Uncovering hidden patterns: use of infant feeding profiles in the first 6 months postpartum to inform the effectiveness of breastfeeding promotion programs
Year: 2026
Type: article
Abstract: Introduction: Longitudinal trends in breastfeeding (BF) are often overlooked in favor of binary or time-to-cessation measures. Characterizing these trends can inform promotion of sustained BF practices. We identified distinct BF profiles among participants of a maternal and child health program. Methods: The Healthy Future program consisted of community health workers delivering a BF curriculum to mothers through monthly home visits. The program was evaluated in rural Sichuan, China with a cluster-randomized controlled trial (assigned to program versus not). We clustered 6-month postpartum trends (n = 949) of maternal-reported infant feeding using dynamic time warping. For each month, participants were categorized as either exclusive breastfeeding (EBF), mixed feeding (MF, feeding breastmilk plus other foods or liquids), or not breastfeeding (NBF). After identifying clusters, we regressed BF profiles on intervention assignment using adjusted multinomial logistic regression. Results: Cluster analysis revealed seven profiles: always EBF, always MF, never breastfed, EBF until the 5th month, MF until the 5th month, mostly EBF, and NBF from the 3rd month. The intervention was associated with improved odds of always EBF (ROR = 2.61, 95% CI 1.25, 5.42), MF until the 5th month (ROR = 2.52, 95% CI 1.18, 5.39), and NBF from the 3rd month (ROR = 2.82, 95% CI 1.16, 6.87) compared to being never breastfed. Mothers in the never breastfed cluster had the lowest age, education, BF knowledge and attitudes, and decision-making power. Discussion: Cluster analyses found the intervention significantly improved EBF, particularly in mothers characterized by higher baseline educational attainment and BF knowledge. Targeted efforts are needed to help mothers initiate EBF from birth and continue EBF through month 6.
DOI: 10.17615/hyfh-2y53
Institution: University of North Carolina at Chapel Hill
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: Deanship of Scientific Research, King Khalid University, Health Commission of Guizhou Province, Cancer Research UK, Indian Council of Medical Research, Deutsche Forschungsgemeinschaft, Agence Nationale de la Recherche, National Natural Science Foundation of China, Bundesministerium für Bildung und Forschung, Bundesministerium für Gesundheit, Ministero della Salute, Narodowe Centrum Nauki, Tohoku University, University of Delhi, Rheinische Friedrich-Wilhelms-Universität Bonn, Jiangsu Provincial Key Laboratory for Interventional Medical Devices, YangZhou Science and Technology Bureau, Consortium of International Agricultural Research Centers, Gdansk University of Physical Education and Sport, Universität Greifswald, Wu Jieping Medical Foundation, Canadian Institutes of Health Research, Australian Centre for International Agricultural Research, Japan Society for the Promotion of Science, National Key Research and Development Program of China, H2020 European Research Council
OpenAlex ID: W7164651471