Insecticide Treated Net Ownership, Utilization and Knowledge of Malaria in Children Residing in Batoke-Limbe, Mount Cameroon Area: Effect on Malariometric and Haematological Indices

Abstract

Background: Insecticide treated nets (ITNs) are the most widely used interventions for malaria control in Africa. The aim of this study was to assess the ownership and utilization of ITNs and the knowledge of malaria and their effects on malariometric and haematological indices in children living in the Mount Cameroon area.Methods: A community-based cross-sectional study involving a total of 405 children aged between 6 months and 14 years living in Batoke-Limbe was carried out between July and October 2017. A semi-structured questionnaire was used to document demographic status, knowledge on malaria and ITN ownership and usage. Venous blood sample was collected from each child to determine the prevalence and intensity of malaria parasitaemia by Giemsa-stained microscopy and full blood count by auto haematology analysis to obtain white blood cell (WBC) and red blood cell (RBC) counts, haemoglobin (Hb) level, haematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH) and mean corpuscular haemoglobin concentration (MCHC). A multilinear regression model was used to determine the relationship between haematological parameter as dependent variable and the independent variables. Results: The overall prevalence of malaria parasitaemia (MP), anaemia, knowledge about malaria, ITN ownership, usage and effective usage was 46.7%, 54.7%, 40.7%, 78.8%, 50.9% and 29.9% respectively. The prevalence of MP was significantly higher (P<0.001) in children who ineffectively utilized ITNs (54.9%) than effective users (27.3%). Having knowledge of malaria, negatively correlated with WBC counts (P = 0.005) but positively correlated with Hb levels (P < 0.001), RBC counts (P < 0.001), Hct (P < 0.001), MCV (P < 0.001) and MCH (P < 0.001). ITN use positively correlated with WBC counts (P = 0.005) but negatively with Hb levels (P = 0.004), RBC counts (P = 0.006), and MCH (P < 0.001). Meanwhile, MP negatively correlated with Hb levels (P = 0.004), RBC counts (P = 0.01), Hct (P = 0.04) and MCHC (P = 0.015). Conclusion: There is need for more sensitization on the benefits of using the ITNs to meet up with the intended and expected impact of the free distribution of ITNs.

Ownership and Utilisation of Long-Lasting Insecticidal Nets in Tiko Health District, Southwest Region, Cameroon: A Cross-Sectional Study

“…The proportion of household heads (24.9%) and residents (1025 (49.1%)) who slept under LLINs the previous night was small compared to ownership. Our findings were lower compared to the 50.9% among children 0–5 years in Batoke [ 36 ] and 94.1% in Fako Division, all in the Southwest Region [ 23 ]. They were also low compared to results obtained elsewhere in Cameroon such as 58.3% in rural and urban Buea [ 26 ], 69.3% in the Bamenda Health District [ 2 ], 69.7% in the Buea Health District [ 16 ], and 77.8% in Mezam Division [ 4 ] as well as out of Cameroon: 52.3% in Ethiopia [ 40 ], 75% among women of childbearing age in Nigeria [ 39 ], and 87.6% in Rwanda [ 38 ].…”

“…The ownership frequency of at least one LLIN per household in this study is higher than the 47–78.8% in Fako Division [ 16 , 23 , 26 , 36 ], the 67.1% in 2013 and 69.7% in 2017 rates reported in the Southwest Region [ 18 ], and the 59.7–73% elsewhere in Cameroon [ 2 , 11 , 24 ] and similar to 81.3% reported in Hohoe (Ghana) [ 37 ], 82.5% reported in Tiko (Cameroon) [ 23 ], and 89.9% in Mezam (Cameroon) [ 4 ]. The 89% ownership of at least one LLIN in our study was higher than the 41–84.1% reported elsewhere in and out of Africa [ 34 , 38 – 45 ] and less than the 93.5% rate reported in Madagascar [ 46 ], the 98.8% in Uganda [ 47 ], and the 99.7% in Northeast Myanmar [ 48 ].…”

Surveys on Familial and Individual Knowledge, Attitudes and Practices (KAP) on Mosquitoes and Malaria Vector Control in Lobito (Angola)

“…A great lot of KAP surveys were implemented in Ethiopia [11][12][13][14][15][16], Tanzania [17][18][19][20], Sudan [21], Swaziland [22,23], Nigeria [24][25][26], Burkina Faso [27], Cameroon [28][29][30], Uganda [31][32][33] among several other.…”