Independent variable Categories Gender (Binary) Female Male Age range (Years) (Categoric) ≤ 24 25 — 44 ≥ 45 Educational level (Categoric) Literate + Illiterate Elementary High school Graduated Construction phase (Categoric) Construction of retaining walls and excavation Construction of foundation blocks and excavation Masonry, screed and structure Installations, facade and finishes Job role on the construction site (Categoric) Electrical services Blacksmith/carpenter Assemblers/welders Machine operators Rough service workers Technical room/administration/Storekeeper Others Training (Categoric) Safety instruction Do not remember No training Regulatory standards Others Construction site organization (Continuous) Likert scale — 0 to 10 Commitment to safety (Continuous) Likert scale — 0 to 10 Work experience (Continuous) Years Each variable listed is assigned its nature (Binary, Categorical or Continuous) and the groups that make it up, respectively. However, some variables, such as ‘Age range’, ‘Job role on the construction site’, ‘Training’ and ‘Rough service workers’, required special specifications due to their complexity in relation to the number of groups or the imbalance in the observations. In this research, ‘Rough service workers’ refers to construction professionals such as servants, bricklayers, concrete mixer and concrete pump operators, highlighting their heavy tasks and specific skills. These particularities could potentially impact the confidence intervals of the statistical model, as discussed by Irala, Fernandez-Crehuet Navajas and Serrano del Catillo (1997). Therefore, additional procedure was taken to deal with these variables in order to mitigate possible distortions in the results and ensure the robustness of the analysis. In this context, for the Age range variable, workers who were illiterate or only literate were included in just one group called “ Literate + Illiterate “. Moreover, this research proposes the use of the “Mature Adult - Plus” classification as an extra resource to minimize distortions in the number of groups and observations. This same reasoning was applied to the variables “Training” and “Job role on the construction site”. In other words, variables that had numerous groups or a large disproportion in the number of observations were grouped together or reallocated, following the same logic as (Gavioli et al., 2014). More specific details on these disparities will be presented in the Results - Descriptive Statistics section, providing a better visualization of the discrepancies observed. The statistic models In the area of health and safety at work, this research adopts data of a binary nature, i.e., categorized into two distinct classes. However, when applying the linear ordinary least squares model, the underlying assumptions could be violated, which would compromise the effectiveness of the analysis (Fernandes et al., 2020). This is because this model is best suitable to continuous and normally distributed data. To overcome this limitation and adapt to the binary nature of the data, the use of the binary logistic regression model is proposed, since the dependent variable is the occurrence (dummy = 1 with a probability of occurrence p) or non-occurrence of accidents (dummy = 0 with a probability of occurrence 1 - p) on the construction sites visited. The logistic regression model specifies that logit(p) = ln p/ (1 – p) represents how the relationship between the probability of an event and various predictors can be expressed as a linear combination (Landwehr; Pregibon; Shoemaker, 1984; Fávero; Belfiore; Souza, 2023). This format is a way of linking the probability of an event to a linear function involving explanatory variables. This equation allows for modeling how changes in these variables affect the probability of the event occurring, showing the impact of each predictor on the probability of the outcome. Equation 1 diagrams this effect mathematically. p i = 1 1 + e − Z i ;   being:   Zi = α + β 1 . X 1 i + β 2 ⋅ X 2 i + … + βK . Xki Eq.1 Where: pi is the probability of the event occurring for each observation; Z is known as logit (the natural logarithm of the odds ratio), expressing the odds of an event occurring; the constant e is the Euler’s number; α is the intercept for equation; βk (k = 1, 2, 3, 4, …, k) is the estimated parameters for each explanatory variable; and X is the explanatory variables and i represents each observation in the sample. Bearing in mind that the chance of an event occurring is given by the odds ratio (OR) between the occurrence (p) and non-occurrence (1 - p) of an event. Solving these equations involves iterations that can predict the beta coefficients and the corresponding standard errors. Obtaining these parameters makes it possible to calculate ORs and confidence intervals (CI). Thus, an analytical approach was adopted in three distinct aspects regarding the nature of the independent variables (IV) considered: dichotomous variables; categorical variables; and continuous variables. The independent variables used in this model include demographic information, the construction phases of the sites, the occupation of the workers, the type of accident