848 resultados para logistic regression analysis
The association between objectively measured neighborhood features and walking in middle-aged adults
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Purpose: To explore the role of the neighborhood environment in supporting walking Design: Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting: The Brisbane City Local Government Area, Australia, 2007. Subjects: Brisbane residents aged 40 to 65 years. Measures Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis: The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results: After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion: The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.
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Background and significance: Older adults with chronic diseases are at increasing risk of hospital admission and readmission. Approximately 75% of adults have at least one chronic condition, and the odds of developing a chronic condition increases with age. Chronic diseases consume about 70% of the total Australian health expenditure, and about 59% of hospital events for chronic conditions are potentially preventable. These figures have brought to light the importance of the management of chronic disease among the growing older population. Many studies have endeavoured to develop effective chronic disease management programs by applying social cognitive theory. However, limited studies have focused on chronic disease self-management in older adults at high risk of hospital readmission. Moreover, although the majority of studies have covered wide and valuable outcome measures, there is scant evidence on examining the fundamental health outcomes such as nutritional status, functional status and health-related quality of life. Aim: The aim of this research was to test social cognitive theory in relation to self-efficacy in managing chronic disease and three health outcomes, namely nutritional status, functional status, and health-related quality of life, in older adults at high risk of hospital readmission. Methods: A cross-sectional study design was employed for this research. Three studies were undertaken. Study One examined the nutritional status and validation of a nutritional screening tool; Study Two explored the relationships between participants. characteristics, self-efficacy beliefs, and health outcomes based on the study.s hypothesized model; Study Three tested a theoretical model based on social cognitive theory, which examines potential mechanisms of the mediation effects of social support and self-efficacy beliefs. One hundred and fifty-seven patients aged 65 years and older with a medical admission and at least one risk factor for readmission were recruited. Data were collected from medical records on demographics, medical history, and from self-report questionnaires. The nutrition data were collected by two registered nurses. For Study One, a contingency table and the kappa statistic was used to determine the validity of the Malnutrition Screening Tool. In Study Two, standard multiple regression, hierarchical multiple regression and logistic regression were undertaken to determine the significant influential predictors for the three health outcome measures. For Study Three, a structural equation modelling approach was taken to test the hypothesized self-efficacy model. Results: The findings of Study One suggested that a high prevalence of malnutrition continues to be a concern in older adults as the prevalence of malnutrition was 20.6% according to the Subjective Global Assessment. Additionally, the findings confirmed that the Malnutrition Screening Tool is a valid nutritional screening tool for hospitalized older adults at risk of readmission when compared to the Subjective Global Assessment with high sensitivity (94%), and specificity (89%) and substantial agreement between these two methods (k = .74, p < .001; 95% CI .62-.86). Analysis data for Study Two found that depressive symptoms and perceived social support were the two strongest influential factors for self-efficacy in managing chronic disease in a hierarchical multiple regression. Results of multivariable regression models suggested advancing age, depressive symptoms and less tangible support were three important predictors for malnutrition. In terms of functional status, a standard regression model found that social support was the strongest predictor for the Instrumental Activities of Daily Living, followed by self-efficacy in managing chronic disease. The results of standard multiple regression revealed that the number of hospital readmission risk factors adversely affected the physical component score, while depressive symptoms and self-efficacy beliefs were two significant predictors for the mental component score. In Study Three, the results of the structural equation modelling found that self-efficacy partially mediated the effect of health characteristics and depression on health-related quality of life. The health characteristics had strong direct effects on functional status and body mass index. The results also indicated that social support partially mediated the relationship between health characteristics and functional status. With regard to the joint effects of social support and self-efficacy, social support fully mediated the effect of health characteristics on self-efficacy, and self-efficacy partially mediated the effect of social support on functional status and health-related quality of life. The results also demonstrated that the models fitted the data well with relative high variance explained by the models, implying the hypothesized constructs under discussion were highly relevant, and hence the application for social cognitive theory in this context was supported. Conclusion: This thesis highlights the applicability of social cognitive theory on chronic disease self-management in older adults at risk of hospital readmission. Further studies are recommended to validate and continue to extend the development of social cognitive theory on chronic disease self-management in older adults to improve their nutritional and functional status, and health-related quality of life.
