Recommendations and Precautions to Prevent Accidents in Construction Soeiro, Alfredo Departamento de Construções Civis / Faculdade de Engenharia da Universidade do Porto / Rua Dr. Roberto Frias, S/ n.º / 4200-465 Porto / Portugal + 351 22 508 19 38 / avsoeiro@fe.up.pt Reis, Cristina Departamento de Engenharias / Universidade de Trás-os-Montes e Alto Douro / Quinta dos Prados / 5001-801 Vila Real / Portugal + 351 259 350 347 / crisreis@utad.pt ABSTRACT The study was based on the analysis of fatal labour accidents in construction in Portugal. The data has been collected from the Labour Inspection Office files with the analysis of the official inquiries of labour accidents during three years. From this data emerged a data-base that, together with the model of analysis, has served as a test for a set of applied tests of hypotheses to verify a possible correlation between the variable that originates the accidents. This analysis allowed the formulation of innumerable recommendations to improve safety in construction sites. These indicators of risk are related with the probabilities of occurrence of fatal labour accidents in construction. With the conclusion of this study it is intended to elaborate a useful tool in the planning of the supervision/control and coordination of construction safety using these risk indicators. Key Word Risk indicator, Construction accidents, Construction safety, safety plan and Fatal accident probability.
1 ITRODUCTIO The study was based on the analysis of fatal work accidents in construction in Portugal. The data had been collected in the Labour General Supervision (IGT).The basic objective is linked to the individual processing of the records of years 2000, 2001 and 2002. Through the analysis of the official inquiries records different relevant aspects of each accident were gathered in a database. Then a model of analysis, based on this series of characteristics, was developed to analyze statistical properties and correlations. A descriptive analysis, based on the 0 (zero) variable, was performed and then it was extended to become a bivariable analysis. This bivariable analysis of the variables considered was performed to analyze the existing dependence between variables This analysis allowed to obtain various combinations of scenarios potentially dangerous. These scenarios, with combinations of different variables, led to a series of recommendations aiming at calling the attention of safety coordinators, safety managers and safety technicians to the increased risks. These risk indicators are related represent increased probabilities of accident occurrence when compared with single variable analysis. This study intends to elaborate a useful tool in planning safety supervision, management and coordination in construction. 2 METHODOLOGY Seven hundred and nine fatal and serious construction accidents occurred in the years of 2000, 2001 and 2002 and were the basis of this study. Out of these accidents four hundred and nineteen were fatal and two hundred and ninety were serious. These records of the accidents are official from the Labour General Supervision (IGT) in the sector of construction. The fatal work accidents and the serious ones were reported by the construction companies, by obligation in agreement with article. 24 of Decree n.º 273/2003 of 29 of October [1], to Labour General Supervision (IGT) in a period of less than 24 hours after the occurrence. After this communication the Labour General Supervision (IGT) visits the place of the accident and elaborates its proper inquiry in order to determine the causes of the event. During three years [2] this study made the extraction of the relevant data in the central offices of the Labour General Supervision (IGT) in Lisboa, Portugal. Of these official inquiries important information was extracted, that had allowed to create the database. In this database a 0 (zero) variable was associated with each of the characteristics considered in the group of relevant data as possible enablers of the accident. For the elaboration of this study it was intended then to use statistics tools, after the retrieval and compilation of this data, to analyze and to interpret all data [3]. Descriptive statistics is used to characterize the data through the denominated statistical pointers, such as average, mode and standard deviation [4]. On the basis of analysis of a data limited set (but representative of the universe) of an assigned it is intended to characterize the universe, from where such data had been obtained. The inductive statistics allows, with base in the observed or tested elements, to take conclusions for a vast domain from where these elements had come. The statistical inferences, that require knowledge of probabilities, are made through intervals reliable and of statistical tests, parametric or distribution free, applied to the random samples [4]. In the inference statistics, one of the used procedures is the essay of hypotheses. The basic objective consists of testing hypotheses in order to verify if the data shown is not compatible with the determined populations. The methodology to carry through an essay of hypotheses consists of the following: 1. Definition of hypotheses; 2. Identification of test statistics and characterization of its distribution;