prevention training, experience (time on the job) and the worker’s opinion of the company’s organization and commitment (Table 3). In addition, the analysis incorporates specific techniques for robust validation of the statistical model adopted. To examine the linearity between each continuous independent variable in the model and the log of the dependent variable, predictors representing the interaction between each variable and its logarithm (Box; Tidwell, 1962; Field; Miles; Field, 2012). This approach made it possible to analyze the linear relationship between the independent variables and the logit of the dependent variable. Finally, to assess the model’s overall predictive capacity, the ROC curve (receiver operating characteristics curve) was constructed (Fawcett, 2006). Results and discussions Sample characterization A total of 432 workers were interviewed, with the majority being male (96% men and 4% women), and the largest proportion being aged between 25 and 44 (57%). The average age was 38.40 (± 11.76) years, with the youngest worker being 17 years old (trainee) and the oldest 67 years old (carpenter). Also, the occupations and levels of education were categorized into distinct groups, illustrating the distributions by age group in Figure 1 and 2. Figure 1 Demographic characteristics: occupation Figure 2 Demographic characteristics: education Figure 1 shows a significant predominance of “25 – 44” in all the occupation clusters used in this research. It is notable that the representations of occupations in the graph seem to maintain a ratio between workers classified as “25 – 44” and those designated as “≥ 45”. A plausible explanation for this phenomenon can be found in common practice in the construction industry, which often values the presence of experienced labor when carrying out specific tasks. Figure 2 follows the same idea of analyzing age groups, but in relation to the workers’ level of education. It is clear that a large proportion of “25 — 44” have up to elementary (9th grade) or high school education. The demographic profile of Ceará’s construction workers, given that the Secretaria de Obras Públicas (SOP) (Department of Public Works) emphasizes that of the 7,044 vacancies created in 2023, 6,199 (88.0%) were occupied by men, especially those with completed secondary education (SOP, 2023). A reasonable justification can also be made for the occupations of rough service workers, blacksmith/carpenter, and electricians/refrigerators, in which these classes of work do not require a high level of schooling, usually only elementary or high school education is required. In contrast, a considerable proportion are classified as having only basic education or are illiterate, especially in the “≥ 45” age group, where 6% (9 out of 153) are illiterate. Corroborating data from Instituto de Pesquisa e Estratégia Econômica do Ceará (IPECE) Economic Research and Strategy Institute of Ceará (IPECE, 2021), which shows that approximately 68% of the municipality’s formal are aged between 25 and 49. This analysis is relevant due to the significant presence of the “Literate + Illiterate” group and the notable representation of the “≥ 45” age group. This scenario may be indicative of a historical context in which illiteracy and informality were issues of concern in the Câmara Brasileira da Indústria da Construção (CBIC) Brazilian Chamber of the Construction Industry (CBIC, 2010), indicating that traces of this period tend to persist throughout the working life of individuals. Therefore, this description suggests that the older, less educated group seems to be the group with the most work experience, which is corroborated by Figure 3. Figure 3 Experience by level of education Figure 3 shows that the majority of workers with the most experience are grouped among those with only basic education or who are illiterate, with the most experienced worker (bricklayer) having 48 years of work dedicated to construction and the least (doorman) having 1 month. This leads to consider two perspectives: the first relates to experience itself and its possible connection with the likelihood of accidents occurring, while the second addresses the association between experience and level of education, but only in a descriptive sense. In the context analyzed, it is believed that a large part of the experience of workers with a low level of schooling is derived from practice and experience in the workplace (Figure 3). Thus, certain workers in this specific group faced difficulties in understanding the purpose of the survey and interpreting the questions put to them. In some cases, it was necessary to pay close attention during the explanations to ensure that no question was misinterpreted. Descriptive statistics on accidents The main point of analysis and discussion in this research revolves around the variables related to construction phase, training, occupation and age group, in an attempt to explain the probability of accidents occurring. Figures 4 to 7 show the relationship between workers who have suffered some kind of accident and the variables mentioned. Figure 4 Main characteristics of reported accidents: Training Figure 5 Main characteristics