Mark J. Johnson

Preterm Birth and Body Composition at Term Equivalent Age: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVE: Infants born preterm are significantly lighter and shorter on reaching term equivalent age (TEA) than are those born at term, but the relation with body composition is less clear. We conducted a systematic review to assess the body composition at TEA of infants born preterm. METHODS: The databases MEDLINE, Embase, CINAHL, HMIC, “Web of Science,” and “CSA Conference Papers Index” were searched between 1947 and June 2011, with selective citation and reference searching. Included studies had to have directly compared measures of body composition at TEA in preterm infants and infants born full-term. Data on body composition, anthropometry, and birth details were extracted from each article. RESULTS: Eight studies (733 infants) fulfilled the inclusion criteria. Mean gestational age and weight at birth were 30.0 weeks and 1.18 kg in the preterm group and 39.6 weeks and 3.41 kg in the term group, respectively. Meta-analysis showed that the preterm infants had a greater percentage total body fat at TEA than those born full-term (mean difference, 3%; P = .03), less fat mass (mean difference, 50 g; P = .03), and much less fat-free mass (mean difference, 460 g; P < .0001). CONCLUSIONS: The body composition at TEA of infants born preterm is different than that of infants born at term. Preterm infants have less lean tissue but more similar fat mass. There is a need to determine whether improved nutritional management can enhance lean tissue acquisition, which indicates a need for measures of body composition in addition to routine anthropometry.

Implementation, context and complexity

BackgroundContext is a problem in research on health behaviour change, knowledge translation, practice implementation and health improvement. This is because many intervention and evaluation designs seek to eliminate contextual confounders, when these represent the normal conditions into which interventions must be integrated if they are to be workable in practice.DiscussionWe present an ecological model of the ways that participants in implementation and health improvement processes interact with contexts. The paper addresses the problem of context as it affects processes of implementation, scaling up and diffusion of interventions. We extend our earlier work to develop Normalisation Process Theory and show how these processes involve interactions between mechanisms of resource mobilisation, collective action and negotiations with context. These mechanisms are adaptive. They contribute to self-organisation in complex adaptive systems.ConclusionImplementation includes the translational efforts that take healthcare interventions beyond the closed systems of evaluation studies into the open systems of ‘real world’ contexts. The outcome of these processes depends on interactions and negotiations between their participants and contexts. In these negotiations, the plasticity of intervention components, the degree of participants’ discretion over resource mobilisation and actors’ contributions, and the elasticity of contexts, all play important parts. Understanding these processes in terms of feedback loops, adaptive mechanisms and the practical compromises that stem from them enables us to see the mechanisms specified by NPT as core elements of self-organisation in complex systems.

Promoting professional behaviour change in healthcare: what interventions work, and why? A theory-led overview of systematic reviews

Objectives Translating research evidence into routine clinical practice is notoriously difficult. Behavioural interventions are often used to change practice, although their success is variable and the characteristics of more successful interventions are unclear. We aimed to establish the characteristics of successful behaviour change interventions in healthcare. Design We carried out a systematic overview of systematic reviews on the effectiveness of behaviour change interventions with a theory-led analysis using the constructs of normalisation process theory (NPT). MEDLINE, CINAHL, PsychINFO and the Cochrane Library were searched electronically from inception to July 2015. Setting Primary and secondary care. Participants Participants were any patients and healthcare professionals in systematic reviews who met the inclusion criteria of having examined the effectiveness of professional interventions in improving professional practice and/or patient outcomes. Interventions Professional interventions as defined by the Cochrane Effective Practice and Organisation of Care Review Group. Primary and secondary outcome measures Success of each intervention in changing practice or patient outcomes, and their mechanisms of action. Reviews were coded as to the interventions included, how successful they had been and which NPT constructs its component interventions covered. Results Searches identified 4724 articles, 67 of which met the inclusion criteria. Interventions fell into three main categories: persuasive; educational and informational; and action and monitoring. Interventions focusing on action or education (eg, Audit and Feedback, Reminders, Educational Outreach) acted on the NPT constructs of Collective Action and Reflexive Monitoring, and reviews using them tended to report more positive outcomes. Conclusions This theory-led analysis suggests that interventions which contribute to normative restructuring of practice, modifying peer group norms and expectations (eg, educational outreach) and relational restructuring, reinforcing modified peer group norms by emphasising the expectations of an external reference group (eg, Reminders, Audit and Feedback), offer the best chances of success. Combining such interventions is most likely to change behaviour.

Nutrition and neurodevelopmental outcomes in preterm infants: a systematic review

A systematic review with meta‐analysis was carried out to investigate the effects of increased nutritional intake, via either macronutrient or multinutrient intervention, during the neonatal period on neurodevelopmental outcomes in infants born at <32 weeks of gestation or weighing <1501 g at birth.