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Overweight and obesity are strongly associated with endometrial cancer. Several independent genome-wide association studies recently identified two common polymorphisms, FTO rs9939609 and MC4R rs17782313, that are linked to increased body weight and obesity. We examined the association of FTO rs9939609 and MC4R rs17782313 with endometrial cancer risk in a pooled analysis of nine case-control studies within the Epidemiology of Endometrial Cancer Consortium (E2C2). This analysis included 3601 non-Hispanic white women with histologically-confirmed endometrial carcinoma and 5275 frequency-matched controls. Unconditional logistic regression models were used to assess the relation of FTO rs9939609 and MC4R rs17782313 genotypes to the risk of endometrial cancer. Among control women, both the FTO rs9939609 A and MC4R rs17782313 C alleles were associated with a 16% increased risk of being overweight (p = 0.001 and p = 0.004, respectively). In case-control analyses, carriers of the FTO rs9939609 AA genotype were at increased risk of endometrial carcinoma compared to women with the TT genotype [odds ratio (OR) = 1.17; 95% confidence interval (CI): 1.03–1.32, p = 0.01]. However, this association was no longer apparent after adjusting for body mass index (BMI), suggesting mediation of the gene-disease effect through body weight. The MC4R rs17782313 polymorphism was not related to endometrial cancer risk (per allele OR = 0.98; 95% CI: 0.91–1.06; p = 0.68). FTO rs9939609 is a susceptibility marker for white non-Hispanic women at higher risk of endometrial cancer. Although FTO rs9939609 alone might have limited clinical or public health significance for identifying women at high risk for endometrial cancer beyond that of excess body weight, further investigation of obesity-related genetic markers might help to identify the pathways that influence endometrial carcinogenesis.
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This study determined the rate and indication for revision between cemented, uncemented, hybrid and resurfacing groups from NJR (6 th edition) data. Data validity was determined by interrogating for episodes of misclassification. We identified 6,034 (2.7%) misclassified episodes, containing 97 (4.3%) revisions. Kaplan-Meier revision rates at 3 years were 0.9% cemented, 1.9% for uncemented, 1.2% for hybrids and 3.0% for resurfacings (significant difference across all groups, p<0.001, with identical pattern in patients <55 years). Regression analysis indicated both prosthesis group and age significantly influenced failure (p<0.001). Revision for pain, aseptic loosening, and malalignment were highest in uncemented and resurfacing arthroplasty. Revision for dislocation was highest in uncemented hips (significant difference between groups, p<0.001). Feedback to the NJR on data misclassification has been made for future analysis. © 2012 Wichtig Editore.
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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.
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Background: This longitudinal analysis examines how patterns of contraceptive use changed over 11 years among Australian women born between 1973 and 1978. Study Design: The analysis included 6708 women sampled from the Australian universal health insurance database who completed four self-report postal surveys between 1996 and 2006. Change over time in use of any method of contraception and the common single methods of the oral contraceptive pill and condom was examined using a longitudinal logistic regression model. Results: The oral contraceptive pill was the most commonly used single method at each survey (27-44%) but decreased over time. Over time, contraceptive users were increasingly more likely to be single or in a de facto relationship or to have had two or more births. Conclusions: Women's contraceptive use and the factors associated with contraceptive use change over time as women move into relationships, try to conceive, have babies and complete their families.
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Background Women change contraception as they try to conceive, space births, and limit family size. This longitudinal analysis examines contraception changes after reproductive events such as birth, miscarriage or termination among Australian women born from 1973 to 1978 to identify potential opportunities to increase the effectiveness of contraceptive information and service provision. Methods Between 1996 and 2009, 5,631 Australian women randomly sampled from the Australian universal health insurance (Medicare) database completed five self-report postal surveys. Three longitudinal logistic regression models were used to assess the associations between reproductive events (birth only, birth and miscarriage, miscarriage only, termination only, other multiple events, and no new event) and subsequent changes in contraceptive use (start using, stop using, switch method) compared with women who continued to use the same method. Results After women experienced only a birth, or a birth and a miscarriage, they were more likely to start using contraception. Women who experienced miscarriages were more likely to stop using contraception. Women who experienced terminations were more likely to switch methods. There was a significant interaction between reproductive events and time indicating more changes in contraceptive use as women reach their mid-30s. Conclusion Contraceptive use increases after the birth of a child, but decreases after miscarriage indicating the intention for family formation and spacing between children. Switching contraceptive methods after termination suggests these pregnancies were unintended and possibly due to contraceptive failure. Women’s contact with health professionals around the time of reproductive events provides an opportunity to provide contraceptive services.
