The composition of human milk is dynamic and can vary according to many maternal factors, such as diet and nutritional status. This study investigated the association of maternal nutrition and body composition with human milk composition. All measurements and analyses were done at three time points: during the first (n = 40), third (n = 22), and sixth (n = 15) month of lactation. Human milk was analyzed using the Miris human milk analyzer (HMA), body composition was measured with bioelectrical bioimpedance (BIA) using a Maltron BioScan 920-II, and the assessment of women’s nutrition was based on a three-day dietary record. The correlation coefficient (Pearson’s r) did not show a significant statistical relationship between human milk composition and nutrients in women’s diet at three time points. For women in the third month postpartum, we observed moderate to strong significant correlations (r ranged from 0.47 to 0.64) between total protein content in milk and the majority of body composition measures as follows: positive correlations: % fat mass (r = 0.60; p = 0.003), fat-free mass expressed in kg (r = 0.63; p = 0.001), and muscle mass (r = 0.47; p = 0.027); and negative correlation: % total body water (r = −0.60; p = 0.003). The variance in milk fat content was related to the body mass index (BMI), with a significant positive correlation in the first month postpartum (r = 0.33; p = 0.048). These findings suggest that it is not diet, but rather the maternal body composition that may be associated with the nutritional value of human milk.

This study determined fatty acid (FA) concentrations in maternal milk and investigated the association between omega-3 fatty acid levels and their maternal current dietary intake (based on three-day dietary records) and habitual dietary intake (based on intake frequency of food products). Tested material comprised 32 samples of human milk, coming from exclusively breastfeeding women during their first month of lactation. Milk fatty acids were analyzed as fatty acid methyl ester (FAME) by gas chromatography using a Hewlett-Packard 6890 gas chromatograph with MS detector 5972A. We did not observe any correlation between current dietary intake of omega-3 FAs and their concentrations in human milk. However, we observed that the habitual intake of fatty fish affected omega-3 FA concentrations in human milk. Kendall’s rank correlation coefficients were 0.25 (p = 0.049) for DHA, 0.27 (p = 0.03) for EPA, and 0.28 (p = 0.02) for ALA. Beef consumption was negatively correlated with DHA concentrations in human milk (r = −0.25; p = 0.046). These findings suggest that current omega-3 FA intake does not translate directly into their concentration in human milk. On the contrary, their habitual intake seems to markedly influence their milk concentration.

The present study investigates the influence of selected infant and maternal factors on the energy and macronutrient composition of mature human milk (HM). The study enrolled 77 mothers at 4–8 weeks postpartum. Each mother provided 1 sample of HM. Each extracted HM sample was formed by mixing four subsamples of HM, each of which were obtained in one predefined 6-h periods of the day. Among maternal factors, the analysis included: anthropometric data before and after pregnancy; weight gain in pregnancy; body composition, assessed using the Maltron BioScan 920-II to analyze bioimpedance; and dietary intake, assessed with three-day dietary records. Among the neonatal factors, birth weight and length, number of daily feedings and type of delivery were included. The composition of HM, including energy content, protein, fat and carbohydrate concentrations, was analyzed using the Miris human milk analyzer. Pearson’s and Spearman’s correlation coefficients and multivariable logistic regression models were used to analyze the association between the selected maternal and infant factors and HM milk composition. It was found that total protein content of HM was correlated with pre-pregnancy BMI (Spearman rho = 0.238; p = 0.037), current lean body mass (Spearman rho = −0.293, p = 0.01) and total water content (Spearman rho = −0.315, p = 0.005). Carbohydrates were the only macronutrients whose composition was significantly affected by the infant factors. It was reported that higher carbohydrate content was associated with male sex (OR = 4.52, p = 0.049). Our results show that maternal and infant factors, especially maternal pre-pregnancy and current nutritional status and infant sex, interact and affect HM composition, suggesting that macronutrient and energy content in HM may be determined in pregnancy and may have unique compositional profile for every mother–infant dyad.

Nutrition-related mobile applications (apps) are commonly used to provide information about the user’s dietary intake, however, limited research has been carried out to assess to what extent their results agree with those from the reference method (RM). The main aim of this study was to evaluate the agreement of popular nutrition-related apps with the Polish RM (Dieta 6.0). The dietary data from two days of dietary records previously obtained from adults (60 males and 60 females) were compared with values calculated in five selected apps (FatSecret, YAZIO, Fitatu, MyFitnessPal, and Dine4Fit). The selection of apps was performed between January and February 2021 and based on developed criteria (e.g., availability in the Polish language, access to the food composition database, and the number of downloads). The data was entered by experienced clinical dietitians and checked by one more researcher. The mean age of study participants was 41.7 ± 14.8. We observed that all the apps tended to overestimate the energy intake, however, when considering the macronutrient intake, over- and underestimation were observed. According to our assumed criterion (±5% as perfect agreement, ±10% as sufficient agreement), none of the apps can be recommended as a replacement for the reference method both for scientific as well as clinical use. According to the Bland-Altman analysis, the smallest bias was observed in Dine4Fit in relation to energy, protein, and fat intake (respectively: −23 kcal; −0.7 g, 3 g), however, a wide range between the upper and lower limits of agreement were reported. According to the carbohydrate intake, the lowest bias was observed when FatSecret and Fitatu were used. These results indicate that the leading nutrition-related apps present a critical issue in the assessment of energy and macronutrient intake. Therefore, the implementation of validation studies for quality assessment is crucial to develop apps with satisfying quality.

The aim of this study was to evaluate iron and zinc concentrations in the mature human milk (HM) and to investigate the relationship between these concentrations and maternal factors. HM samples were collected between 4–6 weeks postpartum from 32 healthy, exclusively breastfeeding mothers. The assessment of dietary intake during breastfeeding was based on a food frequency questionnaire and three-day dietary records. Nutritional status of participants was assessed with body mass index and body composition analysis, measured with bioelectrical impedance. HM intake was assessed with infants’ weighting, whereas iron and zinc contents in HM were determined by inductively coupled plasma mass spectrometer. The median intake of HM was 492.5 mL (466–528.5) and the concentrations of HM iron and zinc were 0.33 mg/L (0.26–0.46) and 2.12 mg/L (1.97–2.45), respectively. Maternal total zinc and iron intake (diet + supplementation) was positively correlated with their concentrations in HM. Consumption frequency of meat, vegetables and legumes was revealed to be a significant factor influencing zinc concentration in HM. Regarding iron, it was the consumption frequency of meat, fish and seafood, vegetables and legumes, nuts and seeds. The intake of iron from HM was low, and after assuming a mean fractional iron absorption, it was only 0.038 mg/d. Our results show that maternal diet influences iron and zinc content in HM, suggesting that adequate intake of food rich in investigated minerals may be a positive factor for their concentrations in HM.