Body composition assessment in nutrition research: value of BIA technology

Background/Objectives:There is wide variability in the shape and size of an individual and their body composition. This partly reflects inherent genetic differences, but to a large extent is determined by the extent to which their intake of energy and nutrients has adequately matched their needs over extended periods of time.Subjects/Methods:During childhood, the effective partitioning of nutrients to tissues reflects the hierarchy of demand for growth and maturation during critical periods of development. At all ages, the structural relationships at the molecular, cellular, tissue and whole-body levels are indicative of functional capability and the capacity to cope with internal and external stresses.Results:Reliable measurements of body composition and their interpretation can mark health, be indicative of the risk of ill-health and be a direct cause of pathology and disease. The bioeletrical impedance of the body has been used as an indirect measure for body composition, because it is a reflection of both its structural and functional characteristics, but the specifics of the relationships between these considerations still need to be determined.Conclusions:The measurement of bioelectrical impedance is simple to carry out and is non-invasive. It could be further refined and developed to fully explore and exploit its potential utility in practice.

Suboptimal nutrition in moderately preterm infants

It is recognised that very preterm infants are at risk of later morbidity, including neurodevelopmental impairment (1), respiratory complications and poor growth (2). However, there is increasing evidence that infants born at later preterm gestations are also at greater risk of such adverse outcomes (3,4), with amalgamated data from follow-up studies showing continuous improvement in IQ scores and decreasing risk of respiratory disease as gestational age at birth increases (5). Moderately preterm infants (32–-34 weeks’ gestation) are at increased risk of respiratory distress syndrome (RDS), sepsis, hypothermia, hypoglycaemia, jaundice and feeding difficulties (6) and account for a high proportion of neonatal unit admissions. Post-discharge, they aremore likely to be rehospitalised with jaundice and feeding difficulties (7). Given that preterm infants are deprived of the rapid intrauterinenutrient accretion and growth that occurs during the third trimester, nutritional factors may influence outcomes, and there is evidence that moderate and late preterm infants experience poor growth in the neonatal period (8). While there are published recommendations for the nutrient requirements of very preterm infants (9), the nutritional requirements of moderate and late preterm infants are less established, although guidance for low birthweight infants <2500 g has been published by the World Health Organization (10). Cumulative nutrient deficits are well described in extremely preterm infants, with poor growth and undernutrition associated with adverse outcomes (11). For moderate and late preterm infants, however, there is a paucity of such data. Nutrition can be modified, so represents a potential target for improving outcomes. We aimed to gain a better understanding of nutrition and growth inmoderate and late preterm infants by carrying out a detailed evaluation of the nutritional care of infants born at 32 + 0 to 34 + 6 weeks’ gestation, between January 1, 2012 and June 30, 2012. Infants of more than 35 weeks’ gestation were excluded, as they are not routinely admitted. Data, including pregnancy and neonatal diagnoses, and daily fluid intakes were extracted from infants’ notes. Daily intakes of ninekeynutrients(energy,protein,carbohydrate,fat,calcium, phosphorous,vitaminA,DandE)associatedwithgrowthand bonehealthwere calculated.Weight andhead circumference datawereconvertedtostandarddeviationscores (SDS)based on UK normative data. Differences between groups were compared using Fisher’s exact test (dichotomous outcomes) orANOVA(continuousoutcomes).Therelationshipbetween nutrition, growth and gestation was explored using linear regression (Stata IC v12.1; Stata Corporation 4905, College Station, TX, USA). Ethical approval was not required as this was a service evaluation. Table 1 shows the study population of 54 infants, with clinical characteristics by gestational age. Of these, 52% were delivered by caesarean section, with RDS being the most common neonatal complication. Mean length of stay was 20.5 days and mean post-conceptional age at discharge was 36 + 4 weeks. Approximately one in six (16%) of the infants had intrauterine growth restriction, (IUGR) with a birthweight below the 10th centile, and seven (14%) infants had a birthweight of less than 1500 g. The mean time to regain birthweight was 10.2 days and mean change in weight SDS between birth and discharge was 0.98. Figure 1 demonstrates the nutritional interventions used in each age group. Nine infants received parenteral nutrition (PN) with a mean duration of 12 days. PN use was more common in infants who were more preterm or

How to use: nutritional assessment in neonates

Adequate nutrition and growth during the neonatal period are important, especially for preterm infants, for whom there is evidence of poor nutrient intakes and growth, and this has important implications for their health in later life. Increased nutritional support while on the neonatal intensive care unit has been shown to improve growth, but such support is not universally available. Being able to carry out and interpret a nutritional assessment is therefore an important skill for paediatricians caring for neonates. This article aims to explain how to use nutritional assessment in neonates and provides some tools to make this process as straightforward as possible.