3. Definition of the decision rule, with specification of the level of significance of the test; 4. Calculation of the test statistics and making decision. Focusing on the results intended to obtain and on was assigned to the bivariable statistics, a model of analysis was created based on the elaboration of a set of questions. The 0 (zero) variables that characterize the accident are twenty four: degree of seriousness of accident, time of day, day of week, year season, material factor, accident consequence, profession of worker, worker age, damages of the equipment, dimension of the company, region of country, worker nationality, equipment of collective protection, preventive measures broken, company organization, safety plan, safety personel, type of employer, job contract, task performed, sub-task performed, number of workers, type of construction work and time in company service. These variables are all of qualitative type in the nominal scale, with exception of age, time in company service and number of workers. So these have been transformed into qualitative variables, assigned into categories. 3 MODEL AALYSIS Based on questions and on type of variables the question is to inquire which would be the test of hypotheses or methods of analysis of the multivariate data to use. For the elaboration of the database, the variables chosen are factors that have influenced in a way or another one the occurrence of the accidents. Since these variables are of the qualitative type, the choice is limited for the tests of hypotheses that would allow testing the dependence between variables. It was applied the test of independence of Qui-square, based on contingency tables to study the dependence of variables in pairs. From this analysis, it was obtained the existing relations in pairs of the 0 (zero) variables that have affected the occurrence of accidents in statistical terms. The chosen 0 (zero) variable have been classified whenever agreement was possible, on the basis of the stipulated concepts and in accordance with legislation. Figure 3.1 - Model of analysis with initial questions[2] Temporary job contract Accident Seriousness Workers characteristics Fulfilment of safety norms Employers characteristics Regional factors Time period Size of company inherent factors Age inherent factors Acidents the work Fulfilment of safety plan Type of construction Profession inherent factors Characteristics of task and of sub-task Cause effect relationship Characteristics of the causing entity Seasonality in construction Accident time of day Assignment of workers to the task Equipment chracteristics
With each branch of this tree an initial question is associated and with each one there is the choice of a, independent and dependent, variable associated. It is presented an example of the choice of question and respective variable. Initial Question: Were safety plans measures and safety staff relevant factors in the reduction of accidents? Table 3.1 Implementation of safety plans Staff [2] Independent - Safety plan measures - Safety Staff Dependent => - Hour of day - Day of week - Season of year - Material factor - Consequences of accident - Worker profession - Worker age - Equipment damages - Region of country - Worker nationality - Equipment of collective protection - Broken prevention rules - Work organization - Type of employer - Job contract - Task - Subtask - umber of workers - Type of construction work - Time in company service It is convenient to stress that the first analysis was the descriptive analysis of the 0 (zero) variable. It allowed to know for each 0 (zero) variable the fashion and the absolute frequency. To proceed with the statiscal analysis a commercial program of statistics (SPSS) was used. The application of the test of independence of Qui-square based on contingency tables and taking into account the need to fulfil the conditions of applicability. The conditions of applicability of the test of qui-square independence are the following ones: - It cannot exist more than 20 of the cells with an expected frequency inferior to 5; - The 1 cannot exist in any cell with expected frequency inferior. The expected frequency is determined by the following expression: e ij = i.. j Being that: e ij - Expected frequency; i. - Frequency observed in category X i ;.j - Frequency observed in category Y j ; - Frequency of sample
