Affiliation:
1. Department of Human Nutrition University of Pretoria Pretoria South Africa
2. Research Centre for Maternal, Fetal, Newborn & Child Health Care Strategies University of Pretoria Atteridgeville South Africa
3. South African Medical Research Council (SA MRC) Maternal and Infant Health Care Strategies Unit Atteridgeville South Africa
4. Department of Paediatrics University of Pretoria Pretoria South Africa
5. Tshwane District Health Services Gauteng Department of Health Pretoria South Africa
6. Department of Statistics University of Pretoria Pretoria South Africa
Abstract
AbstractPost‐natal growth influences short‐ and long‐term preterm infant outcomes. Different growth charts, such as the Fenton Growth Chart (FGC) and INTERGROWTH‐21st Preterm Post‐natal Growth Standards (IG‐PPGS), describe different growth curves and targets. This study compares FGC‐ and IG‐PPGS‐derived weight‐for‐postmenstrual age z‐score (WZ) up to 50 weeks postmenstrual age (PMA50) for predicting 1‐year anthropometry in 321 South African preterm infants. The change in WZ from birth to PMA50 (ΔWZ, calculated using FGC and IG‐PPGS) was correlated to age‐corrected 1‐year anthropometric z‐scores for weight‐for‐age (WAZ), length‐for‐age (LAZ), weight‐for‐length (WLZ) and BMI‐for‐age (BMIZ), and categorically compared with rates of underweight (WAZ < −2), stunting (LAZ < −2), wasting (WLZ < −2) and overweight (BMIZ > + 2). Multivariable analyses explored the effects of other early‐life exposures on malnutrition risk. At PMA50, mean WZ was significantly higher on IG‐PPGS (−0.56 ± 1.52) than FGC (−0.90 ± 1.52; p < 0.001), but ΔWZ was similar (IG‐PPGS −0.26 ± 1.23, FGC −0.11 ± 1.14; p = 0.153). Statistically significant ΔWZ differences emerged among small‐for‐gestational age infants (FGC −0.38 ± 1.22 vs. IG‐PPGS −0.01 ± 1.30; p < 0.001) and appropriate‐for‐gestational age infants (FGC + 0.02 ± 1.08, IG‐PPGS −0.39 ± 1.18; p < 0.001). Correlation coefficients of ΔWZ with WAZ, LAZ, WLZ and BMIZ were low (r < 0.45), though higher for FGC than IG‐PPGS. Compared with IG‐PPGS, ΔWZ < −1 on FGC predicted larger percentages of underweight (42% vs. 36%) and wasting (43% vs. 39%) and equal percentages of stunting (33%), while ΔWZ > + 1 predicted larger percentages overweight (57% vs. 38%). Both charts performed similarly in multivariable analysis. Differences between FGC and IG‐PPGS are less apparent when considering ΔWZ, highlighting the importance of assessing growth as change over time, irrespective of growth chart.