One-year anthropometric follow-up of South African preterm infants in kangaroo mother care: Which early-life factors predict malnutrition?

BACKGROUND: Preterm infants often have poor short- and long-term growth. Kangaroo mother care supports short-term growth, but longer-term outcomes are unclear. METHODS: This study analysed longitudinally collected routine clinical data from a South African cohort of preterm infants (born <37 weeks gestation) attending the outpatient follow-up clinic of a tertiary-level hospital (Tshwane District, South Africa) for 1 year between 2012 and 2019. At 1 year, small-for-gestational age (SGA) and appropriate-for-gestational age (AGA) infants were compared with regard to age-corrected anthropometric z-scores (weight-for-age [WAZ], length-for-age [LAZ], weight-for-length [WLZ] and BMI-for-age [BMIZ]) and rates of underweight (WAZ < -2), stunting (LAZ < -2), wasting (WLZ < -2) and overweight (BMIZ> + 2). Multiple regression analysis was used to investigate associations between maternal/infant characteristics and rates of underweight, stunting, wasting and overweight. RESULTS: At 1 year, compared with AGA infants (n = 210), SGA infants (n = 111) had lower WAZ (-1.26 ± 1.32 vs. -0.22 ± 1.24, p < 0.001), LAZ (-1.50 ± 1.11 vs. -0.60 ± 1.06, p < 0.001), WLZ (-0.66 ± 1.31 vs. 0.11 ± 1.24, p < 0.001) and BMIZ (-0.55 ± 1.31 vs. 1.06 ± 1.23, p < 0.001), despite larger WAZ gains from birth (+0.70 ± 1.30 vs. +0.05 ± 1.30, p < 0.001). SGA infants had significantly more stunting (34.2% vs. 9.1%; p < 0.001), underweight (31.2% vs. 7.2%; p < 0.001) and wasting (12.6% vs. 4.3%, p = 0.012), with no difference in overweight (4.5% vs. 7.7%, p = 0.397). In multiple regression analysis, birth weight-for-GA z-score more consistently predicted 1-year malnutrition than SGA. CONCLUSION: Preterm-born SGA infants remain more underweight, stunted and wasted than their preterm-born AGA peers at 1 year, despite greater WAZ gains. Interventions for appropriate catch-up growth especially for SGA preterm infants are needed.

Integrated growth assessment in the first 1000 d of life: an interdisciplinary conceptual framework.

OBJECTIVES: Prenatal growth affects short- and long-term morbidity, mortality and growth, yet communication between prenatal and postnatal healthcare teams is often minimal. This paper aims to develop an integrated, interdisciplinary framework for foetal/infant growth assessment, contributing to the continuity of care across the first 1000 d of life. DESIGN: A multidisciplinary think-tank met regularly over many months to share and debate their practice and research experience related to foetal/infant growth assessment. Participants' personal practice and knowledge were verified against and supplemented by published research. SETTING: Online and in-person brainstorming sessions of growth assessment practices that are feasible and valuable in resource-limited, low- and middle-income country (LMIC) settings. PARTICIPANTS: A group of obstetricians, paediatricians, dietitians/nutritionists and a statistician. RESULTS: Numerous measurements, indices and indicators were identified for growth assessment in the first 1000 d. Relationships between foetal, neonatal and infant measurements were elucidated and integrated into an interdisciplinary framework. Practices relevant to LMIC were then highlighted: antenatal Doppler screening, comprehensive and accurate birth anthropometry (including proportionality of weight, length and head circumference), placenta weighing and incorporation of length-for-age, weight-for-length and mid-upper arm circumference in routine growth monitoring. The need for appropriate, standardised clinical records and corresponding policies to guide clinical practice and facilitate interdisciplinary communication over time became apparent. CONCLUSIONS: Clearer communication between prenatal, perinatal and postnatal health care providers, within the framework of a common understanding of growth assessment and a supportive policy environment, is a prerequisite to continuity of care and optimal health and development outcomes.

