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Objective: The objectives of this study were to describe (1) body mass indexes (BMIs) using weight and length for gestational age (GA) classifications, and (2) the additional information BMI, as a measure of body proportionality, provides for preterm infant growth assessment and care plans at birth., Study Design: Birth weight, length, and BMI of 188,646 preterm infants (24-36 weeks gestation) admitted to U.S. neonatal intensive care units (Pediatrix Clinical Data Warehouse, 2013-2018) were classified (Olsen curves) as small, appropriate, or large for GA (SGA < 10th, AGA 10-90th, LGA > 90th percentile for GA, respectively). The distribution for the 27 weight-length-BMI combinations was described., Results: At birth, most infants were appropriate for weight (80.0%), length (82.2%), head circumference (82.9%), and BMI (79.9%) for GA. Birth weight for GA identified approximately 20% of infants as SGA or LGA. Infants born SGA (or LGA) for both weight and length ("proportionate" in size) were usually appropriate for BMI (59.0% and 75.6%). BMI distinguished disproportionate weight for length in infants with SGA or LGA weight at birth (58.3%, 49.9%). BMI also identified 11.4% of AGA weight infants as small or large for BMI ("disproportionate" in size) at birth; only using weight for GA missed these underweight/overweight for length infants., Conclusion: The unique, additional information provided by birth BMI further informs individualized preterm infant growth assessment by providing an assessment of an infant's body proportionality (weight relative to its length) in addition to the routine assessment of weight, length, and head circumference for GA and may better inform care plans and impact outcomes., Key Points: · Most preterm infants were born AGA for all growth measures.. · AGA weight infants may be under- or overweight for length.. · BMI distinguished body disproportionality in SGA/LGA infants.. · Recommend BMI assessed along with weight, length and head.. · Further research on BMI in preterm infants is needed.., Competing Interests: None declared., (Thieme. All rights reserved.)

Introduction: Three widely referenced growth curves classify infant birth anthropometric measurements as small (SGA), appropriate (AGA), or large (LGA) for gestational age (GA) differently. We assessed how these differences in assignment affect the identification and prediction of neonatal intensive care unit (NICU) mortality risk in US preterm infants., Methods: Birth data of infants admitted to NICUs from the Pediatrix Clinical Data Warehouse (2013-2018) were analyzed. Birth weight, length, and head circumference of 46,724 singleton infants (24-32 weeks GA) were classified as SGA, AGA, or LGA using the Olsen, Fenton, and INTERGROWTH-21st curves. NICU mortality risk based on birth size classification was analyzed using unadjusted and adjusted logistic regression stratified by GA., Results: Odds of mortality were increased with SGA classification at all GAs, size measurements, and curve sets, compared with AGA infants. LGA classification for weight was associated with lower mortality risk at 24 weeks GA and higher risk at 30 weeks GA. Odds of mortality did not differ significantly across curve sets. Classification of size at birth alone had relatively low predictive ability to identify mortality risk, with unadjusted AUCs near 0.5 for all analyses., Conclusion: There were no significant differences across curve sets in predicting mortality. Classification of size at birth is a relatively imprecise method to identify infants at risk for NICU mortality., (© 2024 S. Karger AG, Basel.)

Background: Clinicians and researchers use a variety of intrauterine growth curves to classify NICU infants as small (SGA), appropriate (AGA), or large for gestational age (LGA). Since curve creation methods and samples vary, SGA/AGA/LGA cut-offs and resulting subgroups of infants vary among curves and impact outcome study findings - limiting generalisability., Aim: Determine how two international and two US-specific curves classified US NICU infants., Subjects and Methods: Classified 192,888 infants from US NICUs (2013-2016) as SGA or LGA for birthweight, length, and head circumference, using the international Fenton and INTERGROWTH-21st curves and US-specific Olsen and Lubchenco (historical) curves., Results: Modern curves classified approximately 10% of infants as SGA up to 32 weeks, but older infants had increased variability. The INTERGROWTH-21st curves consistently had rates above 10% for LGA after 32 weeks., Conclusions: While Olsen and Fenton both fit, the Olsen curves had overall best-fit for our sample of US NICU infants. The INTERGROWTH-21st curves fit the definitions for SGA and LGA for younger ages, but inferences outside of these definitions are unwarranted due to limited sample size. The INTERGROWTH-21st sample used for 33 weeks and older infants was physically smaller at the upper percentiles than our sample of US infants.

