Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-28T10:20:19.451Z Has data issue: false hasContentIssue false

Similarity of social security numbers among twins: data from the Virginia Twin Registry

Published online by Cambridge University Press:  21 February 2012

William F Page*
Affiliation:
Medical Follow-up Agency, Institute of Medicine, National Academy of Sciences, Washington, DC, USA. [email protected]
Linda Corey
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
*
*Correspondence: Dr William Page, Medical Follow-up Agency, National Academy of Sciences, 2101 Constitution Avenue, NW, Washington, DC, 20418, USA. Tel: 202 334 2828; Fax: 202 334 2685

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

At least two twin registries in the United States have been or are being assembled using the similarity of Social Security Numbers in computerized records to help identify possible twin pairs. While the success of such enterprises depends directly on a high probability of twinness given Social Security Numbers, there are theoretical and practical reasons to study the probability of Social Security Number similarity given twinness. For example, the number of twin pairs with similar Social Security Numbers obviously determines the maximum number of twin pairs that can be discovered by similarity algorithms. To study this issue, we examined the similarity of known Social Security Numbers in twin pairs from the Virginia Twin Registry by age, sex, race, and zygosity of the pair. We found that similarity between the Social Security Numbers of twin pairs varies markedly by age, and MZ twin pairs have significantly more similar Social Security Numbers than DZ pairs at all ages. Among older twins, there are also significant differences by sex and race. For younger twins, algorithms that identify putative twin pairs on the basis of the similarity of their Social Security Numbers hold the promise of being able to identify a large proportion of all true twin pairs. Such algorithms will be substantially less successful, however, in identifying a large proportion of older twin pairs.

Type
Articles
Copyright
Copyright © Cambridge University Press 1998