52 research outputs found
Why older adults spend time sedentary and break their sedentary behavior: a mixed methods approach using life-logging equipment
Older adults are recommended to reduce their sedentary time to promote healthy ageing. To develop effective interventions identifying when, why, and how older adults are able to change their sitting habits is important. The aim of this mixed-method study was to improve our understanding of reasons for (breaking) sedentary behavior in older adults. Thirty older adults (74.0 [+/- 5.3] years old, 73% women) were asked about their believed reasons for (breaking) sedentary behavior, and about their actual reasons when looking at a personal storyboard with objective records of activPAL monitor data and time-lapse camera pictures showing all their periods of sedentary time in a day. The most often mentioned believed reason for remaining sedentary was television/radio (mentioned by 48.3%), while eating/drinking was most often mentioned as actual reason (96.6%). Only 17.2% believed that food/tea preparation was a reason to break up sitting, while this was an actual reason for 82.8% of the study sample. Results of this study show that there is a discrepancy between believed and actual reasons for (breaking) sedentary behavior. These findings suggest developing interventions utilizing the actual reasons for breaking sedentary behavior to reduce sedentary time in older adults
Attitudes to ageing and objectively-measured sedentary and walking behaviour in older people: the Lothian Birth Cohort 1936
Background:Prolonged sitting and low activity—both common in older people—are associated with increased mortality and poorer health. Whether having a more negative attitude to ageing is associated with higher levels of these behaviours is unclear.Objective:We investigated the prospective relationship between attitudes to ageing and objectively measured sedentary and walking behaviour.Methods:Participants were 271 members of the Lothian Birth Cohort 1936. At age 72 years, participants completed the Attitudes to Ageing Questionnaire which assesses attitudes on three domains—Psychosocial loss, Physical change and Psychological growth. At age 79 years, participants wore an activPAL activity monitor for seven days. The outcome measures were average daily time spent sedentary, number of sit-to-stand transitions, and step count.Results:There were no significant associations between any of the Attitude to Ageing domain scores and time spent sedentary or number of sit-to-stand transitions. In sex-adjusted analysis, having a more positive attitude to ageing as regards Physical change was associated with a slightly higher daily step count, for a SD increment in score, average daily step count was greater by 1.5% (95% CI 0.6%, 2.4%). On further adjustment for potential confounding factors these associations were no longer significant.Conclusion:We found no evidence that attitudes to ageing at age 72 were predictive of sedentary or walking behaviour seven years later. Future studies should examine whether attitudes to ageing are associated with objectively measured walking or sedentary behaviour at the same point in time. The existence of such an association could inform the development of interventions.<br/
Reliability and validity of ten consumer activity trackers
Background: Activity trackers can potentially stimulate users to increase their physical activity behavior. The aim of this study was to examine the reliability and validity of ten consumer activity trackers for measuring step count in both laboratory and free-living conditions. Method: Healthy adult volunteers (n = 33) walked twice on a treadmill (4.8 km/h) for 30 min while wearing ten different activity trackers (i.e. Lumoback, Fitbit Flex, Jawbone Up, Nike+ Fuelband SE, Misfit Shine, Withings Pulse, Fitbit Zip, Omron HJ-203, Yamax Digiwalker SW-200 and Moves mobile application). In free-living conditions, 56 volunteers wore the same activity trackers for one working day. Test-retest reliability was analyzed with the Intraclass Correlation Coefficient (ICC). Validity was evaluated by comparing each tracker with the gold standard (Optogait system for laboratory and ActivPAL for free-living conditions), using paired samples t-tests, mean absolute percentage errors, correlations and Bland-Altman plots. Results: Test-retest analysis revealed high reliability for most trackers except for the Omron (ICC .14), Moves app (ICC .37) and Nike+ Fuelband (ICC .53). The mean absolute percentage errors of the trackers in laboratory and free-living conditions respectively, were: Lumoback (−0.2, −0.4), Fibit Flex (−5.7, 3.7), Jawbone Up (−1.0, 1.4), Nike+ Fuelband (−18, −24), Misfit Shine (0.2, 1.1), Withings Pulse (−0.5, −7.9), Fitbit Zip (−0.3, 1.2), Omron (2.5, −0.4), Digiwalker (−1.2, −5.9), and Moves app (9.6, −37.6). Bland-Altman plots demonstrated that the limits of agreement varied from 46 steps (Fitbit Zip) to 2422 steps (Nike+ Fuelband) in the laboratory condition, and 866 steps (Fitbit Zip) to 5150 steps (Moves app) in the free-living condition. Conclusion: The reliability and validity of most trackers for measuring step count is good. The Fitbit Zip is the most valid whereas the reliability and validity of the Nike+ Fuelband is low
Reliability, minimal detectable change and responsiveness to change: indicators to select the best method to measure sedentary behaviour in older adults in different study designs
Introduction : Prolonged sedentary behaviour (SB) is associated with poor health. It is unclear which SB measure is most appropriate for interventions and population surveillance to measure and interpret change in behaviour in older adults. The aims of this study: to examine the relative and absolute reliability, Minimal Detectable Change (MDC) and responsiveness to change of subjective and objective methods of measuring SB in older adults and give recommendations of use for different study designs.
