scholarly journals Predictors of Behavioral and Psychological Symptoms in Community-Dwelling Older Adults With Dementia

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 649-649
Author(s):  
Eunhee Cho ◽  
Sujin Kim ◽  
Sinwoo Hwang ◽  
Eunji Kwon ◽  
Seok-Jae Heo ◽  
...  
Keyword(s):  
Older Adults ◽  
Prediction Models ◽  
Environmental Changes ◽  
Psychological Symptoms ◽  
Characteristic Curve ◽  
Community Dwelling ◽  
Activity Levels ◽  
Premorbid Personality ◽  
Community Dwelling Older Adults ◽  
Behavioral And Psychological Symptoms

Abstract Although disclosing the predictors of different behavioral and psychological symptoms of dementia (BPSD) is the first step in developing person-centered interventions, the current understanding is limited as it considers BPSD as a homogenous construct, not accounting for its heterogeneity. Therefore, this study explored the predictors of BPSD subsyndromes, and built prediction models for these subsyndromes in community-dwelling older adults with dementia in Korea. This prospective study consisted of a two-wave dataset. We fit the generalized linear mixed models using Wave 1 data (N = 145) and then validated them using Wave 2 data (N = 59). BPSD and their proximal factors were assessed on a daily basis using diaries written by family caregivers. Sleep and activity levels were objectively measured using actigraphy. The amount of nighttime sleep hours was significantly associated with next-day sleep and nighttime behaviors (OR = 0.87; p = 0.005), with the amounts of energy expenditure showing significant association with euphoria/elation (OR = 0.02; p = 0.019). All subsyndromes except euphoria/elation were found to be significantly associated with either hunger, thirst, urination, or bowl movement; with all BPSD showing a significant association with environmental changes. We also found several background factors, including premorbid personality and taking sedatives as predictors for specific subsyndromes. The area under the receiver operating characteristic curve scores for the data were greater than 0.9 and 0.8 in Waves 1 and 2, respectively, across all subsyndromes. Prediction models for BPSD will help in the development of symptom-targeted, individualized interventions.

scholarly journals Factors Associated With Behavioral and Psychological Symptoms of Dementia: Prospective Observational Study Using Actigraphy (Preprint)

2021 ◽  
Author(s):  
Eunhee Cho ◽  
Sujin Kim ◽  
Sinwoo Hwang ◽  
Eunji Kwon ◽  
Seok-Jae Heo ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Prospective Observational Study ◽  
Psychological Symptoms ◽  
Information Criterion ◽  
Activity Levels ◽  
Contributing Factors ◽  
Factors Associated ◽  
Physical Activity Levels ◽  
Behavioral And Psychological Symptoms

BACKGROUND Although disclosing the predictors of different behavioral and psychological symptoms of dementia (BPSD) is the first step in developing person-centered interventions, current understanding is limited, as it considers BPSD as a homogenous construct. This fails to account for their heterogeneity and hinders development of interventions that address the underlying causes of the target BPSD subsyndromes. Moreover, understanding the influence of proximal factors—circadian rhythm–related factors (ie, sleep and activity levels) and physical and psychosocial unmet needs states—on BPSD subsyndromes is limited, due to the challenges of obtaining objective and/or continuous time-varying measures. OBJECTIVE The aim of this study was to explore factors associated with BPSD subsyndromes among community-dwelling older adults with dementia, considering sets of background and proximal factors (ie, actigraphy-measured sleep and physical activity levels and diary-based caregiver-perceived symptom triggers), guided by the need-driven dementia-compromised behavior model. METHODS A prospective observational study design was employed. Study participants included 145 older adults with dementia living at home. The mean age at baseline was 81.2 (SD 6.01) years and the sample consisted of 86 (59.3%) women. BPSD were measured with a BPSD diary kept by caregivers and were categorized into seven subsyndromes. Independent variables consisted of background characteristics and proximal factors (ie, sleep and physical activity levels measured using actigraphy and caregiver-reported contributing factors assessed using a BPSD diary). Generalized linear mixed models (GLMMs) were used to examine the factors that predicted the occurrence of BPSD subsyndromes. We compared the models based on the Akaike information criterion, the Bayesian information criterion, and likelihood ratio testing. RESULTS Compared to the GLMMs with only background factors, the addition of actigraphy and diary-based data improved model fit for every BPSD subsyndrome. The number of hours of nighttime sleep was a predictor of the next day’s sleep and nighttime behaviors (odds ratio [OR] 0.9, 95% CI 0.8-1.0; <i>P</i>=.005), and the amount of energy expenditure was a predictor for euphoria or elation (OR 0.02, 95% CI 0.0-0.5; <i>P</i>=.02). All subsyndromes, except for euphoria or elation, were significantly associated with hunger or thirst and urination or bowel movements, and all BPSD subsyndromes showed an association with environmental change. Age, marital status, premorbid personality, and taking sedatives were predictors of specific BPSD subsyndromes. CONCLUSIONS BPSD are clinically heterogeneous, and their occurrence can be predicted by different contributing factors. Our results for various BPSD suggest a critical window for timely intervention and care planning. Findings from this study will help devise symptom-targeted and individualized interventions to prevent and manage BPSD and facilitate personalized dementia care.