Background: Longitudinal growth curves, based on repeated measurements from the same group of infants, exist for preterm infant weight and length but not for BMI. Our existing BMI (weight divided by length squared) curves are based on cross-sectional birth data obtained from a different group of infants at each gestational age (GA)., Methods: We calculated BMI over time for 68 693 preterm infants between 24 and 36 weeks GA. Stratifying infants by sex, GA at birth, and quintiles based on birth BMI, we created longitudinal median curves using R and validated the resulting curves for empirical fit, proper classification, and normality of z scores., Results: We created 2 sets of BMI growth charts. The first set displays fitted median curves for all 5 percentile groups in each GA group by sex. The second set displays fitted median curves with their corresponding third and 97th percentiles by percentile group, GA, and sex. In the validation analysis, percentage of daily observations below the median curve approximated the expected 50th percentile after the initial 3 days. Unlike the cross-sectional curves, the longitudinal curves reveal the pattern of change corresponding to nadir; postnadir, these curves remained consistently below the cross-sectional curves and varied by GA and sex as expected. The percentage of observations falling below the 50th percentile for cross-sectional curves (revealing optimal growth) was generally much higher than for longitudinal curves (revealing actual growth)., Conclusions: These new longitudinal curves provide clinicians data on how premature infants' body proportionality changes over time., Competing Interests: POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2018 by the American Academy of Pediatrics.)

Background: Clinicians have observed preterm infants in the neonatal intensive care unit growing disproportionally; however, the only growth charts that have been available were from preterm infants born in the 1950s which utilized the ponderal index. Prior to creating the recently published BMI curves, we found only 1 reference justifying the use of the ponderal index., Objectives: To determine the best measure of body proportionality for assessing growth in US preterm infants., Methods: Using a dataset of 391,681 infants, we determined the body proportionality measure that was most correlated with weight and least correlated with length. We examined the sex-specific overall correlations and then stratified further by gestational age (GA). We then plotted the body proportionality measures versus length to visualize apparent discrepancies in the appropriate measure., Results: The overall correlations showed weight/length3 (ponderal index) was the best measure but stratification by GA indicated that BMI (weight/length2) was the best measure. This seeming inconsistency was due to negative correlations between ponderal index and length at each GA. BMI, on the other hand, had a correlation with length across GAs, but was uncorrelated with length within GAs. Both ponderal index and BMI were positively correlated with weight., Conclusions: BMI is the appropriate measure of body proportionality for preterm infants, contrary to current practice., (© 2017 S. Karger AG, Basel.)

Background and Objectives: Preterm infants experience disproportionate growth failure postnatally and may be large weight for length despite being small weight for age by hospital discharge. The objective of this study was to create and validate intrauterine weight-for-length growth curves using the contemporary, large, racially diverse US birth parameters sample used to create the Olsen weight-, length-, and head-circumference-for-age curves., Methods: Data from 391 681 US infants (Pediatrix Medical Group) born at 22 to 42 weeks' gestational age (born in 1998-2006) included birth weight, length, and head circumference, estimated gestational age, and gender. Separate subsamples were used to create and validate curves. Established methods were used to determine the weight-for-length ratio that was most highly correlated with weight and uncorrelated with length. Final smoothed percentile curves (3rd to 97th) were created by the Lambda Mu Sigma (LMS) method. The validation sample was used to confirm results., Results: The final sample included 254 454 singleton infants (57.2% male) who survived to discharge. BMI was the best overall weight-for-length ratio for both genders and a majority of gestational ages. Gender-specific BMI-for-age curves were created (n = 127 446) and successfully validated (n = 126 988). Mean z scores for the validation sample were ∼0 (∼1 SD)., Conclusions: BMI was different across gender and gestational age. We provide a set of validated reference curves (gender-specific) to track changes in BMI for prematurely born infants cared for in the NICU for use with weight-, length-, and head-circumference-for-age intrauterine growth curves., (Copyright © 2015 by the American Academy of Pediatrics.)

