Evidence map›Paper›PMID 38184552›Full record

ArticleBMC public health2024

Demographic and socio-economic factors affecting bed net ownership, usage, and malaria transmission among adult patients seeking healthcare in two Ghanaian urban cities.

Ellis Kobina Paintsil, Enoch Boadi, Anthony Dwamena, Bless Hayford Addo, Agyei Kumi, Kwasi Obiri-Danso, Linda Aurelia Ofori

Open access · goldAbstract readCase Reports
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.2field-weighted citation impact, top 14% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
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

7 authors at 3 institutions in 1 country.

Ellis Kobina PaintsilKumasi Centre for Collaborative Research in Tropical Medicine (KCCR), Kumasi, Ghana. paintsil@kccr.de.
Enoch BoadiDepartment of Molecular Medicine, School of Medical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Anthony DwamenaDepartment of Medical Diagnostics, Faculty of Allied Health Sciences, School of Medical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Bless Hayford AddoBremang Seventh-Day Adventist Hospital, Suame Municipal, Ghana.
Agyei KumiKumasi Centre for Collaborative Research in Tropical Medicine (KCCR), Kumasi, Ghana.
Kwasi Obiri-DansoDepartment of Theoretical and Applied Biology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Linda Aurelia OforiDepartment of Theoretical and Applied Biology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Kwame Nkrumah University of Science and Technology · GHKumasi Centre for Collaborative Research in Tropical Medicine · GHSunyani Technical University · GH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe most cost-effective malaria prevention and control strategy is the use of a bed net. However, several factors affect the ownership and usage of bed nets among the adult population. Hence, this study aimed to examine socio-demographic factors affecting bed net ownership, usage and malaria transmission among adult patients seeking healthcare in two Ghanaian urban cities.

methodsThis hospital-based cross-sectional study was conducted, between January and September 2021, at Bremang Seventh-Day Adventist Hospital, Suame Municipal, Ashanti Region and Sunyani Municipal Hospital, Sunyani, Bono Region, Ghana. Structured questionnaires were administered to a total of 550 participants to ascertain their ownership and usage of the bed nets. Afterwards, finger prick blood samples were collected for malaria microscopy. Crude and adjusted prevalence ratios (PR) and their respective 95% CIs were calculated, using Poisson regression with robust standard errors, to show associated variables in bivariate and multivariate analyses respectively. R software (version 4.1.1) was used to perform all statistical analyses.

resultsAbout 53.3% (n = 293) of participants owned at least one-bed net but only 21.5% (n = 118) slept under it the previous night. Those married were 2.0 (95% CI: 1.6 - 2.5) and 2.4 (95% CI: 1.6 - 3.5) times more likely to own and use a bed net respectively than those who never married. Also, pregnant women were 1.3 (95% CI: 1.1 - 1.6) and 1.8 (95% CI: 1.3 - 2.5) times more likely to own and use a bed net respectively than non-pregnant. Even though income levels were not associated with bed net ownership and usage, students were 0.4 (95% CI: 0.2 - 0.6) and 0.2 (95% CI: 0.1 - 0.5) times less likely to own and use bed net respectively compared to formally employed persons. The overall malaria prevalence rate was 7.8%. Malaria-negative patients were 1.6 (95% CI: 1.2 - 2.0) and 2.4 (95% CI: 1.4 - 4.1) times more likely to own and use bed nets respectively than malaria positive. Patients with tertiary education recorded the lowest malaria prevalence (3.5%, n = 4). None of those with a monthly income > $300 recorded a case of malaria. On the contrary, majority 83%, n/N = 25/30) of the malaria-positive patients earned ≤ $150.

conclusionThe National Malaria Control Program should conduct comprehensive mapping of all urban population segments before launching mass bed net distribution campaigns, taking into account demographic and socioeconomic factors to enhance bed net utilization and reduce malaria prevalence.

Indexed as

MalariaOwnershipAdultCitiesCross-Sectional StudiesDelivery of Health CareDemographyEconomic FactorsFemaleGhanaHumansPregnancyAdultBed netGhanaMalariaSocio-economicUrban

Identifiers

PMID38184552
PMCPMC10770894
OpenAlexW4390638618

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.