Executive Function and Falls in Older Adults: New Findings from a Five-Year Prospective Study Link Fall Risk to Cognition
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{"title"=>"Executive function and falls in older adults: New findings from a five-year prospective study link fall risk to cognition", "type"=>"journal", "authors"=>[{"first_name"=>"Anat", "last_name"=>"Mirelman", "scopus_author_id"=>"35332484600"}, {"first_name"=>"Talia", "last_name"=>"Herman", "scopus_author_id"=>"56283401200"}, {"first_name"=>"Marina", "last_name"=>"Brozgol", "scopus_author_id"=>"25121364100"}, {"first_name"=>"Moran", "last_name"=>"Dorfman", "scopus_author_id"=>"55270439800"}, {"first_name"=>"Elliot", "last_name"=>"Sprecher", "scopus_author_id"=>"55402313500"}, {"first_name"=>"Avraham", "last_name"=>"Schweiger", "scopus_author_id"=>"56219050000"}, {"first_name"=>"Nir", "last_name"=>"Giladi", "scopus_author_id"=>"7006084033"}, {"first_name"=>"Jeffrey M.", "last_name"=>"Hausdorff", "scopus_author_id"=>"7006799695"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"365133400", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0040297", "scopus"=>"2-s2.0-84863100342", "pmid"=>"22768271", "sgr"=>"84863100342"}, "id"=>"d292ffb6-e5ea-31fd-9e05-a8787b8fc87d", "abstract"=>"BACKGROUND: Recent findings suggest that executive function (EF) plays a critical role in the regulation of gait in older adults, especially under complex and challenging conditions, and that EF deficits may, therefore, contribute to fall risk. The objective of this study was to evaluate if reduced EF is a risk factor for future falls over the course of 5 years of follow-up. Secondary objectives were to assess whether single and dual task walking abilities, an alternative window into EF, were associated with fall risk. METHODOLOGY/MAIN RESULTS: We longitudinally followed 256 community-living older adults (age: 76.4+/-4.5 yrs; 61% women) who were dementia free and had good mobility upon entrance into the study. At baseline, a computerized cognitive battery generated an index of EF, attention, a closely related construct, and other cognitive domains. Gait was assessed during single and dual task conditions. Falls data were collected prospectively using monthly calendars. Negative binomial regression quantified risk ratios (RR). After adjusting for age, gender and the number of falls in the year prior to the study, only the EF index (RR: .85; CI: .74-.98, p = .021), the attention index (RR: .84; CI: .75-.94, p = .002) and dual tasking gait variability (RR: 1.11; CI: 1.01-1.23; p = .027) were associated with future fall risk. Other cognitive function measures were not related to falls. Survival analyses indicated that subjects with the lowest EF scores were more likely to fall sooner and more likely to experience multiple falls during the 66 months of follow-up (p<0.02). CONCLUSIONS/SIGNIFICANCE: These findings demonstrate that among community-living older adults, the risk of future falls was predicted by performance on EF and attention tests conducted 5 years earlier. The present results link falls among older adults to cognition, indicating that screening EF will likely enhance fall risk assessment, and that treatment of EF may reduce fall risk.", "link"=>"http://www.mendeley.com/research/executive-function-falls-older-adults-new-findings-fiveyear-prospective-study-link-fall-risk-cogniti-2", "reader_count"=>211, "reader_count_by_academic_status"=>{"Unspecified"=>4, "Professor > Associate Professor"=>11, "Researcher"=>26, "Student > Doctoral Student"=>14, "Student > Ph. D. Student"=>56, "Student > Postgraduate"=>16, "Student > Master"=>35, "Other"=>15, "Student > Bachelor"=>18, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>3, "Professor"=>11}, "reader_count_by_user_role"=>{"Unspecified"=>4, "Professor > Associate Professor"=>11, "Researcher"=>26, "Student > Doctoral Student"=>14, "Student > Ph. D. Student"=>56, "Student > Postgraduate"=>16, "Student > Master"=>35, "Other"=>15, "Student > Bachelor"=>18, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>3, "Professor"=>11}, "reader_count_by_subject_area"=>{"Unspecified"=>11, "Agricultural and Biological Sciences"=>11, "Arts and Humanities"=>1, "Business, Management and Accounting"=>1, "Computer Science"=>4, "Decision Sciences"=>1, "Engineering"=>21, "Nursing and Health Professions"=>14, "Mathematics"=>1, "Medicine and Dentistry"=>70, "Neuroscience"=>15, "Design"=>1, "Sports and Recreations"=>16, "Physics and Astronomy"=>2, "Psychology"=>37, "Social Sciences"=>4, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>70}, "Social Sciences"=>{"Social