of reported accidents: occupation Figure 6 Main characteristics of reported accidents: construction phase Figure 7 Main characteristics of reported accidents: age range A total of 31 accidents were reported, of which 13 (42%) were reported by rough workers (mostly bricklayers and servants). With regard to the types of accidents, Table 2 shows the “Typical” accident as the most frequent (61.29%), followed by the “Occupational Disease” type (29.03%) and the “ Road Traffic Accidents” type (9.67%). According to the OSST (Brasil, 2023b), in 2022 Fortaleza had 50.3% of bricklayers and servants with accidents. In safety training, a high incidence of accidents was observed, possibly revealing a lack of specific training in these work environments by safety technicians and site managers in the Diálogo Diário de Segurança (DDS) (Daily Safety Dialogues) or negligence on the part of workers in failing to comply with regulatory requirements. Construction phases, “Installations, facades and finishes” was the phase with the highest number of accidents reported (64.5%). In the above finding, it can be analyzed that rough service workers, blacksmith/carpenter and electricians (Figure 1) accounted for 59.49% of the workforce analyzed and these workers work directly on construction sites in the “Installations, facades and finishes” construction phase. There is, therefore, a concern about occupational safety for field workers in this phase of construction, and safety management needs to take urgent action on preventive and corrective actions, whether directed at management or execution. Finally, the 25 – 4 age range group had the highest number of accidents reported (64.5%), can be correlated with the analysis in Figure 1, so older workers are more prone to accidents. It is worth noting that the “≤ 24” group had the same proportion of accidents as the “≥ 45” group. Although the construction phase “installations, facades and finishes” accounts for the majority of accidents, the foundation phases – “Construction of retaining walls and excavation” and “Execution of foundation blocks and excavation” – were the most frequent phases during visits to construction sites made by one of the authors of this research (5 out of 10). Despite this, two of them had no accidents and the other three had 1, 2 and 3. The difference in the average number of accidents between the two phases was thus evident. This difference in the average number of accidents can probably be associated with the lower number of parallel activities in the foundation phase compared to the others. Certainly, the lower the number of parallel activities, the lower the diversity of risks. Parallel activities can occur in the foundation phase, when, for example, the layout of the site can vary due to size restrictions or topographical characteristics of the lot. However, none of the five construction sites in this phase had such restrictions. It is worth mentioning that the imbalance in the dependent variable is anticipated, because even though the construction industry is characterized as a complex environment in terms of the number of agents that cause accidents, the sector is governed by a variety of regulatory standards and strict practices that aim to prevent the integrity and life of workers. Binary logistic regression reports Table 4 shows the results of the binary logistic regression model, where the dependent variable is the occurrence of accidents, while the independent variables include age group, constructive phase, occupation, training, organization, commitment and work experience. Table 4 Binary logistic regression results> Variable Reference Predictors O.R. Estimated C.I. p-value 2.5% 97.5% Age range ≤ 24 25 – 44 3.400 1.223 0.934 12.371 0.063(.) ≥ 45 14.550 2.677 1.587 133.358 0.017(*) Construction phase Masonry, screed and structure Construction of retaining walls and excavation 0.738 -0.303 0.158 3.444 0.699 Construction of foundation blocks and excavation 0.787 -0.238 0.125 4.953 0.798 Installations, facade and finishes 0.313 -1.161 0.084 1.157 0.081(.) Ocupation Rough service workers Electrical services 3.784 1.330 0.785 18.242 0.097(.) Blacksmith/Carpenter 0.935 -0.066 0.207 4.227 0.931 Assemblers/Welders 0.067 -2.692 0.008 0.514 0.009(**) Machine operators 0.565 -0.570 0.125 2.547 0.457 Others 3.743 1.319 0.441 31.718 0.226 Administration 1.317 0.275 0.374 4.636 0.667 Training Regulatory standards Others 1.566 0.448 0.561 4.370 0.391 Do not remember 0.797 -0.226 0.171 3.713 0.773 No training 2.804 1.031 0.736 10.686 0.130 Safety instruction 6.251 1.832 1.027 38.016 0.046(*) Organization – – 1.085 0.082 0.839 1.403 0.530 Commitment – – 1.491 0.399 1.166 1.906 0.001(**) Experience – – 0.951 -0.049 0.893 1.013 0.119 Note: significance codes: (**) p < 0.01; (*) p < 0.05; (.) p < 0.1. Number of obs: 432; AIC = 215.31; PseudoR2 – Nagelkerke = 0.2491. To reinforce the robustness of the model, multicollinearity between categorical qualitative variables was assessed, as reported in Table 5, following the recommendations of Hair et al. (2009) and Fávero, Belfiore and Souza, (2023) in relation to tolerable limits. Table 5 VIF test Independent variable Degrees of freedom VIF