Evidence map›Paper›PMID 39702753›Full record

ArticleContraception and reproductive medicine2024

Intention to use modern contraceptives among current nonusers of reproductive age in Uganda.

Godfrey Tumwizere, Richard Nsenga, Patricia Ndugga, Betty Kwagala

Abstract read
In one paragraph

Article in Contraception and reproductive medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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

4 authors.

Godfrey TumwizereDepartment of Community Health & Behavioural Sciences, School of Public Health, Makerere University, Kampala, Uganda. godfreytumwizere@gmail.com.
Richard NsengaDepartment of Population Studies, School of Population and Planning, Makerere University, Kampala, Uganda.
Patricia NduggaDepartment of Population Studies, School of Population and Planning, Makerere University, Kampala, Uganda.
Betty KwagalaDepartment of Population Studies, School of Population and Planning, Makerere University, Kampala, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWomen's intention to use contraceptive methods is critical for better visualization of future needs and for making it more likely to translate into actual use. This study sought to examine the determinants of intention to use modern contraceptives among current non-users of reproductive age in Uganda.

methodsThe study used secondary data from the 2016 Uganda Demographic and Health Survey (UDHS) dataset. The sample size consisted of 13,088 women aged 15-49 who were not using contraception. The dependent variable was the intention to use contraceptives. STATA version 17 was used for data analysis. A binary logistic regression model was used to identify the predictors of intention to use contraceptives at the 5% level of significance.

resultsFindings indicated that six in ten (60.2%) non-users of contraceptives had an intention to use them in the future. The odds of intention to use contraceptives were higher among women with secondary education (AOR 1.482, CI = 1.168-1.880), women who desired 3-4 children (AOR = 1.343, CI = 1.135-1.590), women with 3-4 living children (AOR = 1.817, CI = 1.391-2.373), women who have ever used a contraceptive method (AOR = 2.457, CI = 1.686-3.579), and women whose last pregnancy was unwanted (AOR = 1.720, CI = 1.231-2.405). On the other hand, the odds of intending to use contraceptives were lower among women aged 35-44 years (AOR = 0.242, CI = 0.143-0.284) and 45-49 years (AOR = 0.028, CI = 0.017-0.044), Muslim women (AOR = 0.676, CI = 0.559-0.817), Pentecostal women (AOR = 0.708, CI = 0.598-0.837), and formerly married women (AOR = 0.672, CI = 0.517-0.875).

conclusionsThe study found that the intention to use contraceptives among Ugandan women not currently using contraception was associated with having secondary education, a preference for having 3-4 children, having 3-4 living children, prior contraceptive use, and experiencing an unwanted pregnancy. The study recommends enhanced access to and completion of at least secondary education for girls. The study further recommends that policymakers and program implementers sensitise communities about the benefits of smaller family sizes through community dialogues highlighting the health, economic, and educational advantages for families and communities.

Indexed as

ContraceptivesIntentionUganda

Identifiers

PMID39702753
PMCPMC11657307

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LicenceCC BY-NC-ND
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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.