Evidence map›Paper›PMID 28302093›Full record

ArticleBMC public health2017

Determination of the predictive factors of long-lasting insecticide-treated net ownership and utilisation in the Bamenda Health District of Cameroon.

Eric B Fokam, Germaine F Kindzeka, Leonard Ngimuh, Kevin T J Dzi, Samuel Wanji

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
4.0field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 58 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Eric B FokamDepartment of Zoology and Animal Physiology, University of Buea, PO Box 63, Buea, Cameroon.
Germaine F KindzekaEpidemiology and Control of Infectious Diseases, Department of Microbiology and Parasitology, University of Buea, PO Box 63, Buea, Cameroon.
Leonard NgimuhEpidemiology and Control of Infectious Diseases, Department of Microbiology and Parasitology, University of Buea, PO Box 63, Buea, Cameroon.
Kevin T J DziEpidemiology and Control of Infectious Diseases, Department of Microbiology and Parasitology, University of Buea, PO Box 63, Buea, Cameroon.
Samuel WanjiEpidemiology and Control of Infectious Diseases, Department of Microbiology and Parasitology, University of Buea, PO Box 63, Buea, Cameroon. swanji@yahoo.fr.
University of Buea · CM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalaria is a serious health concern in Africa. In Cameroon, an endemic country where malaria remains a major public health problem, several control measures have been put in place among which the use of insecticide-treated bednets (LLINs/ITNs) is considered one of the core vector control strategies. However, the greatest challenges include ownership and utilisation by individuals and households. Factors such as age, marital status, gender, education and occupation of the household head, household size, knowledge of bednets, socioeconomic status, and environmental factors have been suggested to have an impact on bednet ownership and utilisation in different settings. The present study sought to determine bednet ownership and utilisation rates and to assess the impact of predictive factors on bednet ownership and use in the Bamenda Health District (BHD) of Cameroon.

methodsA cross-sectional study involving 384 households was conducted in six health areas in the BHD. A structured and semi-structured questionnaire was used to collect data on demographic and household characteristics as well as information on their bednet ownership and utilisation. Descriptive statistics, bivariate and multivariate logistic regression analysis were performed.

resultsFrequency of bednet ownership was relatively high (63.5%) with LLINs being most abundant (91.9%); the majority of households (87.7%) obtained their bednets during the 2011 free distribution campaign. Utilisation was relatively high (69.3%), with negligence (29.3%) and heat discomfort (26.7%) accounting most for non-usage of bednets. Children less than 5 years (63%) and pregnant women (60%) most often used these nets. Households headed by a married couple, those with older household heads, household with smaller size (5-12 persons), and knowledge of bednets (good knowledge) had positive impacts on bednet ownership (p < 0.05). The gender of the household head (males), their educational level, environmental conditions (presence of suitable mosquito breeding sites), bednet number in households (greater number of bednets) and the prioritised groups (children < 5 and pregnant women) had positive impacts on bednet utilisation in households (p < 0.05). There was a negative association between bednet ownership and utilisation by households as bednet ownership was high and utilisation of these nets was low. Marital status and age of household head, household size, and knowledge of bednets had impacts on bednet ownership while gender and educational level of the household head, environmental suitability, the number of bednets and the two prioritised groups had an impact on bednet usage.

conclusionThese factors may be relevant for policy makers and in decision making for the intensification of campaign strategies to ensure more effective subsequent distribution campaigns in the BHD and beyond.

Indexed as

Family CharacteristicsAdultCameroonChild, PreschoolCross-Sectional StudiesEducational StatusEnvironmentFemaleHealth Knowledge, Attitudes, PracticeHumansInsecticide-Treated BednetsLogistic ModelsMalariaMaleMarital StatusMiddle Aged

Identifiers

PMID28302093
PMCPMC5356302
OpenAlexW2596552350

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.