Please use this identifier to cite or link to this item: https://doi.org/10.1186/1471-2318-10-55
DC FieldValue
dc.titleIndicators of "healthy aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival
dc.contributor.authorSwindell, W.R
dc.contributor.authorEnsrud, K.E
dc.contributor.authorCawthon, P.M
dc.contributor.authorCauley, J.A
dc.contributor.authorCummings, S.R
dc.contributor.authorMiller, R.A
dc.date.accessioned2020-10-27T11:36:58Z
dc.date.available2020-10-27T11:36:58Z
dc.date.issued2010
dc.identifier.citationSwindell, W.R, Ensrud, K.E, Cawthon, P.M, Cauley, J.A, Cummings, S.R, Miller, R.A (2010). Indicators of "healthy aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival. BMC Geriatrics 10 : 55. ScholarBank@NUS Repository. https://doi.org/10.1186/1471-2318-10-55
dc.identifier.issn14712318
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/181657
dc.description.abstractBackground: Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF). Methods: We considered only the youngest subjects (n = 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics. Results: Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR ? 0.879 or RH ? 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03). Conclusions: The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept. © 2010 Swindell et al; licensee BioMed Central Ltd.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20201031
dc.subjectaged
dc.subjectaging
dc.subjectarticle
dc.subjectcohort analysis
dc.subjectcomparative study
dc.subjectdata mining
dc.subjectfemale
dc.subjecthealth status
dc.subjecthuman
dc.subjectlongitudinal study
dc.subjectmethodology
dc.subjectmortality
dc.subjectosteoporosis
dc.subjectphysiology
dc.subjectpredictive value
dc.subjectprospective study
dc.subjectsurvival rate
dc.subjectsurvivor
dc.subjectAged
dc.subjectAging
dc.subjectCohort Studies
dc.subjectData Mining
dc.subjectFemale
dc.subjectHealth Status
dc.subjectHumans
dc.subjectLongitudinal Studies
dc.subjectOsteoporosis
dc.subjectPredictive Value of Tests
dc.subjectProspective Studies
dc.subjectSurvival Rate
dc.subjectSurvivors
dc.typeArticle
dc.contributor.departmentOBSTETRICS & GYNAECOLOGY
dc.description.doi10.1186/1471-2318-10-55
dc.description.sourcetitleBMC Geriatrics
dc.description.volume10
dc.description.page55
Appears in Collections:Elements
Staff Publications

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1186_1471-2318-10-55.pdf855.17 kBAdobe PDF

OPEN

NoneView/Download

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons