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The measures were strongly correlated (<jats:italic>r<\/jats:italic> = 0.76, <jats:italic>P<\/jats:italic> &lt; 0.001) and had a kappa agreement of 0.38 for frailty classification, with 37% of participants classified as non\u2010frail by the <jats:styled-content style=\"fixed-case\">FP<\/jats:styled-content> being classified as frail by the <jats:styled-content style=\"fixed-case\">FI<\/jats:styled-content>. Being older, a current smoker, and having multimorbidity and polypharmacy were associated with higher frailty levels by both tools. Female, low income, obesity and living alone were associated with the <jats:styled-content style=\"fixed-case\">FI<\/jats:styled-content>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Frailty prevalence was higher when assessed using the <jats:styled-content style=\"fixed-case\">FI<\/jats:styled-content>. Socioeconomic factors and other health determinants contribute to higher frailty levels.<\/jats:p><\/jats:sec>","DOI":"10.1111\/ajag.12487","type":"journal-article","created":{"date-parts":[[2017,12,5]],"date-time":"2017-12-05T11:13:24Z","timestamp":1512472404000},"page":"120-126","source":"Crossref","is-referenced-by-count":58,"title":["Frailty prevalence and factors associated with the Frailty Phenotype and Frailty Index: Findings from the North West Adelaide Health Study"],"prefix":"10.1111","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6420-4294","authenticated-orcid":false,"given":"Mark Q","family":"Thompson","sequence":"first","affiliation":[{"name":"National Health and Medical Research Council (NHMRC) Centre of Research Excellence: Frailty and Healthy Ageing University of Adelaide Adelaide South Australia Australia"},{"name":"Faculty of Health and Medical Sciences Adelaide Geriatrics Training and Research with Aged Care (G\u2010TRAC) Centre Adelaide Medical 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