Abstract
Obtaining valid estimates of nutrient intake in infants is currently limited by the difficulties of accurately measuring human milk intake. Current methods are either unsuitable for large-scale studies (i.e., the gold standard dose-to-mother stable isotope technique) or use set amounts, regardless of known variability in individual intake.
This cross-sectional study aimed to develop equations to predict human milk intake using simple measures and to carry out external validation of existing methods against the gold standard technique.
Data on human milk intake were obtained using the dose-to-mother stable isotope technique in 157 infants aged 7–10 mo and their mothers. Predictive equations were developed using questionnaire and anthropometric data (Model 1) and additional dietary data (Model 2) using lasso regression. Bland-Altman plots and intraclass correlation coefficients (ICC) also assessed the validity of existing methods (FITS and ALSPAC studies).
The strongest univariate predictors of human milk intake in infants of 8.3 mo on average (46% female) were infant age, infant body mass index (BMI), number of breastfeeds a day, infant formula consumption, and energy from complementary food intake. Mean [95% confidence interval (CI)] differences in predicted versus measured human milk intake [mean (SD): 762 (257) mL/day] were 0.0 mL/day (−26, 26) for Model 1 (ICC 0.74) and 0.5 mL/day (−21, 22) for Model 2 (ICC 0.83). Corresponding differences were −197 mL/day (−233, −161; ICC 0.32) and −175 mL/day (−216, −134; ICC 0.41) for the methods used by FITS and ALSPAC, respectively.
The Human Milk Intake Level Calculation provides substantial improvements on existing methods to estimate human milk intake in infants aged 7–10 mo, while utilizing data commonly collected in nutrition surveys. Although further validation in an external sample is recommended, these equations can be used to estimate human milk intake at this age with some confidence.
This clinical trial was registered at http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=379436) as ACTRN12620000459921.