» Articles » PMID: 23906958

Prediction of Initiation and Cessation of Breastfeeding from Late Pregnancy to 16 Weeks: the Feeding Your Baby (FYB) Cohort Study

Overview
Journal BMJ Open
Specialty General Medicine
Date 2013 Aug 3
PMID 23906958
Citations 12
Authors
Affiliations
Soon will be listed here.
Abstract

Objective: To derive prediction models for both initiation and cessation of breastfeeding using demographic, psychological and obstetric variables.

Design: A prospective cohort study.

Setting: Women delivering at Ninewells Hospital, Dundee, UK.

Data Sources: Demographic data and psychological measures were obtained during pregnancy by questionnaire. Birth details, feeding method at birth and at hospital discharge were obtained from the Ninewells hospital database, Dundee, UK. Breastfeeding women were followed up by text messages every 2 weeks until 16 weeks or until breastfeeding was discontinued to ascertain feeding method and feeding intentions.

Participants: Pregnant women over 30 weeks gestation aged 16 years and above, living in Dundee, booked to deliver at Ninewells Hospital, Dundee, and able to speak English.

Main Outcome Measure: Initiation and cessation of breastfeeding.

Results: From the total cohort of women at delivery (n=344) 68% (95% CI 63% to 73%) of women had started breastfeeding at discharge. Significant predictors of initiating breastfeeding were older age, parity, greater intention to breastfeed from a Theory of Planned Behaviour (TPB)-based questionnaire, higher Iowa Infant Feeding Assessment Scale (IIFAS) score as well as living with a husband or partner. For the final model, the AUROC was 0.967. For those who initiated breastfeeding (n=233), the strongest predictors of stopping were low intention to breastfeed from TPB, low IIFAS score and non-managerial/professional occupations.

Conclusions: The findings from this study will be used to inform the protocol for an intervention study to encourage and support prolonged breastfeeding as intentions appear to be a key intervention focus for initiation. The predictive models could be used to identify women at high risk of not initiating and also women at high risk of stopping for interventions to improve the longevity of breastfeeding.

Citing Articles

Psychological factors affecting breastfeeding during the perinatal period in the UK: an observational longitudinal study.

Amiel Castro R, Ehlert U, Glover V, OConnor T BMC Public Health. 2025; 25(1):946.

PMID: 40065255 PMC: 11895161. DOI: 10.1186/s12889-025-22020-y.


Factors associated with intention to breastfeed in Vietnamese mothers: A cross-sectional study.

Doan D, Binns C, Lee A, Zhao Y, Pham M, Dinh H PLoS One. 2023; 18(12):e0279691.

PMID: 38085730 PMC: 10715656. DOI: 10.1371/journal.pone.0279691.


Association of Maternal Preferred Language with Breastfeeding Attitudes, Intentions, and Knowledge.

Ferguson L, Chervonsky A, Fogel J, Jacobs A J Mother Child. 2023; 27(1):209-216.

PMID: 37991976 PMC: 10664786. DOI: 10.34763/jmotherandchild.20232701.d-23-00026.


Exploring the reasons why mothers do not breastfeed, to inform and enable better support.

Roberts D, Jackson L, Davie P, Zhao C, Harrold J, Fallon V Front Glob Womens Health. 2023; 4:1148719.

PMID: 37122597 PMC: 10132506. DOI: 10.3389/fgwh.2023.1148719.


Perinatal support for breastfeeding using mHealth: A mixed methods feasibility study of the My Baby Now app.

Laws R, Cheng H, Rossiter C, Kuswara K, Markides B, Size D Matern Child Nutr. 2023; 19(2):e13482.

PMID: 36725007 PMC: 10019053. DOI: 10.1111/mcn.13482.


References
1.
Wambach K . Breastfeeding intention and outcome: a test of the theory of planned behavior. Res Nurs Health. 1997; 20(1):51-9. DOI: 10.1002/(sici)1098-240x(199702)20:1<51::aid-nur6>3.0.co;2-t. View

2.
Dungy C, McInnes R, Tappin D, Wallis A, Oprescu F . Infant feeding attitudes and knowledge among socioeconomically disadvantaged women in Glasgow. Matern Child Health J. 2007; 12(3):313-22. DOI: 10.1007/s10995-007-0253-9. View

3.
Pencina M, DAgostino Sr R, DAgostino Jr R, Vasan R . Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2007; 27(2):157-72. DOI: 10.1002/sim.2929. View

4.
Whitford H, Donnan P, Symon A, Kellett G, Monteith-Hodge E, Rauchhaus P . Evaluating the reliability, validity, acceptability, and practicality of SMS text messaging as a tool to collect research data: results from the Feeding Your Baby project. J Am Med Inform Assoc. 2012; 19(5):744-9. PMC: 3422836. DOI: 10.1136/amiajnl-2011-000785. View

5.
Campbell N, Murray E, Darbyshire J, Emery J, Farmer A, Griffiths F . Designing and evaluating complex interventions to improve health care. BMJ. 2007; 334(7591):455-9. PMC: 1808182. DOI: 10.1136/bmj.39108.379965.BE. View