Pregnancies, abortions, and pregnancy intentions: a protocol for modeling and reporting global, regional and country estimates.
Background: Estimates of pregnancies, abortions and pregnancy intentions can help assess how effectively women and couples are able to fulfil their childbearing aspirations. Abortion incidence estimates are also a necessary foundation for research on the safety of abortions performed and the consequ...
| Published in: | Reproductive Health Vol. 16; no. 1 |
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| Main Authors: | , , , , , , |
| Format: | equations & formulas protocol tables/charts Journal Article |
| Published: |
BioMed Central
3/20/2019
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=135440225&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 135440225 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17424755 1D0Q jtl: Reproductive Health issn: 17424755 maglogo: N pubinfo: dt: 3/20/2019 vid: 16 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 135440225 135440225 135440225 10.1186/s12978-019-0682-0 135440225 ppct: 1 formats: tig: atl: Pregnancies, abortions, and pregnancy intentions: a protocol for modeling and reporting global, regional and country estimates. aug: au: Bearak, Jonathan Marc Popinchalk, Anna Sedgh, Gilda Ganatra, Bela Moller, Ann-Beth Tunçalp, Özge Alkema, Leontine affil: Guttmacher Institute, 125 Maiden Ln, 10038, New York, NY, USA sug: subj: Fertilization Pregnancy, Unplanned Attitude to Pregnancy Trends Abortion, Induced Trends Models, Statistical Pregnancy Female Childbirth Incidence Uncertainty Female ab: Background: Estimates of pregnancies, abortions and pregnancy intentions can help assess how effectively women and couples are able to fulfil their childbearing aspirations. Abortion incidence estimates are also a necessary foundation for research on the safety of abortions performed and the consequences of unsafe abortion. Furthermore, periodic estimates of these indicators are needed to help inform policy and programmes. Methods: We will develop a Bayesian hierarchical times series model which estimates levels and trends in pregnancy rates, abortion rates, and percentages of pregnancies and births unintended for each five-year period between 1990 and 2019. The model will be informed by data on abortion incidence and the percentage of births or pregnancies that were unintended. We will develop a data classification process to be applied to all available data. Model-based estimates and associated uncertainty will take account of data sparsity and quality. Our proposed approach will advance previous work in two key ways. First, we will estimate pregnancy and abortion rates simultaneously, and model the propensity to abort an unintended pregnancy, as opposed to modeling abortion rates directly as in prior work. Secondly, we will produce estimates that are reproducible at the country level by publishing the data inputs, data classification processes and source code. Discussion: This protocol will form the basis for updated global, regional and national estimates of intended and unintended pregnancy rates, abortion rates, and the percent of unintended pregnancies ending in abortion, from 1990 to 2019. pubtype: Academic Journal doctype: equations & formulas protocol tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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