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Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors
Joint Authors
Ogunyemi, Theophilus O.
Siadat, Mohammad-Reza
Killinger, Kim A.
Arslanturk, Suzan
Diokno, Ananias C.
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-10-31
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Longitudinal data for studying urinary incontinence (UI) risk factors are rare.
Data from one study, the hallmark Medical, Epidemiological, and Social Aspects of Aging (MESA), have been analyzed in the past; however, repeated measures analyses that are crucial for analyzing longitudinal data have not been applied.
We tested a novel application of statistical methods to identify UI risk factors in older women.
MESA data were collected at baseline and yearly from a sample of 1955 men and women in the community.
Only women responding to the 762 baseline and 559 follow-up questions at one year in each respective survey were examined.
To test their utility in mining large data sets, and as a preliminary step to creating a predictive index for developing UI, logistic regression, generalized estimating equations (GEEs), and proportional hazard regression (PHREG) methods were used on the existing MESA data.
The GEE and PHREG combination identified 15 significant risk factors associated with developing UI out of which six of them, namely, urinary frequency, urgency, any urine loss, urine loss after emptying, subject’s anticipation, and doctor’s proactivity, are found most highly significant by both methods.
These six factors are potential candidates for constructing a future UI predictive index.
American Psychological Association (APA)
Ogunyemi, Theophilus O.& Siadat, Mohammad-Reza& Arslanturk, Suzan& Killinger, Kim A.& Diokno, Ananias C.. 2012. Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors. Advances in Urology،Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-459651
Modern Language Association (MLA)
Ogunyemi, Theophilus O.…[et al.]. Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors. Advances in Urology No. 2012 (2012), pp.1-8.
https://search.emarefa.net/detail/BIM-459651
American Medical Association (AMA)
Ogunyemi, Theophilus O.& Siadat, Mohammad-Reza& Arslanturk, Suzan& Killinger, Kim A.& Diokno, Ananias C.. Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors. Advances in Urology. 2012. Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-459651
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-459651