The concept that adequate nutritional status and normal growth are important is well-accepted. How to assess the adequacy of nutrition and how to define appropriate growth remains an area of active debate. Our goal is to review how growth is assessed at birth and during the hospital stay of prematurely born infants, and to offer a standardized approach., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Objective: The aim of the study was to evaluate the relation between nutritional intake (kilocalories, protein) and weight and length growth in preterm infants, and to describe their metabolic tolerance with a focus on those with high protein intake (≥ 4.6 g · kg(-1) · day(-1))., Methods: Secondary analysis of data from appropriate-for-gestational age preterm infants in a 28-day randomized clinical trial that evaluated growth, tolerance, and safety of a new ultraconcentrated liquid human milk fortifier (original study n = 150). This subset of 56 infants had complete growth and nutrition data and met criteria for the original study's "efficacy analysis" (eg, >80% of kilocalorie intake from study diet). Nutritional intake was estimated, not actual. Regressions were used to test cumulative kilocalories and protein as the predictors of 28-day change in weight and length z scores (growth status), and to evaluate protein tolerance., Results: Average intake was 118 ± 8 kcal · kg(-1) · day(-1) and 4.3 ± 0.4 g protein · kg(-1) · day(-1), with 16 ± 3 g · kg(-1) · day(-1) and 1.1 ± 0.2 cm/week growth for 28 days. Cumulative total kilocalories and protein were significant predictors of improved length z score (P = 0.0054, 0.0005) but not weight z score change. Regression models indicated that protein not kilocalories explained the improvement in length z score, with protein explaining 19% of the variability. The high protein group averaged 4.6 to 5.5 g · kg(-1) · day(-1) (n = 16). Protein tolerance was adequate for all of the study infants based on metabolic measures (blood urea nitrogen, serum carbon dioxide, pH)., Conclusions: Higher cumulative protein intake was tolerated and overall lessened the commonly occurring decline in the length but not weight growth status in a 28-day study of preterm infants.

Objective: The objective of this study was to create and validate new intrauterine weight, length, and head circumference growth curves using a contemporary, large, racially diverse US sample and compare with the Lubchenco curves., Methods: Data on 391 681 infants (Pediatrix Medical Group) aged 22 to 42 weeks at birth from 248 hospitals within 33 US states (1998-2006) for birth weight, length, head circumference, estimated gestational age, gender, and race were used. Separate subsamples were used to create and validate curves. Smoothed percentile curves (3rd to 97th) were created by the Lambda Mu Sigma (LMS) method. The validation sample was used to confirm representativeness of the curves. The new curves were compared with the Lubchenco curves., Results: Final sample included 257 855 singleton infants (57.2% male) who survived to discharge. Gender-specific weight-, length-, and head circumference-for-age curves were created (n = 130 111) and successfully validated (n = 127 744). Small-for-gestational age and large-for-gestational age classifications using the Lubchenco curves differed significantly from the new curves for each gestational age (all P < .0001). The Lubchenco curves underestimated the percentage of infants who were small-for-gestational-age except for younger girls (< or =36 weeks), for whom it was more likely to be overestimated; underestimated percentage of infants (< or =36 weeks) who were large-for-gestational-age; and overestimated percentage of infants (>36 weeks) who were large-for-gestational-age., Conclusions: The Lubchenco curves may not represent the current US population. The new intrauterine growth curves created and validated in this study, based on a contemporary, large, racially diverse US sample, provide clinicians with an updated tool for growth assessment in US NICUs. Research into the ability of the new definitions of small-for-gestational-age and large-for-gestational-age to identify high-risk infants in terms of short-term and long-term health outcomes is needed.

Objective: To evaluate the utility of weight-for-length (defined as gm/cm(3), known as the "ponderal index") as a complementary measure of growth in infants in neonatal intensive care units (NICUs)., Study Design: This was a secondary analysis of infants (n=1214) of gestational age 26 to 29 weeks at birth, included in a registry database (1991-2003), who had growth data at birth and discharge. Weight-for-age and weight-for-length were categorized as small (<10th percentile), appropriate, or large (>90th percentile)., Results: Statistical agreement between the weight-for-age and weight-for-length measures was poor (kappa=0.02 at birth, 0.10 at discharge; Bowker test for symmetry, P< .0001). From birth to discharge, the percentage of small-for-age infants increased from 12% to 21%, the percentage of small-for-length infants decreased from 10% to 4%, the percentage of large-for-age infants remained similar (<1%), and the percentage of large-for-length infants increased from 5% to 17%. At discharge, 92% of the small-for-age infants were appropriate or large-for-length, and 19% of the appropriate-for-age infants were large-for-length., Conclusions: Weight-for-age and weight-for-length are complementary measures. Weight-for-length or other measures of body proportionality should be considered for inclusion in routine growth monitoring of infants in the NICU.

