International Journal of Population Data Science (Mar 2020)

Parity: A key measure of confounding in data-linkage studies of outcomes after medically assisted reproduction

  • Georgina M Chambers, Associate Professor,
  • Christos A Venetis, Dr,
  • Louisa R Jorm, Professor,
  • Claire M Vajdic, Associate Professor

DOI
https://doi.org/10.23889/ijpds.v5i1.1119
Journal volume & issue
Vol. 5, no. 1

Abstract

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Parity is a potential confounder of the association between medically assisted reproduction (MAR) and health outcomes. This concept paper describes a population-based record linkage study design for selecting MAR-unexposed women matched to the parity of MAR-exposed women, at the time of the first exposure to MAR. Women exposed to MAR were identified from claims for government subsidies for relevant procedures and prescription medicines, linked to perinatal records. Women unexposed to MAR were identified from linked perinatal and death records, matched to exposed women by age, rurality, age of first child (if any) and parity at the date of first MAR. The availability of a longitudinal, whole-of-population dataset (“population spine”) based on enrolments in Australia’s universal health insurance scheme was a critical design element. The example application examines cancer risk in women after exposure to MAR. Parity is a confounder in this setting because it is associated with MAR and hormone-sensitive cancers.