Background: Coeliac Disease (CD) often has its onset in childhood and affects 1% of the population. This review aimed to identify important predictive factors for coeliac disease in children and young people which could help GPs decide when to offer testing.
Methods: We searched MEDLINE, Embase and Cochrane Library to April 2024. Included studies were observational or randomized trials reporting the risk of CD when exposed to predictive factor(s) in people ≤25 years of age. Genetic factors were excluded. Risk of Bias was assessed using the Newcastle-Ottawa Scale. Random effects meta-analysis was performed for factors reported in ≥5 studies to calculate pooled odds ratios (OR) or standardized mean differences (SMD).
Results: Of 11,623 unique abstracts, 183 were included reporting on 140+ potentially associated factors. Meta-analyses of 28 factors found 14 significant associations with CD diagnosis: having type 1 diabetes (OR 8.70), having a first degree relative with coeliac disease (OR 5.19), being of white ethnicity (OR 2.56), having thyroid disease (OR 2.16), being female (OR 1.53), more frequent gastroenteritis in early childhood (OR 1.48), having frequent respiratory infections in early childhood (OR 1.47), more gluten ingestion in early life (OR 1.25), having more infections in early life (OR 1.22), antibiotic use in early childhood (OR 1.21), being born in the summer (OR 1.09), breastfeeding (OR 0.79) older age at diagnosis of type 1 diabetes (OR 0.64), and heavier weight (SMD -0.21). The final three were associated with lower risk of CD diagnosis.
Discussion: This is the first systematic review and meta-analysis of predictive factors for CD in children. Amongst the 14 factors we identified that were significant, three were potentially modifiable: breast feeding, antibiotic use and amount of gluten ingestion in early childhood. This work could inform the development of clinical support tools to facilitate the early diagnosis of CD.
Copyright: © 2024 Farrier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.