Auf der Grundlage der Perinataldaten von 1995 - 2000 werden die 1., 2., 3., 4., 5., 10., 25., 50., 75., 90., 95., 96., 97., 98. und 99. Perzentilwerte für das Geburtsgewicht, die Länge, den Kopfumfang und das längenbezogene Geburtsgewicht für Mädchen und Knaben angegeben. Gegenüber den bisherigen deutschen Standardwerten von 1992 [[ 1 ], [ 2 ]] erfolgt damit eine Präzisierung der Werte, insbesondere im unteren Schwangerschaftsbereich. Folgende Verbesserungen bzw. Veränderungen zu den Werten von 1992 wurden vorgenommen: 1. Durch die hohe Fallzahl konnten die Perzentilwerte schon ab 20 vollendeten Schwangerschaftswochen angegeben werden. 2. Die Berechung der Perzentilwerte erfolgte mithilfe des arithmetischen Mittelwertes (x¯) und der Standardabweichung (s) unter der Voraussetzung des Vorliegens einer Normalverteilung der einzelnen Körpermaße. Mit dieser Methode konnten „stark“ differenzierte Perzentilwerte berechnet werden. 3. Um den internationalen Anforderungen gerecht zu werden, wurden auch die Werte x¯ - 2 s und x¯ + 2 s ausgewiesen. Wir hoffen, dass diese neuen Perzentilwerte nach der Publizierung zur somatischen Klassifikation der Neugeborenen schnelle Anwendung finden und damit die Werte von 1992 ablösen. Zur Erleichterung der Klassifikation steht auch in Kürze ein Computerprogramm zur Verfügung. Based on the perinatal data from 1995 - 2000, the 1st, 2nd, 3rd, 4th, 5th, 10th, 25th 50th, 75th, 90th, 95th, 96th, 97th, 98th, 99th percentile values for birth weight, size (length), head circumference, and for length-related birth weight are presented for girls and boys. These data represent more precise percentile values, particularly for the early gestational weeks compared to the currently used German standard data from 1992 [[ 1 ], [ 2 ]]. The following updates and modifications were made to the values from 1992: 1. Due to the large number of probands, we were able to establish percentile values already from the 20th completed week of gestation. 2. The calculation of the percentile values was made by means of the arithmetic mean (x¯) and the standard deviation (s), provided that the individual somatic measures were normally distributed. With this method, strongly differentiated percentile values could also be calculated. 3. In order to meet international standards, the values x¯ - 2 s and x¯ + 2 s are stated as well. We hope that the published percentile values will be applied soon for the somatic classification of newborns and that the data from 1992 will be replaced. For easier use a software programme will be available in the near future.

Significant biological variation in macronutrient content of breast milk is an important barrier that needs to be overcome to meet nutritional needs of preterm infants. To analyze macronutrient content, commercial infrared milk analyzers have been proposed as efficient and practical tools in terms of efficiency and practicality. Since milk analyzers were originally developed for the dairy industry, they must be validated using a significant number of human milk samples that represent the broad range of variation in macronutrient content in preterm and term milk. Aim of this study was to validate two milk analyzers for breast milk analysis with reference methods and to determine an effective sample pretreatment. Current evidence for the influence of (i) aliquoting, (ii) storage time and (iii) temperature, and (iv) vessel wall adsorption on stability and availability of macronutrients in frozen breast milk is reviewed. Breast milk samples (n = 1188) were collected from 63 mothers of preterm and term infants. Milk analyzers: (A) Near-infrared milk analyzer (Unity SpectraStar, USA) and (B) Mid-infrared milk analyzer (Miris, Sweden) were compared to reference methods, e.g. ether extraction, elemental analysis, and UPLC-MS/MS for fat, protein, and lactose, respectively. For fat analysis, (A) measured precisely but not accurately (y = 0.55x + 1.25, r(2) = 0.85), whereas (B) measured precisely and accurately (y = 0.93x + 0.18, r(2) = 0.86). For protein analysis, (A) was precise but not accurate (y = 0.55x + 0.54, r(2) = 0.67) while (B) was both precise and accurate (y = 0.78x + 0.05, r(2) = 0.73). For lactose analysis, both devices (A) and (B) showed two distinct concentration levels and measured therefore neither accurately nor precisely (y = 0.02x + 5.69, r(2) = 0.01 and y = -0.09x + 6.62, r(2) = 0.02 respectively). Macronutrient levels were unchanged in two independent samples of stored breast milk (-20 °C measured with IR; -80 °C measured with wet chemistry) over a period of 14 months. Milk analyzers in the current configuration have the potential to be introduced in clinical routine to measure fat and protein content, but will need major adjustments.

To optimize infant nutrition, the nature of weight gain must be analyzed. This study aims to review publications and develop growth charts for fat and fat-free mass for preterm and term infants. Body composition data measured by air displacement plethysmography (ADP) and dual energy X-ray absorptiometry (DXA) in preterm and term infants until six months corrected age were abstracted from publications (31 December 1990 to 30 April 2019). Age-specific percentiles were calculated. ADP measurements were used in 110 studies (2855 preterm and 22,410 term infants), and DXA was used in 28 studies (1147 preterm and 3542 term infants). At term age, preterm infants had higher percent-fat than term-born infants (16% vs. 11%, p < 0.001). At 52 weeks postmenstrual age (PMA), both reached similar percent-fat (24% vs. 25%). In contrast, at term age, preterm infants had less fat-free mass (2500 g vs. 2900 g) by 400 g. This difference decreased to 250 g by 52 weeks, and to 100 g at 60 weeks PMA (5000 g vs. 5100 g). DXA fat-free mass data were comparable with ADP. However, median percent-fat was up to 5% higher with DXA measurements compared with ADP with PMA > 50 weeks. There are methodological differences between ADP and DXA measures for infants with higher fat mass. The cause of higher fat mass in preterm infants at term age needs further investigation.