Predicting the Future Need of Walking Device or Assistance by Moderate to Vigorous Physical Activity: A 2-Year Prospective Study of Women Aged 75 Years and Above
Abstract:Objective To examine the association between daily moderate to vigorous physical activity (MVPA) and the change in mobility function among community-dwelling Japanese women aged 75 years and above. Methods This prospective study included 330 older women aged 75 years and above who could walk without a walking device or assistance. MVPA and light-intensity physical activity (LPA) were assessed using an accelerometer for seven consecutive days. MVPA was defined as an activity with an intensity of >3 metabolic eq… Show more
“…A total of 34 studies were retained for inclusion. [ 6 , 7 , 21 – 52 ] An additional nine studies were identified through secondary sources [ 53 – 61 ], resulting in a final sample of 43 studies (see Figure 1 ). Fig 1.…”
Background
Disability poses a burden for older persons, and is associated with poor outcomes and high societal costs. Prediction models could potentially identify persons who are at risk for disability. An up to date review of such models is missing.
Objective
To identify models developed for the prediction of functional status in community dwelling older persons.
Methods
A systematic review was performed including studies of older persons that developed and/or validated prediction models for the outcome functional status. Medline and EMBASE were searched, and reference lists and prospective citations were screened for additional references. Risk of bias was assessed using the PROBAST-tool. The performance of models was described and summarized, and the use of predictors was collated using the bag-of-words text mining procedure.
Results
Forty-three studies were included and reported 167 evaluations of prediction models. The median c-statistic values for the multivariable development models ranged between 0.65 and 0.76 (minimum = 0.58, maximum = 0.90), and were consistently higher than the values of the validation models for which median c-statistic values ranged between 0.6 and 0.68 (minimum = 0.50, maximum = 0.81). A total of 559 predictors were used in the models. The five predictors most frequently used were gait speed (n = 47), age (n = 38), cognition (n = 27), frailty (n = 24), and gender (n = 22).
Conclusions
No model can be recommended for implementation in practice. However, frailty models appear to be the most promising, because frailty components (e.g. gait speed) and frailty indexes demonstrated good to excellent predictive performance. However, the risk of study bias was high. Substantial improvements can be made in the methodology.
“…A total of 34 studies were retained for inclusion. [ 6 , 7 , 21 – 52 ] An additional nine studies were identified through secondary sources [ 53 – 61 ], resulting in a final sample of 43 studies (see Figure 1 ). Fig 1.…”
Background
Disability poses a burden for older persons, and is associated with poor outcomes and high societal costs. Prediction models could potentially identify persons who are at risk for disability. An up to date review of such models is missing.
Objective
To identify models developed for the prediction of functional status in community dwelling older persons.
Methods
A systematic review was performed including studies of older persons that developed and/or validated prediction models for the outcome functional status. Medline and EMBASE were searched, and reference lists and prospective citations were screened for additional references. Risk of bias was assessed using the PROBAST-tool. The performance of models was described and summarized, and the use of predictors was collated using the bag-of-words text mining procedure.
Results
Forty-three studies were included and reported 167 evaluations of prediction models. The median c-statistic values for the multivariable development models ranged between 0.65 and 0.76 (minimum = 0.58, maximum = 0.90), and were consistently higher than the values of the validation models for which median c-statistic values ranged between 0.6 and 0.68 (minimum = 0.50, maximum = 0.81). A total of 559 predictors were used in the models. The five predictors most frequently used were gait speed (n = 47), age (n = 38), cognition (n = 27), frailty (n = 24), and gender (n = 22).
Conclusions
No model can be recommended for implementation in practice. However, frailty models appear to be the most promising, because frailty components (e.g. gait speed) and frailty indexes demonstrated good to excellent predictive performance. However, the risk of study bias was high. Substantial improvements can be made in the methodology.
“…This may be especially important for populations such as the elderly or chronically ill, where high-intensity PA might be difficult to achieve for a variety of reasons. 40 , 39 In addition, a change in the intensity of PA within a 24-h daily schedule without changing other components (i.e. SB and sleep) may be an effective strategy to improve some health outcomes.…”
The distribution of time that people spend in physical activity of various intensities has important health implications. Physical activity (commonly categorised by the intensity into light, moderate and vigorous physical activity), sedentary behaviour and sleep, should not be analysed separately, because they are parts of a time-use composition with a natural constraint of [Formula: see text] h/day. To find out how are relative reallocations of time between physical activity of various intensities associated with health, herewith we describe compositional scalar-on-function regression and a newly developed compositional functional isotemporal substitution analysis. Physical activity intensity data can be considered as probability density functions, which better reflects the continuous character of their measurement using accelerometers. These probability density functions are characterised by specific properties, such as scale invariance and relative scale, and they are geometrically represented using Bayes spaces with the Hilbert space structure. This makes possible to process them using standard methods of functional data analysis in the [Formula: see text] space, via centred logratio (clr) transformation. The scalar-on-function regression with clr transformation of the explanatory probability density functions and compositional functional isotemporal substitution analysis were applied to a dataset from a cross-sectional study on adiposity conducted among school-aged children in the Czech Republic. Theoretical reallocations of time to physical activity of higher intensities were found to be associated with larger and more progressive expected decreases in adiposity. We obtained a detailed insight into the dose–response relationship between physical activity intensity and adiposity, which was enabled by using the compositional functional approach.
“…The non-wear time was defined as no acceleration signal obtained for more than 60 min. Only accelerometer data for more than 5 valid days, with at least 10 wearing hours per day, were adopted, and the average duration of PA for each intensity was calculated and used for the analysis 26 ) .…”
[Purpose] To clarify the association between preoperative physical activity and
postoperative ambulation based on physical activity intensity, and independent of
functional capacity and depression, in patients with gastrointestinal cancer.
[Participants and Methods] Seventy patients who underwent surgery for primary colorectal
or gastric cancer were enrolled. Preoperative moderate-to-vigorous-intensity physical
activity, light-intensity physical activity, and sedentary behavior were assessed using an
accelerometer. The primary outcome was the days to postoperative first ambulation (capable
of independently and continuously walking 150 m). Functional capacity and depression, as
confounders, were evaluated by measuring the 6-minute walk distance and using the Hospital
Anxiety and Depression Scale. [Results] Of the 70 patients, 28 had insufficient
accelerometer data, and 42 were included in the analysis. Preoperative light-intensity
physical activity, but not moderate-to-vigorous-intensity physical activity and sedentary
behavior, was negatively associated with the days to postoperative first ambulation, after
adjusting for age, preoperative functional capacity, and preoperative depression.
[Conclusion] Preoperative light-intensity physical activity was associated with the days
to postoperative ambulation independently of age, functional capacity, and depression.
Hence, predicting delayed ambulation by preoperative light-intensity physical activity in
patients with gastrointestinal cancer may be useful.
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