Evidence map›Paper›PMID 24708708›Full record

ArticleBMC public health2014

Towards making efficient use of household resources for appropriate prevention of malaria: investigating households' ownership, use and expenditures on ITNs and other preventive tools in Southeast Nigeria.

Obinna Onwujekwe, Enyi Etiaba, Nkoli Uguru, Benjamin Uzochukwu, Alex Adjagba

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Article in BMC public health, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Obinna Onwujekwe
Enyi EtiabaDepartment of Pharmacology and Therapeutics, Health Policy Research Group, College of Medicine, University of Nigeria Enugu-Campus, Enugu, Nigeria. enyietiaba@yahoo.co.uk.
Nkoli Uguru
Benjamin Uzochukwu
Alex Adjagba

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany households own, use and spend money on many malaria preventive tools, some of which are inappropriate and ineffective in preventing malaria. This is despite the promotion of use of effective preventive methods such as Insecticide treated nets (ITNs) and indoor residual house spraying (IRHS). The use of these ineffective methods imposes some economic burden on households with no resultant reduction in the risk of developing malaria. Hence, global and national targets in use of various effective malaria preventive toools are yet to be achieved in Nigeria. This paper presents new evidence on the differential use and expenditures on effective and non-effective malaria preventive methods in Nigeria.

methodsSemi-structured interviewer administered pre-tested questionnaire were used to collect data from 500 households from two communities in Enugu state, Nigeria. The two study communities were selected randomly while the households were selected systematically. Information was collected on demography, malaria status of children under 5 within the past month, types of malaria preventive tools used by households and how much was spent on these, the per capita household food expenditure and assets ownership of respondents to determine their socio-economic status.

resultsThere was high level of ownership of ITNs (73%) and utilization (71.2%), with 40% utilization by children under 5. There were also appreciable high levels of use of other malaria preventive tools such as window and door nets, indoor spray, aerosol spray and cleaning the environment. No significant inequity was found in ownership and utilization of ITNs and in use of other preventive methods across socioeconomic groups. However, households spent a lot of money on other preventive tools and average expenditures were between N0.83-N172 ($0.005-$1.2) The richest households spent the most on window and door nets (P = 0.04).

conclusionHigh levels of use and expenditure on ITNs and other malaria preventive tools exist. A programmatic challenge will involve designing ways and means of converting some of the inefficient and inappropriate expenditures on many ineffective malaria preventive tools to proven cost-effective methods such as ITNs and IRHS. This will help to achieve universal coverage with malaria preventive tools.

Indexed as

Health ExpendituresAdultChild, PreschoolFemaleHousehold ArticlesHumansInsecticide-Treated BednetsInterviews as TopicMalariaMaleNigeriaOwnershipSocioeconomic FactorsSurveys and Questionnaires

Identifiers

PMID24708708
PMCPMC4022444

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.