Concerning the multivariate statistics it included the analysis methods of relationship between the multiple variables to explore the relations of dependence and the relations of interdependence. Inside the exploratory methods, there are the factorial analyses of main components and of multiple correspondences, the analysis of clusters and the multidimensional ordinance [5]. The analysis of multiple correspondences (ACM) is adjusted to explore associations between categorized changeable multiple (or treated as such). In this case in particular, to compile and to better interpret the obtained results it has been chosen a set of variables as a function of the question to characterize the scenarios of accidents. In the application of multiple correspondences what it is obtained is a characterization of frequent accidents by categories of variables [6]. 4 RECOMMEDATIOS AD PRECAUTIOS OF COSTRUCTIO SAFETY The bivariate analysis included tests and measures of association depending on the type of study data. Contingency tables were used to analyze the independence of adopted variables in pairs, executing the non parametric test, designed as independent Qui-Square test. The objective of the test consists in verifying if the 0 (zero) variable are or not related. The analysis was made for a level of significance of 5. This test then is constituted by the following hypotheses: H 0 : The 0 (zero) variables are independent H 1 : The 0 (zero) variables are dependent The results are presented in the following form: χ 2 (n) = ET, p = k. Being that: χ 2 - Test of independence of Qui-Square based on contingency tables; (n) - umber of degrees of freedom; ET - Value of the test statistics; p - Value of test; k - Value of test. Then for ά = 0,05 (level of significance of 5), the result of the test is the following one: 1) If Value of test 0,05, means that H0 is rejected and that H1 is accepted; 2) If Value of test > 0,05, means that H0 is accepted. The value of test of Qui-Square alone is validated when its conditions of applicability apply and these are following [3]: - ot more than 20 of the cells will have an expected frequency inferior to 5; - one of the expected values will be inferior to 1. The questions chosen had as objective to combine all variables to obtain a dependence matrix using the independence test of the Qui-square. For example: Initial question: The dimension of the company is correlated with the time in company service? Reponse: the dimension of the company has significant influence in the time in company service (χ2 (21) = 83,607, p=0,000).
Table 4.1 - Dependence of the dimension of the company with the time in company service of the worker [2] time in company service of the worker Dimension of the company Total Micro firm Small firm Medium firm Large entreprise The 1-3 The 3-6 The 6 month The 1 -a 2 The 2-3 The 3-4 - 1 month month month - 1 year year year year + 4 year Total 131 37 22 28 22 13 7 28 288 45,5 12,8 7,6 9,7 7,6 4,5 2,4 9,7 100,0 52 16 23 23 30 7 9 25 185 28,1 8,6 12,4 12,4 16,2 3,8 4,9 13,5 100,0 10 7 10 17 11 1 4 23 83 12,0 8,4 12,0 20,5 13,3 1,2 4,8 27,7 100,0 19 12 8 17 11 4 2 29 102 18,6 11,8 7,8 16,7 10,8 3,9 2,0 28,4 100,0 212 72 63 85 74 25 22 105 658 32,2 10,9 9,6 12,9 11,2 3,8 3,3 16,0 100,0 For an easy interpretation of the dependence matrix, according to the confidence level, a scale between 0 and 5 was used to represent the level probability of accident. In the table that follows it is presented the relation between the confidence level and the test that allowed the evaluation of the dependence [2]. Table 4.2 - Scale of probabilities of occurrence [2] Type of Probability Scale Confidence level (c) Probability very low 0 c< 80 Probability very low 1 80 c < 85 Probability low 2 85 c < 90 Average probability 3 90 c < 95 High probability 4 95 c < 99 Very high probability 5 99 c 99.9999 A global matrix was obtained combining all variables considered. To each one of these combinations of two variables of type 4 or 5 a set of prevention measures was studied and proposed. These measures are suggested for the safety personel to take these measures whenever the pair of variables is present at the construction site in a certain occasion. The list of preventive measures obtained from the database is very long due to the large number of combinations with risk levels of 4 or 5. Therefore and just to illustrate the idea an example is presented. This example relates the size of the company and the safety staff working at the construction site. The analysis of this case shows that There is a great risk for a small company without any type of safety staff. For instance for a level 5 combination the preventive measures are listed in the next table. Table 4.3 List of risks related to staff affected to safety and to the dimension of the company [2] Description Level 5 Level 4 Safety Coordinator Large company Small company Safety Technician Micro company Small company o Staff Micro company Small company Micro company o risk Safety Technician Small company o risk Safety Coordinator Medium company o risk Safety Coordinator Large company o risk Safety Coordinator
