Literature DB >> 34900774

Studying the relationship between cognitive impairment and frailty phenotype: a cross-sectional analysis of the Bushehr Elderly Health (BEH) program.

Farshad Sharifi1, Mahtab Alizadeh Khoiee1,2, Reihane Aminroaya2, Mahbube Ebrahimpur1, Gita Shafiee3, Ramin Heshmat3, Moloud Payab4, Zhaleh Shadman1, Hossein Fakhrzadeh1, Seyed Masoud Arzaghi1, Neda Mehrdad1, Afshin Ostovar5, Ali Sheidaei6, Noushin Fahimfar5, Iraj Nabipour7, Bagher Larijani8.   

Abstract

BACKGROUND: Some pathophysiological effects of physical frailty and cognitive impairment might be similar; therefore, finding the associations in epidemiologic studies could guide clinicians and researchers to recognize effective strategies for each type of frailty such as frailty phenotype and frailty index, which in turn will result in a preventive approach. The study aimed to reveal which components of frailty phenotype are more associated with cognitive impairment. The findings of this study may help other researchers clarify the related pathways.
METHODS: This is a cross-sectional analysis of the results of the second phase of Bushehr Elderly Health Program; a community-based elderly prospective cohort study conducted in 2015-2016. The participants were selected through a multistage stratified cluster random sampling method. Frailty was assessed based on the Fried frailty phenotype criteria. Cognitive impairment was assessed by the Mini-Mental State Examination (MMSE), the Mini-Cog, and the Category Fluency Test (CFT). Multiple logistic regression models were applied to determine the association between frailty and cognitive impairment. Depression trait was assessed using the Patient Health Questionnaire-9 (PHQ-9). Activities of daily living were assessed using the Barthel Index and Instrumental Activities of Daily Living (IADLs) using Lawton's IADL.
RESULTS: The studyp conducted among people ≥ 60 years old (N = 2336) with women consisting 51.44% of the sample group. The mean age of the participants was 69.26 years old. The prevalence of pre-frailty and frailty were 42.59% and 7.66%, respectively. In the fully adjusted model, the odds ratio of the association between pre-frailty and frailty with cognitive impairment was 1.239, 95% CI: 1.011 - 1.519 and 1.765, 95% CI: 1.071 - 2.908, respectively (adjusted for age, sex, education, body mass index, smoking, diabetes mellitus, PHQ- 9, Barthel Index, and IADLs). In the fully adjusted multiple logistic regression models, all of the components of Fried frailty phenotype were significantly related to cognitive impairment except weight loss.
CONCLUSION: Cognitive impairment may be associated with frailty phenotype. Moreover, low strength and function of muscles had a stronger association with cognitive impairment. It seems that a consideration of cognitive impairment assessment in older people along with frailty and vice versa in clinical settings is reasonable. © Springer Nature Switzerland AG 2021.

Entities:  

Keywords:  Aged; Category fluency test; Cognitive impairment; Depression; Frailty

Year:  2021        PMID: 34900774      PMCID: PMC8630203          DOI: 10.1007/s40200-021-00847-7

Source DB:  PubMed          Journal:  J Diabetes Metab Disord        ISSN: 2251-6581


  35 in total

1.  Category fluency test: effects of age, gender and education on total scores, clustering and switching in Brazilian Portuguese-speaking subjects.

Authors:  S M D Brucki; M S G Rocha
Journal:  Braz J Med Biol Res       Date:  2004-11-17       Impact factor: 2.590

2.  Sarcopenia, frailty, cognitive impairment and mortality in elderly patients with non-valvular atrial fibrillation.

Authors:  M A Requena Calleja; A Arenas Miquélez; J Díez-Manglano; A Gullón; A Pose; F Formiga; J M Mostaza; J M Cepeda; C Suárez
Journal:  Rev Clin Esp (Barc)       Date:  2019-05-18

3.  Psychometric Properties of the Persian Adaptation of Mini-Cog Test in Iranian Older Adults.

Authors:  Mohammad Rezaei; Vahid Rashedi; Gohar Lotfi; Peymaneh Shirinbayan; Mahshid Foroughan
Journal:  Int J Aging Hum Dev       Date:  2017-08-31

4.  Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): a meta-analysis.

Authors:  Laura Manea; Simon Gilbody; Dean McMillan
Journal:  CMAJ       Date:  2011-12-19       Impact factor: 8.262

Review 5.  Frailty: implications for clinical practice and public health.

Authors:  Emiel O Hoogendijk; Jonathan Afilalo; Kristine E Ensrud; Paul Kowal; Graziano Onder; Linda P Fried
Journal:  Lancet       Date:  2019-10-12       Impact factor: 79.321

Review 6.  Loss of motor function in preclinical Alzheimer's disease.

Authors:  Aron S Buchman; David A Bennett
Journal:  Expert Rev Neurother       Date:  2011-05       Impact factor: 4.618

7.  Prognostic significance of potential frailty criteria.

Authors:  Marc D Rothman; Linda Leo-Summers; Thomas M Gill
Journal:  J Am Geriatr Soc       Date:  2008-12       Impact factor: 5.562

8.  Decline in Weight and Incident Mild Cognitive Impairment: Mayo Clinic Study of Aging.

Authors:  Rabe E Alhurani; Maria Vassilaki; Jeremiah A Aakre; Michelle M Mielke; Walter K Kremers; Mary M Machulda; Yonas E Geda; David S Knopman; Ronald C Petersen; Rosebud O Roberts
Journal:  JAMA Neurol       Date:  2016-04       Impact factor: 18.302

Review 9.  Frailty, Cognitive Decline, Neurodegenerative Diseases and Nutrition Interventions.

Authors:  María Elena Gómez-Gómez; Sara C Zapico
Journal:  Int J Mol Sci       Date:  2019-06-11       Impact factor: 5.923

10.  Iranian Version of Barthel Index: Validity and Reliability in Outpatients' Elderly.

Authors:  Sakar Hormozi; Mahtab Alizadeh-Khoei; Farshad Sharifi; Fahimeh Taati; Reyhaneh Aminalroaya; Sadegh Fadaee; Leila Angooti-Oshnari; Homan Saghebi
Journal:  Int J Prev Med       Date:  2019-08-01
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