Background: To support age-appropriate growth and to prevent and treat malnutrition in children with cystic fibrosis (CF), energy requirements for those children are often set above the requirements for healthy children. Care providers use one of several empirically derived formulas to calculate energy requirements, yet the validity of these formulas has seldom been tested., Objective: We evaluated 6 proposed formulas for calculating energy requirements in children with CF against a total energy requirement for children with CF (TER-CF) derived from measured total energy expenditure, fecal fat energy loss, and the theoretic energy required for age-appropriate tissue accretion., Design: Subjects were children aged 6-8 y who had CF and pancreatic insufficiency. Calculated TERs from each formula were evaluated against TER-CF by using summary statistics, regression analysis, and residual plots., Results: Subjects (n = 53) had suboptimal nutrition and growth status and mild-to-moderate lung disease. The formula that most closely (within 2%) approximated TER-CF was the estimated energy requirement (EER) formula at the active level (EERact). Regression analysis of TER-CF onto calculated TER from each formula yielded the best indexes of model fit for the EERact formula; residual plots of the EERact formula were tightly and normally distributed around zero., Conclusions: The EERact formula should be used to establish TER-CF in children in this age group who have mild-to-moderate CF. Changes in weight, height, and other indicators of nutritional status must be monitored to modify TER-CF as needed to support individual patient care goals.

Background: Suboptimal growth and nutritional status are common among children with cystic fibrosis (CF) and pancreatic insufficiency (PI). A better understanding of energy balance is required to improve prevention and treatment of malnutrition., Objective: Our objective was to characterize energy balance and the reporting accuracy of dietary intake in children with CF by evaluating the relations between energy intake (EI), energy expenditure (EE), fecal energy loss, nutritional status, and growth., Design: The subjects were participants of a 24-mo prospective study of children 6-10 y of age with CF and PI. EE, EI, fecal energy loss, and anthropometric measures were obtained at baseline and at 24 mo., Results: The children (n = 69) had suboptimal growth at baseline (x +/- SD: weight-for-age z score, -0.53 +/- 1.19; adjusted height-for-age z score, -0.67 +/- 1.06; body mass index z score, -0.29 +/- 1.12), and these variables remained suboptimal at 24 mo. The median ratios of EI to EE at baseline and 24 mo were 1.15 and 1.18, respectively, which decreased to 1.09 and 1.10, respectively, when adjusted for fecal energy loss (EI(-FL):EE). At baseline, 7% of subjects were underreporters, 64% were accurate reporters, and 23% were overreporters of energy intake; the percentages were similar at 24 mo., Conclusions: Although EI(-FL):EE ratios were higher than expected at both baseline and 24 mo, this cohort showed only age-appropriate weight gain. Self-reported dietary intake data at the individual level should be interpreted with caution, and weight gain velocity may serve as an objective measure of long-term energy balance.

Objective: Describe the level of registered dietitian (RD) involvement in neonatal intensive care units (NICUs) and associations with NICU nutrition practices., Design: Questionnaires were mailed to 820 NICUs in the United States with two follow-up mailings to nonresponders. Abbreviated phone surveys were conducted with a random sample of 10% of nonresponders. A nutrition care score was devised based on a sum of 10 survey questions (range 0 to 10) to summarize the intensity of reported practices., Subjects/setting: Directors of NICUs in the United States and RDs associated with them., Statistical Analyses: Chi2, analysis of variance, Bonferroni and Duncan multiple range tests, regression., Results: Respondents from 417 (54%) of the 772 NICUs eligible for the study provided completed questionnaires. Among NICUs responding, 76% involved RDs in care (41% employed full- or part-time RDs, 35% employed consult RDs), and 24% had no RD. NICUs with full- or part-time RDs provided fewer kilocalories and more protein parenterally, and more kilocalories and protein enterally. NICUs with less RD involvement were more likely to provide full-term infant feedings (eg, unfortified breast milk, full-term formula) to very-low-birth-weight infants. Mean nutrition care score varied with RD involvement from 4.6+/-1.7 (mean+/-standard deviation) for NICUs with a consult RD and 4.7+/-1.4 for NICUs employing no RD to 5.6+/-1.7 for NICUs with a full- or part-time RD (overall P<.001)., Conclusions: More involvement of RDs in NICUs increased the intensity of important aspects of nutrition care that may improve outcomes of very-low-birth-weight infants in NICUs. These findings highlight the importance of RDs as NICU team members.