The preventive measures are various and some are presented just for the safety plan. The others are related with safety personel and their functions in the construction site. SAFETY PLA (Prevention Measures) - To inform construction owner of need to implement the safety plan in the design phase. - The safety plan needs to be adapted to the staff and technologies being used in the construction site. - The safety plan must have authorship and responsibility by an authorized engineer or technician. - The safety plan must be included in the bidding and contracting phases. - The safety plan must have the design of temporary structures like scaffolding or earth temporary retaining walls. [7]. 5 COCLUSIOS After analyzing the seven hundred and nineteen fatal or serious accidents in construction and performing the statistical analysis of the variables a set of risk indicators have been obtained. It is intended that this survey contributes for the reduction of serious or fatal accidents in construction. Some multivariate analysis have been conducted with selected group of variables. An example is the first set of chosen variables to characterize the safety management. These variables are Material factor, Consequence of accident, Task being performed, Sub-task being performed, Type of construction, Broken Safety rules and Seriousness of accident. When applied the analysis of multiple correspondences to this set of variables it is verified that four groups of components with stronger dependencies exist. In a first group it is verified that the accidents due to earth collapse occur because of soil sliding and lack of temporary retaining walls. These results obtained with the bivariate analysis and with multivariate analysis show that it is possible to identify dangerous combinations of pairs of characterisitics and multivariate associations of factors that create the most potentially risky events on a construction site. This type of information is effective for the safety personel to pay more attention to the risky occurrences. It is not possible to handle all risks in terms of preventive measures but with the help of this database it is possible to examine more carefully the potentially riskier situations. More work needs to be done in terms of the analysis of the pairs of variables and especially in the multivariate analiysis of the factors. The database, the analysis and the prevention measures should become public and accessible to all so that other analysis can be made and a dynamic forum is established to publicize and discuss these preventive measures.
Figure 5.1 - multivariate analysis of the factors Dimension 2 4 3 2 1 0-1 -2 Consequence of accidents Material factor Gravity Soil collapse and burial Broken prevention rules Loosening and fall Temporary retailining walls Subtask Task Wall covers Fall Energy cut Concrete strutures Type of construction Border Withdrawing concrete moulds Infrastructures ST Warehouse Bridges Task Concrete pouring House Building roof Infrastructures Finishings of building cover Electrocussion Serious Energy Bridges Individual protection equipment Infrastructures T Mortal Building Collective protection equipment signs Other FM Loads Other C Site properness and organization Construction yard Equipment inspection Run over Machine Roads Pavement -3-4 -2 0 2 Dimension 1 6 BIBLIOGRAPHICAL REFERECES [1] Ministério da Segurança Social e do Trabalho Decreto-lei n.º 273/2003,DR I Série A, n.º 251, de 29 de Outubro de 2003, referentes as condições de segurança no trabalho em estaleiros temporários ou móveis que vem revogar o decreto-lei n.º 155/95 de 1 de Julho de 1995 [2] REIS, Cristina - Dissertação para obtenção do grau de doutor em engenharia civil Melhoria da Eficácia dos Planos de Segurança na Redução dos Acidentes na Construção FEUP, Março de 2008 [3] GUIMARÃES, Rui Campos; SARSFIELD CABRAL, José A. Estatística Edição revista, Mc Graw Hill [4] PESTAA, Maria Helena; GAGEIRO, João unes Análise de dados para ciências sociais A complementaridade do SPSS, 3ª Edição, Revista e aumentada, Edições Sílabo Lda., Março de 2003 [5] REIS, Elizabeth Estatística Multivariada Aplicada, Edições Silabo Lda., ovembro de 1997 [6] CARVALHO, Helena Apontamentos de Análise de Correspondências Múltiplas Pós graduação em análise de dados para ciências sociais, ISCTE 2007 [7] SOEIRO, Alfredo; REIS, Cristina Workshop A Prevenção de Acidentes na Fase de Project A Segurança na Construção Civil novos desafios VERLAG DASHOFER, EXPOOR, 27 de Outubro de 2005