ESPE2024 Poster Category 2 Growth and Syndromes (39 abstracts)
Hamad General Hospital, Doha, Qatar
Background: Understanding the growth trajectories of preterm Appropriate for Gestational Age (AGA) infants with birth weights under 1.5 kg is crucial for optimizing their long-term health outcomes. This study explores the correlations between various growth parameters over five years to identify predictive markers for future growth.
Methods: A longitudinal cohort study was conducted on preterm AGA infants (n = 50) born between Sep 2017 – Sep 2018 with birth weights less than 1.5 kg. Growth parameters measured included Weight for Age Z-score (WAZ), Length for Age Z-score (LAZ), Weight for Length Z-score (WLZ), Body Mass Index (BMI), and BMI Z-score (BMIZ). Data were collected at birth and multiple intervals up to 60 months. Correlation analysis assessed the relationships between these growth metrics over time.
Results: WAZ at 60 months showed moderate to high correlations with earlier WAZ measurements, indicating a persistent influence of early weight status. WLZ at younger ages moderately predicted WAZ at 60 months. Early length measurements were less predictive of later weight. Length at 60 months correlated moderately with earlier LAZ measurements, especially LAZ at 36 months (r = 0.52, P <0.01), suggesting consistent length growth. BMIZ at 60 months had high correlations with earlier BMIZ, particularly at 36 months *r = 0.58, P < 0.01). This suggests that BMI is a consistent indicator over time. Moderate correlations of BMIZ at 60 months with WAZ and WLZ scores indicate the relevance of both absolute weight and body proportions in predicting future BMI.
Conclusion: The study highlights that early weight status and BMI are significant predictors of similar outcomes at 60 months in preterm AGA infants with low birth weights. Length measurements show consistent growth but are less predictive of weight outcomes. These findings underscore the importance of monitoring specific growth parameters in early childhood for predicting long-term growth trends in this vulnerable population.