Accuracy of Offspring-Reported Parental Hip Fractures: A Novel Population-Based Parent-Offspring Record Linkage Study

Am J Epidemiol. 2017 May 15;185(10):974-981. doi: 10.1093/aje/kww197.

Abstract

The objective of this study was to test the validity of offspring-reported parental hip fracture in a unique bone mineral density (BMD) registry linked to administrative databases spanning 4 decades. Population-based data were from Manitoba, Canada, and included hospital abstracts, health insurance registrations, and the provincewide BMD registry. The cohort included individuals aged ≥40 years with BMD tests and self-reports of parental hip fracture between 2006 and 2014. Population registry data for 1966-2014 were used to link offspring with their parents, and hospital records were used to ascertain parental fractures. Overall, 8,112 offspring met the inclusion criteria; 13.6% had a parental hip fracture diagnosis in administrative data during an average of 32.9 years of follow-up. Agreement between parental hip fracture from offspring reports and diagnoses in administrative data was good (κ = 0.68). The sensitivity of offspring reports was 0.70 (95% confidence interval: 0.67, 0.73), and specificity was 0.96 (95% confidence interval: 0.96, 0.97). Offspring characteristics associated with disagreement included male sex, northern rural residence, early BMD test year, and longer interval between BMD test and parental hip fracture diagnosis. This proof-of-concept study focused on hip fractures, but use of record linkage techniques to validate offspring-reported parental information can be extended to other conditions.

Keywords: data linkage; database; family characteristics; hip fracture; pedigree; registries; validation studies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Adult Children / statistics & numerical data*
  • Bone Density*
  • Female
  • Hip Fractures / epidemiology*
  • Humans
  • Male
  • Manitoba
  • Medical Record Linkage / standards*
  • Middle Aged
  • Registries / statistics & numerical data*
  • Reproducibility of Results
  • Residence Characteristics
  • Sex Factors
  • Time Factors