The Use of Sucking Time to Establish Models to Estimate Breastmilk Intake of One Breastfeeding Session for 1-12-Month Infants: A Cross-sectional Study

Abstract BackgroundObservation method of assessing breastmilk intake (BI) by observing medical indices has less interference in breastfeeding than test-weighing method, but for the calculation certain influential predictor variables had not been recognized and needed to be further studied. MethodInfants between 1 and 12 months were enrolled in a hospital of Shenzhen city in northern China. A cross-sectional survey was conducted in a sample of mother-infant dyads. A breastfeeding session of each participating mother subject was observed in the clinic. 150 mother-infant dyads were adopted for data analysis. BI was measured by test-weighing method. Sucking time (ST), Information of maternal and infant health, maternal breast, and infant feeding practice were collected. ResultsThere was a relationship between sucking time and breastmilk intake per breastfeeding session (r=0.57, p<0.05). In the 4 multilevel models (r>0.6, p<0.05) established to estimate breastmilk intake the best fit multilevel model was to estimate breastmilk intake per kg (infant weight) for 1-4-month infants (R2=0.53, p<0.05). Sucking time as the key variable and other factors including infant birth weight/ birth weight, breast side, maternal BMI, maternal vocation significantly had effect on breastmilk intake and those factors that remained significant varied according to different age groups. ConclusionsSucking time had a significant association with breastmilk intake in a breastfeeding session. Establishing multilevel models based on sucking time to estimate breastmilk intake per infant weight for specific age group of infants greatly improved the effectiveness. But the accuracy of the estimation needed to be improved for further application in telemedicine.