Sciences"=>4}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>16}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Psychology"=>{"Psychology"=>37}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>11}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>21}, "Neuroscience"=>{"Neuroscience"=>15}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>11}, "Computer Science"=>{"Computer Science"=>4}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>14}}, "reader_count_by_country"=>{"Canada"=>2, "Netherlands"=>1, "United States"=>3, "Japan"=>2, "Taiwan"=>1, "Brazil"=>1, "United Kingdom"=>1, "France"=>1, "Germany"=>4}, "group_count"=>13}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/616229"], "description"=>"*<p>Among the subject characteristics (i.e., demographics, affect, and grip strength), measures that were significantly correlated with EF are indicated, except for the Charlson index where the association was borderline (p = .068). The correlations were generally mild to moderate (i.e., |r| values less than .25; p<.01).</p>#<p>and <sup>##</sup> indicate that this variable was marginally (.15>p>.05) or significantly associated with future fall risk, respectively, in univariate analysis among the measures listed under demographics. Univariate associations for the other measures are presented in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040297#pone-0040297-t002\" target=\"_blank\">Tables 2</a> and <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040297#pone-0040297-t003\" target=\"_blank\">3</a>.</p>x<p>Higher values indicate better performance on these computerized measures of cognitive function. 100 on these IQ-like scales represent the age and education adjusted norms.</p>", "links"=>[], "tags"=>["characteristics", "subjects"], "article_id"=>286717, "categories"=>["Physiology", "Medicine", "Biotechnology", "Neuroscience"], "users"=>["Anat Mirelman", "Talia Herman", "Marina Brozgol", "Moran Dorfman", "Elliot Sprecher", "Avraham Schweiger", "Nir Giladi", "Jeffrey M. Hausdorff"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040297.t001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Baseline_characteristics_of_the_subjects_n_8202_8202_256_/286717", "title"=>"Baseline characteristics of the subjects (n = 256).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:10:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/616148"], "description"=>"*<p>Rate ratios based on a 10 point change in each of the cognitive measures. Higher scores on the cognitive measures represent better performance and thus lower rate ratios represent a lower risk for falls. Because of (randomly) missing data for some tests, not all analyses included the same number of cases. Although it did not alter the conclusions, one subject, who met all study admission criteria and who was not otherwise atypical, was removed from NBR analysis because of his extremely high number of falls (49 falls) relative to all other subjects, and the ensuing disproportionate leverage his case had on the statistical models. His data were used for all other statistical tests. All of the results reported here and in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040297#pone-0040297-t003\" target=\"_blank\">Tables 3</a> and <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040297#pone-0040297-t004\" target=\"_blank\">4</a> were essentially unchanged if we also included the number of prescription medications in the fully adjusted model. BMI: body-mass index.</p>", "links"=>[], "tags"=>["measures", "falls", "66", "months"], "article_id"=>286638, "categories"=>["Physiology", "Medicine", "Biotechnology", "Neuroscience"], "users"=>["Anat Mirelman", "Talia Herman", "Marina Brozgol", "Moran Dorfman", "Elliot Sprecher", "Avraham Schweiger", "Nir Giladi", "Jeffrey M. Hausdorff"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040297.t002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cognitive_measures_and_their_ability_to_predict_falls_over_the_66_months_of_follow_up_/286638", "title"=>"Cognitive measures and their ability to predict falls over the 66 months of follow-up.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:10:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/616196"], "description"=>"*<p>In general, as expected, only age and history of falls were significantly associated with future fall risks. Note that in contrast to the results shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040297#pone-0040297-t002\" target=\"_blank\">Table 2</a>, where higher values reflect better performance and lower risk of falls, for dual tasking gait variability and the Timed Up and Go, higher values indicate worse performance. Higher scores on these two measures were associated with an increased fall risk. During the 66 months of follow-up, 3 subjects were diagnosed with Parkinson's disease (1.1%), 4 with Alzheimer's disease (1.5%) and 2 sustained a stroke (.7%). The results summarized in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040297#pone-0040297-t002\" target=\"_blank\">Tables 2</a>–<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040297#pone-0040297-t003\" target=\"_blank\"></a><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040297#pone-0040297-t004\" target=\"_blank\">4</a> were essentially unchanged when analyses were repeated after excluding these subjects.BMI: body-mass index.