The Associations between Snack Intake and Cariogenic Oral Microorganism Colonization in Young Children of a Low Socioeconomic Status.
Ahmed AlkadiNaemah AlkharsSamantha ManningHongzhe XuMichael SohnJin XiaoYing MengPublished in: Nutrients (2024)
Cariogenic microorganisms are crucial pathogens contributing to the development of early childhood caries. Snacks provide fermentable carbohydrates, altering oral pH levels and potentially affecting microorganism colonization. However, the relationship between snack intake and cariogenic microorganisms like Candida and Streptococcus mutans in young children is still unclear. This study aimed to assess this association in a prospective underserved birth cohort. Data from children aged 12 to 24 months, including oral microbial assays and snack intake information, were analyzed. Sweet and non-sweet indices based on the cariogenic potential of 15 snacks/drinks were created. Mixed-effects models were used to assess the associations between sweet and non-sweet indices and S. mutans and Candida carriage. Random forest identified predictive factors of microorganism carriage. Higher non-sweet index scores were linked to increased S. mutans carriage in plaques (OR = 1.67, p = 0.01), potentially strengthening with age. Higher sweet index scores at 12 months were associated with increased Candida carriage, reversing at 24 months. Both indices were top predictors of S. mutans and Candida carriage. These findings underscore the associations between snack intake and cariogenic microorganism carriage and highlight the importance of dietary factors in oral health management for underserved young children with limited access to dental care and healthy foods.
Keyphrases
- candida albicans
- biofilm formation
- oral health
- pseudomonas aeruginosa
- staphylococcus aureus
- escherichia coli
- weight gain
- healthcare
- palliative care
- climate change
- body mass index
- electronic health record
- health information
- deep learning
- antimicrobial resistance
- artificial intelligence
- multidrug resistant
- data analysis