Methods : SB of 18 older adults (aged 71 (IQR 7) years) was assessed using a systematic set of six subjective tools, derived from the TAxonomy of Self report Sedentary behaviour Tools (TASST), and one objective tool (activPAL3c), over 14 days. Relative reliability (Intra Class Correlation coefficients-ICC), absolute reliability (SEM), MDC, and the relative responsiveness (Cohen's d effect size (ES) and Guyatt's Responsiveness coefficient (GR)) were calculated for each of the different tools and ranked for different study designs.
Results : ICC ranged from 0.414 to 0.946, SEM from 36.03 to 137.01 min, MDC from 1.66 to 8.42 hours, ES from 0.017 to 0.259 and GR from 0.024 to 0.485. Objective average day per week measurement ranked as most responsive in a clinical practice setting, whereas a one day measurement ranked highest in quasi-experimental, longitudinal and controlled trial study designs. TV viewing Previous Week Recall (PWR) ranked as most responsive subjective measure in all study designs.
Conclusions : The reliability, Minimal Detectable Change and responsiveness to change of subjective and objective methods of measuring SB is context dependent. Although TV viewing-PWR is the more reliable and responsive subjective method in most situations, it may have limitations as a reliable measure of total SB. Results of this study can be used to guide choice of tools for detecting change in sedentary behaviour in older adults in the contexts of population surveillance, intervention evaluation and individual care
Barriers and facilitators for screening older adults on fall risk in a hospital setting: Perspectives from patients and healthcare professionals
We aimed to gain insight into the barriers and facilitators to fall risk screening of older adults visiting the hospital as experienced by patients and healthcare professionals, and to examine the differences between chronic- and acute-care patients. We invited patients (≥ 70 years) attending the nephrology and emergency department to participate in the screening. Patients and their healthcare professionals were asked to complete a self-administered questionnaire based on the “Barriers and Facilitators Assessment Instrument”. Differences in barriers and facilitators between acute- and chronic-care patients were examined with chi-square tests. A total of 216 patients were screened, and 103 completed the questionnaire. They considered many factors as facilitators, and none as barriers. Acute-care patients were more positive than chronic-care patients about healthcare worker characteristics, such as knowledge and skills. After screening, patients were more open to receiving advice regarding fall prevention. The 36 healthcare professionals considered program characteristics to be facilitators and mainly factors regarding healthcare worker characteristics as barriers to implementation. For patients, the outpatient setting seemed to be a good place to be screened for fall risk. Healthcare professionals also suggested that program characteristics could enhance implementation. However, healthcare professionals’ mindsets and the changing of routines are barriers that have to be addressed first
Orvieto, Angiolo
Objective. Although regular physical activity is an effective secondary prevention strategy for patients with a chronic disease, it is unclear whether patients change their daily physical activity after being diagnosed. Therefore, the aims of this study were to (1) describe changes in levels of physical activity in middle-aged women before and after diagnosis with a chronic disease (heart disease, diabetes, asthma, breast cancer, arthritis, depression); and to (2) examine whether diagnosis with a chronic disease affects levels of physical activity in these women. Methods. Data from 5 surveys (1998-2010) of the Australian Longitudinal Study on Women's Health (ALSWH) were used. Participants (N = 4840, born 1946-1951) completed surveys every three years, with questions about diseases and leisure time physical activity. The main outcome measure was physical activity, categorized as: nil/sedentary, low active, moderately active, highly active. Results. At each survey approximately half the middle-aged women did not meet the recommended level of physical activity. Between consecutive surveys, 41%-46% of the women did not change, 24%-30% decreased, and 24%-31% increased their physical activity level. These proportions of change were similar directly after diagnosis with a chronic disease, and in the years before or after diagnosis. Generalized estimating equations showed that there was no statistically significant effect of diagnosis with a chronic disease on levels of physical activity in women. Conclusion. Despite the importance of physical activity for the management of chronic diseases, most women did not increase their physical activity after diagnosis. This illustrates a need for tailored interventions to enhance physical activity in newly diagnosed patients. (C) 2015 Elsevier Inc. All rights reserved
Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: a novel compositional data analysis approach
