{"doi":"10.1111/ggi.12122","title":"<scp>F</scp>railty <scp>I</scp>ndex in <scp>E</scp>uropeans: Association with determinants of health","abstract":"<jats:sec><jats:title>Aim</jats:title><jats:p>The <jats:styled-content style=\"fixed-case\">F</jats:styled-content>railty <jats:styled-content style=\"fixed-case\">I</jats:styled-content>ndex (<jats:styled-content style=\"fixed-case\">FI</jats:styled-content>) summarizes differences in health status within individuals, and the determinants of health drive that variability. The aim of the present study was to investigate the influence of education, income, smoking, alcohol intake and parental longevity on the <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> variability in subjects of the same chronological age group.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Analyses were based on a 40‐item <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> based on the first wave of the <jats:styled-content style=\"fixed-case\">S</jats:styled-content>urvey of <jats:styled-content style=\"fixed-case\">H</jats:styled-content>ealth, <jats:styled-content style=\"fixed-case\">A</jats:styled-content>ging and <jats:styled-content style=\"fixed-case\">R</jats:styled-content>etirement in <jats:styled-content style=\"fixed-case\">E</jats:styled-content>urope (<jats:styled-content style=\"fixed-case\">SHARE</jats:styled-content>, <jats:ext-link xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"http://www.share-project.org/\">http://www.share‐project.org/</jats:ext-link>), including 29 905 participants aged ≥50 years from 12 countries. For each sex, the sample was divided into age categories (50s, 60s, 70s, 80s and ≥90), and <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> quartiles within age categories were calculated. Multivariate ordinal regressions were computed to assess the relative contribution of the health determinants on the <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> quartiles in each age group.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In women, the most significant multivariate predictors were years of education (odds ratios [<jats:styled-content style=\"fixed-case\">OR</jats:styled-content>] around 0.9), and difficulties making ends meet (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> between 1.8 and 2.1). In men, the most significant multivariate predictors were years of education (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> around 0.9), difficulties making ends meet (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> between 1.6 and 2.1), mother's age at death (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> under 1), and father's age at death (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> under 1).</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Consistently with the literature, education and income explained, in both sexes, cross‐sectional variability in <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> in subjects of the same chronological age group. The influence of parental longevity seemed to be greater in men, which mirrors previous studies showing that genetic factors might have a higher impact on longevity in men. <jats:bold>Geriatr Gerontol Int 2014; 14: 420–429.</jats:bold></jats:p></jats:sec>","journal":"Geriatrics &amp; Gerontology International","year":2014,"id":631431,"datarank":0.6414999178524083,"base_score":4.276666119016055,"endowment":4.276666119016055,"self_citation_contribution":0.6414999178524083,"citation_network_contribution":0.0,"self_endowment_contribution":0.6414999178524083,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":71,"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":1636368,"name":"Roman Romero‐Ortuno","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"<scp>F</scp>railty <scp>I</scp>ndex in <scp>E</scp>uropeans: Association with determinants of health","abstract":"<jats:sec><jats:title>Aim</jats:title><jats:p>The <jats:styled-content style=\"fixed-case\">F</jats:styled-content>railty <jats:styled-content style=\"fixed-case\">I</jats:styled-content>ndex (<jats:styled-content style=\"fixed-case\">FI</jats:styled-content>) summarizes differences in health status within individuals, and the determinants of health drive that variability. The aim of the present study was to investigate the influence of education, income, smoking, alcohol intake and parental longevity on the <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> variability in subjects of the same chronological age group.