Construction phase 3 1.6839 Age range 2 3.0890 Experience 1 3.0128 Ocupation 6 2.9106 Training 4 1.8987 Organization 1 2.0233 Commitment 1 2.0677 VIF Average 2.3837 The evaluation of the linear relationship between the continuous independent variables and the logit of the dependent variable was carried out in accordance with the literature (Field; Miles; Field, 2012), showing a p-value < 0.05, indicating a linear relationship, satisfying the assumption. Moreover, the accuracy of the model was assessed using the area under the ROC curve (Receiver Operating Characteristic) (Fawcett, 2006; Hair et al., 2009; Fávero; Belfiore; Souza, 2023), where can be found an area of 80%, as shown in Figure 8. These evaluation indices indicate that the model adopted proved to be satisfactory in terms of accuracy. Figure 8 ROC curve and area under curve The logistic model revealed statistical significance in at least one of the groups for each of the categorical variables analyzed. The analysis showed that the “age group” variable has a higher odds ratio for accidents in the “25 – 44” and “≥ 45” groups compared to the “≤ 24” group. Specifically, according to Figure 9, the estimators showed that the “25 – 44” group was 3.4 times more likely, while the “≥ 45” group was 14.55 times more likely, contradicting hypothesis H1. Figure 9 Odds ratios for significant variables However, this result raises a question about the prevalence of a higher accident rate among the more mature age groups, even considering the accumulation of professional experience over time (Figure 3). A plausible explanation for this phenomenon is linked to the possible complacency and decreased alertness associated with older age. Studies such as Ling, Liu and Woo (2009), discuss the influence of ageing on cognitive and physical performance, suggesting that although experience can be vast, the natural decline in cognitive and physical capacities associated with age can affect risk perception and readiness to react to potentially dangerous situations. In this context, Figure 1 also shows that regardless of the type of occupation, the “≥ 45” class is always present. To put it another way, although Figure 1 shows that all age groups are represented in each of the professional occupation categories, the over-45 category is emphasized due to the wealth of discussion that associates older age with experience acting as a vector for two divergent arguments: on the positive side, experience gives workers extensive knowledge of the risks involved in their activities; on the negative side, age brings with it both the possibility of cognitive decline and undesirable overconfidence leading to negligent behavior when carrying out activities (Varghese; Koshy, 2023), especially in an environment where workers often exceed their working hours and, in the case of Fortaleza, are exposed to high temperatures. Thus, the requirements for on-site training should be more inclusive and accessible to the general public, since most of them have a low level of education. Safety technicians together with site management need to provide more periodic training in a more appropriate language for all workers. The literature contributes to the discussion by highlighting that the severity of accidents tends to increase with advancing age, especially among workers aged between 60 and 65 (López Arquillos; Rubio Romero; Gibb, 2012). In addition, there are indications that serious and fatal accidents involving occupations that deal with electricity are more common in individuals over the age of 45 (Suárez-Cebador; Rubio-Romero; López-Arquillos, 2014). The results obtained by the logistic model corroborate the previous observation that electricians face a greater risk in the workplace. The model’s estimators revealed that the group associated with “electrical services” shows a substantially higher susceptibility to accidents compared to the category of gross service workers (OR = 3.784; p-value < 0.1). Accidents involving electricity usually have significant consequences, highlighting the vulnerability of the “electrical services” group. This reinforces the rigorous importance of specific safety and prevention procedure. The specific standard for this group highlights three important points linked to electrical activities. Firstly, it emphasizes the need for workers, both direct and indirect, to review the appropriate training before performing any function and to carefully analyze the workplace to identify potential agents that could compromise physical integrity. This ensures constant updating of the skills and tools needed to deal with the risks inherent in electrical activities. Insulation tests on tools and Equipamentos de Proteção Individual (EPI’s) (Personal Protective Equipments) (gloves, wrenches, high and low voltage tests) were some of the practices observed during work involving high voltages (Hospital Construction). In addition, detailed documentation of electrical installations is mandatory, including the creation of a medical record and the carrying out of risk analysis and the clear definition of orientation zones in the workplace, such as danger zones, controlled zones and free zones. The main electrical