文章基本信息

标题：Parity: A key measure of confounding in data-linkage studies of outcomes after medically assisted reproduction
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作者：Georgina M Chambers ; Christos A Venetis ; Louisa R Jorm 等
期刊名称：International Journal of Population Data Science
电子版ISSN：2399-4908
出版年度：2020
卷号：5
期号：1
页码：1-5
DOI：10.23889/ijpds.v5i1.1119
出版社：Swansea University
摘要：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.
其他摘要：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.