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The Consang-Mashup Database System for the study of consanguinity

Black, M.L., Tangtulyangkul, P., Hunter, A., Bellgard, M. and Bittles, A.H. (2008) The Consang-Mashup Database System for the study of consanguinity. In: International Conference on Medical and Community Genetics, 15 - 17 February, Chandigarh, India.


Introduction: As a working definition, marriages contracted between persons genetically related as second cousins or closer (F ≥ 0.0156) are categorized as consanguineous. The ability to evaluate the incidence and types of consanguineous marriage in specific communities, regions or nations has become increasingly vital in terms of genetic education and genetic counseling programmes, and in assessing genetic association and genetic linkage studies.

Objectives : Using the website as starting-point, the aim was to create a user-friendly, interactive public database on the global prevalence of consanguineous marriage and its clinical, genetic and demographic outcomes.

Methods: A publicly accessible web application was constructed using data from with the open-source cakePHP framework ( and Google Map Application Programming Interface (API) (

Results: The resulting database provides an interactive and readily updatable global catalogue of consanguineous marriage, with precise geographical mapping of published studies. The visual display capacity has revealed important sampling and analysis patterns not previously resolved, in particular the unrepresentative regional clustering of data within specific countries.

Conclusion: Since its inception has proved to be a popular, frequently accessed website for both health professionals and the general public. The new Consang-Google Map will enable researchers to assess consanguineous marriage and its health outcomes with greater ease, clarity, and detail. It will also help in the planning and focus of future health-based studies on communities and areas for which current information is inadequate.

Item Type: Conference Item
Murdoch Affiliation(s): Centre for Comparative Genomics
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