Malaria Prevalence Investigation among Pregnant Women in Relation to Their Social Well Being: A Case Study of Lugbe and Gosa, Abuja, Nigeria
Ngozi Edith Onyemaechi, Yoila David Malann
International Journal of Pathogen Research · pp. 7–15 · Published 18 May 2020
10.9734/ijpr/2020/v4i230107Abstract
Aim: This research aim was to investigate the impact of living conditions (Socio demographic characteristics) of pregnant women on their malarial status. Study Design: In order to achieve the objectives of the study, Cross sectional survey was used. This is because only a subsect of the population was used. Descriptive designs was utilised in the Questionnaire aspect of the study. Place and Duration of Study: The Presidential Malarial initiative PMI/USAID - funded Insectary Laboratory at Nasarawa State University, Keffi/six (6) Months. Methodology: Blood samples were collected from the participating pregnant women by pricking their thumb and the blood droplet was examined using a direct thin and thick blood smear preparation stained with giemsa for the presence of the ring form stages of the parasites in the blood of the individuals in the laboratory. Qualitative data were sourced through Questionnaire administration to 589 pregnant women in Antenatal care clinics (ANC) in the area and their malaria status was also determined. Results: Study results showed a high prevalence rate of malaria in pregnancy (70.5%), the greater number of occurrences being in Lugbe (42.3%) than in Gosa (28.2%). Those living in houses built with wood recorded more positive cases of malaria and are at greater risk of infection (odds = 1.866%). Conclusion: This study has shown an increased rate of malaria infection amongst pregnant women living in wood and mud houses. The result also shows high rate of malaria occurrences due to low living conditions amongst pregnant women domiciled in this area of study. Hence, pregnant women should as a routine be placed on malaria prophylaxis and periodically checked as they can be asymptomatic, only exhibiting symptoms when its already late.
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