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The Australian Securities Exchange (ASX) listing rule 3.1 requires listed companies to immediately disclose price sensitive information to the market via the ASX’s Company Announcements Platform (CAP) prior to release through other disclosure channels. Since 1999, to improve the communication process, the ASX has permitted third-party mediation in the disclosure process that leads to the release of an Open Briefing (OB) through CAP. An OB is an interview between senior executives of the firm and an Open Briefing analyst employed by Orient Capital Pty Ltd (broaching topics such as current profit and outlook). Motivated by an absence of research on factors that influence firms to use OBs as a discretionary disclosure channel, this study examines (1) Why do firms choose to release information to the market via OBs?, (2) What are the firm characteristics that explain the discretionary use of OBs as a disclosure channel?, and (3) What are the disclosure attributes that influence firms’ decisions to regularly use OBs as a disclosure channel? Based on agency and information economics theories, a theoretical framework is developed to address research questions. This theoretical framework comprises disclosure environments such as firm characteristics and external factors, disclosure attributes and disclosure consequences. In order to address the first research question, the study investigates (i) the purpose of using OBs, (2) whether firms use OBs to provide information relating to previous public announcements, and (3) whether firms use OBs to provide routine or non-routine disclosures. In relation to the second and third research questions, hypotheses are developed to test factors expected to explain the discretionary use of OBs and firms’ decisions to regularly use OBs, and to explore the factors influencing the nature of OB disclosure. Content analysis and logistic regression models are used to investigate the research questions and test the hypotheses. Data are drawn from a hand-collected population of 1863 OB announcements issued by 239 listed firms between 2000 and 2010. The results show that types of information disclosed via an OB announcement are principally on matters relating to corporate strategies and performance and outlook. Most OB announcements are linked with a previous related announcement, with the lag between announcements significantly longer for loss-making firms than profitmaking firms. The main results show that firms which tend to be larger, have an analyst following, and have higher growth opportunities, are more likely to release OBs. Further, older firms and firms that release OB announcements containing good news, historical information and less complex information tend to be regular OB users. Lastly, firms more likely to disclose strategic information via OBs tend to operate in industries facing greater uncertainty, do not have analysts following, and have higher growth opportunities are less likely to disclose good news, historical information and complex information via OBs. This study is expected to contribute to disclosure literature in terms of disclosure attributes and firm characteristics that influence behaviour in this unique (OB) disclosure channel. With regard to practical significance, regulators can gain an understanding of how OBs are disclosed which can assist them in monitoring the use of OBs and improving the effectiveness of communications with stakeholders. In addition, investors can have a better comprehension of information contained in OB announcements, which may in turn better facilitate their investment decisions.