</p>", "links"=>[], "tags"=>["measures", "gait", "mobility", "falls", "66", "months"], "article_id"=>286676, "categories"=>["Physiology", "Medicine", "Biotechnology", "Neuroscience"], "users"=>["Anat Mirelman", "Talia Herman", "Marina Brozgol", "Moran Dorfman", "Elliot Sprecher", "Avraham Schweiger", "Nir Giladi", "Jeffrey M. Hausdorff"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040297.t003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_based_measures_of_gait_and_mobility_and_their_ability_to_predict_falls_over_the_66_months_of_follow_up_/286676", "title"=>"Performance-based measures of gait and mobility and their ability to predict falls over the 66 months of follow-up.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:10:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/616081"], "description"=>"<p>Differences were found in ‘time to first fall’ between the highest (indicated as 1<sup>st</sup> on the graph) and lowest EF (indicated as 4<sup>th</sup> on the graph) quartile (P = 0.017) and time to second fall (P = 0.023). Subjects with in lowest quartile were more likely to fall sooner (LEFT) and more likely to become multi-fallers sooner (RIGHT) than those in highest quartile. Note when performing similar analyses on those subjects who reported no falls in the year prior to the study, subjects with lowest quartile of EF were also more likely to fall during the follow-up period, similar to what is observed if the entire cohort is included in the analysis. EF quartile was defined based on the ranking of EF scores obtained at baseline using the computerized cognitive battery. By definition, subjects in the lowest quartile had the lowest (i.e., relatively worst) EF scores, whereas subjects in the highest quartile had the highest (i.e., best) scores.</p>", "links"=>[], "tags"=>["curves", "illustrating", "percent", "subjects", "did"], "article_id"=>286554, "categories"=>["Physiology", "Medicine", "Biotechnology", "Neuroscience"], "users"=>["Anat Mirelman", "Talia Herman", "Marina Brozgol", "Moran Dorfman", "Elliot Sprecher", "Avraham Schweiger", "Nir Giladi", "Jeffrey M. Hausdorff"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040297.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Survival_curves_illustrating_the_percent_of_subjects_who_did_not_fall_as_a_function_of_time_and_executive_function_EF_/286554", "title"=>"Survival curves illustrating the percent of subjects who did not fall as a function of time and executive function (EF).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 03:09:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/616279"], "description"=>"*<p>Each of these negative binomial regression models were adjusted for age, gender, years of education, BMI, history of falls and grip force. Only components that were significantly associated or tended to be associated (P<.15) with falls are shown. Rate ratios based on raw scores of these test components, except for the response time results which are reported based on 100 msec changes, instead of 1 msec; this transformation does not affect the p-value.</p>**<p>Arbitrary units that reflect the total score (summed accuracy across sublevels, weighted by difficulty).</p>", "links"=>[], "tags"=>["ef", "indices", "falls", "66", "months"], "article_id"=>286757, "categories"=>["Physiology", "Medicine", "Biotechnology", "Neuroscience"], "users"=>["Anat Mirelman", "Talia Herman", "Marina Brozgol", "Moran Dorfman", "Elliot Sprecher", "Avraham Schweiger", "Nir Giladi", "Jeffrey M. Hausdorff"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040297.t004", "stats"=>{"downloads"=>4, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Components_that_contribute_to_the_EF_and_attention_indices_that_were_associated_with_falls_over_the_66_months_of_follow_up_/286757", "title"=>"Components that contribute to the EF and attention indices that were associated with falls over the 66 months of follow-up.<sup>*</sup>", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:10:48"}

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Relative Metric

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