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. 2016 Aug;16(3):e335-40.
doi: 10.18295/squmj.2016.16.03.012. Epub 2016 Aug 19.

Public Knowledge of Oral Cancer and Modelling of Demographic Background Factors Affecting this Knowledge in Khartoum State, Sudan

Hamdi A Al-Hakimi  1 , Abdulqaher E Othman  2 , Omima G Mohamed  3 , Abdulaal M Saied  2 , Waled A Ahmed  1
Affiliations

Public Knowledge of Oral Cancer and Modelling of Demographic Background Factors Affecting this Knowledge in Khartoum State, Sudan

Hamdi A Al-Hakimi et al. Sultan Qaboos Univ Med J. 2016 Aug.

Abstract

Objectives: Knowledge of oral cancer affects early detection and diagnosis of this disease. This study aimed to assess the current level of public knowledge of oral cancer in Khartoum State, Sudan, and examine how demographic background factors affect this knowledge.

Methods: This cross-sectional study involved 501 participants recruited by systematic random sampling from the outpatient records of three major hospitals in Khartoum State between November 2012 and February 2013. A pretested structured questionnaire was designed to measure knowledge levels. A logistic regression model was utilised with demographic background variables as independent variables and knowledge of oral cancer as the dependent variable. A path analysis was conducted to build a structural model.

Results: Of the 501 participants, 42.5% had no knowledge of oral cancer, while 5.4%, 39.9% and 12.2% had low, moderate and high knowledge levels, respectively. Logistic regression modelling showed that age, place of residence and education levels were significantly associated with knowledge levels (P = 0.009, 0.017 and <0.001, respectively). According to the structural model, age and place of residence had a prominent direct effect on knowledge, while age and residence also had a prominent indirect effect mediated through education levels.

Conclusion: Education levels had the most prominent positive effect on knowledge of oral cancer among outpatients at major hospitals in Khartoum State. Moreover, education levels were found to mediate the effect of other background variables.

Keywords: Knowledge; Logistic Regression; Oral Cancer; Patient-Specific Modeling; Statistical Model; Sudan.

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Figures

Figure 1:
Figure 1:
Path analysis structural model of the effect of background variables on knowledge of oral cancer among outpatients at three major hospitals in Khartoum State, Sudan (N = 501). df = degrees of freedom; RMS = root-mean-square.
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