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Association of factors with childhood asthma and allergic diseases using latent class analysis
Teresa To1, Cornelia M Borkhoff2, Laura N Anderson3
1Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, Hospital for Sick Children, 686 Bay St, Toronto, ON, M5G 0A4, Canada. teresa.to@sickkids.ca.
Insights
Children from disadvantaged backgrounds face higher risks of asthma, allergic rhinitis, and eczema. These health disparities are linked to specific mother-child clusters identified through latent class analysis (LCA), highlighting the impact of socioeconomic and environmental factors.
Area of Science:
- Pediatric Health Research
- Epidemiology
- Social Determinants of Health
Background:
- Children from deprived backgrounds often experience poorer health outcomes.
- Identifying clusters of determinants is crucial for understanding early childhood disease risks.
- Longitudinal studies are essential for tracking health trajectories from birth.
Purpose of the Study:
- To identify clusters of maternal and child determinants using latent class analysis (LCA).
- To estimate the risk of early childhood diseases (asthma, allergic rhinitis, eczema) associated with these clusters.
- To quantify children's health services use (HSU) in relation to identified clusters.
Main Methods:
- A 1993-2019 longitudinal cohort study combining three Canadian pediatric cohorts.
- Latent class analysis (LCA) used to cluster mothers and children based on 16 indicators across maternal, socioeconomic, and environmental domains.
- Cox proportional hazards regression and Poisson regression used to quantify disease risks and health services use.
Main Results:
- Four distinct mother-clusters were identified among 15,724 mother-child pairs.
- Mothers in younger, immigrant/refugee clusters (Classes 3 and 4) with lower SES and poorer environmental exposures had children with significantly higher risks of asthma, allergic rhinitis, and eczema compared to Class 1.
- Children with allergic rhinitis or eczema in Class 3 showed increased physician and emergency department visits.
Conclusions:
- Latent class analysis effectively identified mother-child clusters associated with differential health outcomes.
- Disadvantaged socioeconomic and environmental factors within specific clusters are linked to increased risks of childhood allergic diseases.
- These findings underscore the importance of addressing multifactorial determinants in pediatric health and healthcare utilization.
Abstract:
We hypothesize that children characterized by deprived factors have poorer health outcomes. We aim to identify clustering of determinants and estimate risk of early childhood diseases. This 1993-2019 longitudinal cohort study combines three Canadian pediatric cohorts and their families. Mothers and children are clustered using latent class analysis (LCA) by 16 indicators in three domains (maternal and newborn; socioeconomic status [SES] and neighbourhood; environmental exposures). Hazard ratios (HR) of childhood asthma, allergic rhinitis (AR), and eczema are quantified with Cox proportional hazard (PH) regression. Rate ratios (RR) of children's health services use (HSU) are estimated with Poisson regression. Here we report the inclusion of 15,724 mother-child pairs; our LCA identifies four mother-clusters. Classes 1 and 2 mothers are older (30-40 s), non-immigrants with university education, living in high SES neighbourhoods; Class 2 mothers have poorer air quality and less greenspace. Classes 3 and 4 mothers are younger (20-30 s), likely an immigrant/refugee, with high school-to-college education, living in lower SES neighborhoods with poorer air quality and less greenspace. Children's outcomes differ by Class, in comparison to Class 1. Classes 3 and 4 children have higher risks of asthma (HR 1.24, 95% CI 1.11-1.37 and HR 1.39, 95% CI 1.22-1.59, respectively), and similar higher risks of AR and eczema. Children with AR in Class 3 have 20% higher all-cause physician visits (RR = 1.20, 95% CI 1.10-1.30) and those with eczema have 18% higher all-cause emergency department visits (RR = 1.18, 95% CI 1.09-1.28) and 14% higher all-cause physician visits (RR = 1.14, 95% CI 1.09-1.19). Multifactorial-LCA mother-clusters may characterize associations of children's health outcomes and care, adjusting for interrelationships.
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