<div><p>The associations between time spent in sleep, sedentary behaviors (SB) and physical activity with health are usually studied without taking into account that time is finite during the day, so time spent in each of these behaviors are codependent. Therefore, little is known about the combined effect of time spent in sleep, SB and physical activity, that together constitute a composite whole, on obesity and cardio-metabolic health markers. Cross-sectional analysis of NHANES 2005–6 cycle on N = 1937 adults, was undertaken using a compositional analysis paradigm, which accounts for this intrinsic codependence. Time spent in SB, light intensity (LIPA) and moderate to vigorous activity (MVPA) was determined from accelerometry and combined with self-reported sleep time to obtain the 24 hour time budget composition. The distribution of time spent in sleep, SB, LIPA and MVPA is significantly associated with BMI, waist circumference, triglycerides, plasma glucose, plasma insulin (all p<0.001), and systolic (p<0.001) and diastolic blood pressure (p<0.003), but not HDL or LDL. Within the composition, the strongest positive effect is found for the proportion of time spent in MVPA. Strikingly, the effects of MVPA replacing another behavior and of MVPA being displaced by another behavior are asymmetric. For example, re-allocating 10 minutes of SB to MVPA was associated with a lower waist circumference by 0.001% but if 10 minutes of MVPA is displaced by SB this was associated with a 0.84% higher waist circumference. The proportion of time spent in LIPA and SB were detrimentally associated with obesity and cardiovascular disease markers, but the association with SB was stronger. For diabetes risk markers, replacing SB with LIPA was associated with more favorable outcomes. Time spent in MVPA is an important target for intervention and preventing transfer of time from LIPA to SB might lessen the negative effects of physical inactivity.</p></div
Positive and negative well-being and objectively measured sedentary behaviour in older adults: evidence from three cohorts
Background:
Sedentary behaviour is related to poorer health independently of time spent in moderate to vigorous physical activity. The aim of this study was to investigate whether wellbeing or symptoms of anxiety or depression predict sedentary behaviour in older adults.
Method:
Participants were drawn from the Lothian Birth Cohort 1936 (LBC1936) (n = 271), and the West of Scotland Twenty-07 1950s (n = 309) and 1930s (n = 118) cohorts. Sedentary outcomes, sedentary time, and number of sit-to-stand transitions, were measured with a three-dimensional accelerometer (activPAL activity monitor) worn for 7 days. In the Twenty-07 cohorts, symptoms of anxiety and depression were assessed in 2008 and sedentary outcomes were assessed ~ 8 years later in 2015 and 2016. In the LBC1936 cohort, wellbeing and symptoms of anxiety and depression were assessed concurrently with sedentary behaviour in 2015 and 2016. We tested for an association between wellbeing, anxiety or depression and the sedentary outcomes using multivariate regression analysis.
Results:
We observed no association between wellbeing or symptoms of anxiety and the sedentary outcomes. Symptoms of depression were positively associated with sedentary time in the LBC1936 and Twenty-07 1950s cohort, and negatively associated with number of sit-to-stand transitions in the LBC1936. Meta-analytic estimates of the association between depressive symptoms and sedentary time or number of sit-to-stand transitions, adjusted for age, sex, BMI, long-standing illness, and education, were β = 0.11 (95% CI = 0.03, 0.18) and β = − 0.11 (95% CI = − 0.19, −0.03) respectively.
Conclusion:
Our findings indicate that depressive symptoms are positively associated with sedentary behavior. Future studies should investigate the causal direction of this association
Characteristics of a protocol to collect objective physical activity/sedentary behaviour data in a large study : seniors USP (understanding sedentary patterns)
The Seniors USP study measured sedentary behaviour (activPAL3, 9 day wear) in older adults. The measurement protocol had three key characteristics: enabling 24-hour wear (monitor location, waterproofing); minimising data loss (reducing monitor failure, staff training, communication); and quality assurance (removal by researcher, confidence about wear). Two monitors were not returned; 91% (n=700) of returned monitors had 7 valid days of data. Sources of data loss included monitor failure (n=11), exclusion after quality assurance (n=5), early removal for skin irritation (n=8) or procedural errors (n=10). Objective measurement of physical activity and sedentary behaviour in large studies requires decisional trade-offs between data quantity (collecting representative data) and utility (derived outcomes that reflect actual behaviour). Keywords: methodology; accelerometer; adherence; data loss; activPAL; postur
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