{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T20:52:27Z","timestamp":1793479947811,"version":"4.5.0"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T00:00:00Z","timestamp":1725494400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>As the population ages, the occurrence of cognitive decline and dementia is continuously increasing. Frailty is a prevalent problem among older adults. Epidemiologic studies have shown a comorbidity between frailty and cognitive impairment. However, their relationship remains unclear. The frailty index is an important indicator for measuring frailty. This study aims to investigate the relationship between frailty index and cognitive dysfunction in older adults aged 60\u2009years and older in the United States from the 2011\u20132014 National Health and Nutrition Examination Survey (NHANES).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Community-dwelling older adults aged 60\u2009years or older from 2011 to 2014 were extracted from the NHANES database. The frailty index was calculated using the formula: frailty index\u2009=\u2009total number of deficits present\/total number of deficits measured. The Animal Fluency (AF), the Digit Symbol Substitution Test (DSST), the Consortium to Establish a Registry for Alzheimer\u2019s disease Delayed Recall (CERAD-DR), and Word Learning (CERAD-WL) were used to evaluate cognitive dysfunction. Firstly, weighted logistic regression analysis was used to explore the relationship between frailty index and cognitive dysfunction. Secondly, the influence of covariates on the frailty index was evaluated by subgroup analysis and interaction. Finally, the non-linear relationship is discussed by using the restricted cubic spline regression model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Our study included a total of 2,574 patients, weighted logistic regression analysis, after adjusting for all covariates, showed that the frailty index was associated with every test score. The interaction showed that covariates had no significant effect on this association in AF. The association between the frailty index and AF in the restricted cubic spline regression model is non-linear. As the frailty index increased, the risk of AF reduction increased, suggesting a higher risk of cognitive dysfunction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>In general, a high frailty index appears to be associated with an increased risk of cognitive dysfunction in the elderly. Consequently, protecting against cognitive decline necessitates making geriatric frailty prevention and treatment top priorities.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnagi.2024.1458542","type":"journal-article","created":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T00:37:03Z","timestamp":1725496623000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Association between frailty index and cognitive dysfunction in older adults: insights from the 2011\u20132014 NHANES data"],"prefix":"10.3389","volume":"16","author":[{"given":"Jianlong","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yadi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lv","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rensong","family":"Yue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,9,5]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"j2856","DOI":"10.1136\/bmj.j2856","article-title":"Temporal trend in dementia incidence since 2002 and projections for prevalence in England and Wales to 2040: modelling study","volume":"358","author":"Ahmadi-Abhari","year":"2017","journal-title":"BMJ"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1001\/jamainternmed.2015.7841","article-title":"Association between lifetime marijuana use and cognitive function in middle age: the coronary artery risk development in Young adults (CARDIA) study","volume":"176","author":"Auer","year":"2016","journal-title":"JAMA Intern. 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