Milk flow rate may play an important role in an infant's ability to safely and efficiently coordinate sucking, swallowing, and breathing during feeding.
To test milk flow rates from bottle nipples used in the hospital and after discharge.
Bottle nipples used in hospitals (10 unique types) and available nationwide at major retailers (15 unique types) were identified. For each of the 25 nipple types, 15 nipples of that type were tested by measuring the amount of infant formula extracted in 1 minute by a breast pump. Mean milk flow rate (mL/min) and coefficient of variation (CV) were calculated for each nipple type. Comparisons between nipple types were made within brand and within category (eg, Slow, Standard). A cluster analysis was conducted to identify nipples of comparable flow.
A total of 375 individual nipples were tested. Milk flow rates varied widely, from 0.86 to 37.61 mL/min. There was also a wide range of CVs, from 0.03 to 0.35. Packing information did not accurately reflect the flow rates of bottle nipples. The cluster analysis revealed 5 clusters of nipples, with flow rates from Extra Slow to Very Fast.
These data can be used to guide decisions regarding nipples to use for feeding infants with medical complexity in the hospital and after discharge.
Research on infant feeding should consider the flow rate and variability of nipples used, as these factors may impact findings.
Boston College William F. Connell School of Nursing, Chestnut Hill, Massachusetts (Drs Pados and Park); and NICU Feeding and Developmental Therapy Team, Department of Newborn Medicine, Brigham and Women's Hospital, Boston, Massachusetts (Dr Dodrill).
Correspondence: Britt Frisk Pados, PhD, RN, NNP-BC, Boston College William F. Connell School of Nursing, Maloney Hall 268, 140 Common-wealth Ave, Chestnut Hill, MA 02467 (email@example.com).
Institution where work occurred: Boston College and Brigham and Women's Hospital.
The authors acknowledge all of the students who contributed their time to this study, including Audrey (Abby) Basler, Nina Hofmann, Elisa Kang, Lauren Mundy, Elaina Parrillo, and Mikaila Richards.
The authors report no conflict of interest.