Profile of Physical Activity Levels in Community-Dwelling Older Adults

2005 ◽  
Vol 37 (10) ◽  
pp. 1774-1784 ◽  
Author(s):  
KAREN E. CHAD ◽  
BRUCE A. REEDER ◽  
ELIZABETH L. HARRISON ◽  
NIGEL L. ASHWORTH ◽  
SUZANNE M. SHEPPARD ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Community Dwelling ◽  
Activity Levels ◽  
Physical Activity Levels ◽  
Community Dwelling Older Adults

scholarly journals Physical activity levels of older community-dwelling adults are influenced by summer weather variables

2009 ◽  
Vol 34 (2) ◽  
pp. 182-190 ◽  
Author(s):  
Caitlin A. Brandon ◽  
Dawn P. Gill ◽  
Mark Speechley ◽  
Jason Gilliland ◽  
Gareth R. Jones
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Repeated Measures ◽  
Maximal Oxygen Consumption ◽  
Functional Independence ◽  
Community Dwelling ◽  
Curvilinear Relationship ◽  
Activity Levels ◽  
Weather Variables ◽  
Community Dwelling Older Adults

Adequate daily physical activity (PA) is important for maintaining functional capacity and independence in older adults. However, most older adults in Canada do not engage in enough PA to sustain fitness and functional independence. Environmental influences, such as warmer daytime temperatures, may influence PA participation; however, few studies have examined the effect of summertime temperatures on PA levels in older adults. This investigation measured the influence of summertime weather variables on PA in 48 community-dwelling older adults who were randomly recruited from a local seniors’ community centre. Each participant wore an accelerometer for a single 7-consecutive-day period (between 30 May and 9 August 2006) during waking hours, and completed a PA logbook to remark on major daily PA events. Local weather variables were collected from a national weather service and compared with PA counts per minute. Regression analysis revealed a curvilinear relationship between log-transformed PA and mean daily temperature (r2 = 0.025; p < 0.05). Linear mixed effects models that accounted for repeated measures nested within individuals were performed for monthly periods, meteorological variables, sex, age, and estimated maximal oxygen consumption, with PA as the dependent variable. Age and Air Quality Index remained significant variables within the model. Higher fitness levels had no effect on allowing individuals to perform more vigorous PA in warmer temperatures.

scholarly journals Automated Loss-of-Balance Event Identification in Older Adults at Risk of Falls during Real-World Walking Using Wearable Inertial Measurement Units

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4661
Author(s):  
Jeremiah Hauth ◽  
Safa Jabri ◽  
Fahad Kamran ◽  
Eyoel W. Feleke ◽  
Kaleab Nigusie ◽  
...  
Keyword(s):  
Older Adults ◽  
Real World ◽  
Characteristic Curve ◽  
Community Dwelling ◽  
Recording Device ◽  
Learning Approaches ◽  
Discriminative Ability ◽  
Inertial Measurement ◽  
Loss Of Balance ◽  
Community Dwelling Older Adults

Loss-of-balance (LOB) events, such as trips and slips, are frequent among community-dwelling older adults and are an indicator of increased fall risk. In a preliminary study, eight community-dwelling older adults with a history of falls were asked to perform everyday tasks in the real world while donning a set of three inertial measurement sensors (IMUs) and report LOB events via a voice-recording device. Over 290 h of real-world kinematic data were collected and used to build and evaluate classification models to detect the occurrence of LOB events. Spatiotemporal gait metrics were calculated, and time stamps for when LOB events occurred were identified. Using these data and machine learning approaches, we built classifiers to detect LOB events. Through a leave-one-participant-out validation scheme, performance was assessed in terms of the area under the receiver operating characteristic curve (AUROC) and the area under the precision recall curve (AUPR). The best model achieved an AUROC ≥0.87 for every held-out participant and an AUPR 4-20 times the incidence rate of LOB events. Such models could be used to filter large datasets prior to manual classification by a trained healthcare provider. In this context, the models filtered out at least 65.7% of the data, while detecting ≥87.0% of events on average. Based on the demonstrated discriminative ability to separate LOBs and normal walking segments, such models could be applied retrospectively to track the occurrence of LOBs over an extended period of time.