tool is accident 0, as reported. All these specific provisions are aimed at preventing workers from being exposed to unnecessary risks, in line with the general guidelines of NR 35, work at height. Just like the “electrical services” group, scaffolding erectors and metal structure welders deal with agents that constantly expose their integrity to the risks inherent in the activities they perform. However, this discussion goes deeper and gains relevance when analyzing the estimators associated with this specific group. The two statistically significant occupations, Electrical services and Assemblers/Welders, are occupations in which workers receive hazardous pay (Brasil, 1977). Professionals linked to these occupations are naturally exposed to a higher level of risk compared to jobs that are not covered by the dangerousness criteria in the workplace. These occupations cover different activities, involving both exposure to low and high electrical voltages and working at heights. These discrepancies were readily observed during visits to the workplaces. Notably, on site, specific practices were adopted to mitigate the risks inherent in these activities. For example, it was recurrently observed that teams of fitters received specific guidance to develop risk perception, including training aimed at sharpening the five senses, helping to identify possible risk factors at an early stage. Literature and practice converge in showing that the perception of risk between technicians and workers is different, reverberating in the conflict between perceived risk and real risk (Varghese; Koshy, 2023). These strategies demonstrate an effort to increase situational awareness and the ability to detect threats. It is important to discuss that observations in the field revealed that safety professionals value good safety management. Investments and efforts to organize the spaces of the construction sites that were the targets of this research were identified. In the literature the Lean philosophy reinforces this idea, as it promotes efficiency in site organization and improves the safety culture. The application of lean principles contributes to the optimization of processes, reduction of waste and greater attention to safety aspects, further strengthening the positive perception of safety professionals in relation to the sites visited (Koskela, 1992; Aslam; Gao; Smith, 2020). Although the analysis of safety culture and the principles of Lean Construction are beyond the scope of this article, these types of investments and efforts can probably influence the organization of the work environment and the safety culture, based on the worker’s perception of this environment. The ability to effectively perceive one’s surroundings in the workplace is considered fundamental by the team of safety technicians on site. This ability can be important for identifying potential causes when reporting accidents. As outlined in the Comunicação de Acidentes de Trabalho (CAT’s) (Work Accident Report), the employer is legally obliged to report the accident by the next working day. In fatal cases, communication must be immediate, and all related procedures can be carried out online. Following this logic and analyzing the particularities of activities at height, the finding that the construction phase of “Installations, facade and finishes” has a lower probability of accidents when compared to the “Masonry, Subfloor and Structure” phase (OR = 0.313; p-value < 0.1) contradicts hypothesis H2, refuting it. Although the results of this study seem to refute our hypotheses, we reinforce the notion that, at least in the reality investigated, the environment in the construction industry in Fortaleza seems to be in more controllable conditions. Statistical data from Fortaleza’s Célula de Referência em Saúde do Trabalhador (CEREST) (Workers’ Health Reference Cell) indicates a significant 52% reduction in accident notifications in the building construction sector between 2012 and 2022, despite a 9.2% increase being recorded between 2021 and 2022 by OSST (BRASIL, 2023b). This reduction over the period analyzed suggests successful efforts in terms of accident control and prevention and on-site training, although a recent slight increase demands continued attention to maintain this positive trend. Manual labor, often associated with production in construction environments, is linked to human error and has been identified as the main cause of accidents on construction sites (George; Fidelis; John, 2023). There are authors who defend the obligation and importance of training on construction sites, pointing out that investments in this area can reduce costs (Waehrer et al., 2007), especially in countries like Brazil, where legislation and labor unions can lead to high costs related to accidents. However, this study reveals a worrying trend: workers’ perception of management’s commitment to safety has a direct impact on the occurrence of accidents (OR =1.491; p-value < 0.001). A false sense of security can lead to negligence in safety procedures, and workers’ perception of risk is important for prevention, as the slightest carelessness can result in serious incidents. Surprisingly, safety