Developing a new screening tool for nutritional risk in neonatal intensive care

1.National Institute for Health Research, Southampton Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, Southampton, UK 2.Department of Neonatal Medicine, Princess Anne Hospital, University Hospital Southampton NHS Foundation Trust, Southampton, UK 3.Department of Nutrition and Dietetics, University Hospital Southampton NHS Foundations Trust, Southampton, UK 4.National Institute for Health Research, Southampton Respiratory Biomedical Research Unit, University Hospital Southampton NHS Foundation Trust and University of Southampton, Southampton, UK

Development of a novel electronic neonatal nutrition assessment tool

Background Poor growth is common in preterm infants in the neonatal period, with poor weight gain, short stature and altered body composition when compared to term infants. Achieving recommended nutrient intakes is difficult; however it is not easy to demonstrate this contemporaneously in routine clinical practice. Methods We developed a customised electronic tool (SENNAT) to capture and analyse growth and nutritional data, with the aim of gaining better understanding of neonatal nutrition at individual and population level. SENNAT uses pre-loaded information on the nutritional content of feeds and fluids to calculate an individuals total daily nutrient intake from daily fluid volumes, and compares these to current recommendations (Tsang 2005). Graphical reports are produced to aid clinical decisions. SENNAT was used to carry out a retrospective review of all infants with a birth weight <1500 g or gestational age at birth <30 weeks, in-born during 2009. Results From 70 eligible infants, case notes were available for 64. Intakes of selected nutrients compared to recommendations for the first week of life through to 36 weeks post conceptual age (PCA) are shown in table 1, together with standard deviation scores (SDS) for weight and head circumference. Figures are mean (SD). Abstract G73 Table 1 Nutrient intakes (as percentage of recommendations) and Growth by week of age Nutrient Week 1 (n=64) Week 2 (n=60) Week 4 (n=50) 36 Weeks PCA (n=37) Energy 84.0 (22.1)* 104.4 (15.7) 98.9 (12.7) 94.2 (16.5)† Protein 42.6 (15.8)* 76.6 (14.5)* 79.8 (17.3)* 83.2 (21.0)* Zinc 114.2 (29.3)* 83.1 (17.9)* 74.2 (20.6)* 87.4 (21.3)* Copper 265.6 (106.4)* 116.0 (37.9)* 87.9 (32.7)† 78.2 (21.0)* Selenium 265.6 (106.4)* 104.8 (9.27)* 98.3 (4.3)* 95.8 (12.2)† Vitamin A 37.6 (17.0)* 83.8 (19.9)* 190.8 (103.9)* 170.7 (69.3)* Vitamin D 55.7 (26.7)* 73.5 (25.8)* 86.3 (31.2)† 96.0 (28.3) Vitamin E 29.8 (16.1)* 60.4 (20.7)* 55.8 (29.7)* 70.8 (29.3)* Vitamin C 30.8 (13.8)* 68.9 (18.2)* 148.2 (86.4)* 146.3 (54.5)* Growth Weight SDS −0.56 (1.18) −1.42 (1.01) −1.35 (0.97) −1.76 (1.03) Head circumference SDS −1.13 (1.27) −1.22 (1.26) −1.7 (1.20) −1.70 (1.29) * p<0.001 and † p<0.05 for difference from recommendations (one-sample t-test). Conclusions Patterns of nutrient intake changed, reflecting periods on parental nutrition, transition to milk feeds and use of nutritional supplements. Intakes of protein were low throughout stay, whilst micronutrient intakes varied. At 36 weeks PCA most intakes were below recommended values and this was reflected in poor growth. We anticipate that modifications to our nutrition policy, combined with weekly assessment using SENNAT, will result in improved nutrient intakes and growth during prospective study in 2012.

5.10 Using detailed clinical nutritional data to predict optimal energy and protein intakes for preterm infants

Background Preterm infants often experience poor growth during the neonatal period, and are discharged with weights and head circumferences on centiles well below that on which they were born. One reason for this is inadequate nutrient provision. Whilst recommendations for nutrient intakes exist, their validity is the subject of debate, and there is a need to better understand optimal nutrient intakes for these infants. Methods Detailed nutrient intake and growth data collected on preterm infants as part of another study was used. Growth was assessed using the difference in standard deviation score (dSDS) for weight and head circumference between birth and discharge. Linear regression of growth and mean intakes of protein and energy during hospital stay was carried out, and optimal intakes were then estimated assuming that ideal growth would result in a dSDS of zero. Results 186 preterm infants were included, with a mean (SD) gestational age and birth weight of 28.6(2.8) weeks and 1.01(0.28)kg. Mean intakes of energy and protein were significantly associated with weight dSDS, with coefficients (95% confidence intervals) of 0.01 (0.001–0.020) and 0.56 (0.307–0.818) respectively. Using regression constants, this equates to estimated optimal intakes of 174 kcal/kg/day and 4.11 g/kg/day protein. However, r 2 values were low at 0.02 and 0.09 respectively. Conclusions This study demonstrates the utility of detailed clinical nutritional data in studying the relationships between intake and growth. Whilst r2 values were low, these findings suggest that energy and protein intakes required for growth along birth centile line may be higher than those currently recommended, and warrant further investigation.