Objectives: The purpose of the study is to examine whether there is an association between neighbourhood deprivation and incidence of congenital heart disease (CHD), after accounting for family- and individual-level potential confounders. Methods: All children aged 0 to 11 years and living in Sweden (n = 748,951) were followed between January 1, 2000 and December 31, 2010. Data were analysed by multilevel logistic regression, with family- and individual-level characteristics at the first level and level of neighbourhood deprivation at the second level. Results: During the study period, among a total of 748,951 children, 1499 (0.2 %) were hospitalised with CHD. Age-adjusted cumulative hospitalisation rates for CHD increased with increasing level of neighbourhood deprivation. In the study population, 1.8 per 1000 and 2.2 per 1000 children in the least and most deprived neighbourhoods, respectively, were hospitalised with CHD. The incidence of hospitalisation for CHD increased with increasing neighbourhood-level deprivation across all family and individual-level socio-demographic categories. The odds ratio (OR) for hospitalisation for CHD for those living in high-deprivation neighbourhoods versus those living in low-deprivation neighbourhoods was 1.23 (95 % confidence interval (CI) = 1.04–1.46). In the full model, which took account for age, paternal and maternal individual-level socio-economic characteristics, comorbidities (e.g. maternal type 2 diabetes, OR = 3.03; maternal hypertension, OR = 2.01), and family history of CHD (OR = 3.27), the odds of CHD were slightly attenuated but did not remain significant in the most deprived neighbourhoods (OR = 1.20, 95 % CI = 0.99–1.45, p = 0.057). Conclusions: This study is the largest so far on neighbourhood influences on CHD, and the results suggest that deprived neighbourhoods have higher rates of CHD, which represents important clinical knowledge. However, the association does not seem to be independent of individual- and family-level characteristics.
- Congenital heart disease
- Multilevel modelling
- Neighbourhood-level deprivation
- Socio-demographic factors