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BackgroundLinkage of demographic, health, and developmental administrative data can enrich population-based surveillance and research on developmental and educational outcomes. Transparency of the record linkage process and results are required to assess potential biases. ObjectivesTo describe the approach used to link records of kindergarten children from the Early Development Instrument (EDI) in Ontario to health administrative data and test differences in characteristics of children by linkage status. We demonstrate how socio-demographic and medical risk factors amass in their contribution to early developmental vulnerability and test the concordance of health diagnoses in both the EDI and health datasets of linked records. MethodsChildren with records in the 2015 EDI cycle were deterministically linked to a population registry in Ontario, Canada. We compared sociodemographic and developmental vulnerability data between linked and unlinked records. Among linked records, we examined the contribution of medical and social risk factors obtained from health administrative data to developmental vulnerability identified in the EDI using descriptive analyses. ResultsOf 135,937 EDI records, 106,217 (78.1%) linked deterministically to a child in the Ontario health registry using birth date, sex, and postal code. The linked cohort was representative of children who completed the EDI in age, sex, rural residence, immigrant status, language, and special needs status. Linked data underestimated children living in the lowest neighbourhood income quintile (standardized difference [SD] 0.10) and with higher vulnerability in physical health and well-being (SD 0.11) , social competence (SD 0.10), and language and cognitive development (SD 0.12). Analysis of linked records showed developmental vulnerability is sometimes greater in children with social risk factors compared to those with medical risk factors. Common childhood conditions with records in health data were infrequently recorded in EDI records. ConclusionsLinkage of early developmental and health administrative data, in the absence of a single unique identifier, can be successful with few systematic biases introduced. Cross-sectoral linkages can highlight the relative contribution of medical and social risk factors to developmental vulnerability and poor school achievement.

The Canadian Neighbourhoods Early Child Development (CanNECD) database is a unique resource for research on child developmental health and well-being within the socioeconomic and cultural context of Canadian neighbourhoods. This paper describes the CanNECD database and highlights its potential for advancing research at the intersection of child development, social determinants of health, and neighborhood effects. The CanNECD database contains Pan-Canadian population-level child developmental health data collected through regional implementation of the Early Development Instrument (EDI), geo-coded information on residential neighbourhoods covering all of Canada, and socioeconomic and demographic variables from the Canada Census and Income Taxfiler database. The data are de-identified but linkable across datasets through use of common numeric sequences. The nearly 800,000 records spanning 2003-2014 and representing all Canadian provinces and territories (with the exception of Nunavut) are compiled in a secure electronic collection system at the Offord Centre for Child Studies, McMaster University in Hamilton, Canada. Early studies using the EDI demonstrated its utility as a tool for assessing child developmental health at a population level, and its potential for both community-level and large-scale monitoring of child populations. Research using the CanNECD database is now examining to what extent social determinants and the steepness of the social gradients of developmental health differ between geographical jurisdictions and between different sub-populations. We are also working to identify outlier neighbourhoods in which EDI scores are substantially higher or lower than predicted by a neighbourhood’s demographic and socioeconomic characteristics, and exploring other potentially important determinants of children’s developmental health. Finally, we are examining the extent to which change-over-time in aggregate EDI scores vary geographically, and how well it coincides with changes in socioeconomic factors. Thus, the CanNECD database offers the opportunity for research that will inform national policies and strategies on child developmental health.

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