Association of Prenatal Placental Function with Anthropometry and Body Composition through 2 years of Age in South African Infants: The UmbiBaby Study.

BACKGROUND: Placental insufficiency negatively impacts fetal growth and body composition (BC), potentially affecting lifelong health. Placental insufficiency, detectable as an abnormal umbilical artery resistance index (UmA-RI) on Doppler ultrasonography, is highly prevalent in otherwise healthy South African pregnant women. Appropriate intervention reduces stillbirth and perinatal death, but research on long-term outcomes of surviving infants is lacking. OBJECTIVES: This study aimed to describe and compare anthropometry and BC during the first 2 y of life in a cohort of term-born infants with normal and abnormal prenatal UmA-RI. METHODS: Term-born infants (n = 81; n = 55 normal, n = 26 abnormal UmA-RI on third trimester Doppler screening) were followed up at 8-time points until age 2 y. Anthropometric measurements were taken, and FFM and FM were assessed by deuterium dilution. Age- and sex-specific z-scores were calculated for anthropometric indices, FM, FFM, FM index (FMI), and FFM index (FFMI) using appropriate reference data. Anthropometry and BC of infants with normal and abnormal UmA-RI were compared using an independent t-test or Mann-Whitney test. RESULTS: At most ages, group mean z-scores were <0 for length-for-age and FM and >0 for weight-for-length and FFM. Compared with infants with normal UmA-RI, infants with abnormal UmA-RI had significantly lower weight-for-age z-scores at birth (-0.77 ± 0.75 compared with -0.30 ± 1.10, P = 0.026), ages 10 wk to 9 mo (-0.4 ± 0.87 to -0.2 ± 1.12 compared with 0.3 ± 0.85 to 0.6 ± 1.09; P = 0.007-0.017) and 18 mo (-0.6 ± 0.82 compared with 0.1 ± 1.18; P = 0.037); length-for-age z-scores at ages ≤14 wk (-1.3 ± 1.25 to -0.9 ± 0.87 compared with -0.2 ± 1.04 to -0.1 ± 1.00; P = 0.004-0.021); and FFM-for-age z-scores at ages ≤9 mo (-0.1 ± 0.82 to 0.7 ± 0.71 compared with 0.7 ± 1.00 to 1.3 ± 0.85; P = 0.002-0.028). FFMI, percentage FFM, FM, percentage FM, and FMI showed no consistent significant differences. CONCLUSIONS: Infants with abnormal UmA-RI had lower weight-for-age and length-for-age z-scores, particularly at younger ages, with proportionally lower FFM but no consistent differences in percentage FFM and FFMI. These findings merit further investigation in larger cohorts.

A novel screening tool to predict severe acute malnutrition through automated monitoring of weight-for-age growth curves.

Weight-for-age (WFA) growth faltering often precedes severe acute malnutrition (SAM) in children, yet it is often missed during routine growth monitoring. Automated interpretation of WFA growth within electronic health records could expedite the identification of children at risk of SAM. This study aimed to develop an automated screening tool to predict SAM risk from WFA growth, and to determine its predictive ability compared with simple changes in weight or WFA z-score. To develop the screening tool, South African child growth experts (n = 30) rated SAM risk on 100 WFA growth curves, which were then used to train an artificial neural network (ANN) to assess SAM risk from consecutive WFA z-scores. The ANN was validated in 185 children under five (63 SAM cases; 122 controls) using diagnostic accuracy methodology. The ANN's performance was compared with that of changes in weight or WFA z-score. Even though experts' SAM risk ratings of the WFA growth curves differed considerably, the ANN achieved a sensitivity of 73.0% (95% confidence interval [CI]: 60.3; 83.4), specificity of 86.1% (95% CI: 78.6; 91.7) and receiver-operating characteristic curve area of 0.795 (95% CI: 0.732; 0.859) during validation with real cases, outperforming changes in weight or WFA z-scores. The ANN, as an automated screening tool, could markedly improve the identification of children at risk of SAM using routinely collected WFA growth information.