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Background Cervical cancer and infection with human immunodeficiency virus (HIV) are both important public health problems in South Africa (SA). The aim of this study was to determine the prevalence of cervical squamous intraepithelial lesions (SILs), high-risk human papillomavirus (HR-HPV), HPV viral load and HPV genotypes in HIV positive women initiating anti-retroviral (ARV) therapy. Methods A cross-sectional survey was conducted at an anti-retroviral (ARV) treatment clinic in Cape Town, SA in 2007. Cervical specimens were taken for cytological analysis and HPV testing. The Digene Hybrid Capture 2 (HC2) test was used to detect HR-HPV. Relative light units (RLU) were used as a measure of HPV viral load. HPV types were determined using the Roche Linear Array HPV Genotyping test. Crude associations with abnormal cytology were tested and multiple logistic regression was used to determine independent risk factors for abnormal cytology. Results The median age of the 109 participants was 31 years, the median CD4 count was 125/mm3, 66.3% had an abnormal Pap smear, the HR-HPV prevalence was 78.9% (Digene), the median HPV viral load was 181.1 RLU (HC2 positive samples only) and 78.4% had multiple genotypes. Among women with abnormal smears the most prevalent HR-HPV types were HPV types 16, 58 and 51, all with a prevalence of 28.5%. On univariate analysis HR-HPV, multiple HPV types and HPV viral load were significantly associated with the presence of low and high-grade SILs (LSIL/HSIL). The multivariate logistic regression showed that HPV viral load was associated with an increased odds of LSIL/HSIL, odds ratio of 10.7 (95% CI 2.0 – 57.7) for those that were HC2 positive and had a viral load of ≤ 181.1 RLU (the median HPV viral load), and 33.8 (95% CI 6.4 – 178.9) for those that were HC2 positive with a HPV viral load > 181.1 RLU. Conclusion Women initiating ARVs have a high prevalence of abnormal Pap smears and HR-HPV. Our results underscore the need for locally relevant, rigorous screening protocols for the increasing numbers of women accessing ARV therapy so that the benefits of ARVs are not partially offset by an excess risk in cervical cancer.
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Pesticide spraying by farmers has an adverse impact on their health. However, in studies to date examining farmers’ exposure to pesticides, the costs of ill health and their determinants have been based on information provided by farmers themselves. Some doubt has therefore been cast on the reliability of these estimates. In this study, we address this by conducting surveys among two groups of farmers who use pesticides on a regular basis. The first group is made up of farmers who perceive that their ill health is due to exposure to pesticides and have obtained at least some form of treatment (described in this article as the ‘general farmer group’). The second group is composed of farmers whose ill health has been diagnosed by doctors and who have been treated in hospital for exposure to pesticides (described here as the ‘hospitalised farmer group’). Cost comparisons are made between the two groups of farmers. Regression analysis of the determinants of health costs show that the most important determinants of medical costs for both samples are the defensive expenditure, the quantity of pesticides used per acre per month, frequency of pesticide use and number of pesticides used per hour per day. The results have important policy implications.
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This research identifies residential mobility behaviour impacts of residential dissonance in Transit Oriented Developments (TODs) vs. non-TODs in Brisbane, Australia. Based on the characteristics of living environments (density, diversity, connectivity, and accessibility) and the travel preferences of 4545 individuals, respondents in 2009 were classified into one of four categories including: TOD consonants, TOD dissonants, non-TOD dissonants, and non-TOD consonants. Binary logistic regression analyses were employed to identify residential mobility behaviour of groups between 2009 and 2011; controlling for time varying covariates. The findings show that both TOD dissonants and TOD consonants move residences at an equal rate. However, TOD dissonants are more likely to move residences to their preferred non-TOD areas. In contrast, non-TOD dissonants not only moved residences at a lower rate, but their rate of mobility to their preferred TOD neighbourhood is also significantly lower due to costs and other associated factors. The findings suggest that discrete land use policy development is required to integrate non-TOD dissonant and TOD dissonant behaviours to support TOD development in Brisbane.
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We evaluated the Minnesota Multiphasic Personality Inventory-Second Edition (MMPI-2) Response Bias Scale (RBS). Archival data from 83 individuals who were referred for neuropsychological assessment with no formal diagnosis (n = 10), following a known or suspected traumatic brain injury (n = 36), with a psychiatric diagnosis (n = 20), or with a history of both trauma and a psychiatric condition (n = 17) were retrieved. The criteria for malingered neurocognitive dysfunction (MNCD) were applied, and two groups of participants were formed: poor effort (n = 15) and genuine responders (n = 68). Consistent with previous studies, the difference in scores between groups was greatest for the RBS (d = 2.44), followed by two established MMPI-2 validity scales, F (d = 0.25) and K (d = 0.23), and strong significant correlations were found between RBS and F (rs = .48) and RBS and K (r = −.41). When MNCD group membership was predicted using logistic regression, the RBS failed to add incrementally to F. In a separate regression to predict group membership, K added significantly to the RBS. Receiver-operating curve analysis revealed a nonsignificant area under the curve statistic, and at the ideal cutoff in this sample of >12, specificity was moderate (.79), sensitivity was low (.47), and positive and negative predictive power values at a 13% base rate were .25 and .91, respectively. Although the results of this study require replication because of a number of limitations, this study has made an important first attempt to report RBS classification accuracy statistics for predicting poor effort at a range of base rates.