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Analyses were based on a 40‐item <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> based on the first wave of the <jats:styled-content style=\"fixed-case\">S</jats:styled-content>urvey of <jats:styled-content style=\"fixed-case\">H</jats:styled-content>ealth, <jats:styled-content style=\"fixed-case\">A</jats:styled-content>ging and <jats:styled-content style=\"fixed-case\">R</jats:styled-content>etirement in <jats:styled-content style=\"fixed-case\">E</jats:styled-content>urope (<jats:styled-content style=\"fixed-case\">SHARE</jats:styled-content>, <jats:ext-link xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"http://www.share-project.org/\">http://www.share‐project.org/</jats:ext-link>), including 29 905 participants aged ≥50 years from 12 countries. For each sex, the sample was divided into age categories (50s, 60s, 70s, 80s and ≥90), and <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> quartiles within age categories were calculated. Multivariate ordinal regressions were computed to assess the relative contribution of the health determinants on the <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> quartiles in each age group.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In women, the most significant multivariate predictors were years of education (odds ratios [<jats:styled-content style=\"fixed-case\">OR</jats:styled-content>] around 0.9), and difficulties making ends meet (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> between 1.8 and 2.1). In men, the most significant multivariate predictors were years of education (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> around 0.9), difficulties making ends meet (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> between 1.6 and 2.1), mother's age at death (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> under 1), and father's age at death (<jats:styled-content style=\"fixed-case\">OR</jats:styled-content> under 1).</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Consistently with the literature, education and income explained, in both sexes, cross‐sectional variability in <jats:styled-content style=\"fixed-case\">FI</jats:styled-content> in subjects of the same chronological age group. The influence of parental longevity seemed to be greater in men, which mirrors previous studies showing that genetic factors might have a higher impact on longevity in men. <jats:bold>Geriatr Gerontol Int 2014; 14: 420–429.</jats:bold></jats:p></jats:sec>","is_dataset_classified":null,"base_score":4.276666119016055,"endowment":4.276666119016055,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"23879634","pmcid":"PMC3843989","openalex_id":"https://openalex.org/W2159427772","authors":[],"funders":[{"funder_name":"NIA NIH HHS","grant_id":"P01 AG005842","title":null},{"funder_name":"NIA NIH HHS","grant_id":"P01 AG008291","title":null},{"funder_name":"NIA NIH HHS","grant_id":"R21 AG025169","title":null},{"funder_name":"NIA NIH HHS","grant_id":"U01 AG09740-13S2","title":null},{"funder_name":"NIA NIH HHS","grant_id":"P30 AG12815","title":null},{"funder_name":"NIA NIH HHS","grant_id":"P30 AG012815","title":null},{"funder_name":"NIA NIH HHS","grant_id":"P01 AG08291","title":null},{"funder_name":"NIA NIH HHS","grant_id":"U01 AG009740","title":null},{"funder_name":"NIA NIH HHS","grant_id":"Y1-AG-4553-01","title":null}],"total_grants":9,"fwci":2.6189,"citation_percentile":0.89099082,"influential_citations":0,"citation_trend":[{"year":2014,"count":4},{"year":2015,"count":7},{"year":2016,"count":6},{"year":2017,"count":8},{"year":2018,"count":8},{"year":2019,"count":10},{"year":2020,"count":5},{"year":2021,"count":8},{"year":2022,"count":1},{"year":2023,"count":3},{"year":2024,"count":6},{"year":2025,"count":4},{"year":2026,"count":1}],"oa_status":"closed","license":"http://onlinelibrary.wiley.com/termsAndConditions#vor","oa_locations":[{"url":"https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fggi.12122","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1111/ggi.12122","host_type":"publisher"},{"url":"https://doi.org/10.1111/ggi.12122","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/23879634","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3843989","host_type":"repository"}],"fields_of_study":["Frailty in Older Adults","Nutrition and Health in Aging","Genetics, Aging, and Longevity in Model Organisms"],"mesh_terms":["Aged","Aged, 80 and over","Cross-Sectional Studies","Europe","Female","Health Status","Humans","Male","Middle Aged","Risk Factors","Socioeconomic Factors","Geriatric Assessment","Frail Elderly"],"keywords":["Medicine","Association (psychology)","Psychology","Sex differences","SEVERITY OF ILLNESS INDEX","Socioeconomic status","Frail Elderly","Epidemiological Factors"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-05T23:37:04.792897Z","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":[]}