scholarly journals A Prediction Model for Falls in Community-Dwelling Older Adults in Podiatry Practices

Gerontology ◽  
2022 ◽  
pp. 1-10
Author(s):  
Danique J.J. van Gulick ◽  
Sander I.B. Perry ◽  
Marike van der Leeden ◽  
Jolan G.M. van Beek ◽  
Cees Lucas ◽  
...  
Keyword(s):  
Older Adults ◽  
Prediction Model ◽  
Gait Speed ◽  
Fall Risk ◽  
Model Building ◽  
Characteristic Curve ◽  
External Validation ◽  
Community Dwelling ◽  
Internal Validation ◽  
Community Dwelling Older Adults

<b><i>Introduction:</i></b> Falls are a worldwide health problem among community-dwelling older adults. Emerging evidence suggests that foot problems increase the risk of falling, so the podiatrist may be crucial in detecting foot-related fall risk. However, there is no screening tool available which can be used in podiatry practice. The predictive value of existing tools is limited, and the implementation is poor. The development of risk models for specific clinical populations might increase the prediction accuracy and implementation. Therefore, the aim of this study was to develop and internally validate an easily applicable clinical prediction model (CPM) that can be used in podiatry practice to predict falls in community-dwelling older adults with foot (-related) problems. <b><i>Methods:</i></b> This was a prospective study including community-dwelling older adults (≥65 years) visiting podiatry practices. General fall-risk variables, and foot-related and function-related variables were considered as predictors for the occurrence of falls during the 12-month follow-up. Logistic regression analysis was used for model building, and internal validation was done by bootstrap resampling. <b><i>Results:</i></b> 407 participants were analyzed; the event rate was 33.4%. The final model included fall history in the previous year, unsteady while standing and walking, plantarflexor strength of the lesser toes, and gait speed. The area under the receiver operating characteristic curve was 0.71 (95% CI: 0.66–0.76) in the sample and estimated as 0.65 after shrinkage. <b><i>Conclusion:</i></b> A CPM based on fall history in the previous year, feeling unsteady while standing and walking, decreased plantarflexor strength of the lesser toes, and reduced gait speed has acceptable accuracy to predict falls in our sample of podiatry community-dwelling older adults and is easily applicable in this setting. The accuracy of the model in clinical practice should be demonstrated through external validation of the model in a next study.

scholarly journals Prevalence and risk factors of sarcopenia in community-dwelling older adults visiting regional medical institutions from the Kadoma Sarcopenia Study

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Satoshi Kurose ◽  
Satoru Nishikawa ◽  
Takayasu Nagaoka ◽  
Masahiro Kusaka ◽  
Jun Kawamura ◽  
...  
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Characteristic Curve ◽  
Laboratory Data ◽  
Multivariate Logistic Regression Analysis ◽  
Community Dwelling ◽  
Term Care ◽  
Medical Institutions ◽  
Regional Medical ◽  
Community Dwelling Older Adults

Abstract This study aimed to investigate risk factors for sarcopenia in community-dwelling older adults visiting regional medical institutions. We retrospectively analyzed medical records of 552 participants (mean age: 74.6 ± 6.7 years, males 31.3%) who underwent body composition evaluation between March 2017 and December 2018 at one of 24 medical institutions belonging to the Kadoma City Medical Association in Japan. We collected the participant’s characteristics and laboratory data. Sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia 2019. Sarcopenia, including severe sarcopenia, was detected in 22.3% of all participants, 17.3% of men, and 24.5% of women; rates increased with age. Multivariate logistic regression analysis revealed age (odds ratio [OR]: 2.12; 95% confidence interval [CI] 1.20–3.75), obesity (OR: 0.15; 95% CI 0.07–0.32), hypertension (OR: 0.44; 95% CI 0.25–0.76), certification of long term care (OR: 3.32; 95% CI 1.41–7.81), number of daily conversations (OR: 0.44; 95% CI 0.25–0.77), and malnutrition (OR: 2.42; 95% CI 1.04–5.60) as independent predictors of sarcopenia. Receiver operating characteristic curve analysis demonstrated that the cut-off for daily conversations defining sarcopenia was 4.8 persons. The prevalence of sarcopenia in this study was 22.3%. Besides traditional risk factors for sarcopenia, the number of daily conversations was an independent factor.