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Objective: To compare access and utilisation of EDs in Queensland public hospitals between people who speak only English at home and those who speak another language at home. Methods: A retrospective analysis of a Queensland statewide hospital ED dataset (ED Information System) from 1 January 2008 to 31 December 2010 was conducted. Access to ED care was measured by the proportion of the state’s population attending EDs. Logistic regression analyses were performed to determine the relationships between ambulance use and language, and between hospital admission and language, both after adjusting for age, sex and triage category. Results: The ED utilisation rate was highest in English only speakers (290 per 1000 population), followed by Arabic speakers (105), and lowest among German speakers (30). Compared with English speakers, there were lower rates of ambulance use in Chinese (odds ratio 0.50, 95% confidence interval, 0.47–0.54), Vietnamese (0.87, 0.79–0.95), Arabic (0.87, 0.78–0.97), Spanish (0.56, 0.50–0.62), Italian (0.88, 0.80–0.96), Hindi (0.61, 0.53–0.70) and German (0.87, 0.79–0.90) speakers. Compared with English speakers, German speakers had higher admission rates (odds ratio 1.17, 95% confidence interval, 1.02–1.34), whereas there were lower admission rates in Chinese (0.90, 0.86–0.99), Arabic (0.76, 0.67–0.85) and Spanish (0.83, 0.75–0.93) speakers. Conclusion: This study showed that there was a significant association between lower utilisation of emergency care and speaking languages other than English at home. Further researches are needed using in-depth methodology to investigate if there are language barriers in accessing emergency care in Queensland.
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Recent literature has argued that environmental efficiency (EE), which is built on the materials balance (MB) principle, is more suitable than other EE measures in situations where the law of mass conversation regulates production processes. In addition, the MB-based EE method is particularly useful in analysing possible trade-offs between cost and environmental performance. Identifying determinants of MB-based EE can provide useful information to decision makers but there are very few empirical investigations into this issue. This article proposes the use of data envelopment analysis and stochastic frontier analysis techniques to analyse variation in MB-based EE. Specifically, the article develops a stochastic nutrient frontier and nutrient inefficiency model to analyse determinants of MB-based EE. The empirical study applies both techniques to investigate MB-based EE of 96 rice farms in South Korea. The size of land, fertiliser consumption intensity, cost allocative efficiency, and the share of owned land out of total land are found to be correlated with MB-based EE. The results confirm the presence of a trade-off between MB-based EE and cost allocative efficiency and this finding, favouring policy interventions to help farms simultaneously achieve cost efficiency and MP-based EE.
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Background: There is a well developed literature on research investigating the relationship between various driving behaviours and road crash involvement. However, this research has predominantly been conducted in developed economies dominated by western types of cultural environments. To date no research has been published that has empirically investigated this relationship within the context of the emerging economies such as Oman. Objective: The present study aims to investigate driving behaviour as indexed in the Driving Behaviour Questionnaire (DBQ) among a group of Omani university students and staff. Methods: A convenience non-probability self- selection sampling approach was utilized with Omani university students and staff. Results: A total of 1003 Omani students (n= 632) and staff (n=371) participated in the survey. Factor analysis of the BDQ revealed four main factors that were errors, speeding violation, lapses and aggressive violation. In the multivariate logistic backward regression analysis, the following factors were identified as significant predictors of being involved in causing at least one crash: driving experience, history of offences and two DBQ components i.e. errors and aggressive violation. Conclusion: This study indicates that errors and aggressive violation of the traffic regulations as well as history of having traffic offences are major risk factors for road traffic crashes among the sample. While previous international research has demonstrated that speeding is a primary cause of crashing, in the current context, the results indicate that an array of factors is associated with crashes. Further research using more rigorous methodology is warranted to inform the development of road safety countermeasures in Oman that improves overall traffic safety culture.