Evidence map›Paper›PMID 32993596›Full record

ArticleBMC public health2020

Distribution and predictors associated with the use of breast cancer screening services among women in 14 low-resource countries.

Rashidul Alam Mahumud, Jeff Gow, Syed Afroz Keramat, Sonja March, Jeff Dunn, Khorshed Alam, Andre M N Renzaho

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

12 citing papers in PubMed, 19 citations in OpenAlex.

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  10. A consensus approach: Understanding the support needs of women in Newport West, Wales, to participate in breast screening.Health expectations : an international journal of public participation in health care and health policy · 2023
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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

7 authors at 4 institutions in 3 countries.

Rashidul Alam MahumudSchool of Social Sciences, Western Sydney University, Penrith, New South Wales, 2751, Australia. rashed.mahumud@gmail.com.ORCID http://orcid.org/0000-0001-9788-1868
Jeff GowHealth Economics and Policy Research, School of Commerce, Centre for Health Research, University of Southern Queensland, Toowoomba, Queensland, 4350, Australia.
Syed Afroz KeramatDepartment of Economics, American International University-Bangladesh, Dhaka, 1212, Bangladesh.
Sonja MarchSchool of Psychology and Counselling, University of Southern Queensland, Toowoomba, Queensland, 4300, Australia.
Jeff DunnHealth Economics and Policy Research, School of Commerce, Centre for Health Research, University of Southern Queensland, Toowoomba, Queensland, 4350, Australia.
Khorshed AlamHealth Economics and Policy Research, School of Commerce, Centre for Health Research, University of Southern Queensland, Toowoomba, Queensland, 4350, Australia.
Andre M N RenzahoSchool of Social Sciences, Western Sydney University, Penrith, New South Wales, 2751, Australia.
University of Southern Queensland · AUTranslational Research Institute · AUAmerican International University-Bangladesh · BDProstate Cancer Foundation of Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer is one of the leading public health problem globally, especially in low-resource countries (LRCs). Breast cancer screening (BCS) services are an effective strategy for early determining of breast cancer. Hence, it is imperative to understand the utilisation of BCS services and their correlated predictors in LRCs. This study aims to determine the distribution of predictors that significantly influence the utilisation of BCS services among women in LRCs.

methodsThe present study used data on 140,974 women aged 40 years or over from 14 LRCs. The data came from country Demographic and Health Surveys (DHS) between 2008 and 2016. Multivariate logistic regression analysis was employed to investigate the significant predictors that influence the use of BCS services.

resultsThe utilisation of BCS services was 15.41%, varying from 81.10% (95% CI: 76.85-84.73%) in one European country, to 18.61% (95% CI: 18.16 to 19.06%) in Asian countries, 14.30% (95% CI: 13.67-14.96%) in American countries, and 14.29% (95% CI: 13.87-14.74%). Factors that were significantly associated to increase the use of BCS services include a higher level of education (OR = 2.48), advanced age at first birth (> 25 years) (OR = 1.65), female-headed households (OR = 1.65), access to mass media communication (OR = 1.84), health insurance coverage (OR = 1.09), urban residence (OR = 1.20) and highest socio-economic status (OR = 2.01). However, obese women shown a significantly 11% (OR = 0.89) lower use of BSC services compared to health weight women.

conclusionThe utilisation of BCS services is low in many LRCs. The findings of this study will assist policymakers in identifying the factors that influence the use of BCS services. To increase the national BCS rate, more attention should be essential to under-represented clusters; in particular women who have a poor socioeconomic clusters, live in a rural community, have limited access to mass media communication, and are have a low level educational background. These factors highlight the necessity for a new country-specific emphasis of promotional campaigns, health education, and policy targeting these underrepresented groups in LRCs.

Indexed as

AdultAgedAsiaBreast NeoplasmsEarly Detection of CancerEuropeFemaleHealth EducationHealth Services AccessibilityHumansMiddle AgedUnited StatesWomen's HealthWomen's Health ServicesBreast cancer screening servicesDeterminantsLow-resource countriesReproductive women

Identifiers

PMID32993596
PMCPMC7526143
OpenAlexW3091157843

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.