scholarly journals Factors Associated With Behavioral and Psychological Symptoms of Dementia: Prospective Observational Study Using Actigraphy

10.2196/29001 ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. e29001
Author(s):  
Eunhee Cho ◽  
Sujin Kim ◽  
Sinwoo Hwang ◽  
Eunji Kwon ◽  
Seok-Jae Heo ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Prospective Observational Study ◽  
Psychological Symptoms ◽  
Information Criterion ◽  
Activity Levels ◽  
Contributing Factors ◽  
Factors Associated ◽  
Physical Activity Levels ◽  
Behavioral And Psychological Symptoms

Background Although disclosing the predictors of different behavioral and psychological symptoms of dementia (BPSD) is the first step in developing person-centered interventions, current understanding is limited, as it considers BPSD as a homogenous construct. This fails to account for their heterogeneity and hinders development of interventions that address the underlying causes of the target BPSD subsyndromes. Moreover, understanding the influence of proximal factors—circadian rhythm–related factors (ie, sleep and activity levels) and physical and psychosocial unmet needs states—on BPSD subsyndromes is limited, due to the challenges of obtaining objective and/or continuous time-varying measures. Objective The aim of this study was to explore factors associated with BPSD subsyndromes among community-dwelling older adults with dementia, considering sets of background and proximal factors (ie, actigraphy-measured sleep and physical activity levels and diary-based caregiver-perceived symptom triggers), guided by the need-driven dementia-compromised behavior model. Methods A prospective observational study design was employed. Study participants included 145 older adults with dementia living at home. The mean age at baseline was 81.2 (SD 6.01) years and the sample consisted of 86 (59.3%) women. BPSD were measured with a BPSD diary kept by caregivers and were categorized into seven subsyndromes. Independent variables consisted of background characteristics and proximal factors (ie, sleep and physical activity levels measured using actigraphy and caregiver-reported contributing factors assessed using a BPSD diary). Generalized linear mixed models (GLMMs) were used to examine the factors that predicted the occurrence of BPSD subsyndromes. We compared the models based on the Akaike information criterion, the Bayesian information criterion, and likelihood ratio testing. Results Compared to the GLMMs with only background factors, the addition of actigraphy and diary-based data improved model fit for every BPSD subsyndrome. The number of hours of nighttime sleep was a predictor of the next day’s sleep and nighttime behaviors (odds ratio [OR] 0.9, 95% CI 0.8-1.0; P=.005), and the amount of energy expenditure was a predictor for euphoria or elation (OR 0.02, 95% CI 0.0-0.5; P=.02). All subsyndromes, except for euphoria or elation, were significantly associated with hunger or thirst and urination or bowel movements, and all BPSD subsyndromes showed an association with environmental change. Age, marital status, premorbid personality, and taking sedatives were predictors of specific BPSD subsyndromes. Conclusions BPSD are clinically heterogeneous, and their occurrence can be predicted by different contributing factors. Our results for various BPSD suggest a critical window for timely intervention and care planning. Findings from this study will help devise symptom-targeted and individualized interventions to prevent and manage BPSD and facilitate personalized dementia care.

scholarly journals Effects of the Matter of Balance Program on Self-Reported Physical Activity in Community-Dwelling Older Adults

2019 ◽  
Vol 5 ◽  
pp. 233372141988069
Author(s):  
Walter E. Palmer ◽  
Vicki S. Mercer
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Rapid Assessment ◽  
Community Dwelling ◽  
Activity Levels ◽  
Step Counter ◽  
Counter Measures ◽  
Community Dwelling Older Adults ◽  
Counter Data

Objective: To (a) evaluate effects of the Matter of Balance (MOB) program on self-reported physical activity (PA) in older adults as measured by the program’s activity (MOB-PA) measure and the Rapid Assessment of Physical Activity, Part 1 (RAPA1) and (b) for a separate Community cohort, explore correlations between MOB-PA and RAPA1 scores and step counts obtained using accelerometry. Methods: Community-dwelling older adults recruited from upcoming MOB classes and from in-person contacts comprised MOB ( N = 56) and Community ( N = 23) cohorts, respectively. For the MOB cohort, paired t tests were computed for baseline and follow-up MOB-PA and RAPA1 scores. For the Community cohort, Pearson’s correlations between self-reported PA and step counter measures were calculated. Results: Self-reported PA did not change following MOB participation. The MOB-PA had substantial ceiling effects, which weakened relationships with step counter data. Discussion: No evidence was found that MOB participation increased PA. The MOB-PA may not be appropriate for measuring activity levels.

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