Maternal and demographic factors influencing oral Candida albicans in infants: A stratified analysis using a novel partial linear semiparametric mixed-effects model.

Candida albicans, a pathogenic fungus implicated in early childhood caries (ECC), plays a crucial role in oral health. While its colonization usually begins at birth, the extent of maternal involvement in yeast transmission to their offspring, particularly across different racial groups, remains unclear. Studies have shown elevated levels of C. albicans in both mothers and children, with genetically related fungal strains, suggesting maternal transmission, but the racial component, notably higher levels in Black children, lacks thorough investigation of underlying factors. Our research aimed to address this gap by investigating how maternal and demographic factors such as socioeconomic status and oral health affect C. albicans levels in infants across Black and non-Black populations. Employing a partial linear semiparametric mixed-effects model (PLSMM) with variable selection and race-based stratification, we identified predictors that have different effects depending on the infant's race among a large pool of predictors. Through this stratified analysis, we aimed to discern crucial factors significantly contributing to C. albicans colonization while minimizing the impact of irrelevant or redundant variables. In this stratified analysis, exclusive breastfeeding ([Formula: see text]) and maternal marriage ([Formula: see text]) were significant predictors among non-Black infants, while maternal employment ([Formula: see text]) and post-delivery maternal C. albicans ([Formula: see text]) were significant among Black infants. Our findings highlighted race-specific associations between C. albicans levels in children and factors such as breastfeeding practices, marital status, maternal oral hygiene, and maternal C. albicans levels. Our study underscores the importance of race-specific considerations in understanding C. albicans colonization in infants, offering insights for tailored interventions and healthcare strategies, particularly for vulnerable populations.