Defining Low Milk Supply: A Data-Driven Diagnostic Framework and Risk Factor Analysis for Breastfeeding Women

<b>Background:</b> Current low milk supply (LMS) definitions use subjective maternal perceptions or arbitrary thresholds for 24 h milk production (MP), potentially misclassifying cases. This study aimed to re-evaluate the definition of LMS using data-driven approaches and investigate associated maternal risk factors. <b>Methods:</b> Lactating mothers 4-26 weeks postpartum (n = 460) provided demographic, obstetric, and infant data and measured 24 h MP and infant milk intake using the test-weighing method. Infant growth was calculated as their weight-for-age z-score. Latent profile analysis, receiver operating characteristic curve analysis, and multinomial logistic regression were used for classification, diagnostic evaluation, and risk factor assessment for LMS. <b>Results:</b> Four milk supply classes emerged: Class 1 with adequate MP, infant intake and infant growth (n = 254); Class 2 with high MP exceeding infant demand and adequate growth (n = 30); Class 3 with slow infant growth despite moderate MP (n = 120); and Class 4 with extremely low MP and high formula intake (n = 56). Classes 1 and 2 were grouped as the normal milk supply group (61.7%), while Classes 3 and 4 formed the LMS group (38.3%). New thresholds were identified for 24 h MP (708 mL/24 h, area under the curve (AUC) = 0.92) and infant breast milk intake (694 mL/24 h, AUC = 0.94) with high diagnostic accuracy. Moreover, practical alternative thresholds for infant average daily weight gain (26 g, AUC = 0.89), formula intake (122 mL/24 h, AUC = 0.89) and formula-to-growth ratio (4 mL/g, AUC = 0.94) were established for the identification of LMS. Minimal breast growth during pregnancy (Odds ratio (OR) = 4.6, 95% confidence interval (CI): 2.3-9.6), advanced maternal age (OR = 2.1, 95% CI: 1.0-4.5), and gestational diabetes mellitus (OR = 2.1, 95% CI: 1.1-4.0) were significant risk factors related to the LMS subgroups. Co-existence of maternal advanced age and overweight showed greatly amplified risk of LMS (OR = 3.7, 95% CI: 1.3-10.5), and a more pronounced risk was observed for the combination of minimal breast growth and advanced maternal age (OR = 9.2, 95% CI: 3.0-28.3). <b>Conclusions:</b> This data-driven classification of LMS and identified risk factors may enhance the precision of LMS diagnosis and guide targeted interventions for lactating mothers.

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Journal
Nutrients
Published
2025-11-11
DOI
https://doi.org/10.3390/nu17223524
Primary Topic
Breastfeeding Practices and Influences
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article
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article

Defining Low Milk Supply: A Data-Driven Diagnostic Framework and Risk Factor Analysis for Breastfeeding Women

Donna Tracy Geddes, Ching Tat Lai, Ghulam Mubashar Hassan, Jacki L. McEachran et al.
Nutrients
Breastfeeding Practices and Influences
article

Defining Low Milk Supply: A Data-Driven Diagnostic Framework and Risk Factor Analysis for Breastfeeding Women

Donna Tracy Geddes, Ching Tat Lai, Ghulam Mubashar Hassan, Jacki L. McEachran, Zoya Gridneva, Sharon L. Perrella, Xuehua Jin, Nicolas L. Taylor
article en

Abstract

<b>Background:</b> Current low milk supply (LMS) definitions use subjective maternal perceptions or arbitrary thresholds for 24 h milk production (MP), potentially misclassifying cases. This study aimed to re-evaluate the definition of LMS using data-driven approaches and investigate associated maternal risk factors. <b>Methods:</b> Lactating mothers 4-26 weeks postpartum (n = 460) provided demographic, obstetric, and infant data and measured 24 h MP and infant milk intake using the test-weighing method. Infant growth was calculated as their weight-for-age z-score. Latent profile analysis, receiver operating characteristic curve analysis, and multinomial logistic regression were used for classification, diagnostic evaluation, and risk factor assessment for LMS. <b>Results:</b> Four milk supply classes emerged: Class 1 with adequate MP, infant intake and infant growth (n = 254); Class 2 with high MP exceeding infant demand and adequate growth (n = 30); Class 3 with slow infant growth despite moderate MP (n = 120); and Class 4 with extremely low MP and high formula intake (n = 56). Classes 1 and 2 were grouped as the normal milk supply group (61.7%), while Classes 3 and 4 formed the LMS group (38.3%). New thresholds were identified for 24 h MP (708 mL/24 h, area under the curve (AUC) = 0.92) and infant breast milk intake (694 mL/24 h, AUC = 0.94) with high diagnostic accuracy. Moreover, practical alternative thresholds for infant average daily weight gain (26 g, AUC = 0.89), formula intake (122 mL/24 h, AUC = 0.89) and formula-to-growth ratio (4 mL/g, AUC = 0.94) were established for the identification of LMS. Minimal breast growth during pregnancy (Odds ratio (OR) = 4.6, 95% confidence interval (CI): 2.3-9.6), advanced maternal age (OR = 2.1, 95% CI: 1.0-4.5), and gestational diabetes mellitus (OR = 2.1, 95% CI: 1.1-4.0) were significant risk factors related to the LMS subgroups. Co-existence of maternal advanced age and overweight showed greatly amplified risk of LMS (OR = 3.7, 95% CI: 1.3-10.5), and a more pronounced risk was observed for the combination of minimal breast growth and advanced maternal age (OR = 9.2, 95% CI: 3.0-28.3). <b>Conclusions:</b> This data-driven classification of LMS and identified risk factors may enhance the precision of LMS diagnosis and guide targeted interventions for lactating mothers.

NutrientsVol. 17(22)
The University of Western Australia (AU), Community Arts Network (AU)
Openalex Percentile: Top 55%
Breastfeeding Practices and Influences
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