{"doi":"10.1093/gerona/glz223","title":"Testing Proposed Quantifications of Biological Aging in Taiwanese Older Adults","abstract":"<jats:title>Abstract</jats:title><jats:p>Quantification of biological aging is of interest in gerontology as a means to surveil aging rates in the population and to evaluate the effects of interventions to increase healthy life span. Analysis of proposed methods to quantify biological aging has focused on samples of midlife or mixed-age adults in the West. Research is needed to test whether quantifications of biological aging can differentiate aging rates among older adults and if quantifications of biological aging developed in Western samples can differentiate aging rates in non-Western populations. We conducted analysis of Klemera-Doubal method (KDM) Biological Age and homeostatic dysregulation measures of biological aging developed in the U.S. NHANES and tested in a sample of older Taiwanese adults in the Social Environment and Biomarkers of Aging Study. We conducted analysis of physical and cognitive function and mortality, comparing quantifications of biological aging to a biomarker index based on norms within our analysis sample and to participants’ ratings of their own health. Results showed that quantifications of biological aging (a) predicted differences in physical and cognitive function and in mortality risk among Taiwanese older adults and (b) performed as well as a traditional biomarker index and participant self-rated health for prediction of these outcomes.</jats:p>","journal":"The Journals of Gerontology: Series A","year":2020,"id":606826,"datarank":0.47670807455219194,"base_score":3.1780538303479458,"endowment":3.1780538303479458,"self_citation_contribution":0.47670807455219194,"citation_network_contribution":0.0,"self_endowment_contribution":0.47670807455219194,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":23,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":109249,"name":"Daniel W. Belsky","orcid":"0000-0001-5463-2212","position":1,"is_corresponding":false},{"id":1557986,"name":"Dana A Glei","orcid":null,"position":2,"is_corresponding":false},{"id":298443,"name":"Noreen Goldman","orcid":"0000-0003-2865-9491","position":3,"is_corresponding":false},{"id":109248,"name":"Lauren Gaydosh","orcid":"0000-0002-0036-626X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Testing Proposed Quantifications of Biological Aging in Taiwanese Older Adults","abstract":"<jats:title>Abstract</jats:title><jats:p>Quantification of biological aging is of interest in gerontology as a means to surveil aging rates in the population and to evaluate the effects of interventions to increase healthy life span. Analysis of proposed methods to quantify biological aging has focused on samples of midlife or mixed-age adults in the West. Research is needed to test whether quantifications of biological aging can differentiate aging rates among older adults and if quantifications of biological aging developed in Western samples can differentiate aging rates in non-Western populations. We conducted analysis of Klemera-Doubal method (KDM) Biological Age and homeostatic dysregulation measures of biological aging developed in the U.S. NHANES and tested in a sample of older Taiwanese adults in the Social Environment and Biomarkers of Aging Study. We conducted analysis of physical and cognitive function and mortality, comparing quantifications of biological aging to a biomarker index based on norms within our analysis sample and to participants’ ratings of their own health. Results showed that quantifications of biological aging (a) predicted differences in physical and cognitive function and in mortality risk among Taiwanese older adults and (b) performed as well as a traditional biomarker index and participant self-rated health for prediction of these outcomes.</jats:p>","is_dataset_classified":null,"base_score":3.1780538303479458,"endowment":3.1780538303479458,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"31566204","pmcid":"PMC7494028","openalex_id":"https://openalex.org/W2977922499","authors":[],"funders":[{"funder_name":"Office of Behavioral and Social Science Research of the National Institute on Aging","grant_id":"R01AG16661 and R01AG16790","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"P2CHD047879","title":null},{"funder_name":"National Institute on Aging","grant_id":"R21AG054846","title":null},{"funder_name":"NIA NIH HHS","grant_id":"R01 AG016661","title":null},{"funder_name":"NIA NIH HHS","grant_id":"R01 AG016790","title":null}],"total_grants":5,"fwci":0.8065,"citation_percentile":0.67509837,"influential_citations":0,"citation_trend":[{"year":2020,"count":2},{"year":2021,"count":1},{"year":2022,"count":7},{"year":2023,"count":5},{"year":2024,"count":4},{"year":2025,"count":2},{"year":2026,"count":2}],"oa_status":"green","license":"https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model","oa_locations":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7494028","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7494028","host_type":"repository"},{"url":"http://academic.oup.com/biomedgerontology/advance-article-pdf/doi/10.1093/gerona/glz223/31108968/glz223.pdf","host_type":"publisher"},{"url":"http://academic.oup.com/biomedgerontology/article-pdf/75/9/1680/33753992/glz223.pdf","host_type":"publisher"},{"url":"https://doi.org/10.1093/gerona/glz223","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/31566204","host_type":"repository"}],"fields_of_study":["Genetics, Aging, and Longevity in Model Organisms","Aging and Gerontology Research","Frailty in Older Adults","Age Factors","Aged","Aging","Biomarkers","Cognitive Aging","Female","Hand Strength","Humans","Longitudinal Studies","Male","Mental Status and Dementia Tests","Mortality","Nutrition Surveys","Peak Expiratory Flow Rate","Physical Fitness","Risk Factors","Taiwan","Walking Speed"],"mesh_terms":["Cognitive Aging","Walking Speed","Mental Status and Dementia Tests","Age Factors","Aged","Aging","Female","Humans","Longitudinal Studies","Male","Mortality","Nutrition Surveys","Peak Expiratory Flow Rate","Physical Fitness","Risk Factors","Taiwan","Biomarkers","Hand Strength"],"keywords":["Biological age","Gerontology","Successful aging","Biomarker","Healthy aging","Ageing","Population ageing","Cognition","Population","Psychology","Medicine","Environmental health","Biology","Internal medicine","Psychiatry","Mortality","Biomarkers","Physical performance","Cognitive Decline"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-30T05:14:07.244883Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}