Literature DB >> 18313563

Unlinked vital events in census-based longitudinal studies can bias subsequent analysis.

Dermot O'Reilly1, Michael Rosato, Sheelah Connolly.   

Abstract

OBJECTIVE: To examine the potential biases arising from the nonlinkage of census records and vital events in longitudinal studies. STUDY DESIGN AND
SETTING: A total of 56,396 deaths of residents of Northern Ireland in the 4 years after the 2001 Census were linked to the 2001 Census records. The characteristics of matched and nonmatched death records were compared using multivariate logistic regression. Subject attributes were as recorded on the death certificate.
RESULTS: In total, 3,392 (6.0%) deaths could not be linked to a census record. Linkage rates were lowest in young adults, males, the unmarried, people living in communal establishments, or living in areas that were more deprived or had recorded low census enumeration. For those aged less than 65 years at census, this linkage would exclude from analysis 20.2% of suicides and 19.7% of deaths by external causes.
CONCLUSION: The nonlinkage of census and death records is a combination of nonenumeration at census and deficient information about the deceased recorded at the time of death. Unmatched individuals may have been more disadvantaged or socially isolated, and analysis based on the linked data set may therefore show some bias and perhaps understate true social gradients.

Entities:  

Mesh:

Year:  2007        PMID: 18313563     DOI: 10.1016/j.jclinepi.2007.05.012

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  9 in total

1.  Impact of unlinked deaths and coding changes on mortality trends in the Swiss National Cohort.

Authors:  Kurt Schmidlin; Kerri M Clough-Gorr; Adrian Spoerri; Matthias Egger; Marcel Zwahlen
Journal:  BMC Med Inform Decis Mak       Date:  2013-01-04       Impact factor: 2.796

2.  Creating a Powerful Platform to Explore Health in a Correctional Population: A Record Linkage Study.

Authors:  Kathryn E McIsaac; Shanna Farrell MacDonald; Nelson Chong; Andrea Moser; Rahim Moineddin; Angela Colantonio; Avery Nathens; Flora I Matheson
Journal:  PLoS One       Date:  2016-08-17       Impact factor: 3.240

3.  On the plausibility of socioeconomic mortality estimates derived from linked data: a demographic approach.

Authors:  Mathias Lerch; Adrian Spoerri; Domantas Jasilionis; Francisco Viciana Fernandèz
Journal:  Popul Health Metr       Date:  2017-07-14

4.  Comparison of reproductive history gathered by interview and by vital records linkage after 40 years of follow-up: Bogalusa Babies.

Authors:  Emily W Harville; Marni Jacobs; Tian Shu; Dorothy Breckner; Maeve Wallace
Journal:  BMC Med Res Methodol       Date:  2019-06-04       Impact factor: 4.615

5.  The increasing lifespan variation gradient by area-level deprivation: A decomposition analysis of Scotland 1981-2011.

Authors:  Rosie Seaman; Tim Riffe; Alastair H Leyland; Frank Popham; Alyson van Raalte
Journal:  Soc Sci Med       Date:  2019-04-16       Impact factor: 4.634

6.  The association between self-reported mental health, medication record and suicide risk: A population wide study.

Authors:  Ifeoma N Onyeka; Dermot O'Reilly; Aideen Maguire
Journal:  SSM Popul Health       Date:  2021-02-02

7.  Parental mental health and risk of poor mental health and death by suicide in offspring: a population-wide data-linkage study.

Authors:  A Maguire; E Ross; D O'Reilly
Journal:  Epidemiol Psychiatr Sci       Date:  2022-04-19       Impact factor: 7.818

8.  A guide to evaluating linkage quality for the analysis of linked data.

Authors:  Katie L Harron; James C Doidge; Hannah E Knight; Ruth E Gilbert; Harvey Goldstein; David A Cromwell; Jan H van der Meulen
Journal:  Int J Epidemiol       Date:  2017-10-01       Impact factor: 7.196

9.  Which long-term illnesses do patients find most limiting? A census-based cross-sectional study of 340,000 people.

Authors:  David M Wright; Michael Rosato; Dermot O'Reilly
Journal:  Int J Public Health       Date:  2016-12-09       Impact factor: 3.380

  9 in total

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