procedure and frequent training do not seem to contribute to reducing the chances of accidents, as indicated by the estimators in the “Safety instruction” group. Some research suggests using digital technologies, such as virtual reality, to improve the assimilation of information during training (Rokooei et al., 2023), providing greater immersion for workers. Interestingly, Figure 2 shows that a large part of the sample has either only elementary school (9th grade) or basic education (reading and writing) or are illiterate, which corresponds to 54% of the sample (234 workers). Thus, these characteristics may be impairing the workers’ understanding of practical procedures, reviving the arguments about declining cognitive abilities over the years and justifying the fact that the “Safety instruction” training group has a higher chance of accidents compared to those with “regulatory standards” training. Conclusions The purpose of this study was to investigate the likelihood of accidents occurring, considering the variables collected in the field, age group, construction phase, occupation, training and workers’ perception of the companies’ commitment to safety on 10 construction sites in Fortaleza, CE, in real time, i.e. the worker was approached to talk about the current moment in his career. Initially, we hypothesized that more experienced groups would be less likely to suffer accidents, given their familiarity with the work environment. However, the inferential analysis results revealed the opposite reality, refuting hypothesis H1. The main point of reflection for this idea is age-related work experience. We analyzed that the more experienced the workers were, the more accustomed they would be to the work environment. Therefore, they would have control and they would be aware of most of the agents that cause accidents. However, the inferential results showed us another reality, which was confirmed by the literature. There are cases in which more experienced workers can become overconfident in their own experience and, as a result, neglect basic safety factors and procedures. Along these lines, when examining the construction phases, we noticed a dichotomy between different stages of the process. In contrast to hypothesis H2, it was found that the “Installations, Facades and Finishes” phase had a lower probability of accidents compared to the “Masonry, Subfloor and Structure” phase. This finding challenges preconception and suggests the existence of peculiarities in the risks associated with each stage of construction, indicating the need for specific approaches to safety in each of them. The probable inadequacy of the analysis of this result lies in the possibility of understanding the “Installations, Facades and Finishes” phase as a phase in which such activities can be internal or external. The inadequacy of the analysis may be because these two types of activities comprise different risks in terms of severity. However, in the particular case of the construction sites visited, two aspects may explain why the result of the logistic model and the conclusions are appropriate. Firstly, only 3 of the 10 sites visited were at this stage of construction. Secondly, the 3 sites in question were only carrying out internal activities, with less severe risks. The results relating to occupations, especially those linked to electrical services and assembly/welding, provided important discussions. Workers in these occupations face substantial risks, highlighting the need for targeted safety procedures specific to these groups. The study highlighted the relevance of differentiated strategies due to the hazardous nature of the tasks performed by these professionals. Surprisingly, the analysis of training revealed that, despite efforts to provide safety instruction, the provision of training did not appear to reduce the likelihood of accidents. This finding points to the importance not only of availability, but of the effectiveness and appropriateness of training methods. The research suggests that practical understanding of safety procedures may be limited, especially among workers with lower levels of education, emphasizing the need for more inclusive and accessible teaching methods. One of the notable findings was the impact of managers’ perceived commitment to workplace safety. The survey revealed that workers’ perception of management’s commitment to safety had a direct impact on the occurrence of accidents. This highlights the importance of not only having safety procedures in place, but also the culture and commitment of the leadership in promoting a safe environment. Promoting a safer working environment through management commitment means developing a safety culture in the organization as a whole and, therefore, on construction sites. Although this argument was not part of the scope of this article, this line of research could certainly be developed in the future by other authors. Finally, we highlight the importance of the process of formulating and testing hypotheses. It is emphasized that hypotheses should be tested and discussed, not simply confirmed or refuted. 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