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  • 1. Ossai, Peter Awareness, Accessibility And Use Of Malaria Control Interventions Among At-Risk Groups In Lagos Metropolis, Nigeria

    PHD, Kent State University, 2014, College of Public Health

    Abstract With just a year remaining to the Millennium Development Goals (MDGs) deadline, there is limited evidence for and adequate level of awareness/use of malaria intervention strategies and by extension, decreases in malaria-related mortality and morbidity. This is a cross-sectional study on awareness and use of malaria control interventions based on data collected from a household survey from two of the 20 local government areas (LGAs) of Lagos State, Nigeria – Alimosho and Kosofe where a malaria control program of Roll Back Malaria (RBM) is being implemented. The sample included pregnant women (n = 250) and mothers of children under five years old (n = 233) that were interviewed using interviewer-administered, semi-structured questionnaires in a household survey. Questionnaires developed by the research staff of the Nigerian Institute for Medical Research probed respondents' demographic characteristics; knowledge and compliance of policy guidelines on the awareness and use of malaria intervention strategies. The study was implemented over a 6-month period from February to August 2014. This study used both linear and logistic regression analysis. Linear regression was used to predict the Compliance Index as a function of the independent variables of Age, Marital Status, Maternal Status, Religion, Education and Local Government Area of residence, while logistic regression was used to predict alignment into high/moderate or low knowledge of malaria categories also as a function of Age, Marital Status, Maternal Status, Religion, Education and Local Government Area of residence. Results of the linear regression showed that the overall model of the six independent variables was able to significantly predict the compliance index, R2 = .163, F(6,409) = 13.28, p <.001. Age, Education and LGA were significant predictors. Results of the logistic regression showed the Exp(B) of two predictors, LGA and Maternal Status, as statistically reliable in distinguishing b (open full item for complete abstract)

    Committee: Sonia Alemagno Ph.D (Advisor); Jonathan VanGeest Ph.D (Committee Chair); James Mark Ph.D (Committee Member); Bhatta Madhav Ph.D (Committee Member); John Graham Ph.D (Committee Member) Subjects: Public Health