Objectives: To describe bone status in children with Alagille syndrome (AGS) and healthy control children adjusted for age, gender and height (HT), and to identify dietary intake and AGS-related factors associated with bone status., Methods: Prepubertal children with AGS and healthy controls comparable in age and ethnicity were evaluated. Subjects were > or =4 years of age, prepubertal and had whole body (WB) and/or lumbar spine (LS) dual energy X-ray absorptiometry (DXA) scans of acceptable quality. Anthropometric (weight, HT), diet and AGS-specific data (e.g., coefficient of fat absorption, labs, liver transplantation) were also collected. Bone area (BA), bone mineral content (BMC) and HT were log transformed for best fit. Bone data were analyzed unadjusted, adjusted for gender, age and HT, and as HT-specific z-scores., Results: AGS and control groups were similar in age, pubertal status and ethnicity. Children with AGS were small-for-age, had decreased BA and BMC-for-age, and decreased WB BA and BMC-for-HT z-scores compared to healthy controls. Prevalence of low BMC-for-HT z-scores (< -2) among AGS subjects was 20% for the WB and 39% for the LS. Bone mineralization was positively related to fat absorption but not dietary intake., Conclusions: Children with AGS have deficits in bone size and bone mass relative to body size. Modifiable factors, such as treatment of malabsorption should be explored as an early focus of AGS care to prevent bone fragility.

Background and Objective: Transfer of infants between hospitals or their discharge home may bias comparisons of the performance across neonatal intensive care units (NICUs). This study attempts to show the potential size of transfer bias in the context of a large cohort study and describe strategies for minimizing this type of bias., Methods: To limit transfer bias in a neonatal growth study of extremely premature infants in six tertiary NICUs, we restricted eligibility to infants <30 weeks gestation at birth and substituted matched replacements for early transfers (infants transferred or discharged prior to day of life 16)., Results: The restriction strategy was successful, reducing the overall early transfer rate from 16.4 to 3.6% and the range of transfer rates among individual NICUs from 0.6-32.7% to 0-11.0%. Replacement by matched substitutes had a much smaller effect because of the small number of early transfers and our inability to match on all factors distinguishing early transfers., Conclusion: Sampling strategies to minimize infants lost to follow-up were more successful than replacement strategies in limiting transfer bias in a NICU growth study. Although complete elimination of bias is likely impossible, valid studies require efforts to minimize, quantify, and test the effect of transfer bias.

Objective: To explain differences in weight growth velocity of extremely premature infants among 6 level III neonatal intensive care units (NICUs)., Methods: In 6 NICUs, we studied 564 infants, stratified by gestational age (GA), who were first admissions, survivors, <30 weeks' GA at birth, and in the NICU at least 16 days. Case mix (eg, birth weight, GA, race, illness severity, prenatal steroids), exposure to medical practices/complications (eg, respiratory support, postnatal steroids, necrotizing enterocolitis, infection), and nutritional intake (kcal/kg/d and protein in g/kg/d) were collected and used to predict weight growth velocity between day 3 and day 28 (or discharge, if transferred early) in multiple linear regression models., Results: Weight growth velocities varied significantly among the 6 NICUs. Adjustment for case mix and medical factors explained little of this variability, but additional control for calorie and especially protein intake accounted for much of the intersite variability. For the average infant, adjusted growth velocity ranged from 10.4 to 14.3 g/kg/d among the sites studied. The final predictive model, including case mix and medical and nutritional factors, explained 53% of the overall variance in growth velocity. Prolonged (> or =15 days) exposure to postnatal steroids and greater severity of illness both decreased growth velocity. The model predicted that adding 1 g/kg/d protein to the mean intake for our sample would increase growth by 4.1 g/kg/d., Conclusions: Variation in nutrition explained much of the difference in growth among the NICUs studied. Mean intake of calories and protein failed to meet recommended levels, and the average growth in only 1 NICU approximated intrauterine growth standards. Increasing nutritional intake into the recommended ranges, in particular of protein, may increase growth of extremely premature infants up to or above intrauterine rates.