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Occupational Health and Safety Implications in the Oil and Gas Industry, Nigeria
Author(s)
Benson, Chizubem
Advisor(s)
Μπούστρας, Γιώργος
Abstract
Workplace risks, hazards, and accidents remain a significant concern for workers in the oil and gas industry. Workers are continuously exposed to different occupational risks, threats, and recurrence of several accidents in the industry globally. Because of the various activities that occur during the exploration and production phase, the oil and gas industry is thought to be one of the most dangerous workplaces. Tackling the challenges, the industry is facing is very important to workers in the industry and operational environment. The study aims to identify ways to reduce the danger, threat, and accident associated with the Nigerian oil and gas industry using secondary and primary data information. A total of 1000 questionnaires were distributed to various departments within the study industry and who may have been affected by a
health problem or have encountered some threat that could jeopardize their health or even result in death at work in 27 oil and gas stations, of which 19 separate companies operated and 327 were returned to the research team. Statistical Package
for Social Sciences (SPSS V.20.0 IBM) was used to analyze data for the study to convert both items and sub-items into variables that were important to the study. The participant's various responses "answers" were coded using value labels, and the variables were entered for analysis. Categorical data such as age, gender, general working knowledge, and awareness of health and safety procedures and protocols, descriptive statistics, such as percentages, frequencies, means, ranges, and standard deviations, corrections of variables were measured. The Generalized Linear Model
(GLM) was fitted using the Poisson distribution because the number of responses to each question is counted. Chi-square statistical test was utilized to compare the differences in the number of the levels of the answers (strongly agree, agree,
disagree, strongly disagree and neutral) to each question in the questionnaire concerning the various factors that influence the safety and health of workers in the study industry.
Factor analysis was used to classify the latent constructs when many of the variables were understudied. Principal component factoring and orthogonal Varimax rotation were subjected to test. Multiple regression analysis was used to determine the factor that has a more predictive influence on significant accidents and risks that may affect
workers health in the oil and gas industry. The study's findings and recommendations will aid the oil and gas industry to improve worker safety and health in their operational environment on a local and worldwide scale. It will also assist the
industry in detecting a safety deficiency and reducing the number of threats, hazards, and injuries in the industry.
health problem or have encountered some threat that could jeopardize their health or even result in death at work in 27 oil and gas stations, of which 19 separate companies operated and 327 were returned to the research team. Statistical Package
for Social Sciences (SPSS V.20.0 IBM) was used to analyze data for the study to convert both items and sub-items into variables that were important to the study. The participant's various responses "answers" were coded using value labels, and the variables were entered for analysis. Categorical data such as age, gender, general working knowledge, and awareness of health and safety procedures and protocols, descriptive statistics, such as percentages, frequencies, means, ranges, and standard deviations, corrections of variables were measured. The Generalized Linear Model
(GLM) was fitted using the Poisson distribution because the number of responses to each question is counted. Chi-square statistical test was utilized to compare the differences in the number of the levels of the answers (strongly agree, agree,
disagree, strongly disagree and neutral) to each question in the questionnaire concerning the various factors that influence the safety and health of workers in the study industry.
Factor analysis was used to classify the latent constructs when many of the variables were understudied. Principal component factoring and orthogonal Varimax rotation were subjected to test. Multiple regression analysis was used to determine the factor that has a more predictive influence on significant accidents and risks that may affect
workers health in the oil and gas industry. The study's findings and recommendations will aid the oil and gas industry to improve worker safety and health in their operational environment on a local and worldwide scale. It will also assist the
industry in detecting a safety deficiency and reducing the number of threats, hazards, and injuries in the industry.
Date Issued
2022-03-27
School
Publisher
School of Sciences : Department of Computer Science and Engineering : PHD Occupational health and Safety