Physical Activity In Older Population Research Articles

SMOOTHING SPLINE ANOVA MONITORING PHYSICAL ACTIVITY AND FALL RISK IN COMMUNITY-DWELLING OLDER ADULTS

Abstract Emerging sensing techniques, which are easily transportable, user-friendly, and cost-effective, may reveal new possibilities in monitoring daily objectively measured physical activity (PA) and fall risk appraisal (FRA) identification. We used a Smoothing Spline Analysis of Variance (SS-ANOVA) to profile the daily PA using accelerometer-based device across FRA groups. Using the BTrackS system (static balance assessment) and a short Fall-Efficacy Scale-International, 124 participants (mean age 75, range 60-96, 77% female, 72% no history of falls) were categorized into four different FRA groups: rational (46.8%, low fear of falling (FOF) and normal balance), irrational (17.7%, high FOF and normal balance), incongruent (19.4%, low FOF and poor balance), and congruent (16.1%, high FOF and poor balance). The vector magnitude (VM) and the number of steps were extracted per second from an average 10 (SD=4.89) consecutive days of PA recording. Daily (0-24h) temporal trend was analyzed from 1.7 million records. Groupwise, PA of the congruent group was significantly lower than other three groups, while the rational group had the highest PA based on 95% Bayesian C.I. It is evident that there is a periodic trend in PA; in particular, inactive during night (12-5am), increasing trend in the morning (5am-noon) and peak at noon, moderately decrease in the afternoon (noon-6pm), and significantly decline in the evening. No significant gender differences in PA were found. These results indicate that FOF associated with poor balance contributes to low PA, highlighting the necessity of balance enhancing intervention and cognitive reframing to promote PA in older populations.

Physical activity, well-being, and priorities of older women during the COVID-19 pandemic: a survey of Women's Health Initiative Strong and Healthy (WHISH) intervention participants.

Sheltering-in-place, social distancing, and other strategies to minimize COVID-19 transmission may impact physical activity (PA) and well-being in older adults. To assess self-reported PA changes, well-being, and priorities of older women across the USA early in the COVID-19 pandemic. In May 2020, a 10-question survey was emailed to 5,822 women, aged over 70 years, who had been assigned to the Women’s Health Initiative (WHI) Strong and Healthy (WHISH) trial PA intervention and had provided email addresses. The survey assessed general and physical well-being, current priorities, and PA levels before and during the COVID-19 pandemic. Demographic and physical function data were collected previously. Descriptive analyses characterized participants’ priorities and PA changes from before the pandemic to the time of data collection during the pandemic. Differences in PA change by age, physical function, and geographic region were assessed by Kruskal-Wallis and post hoc Dunn tests. Among 2,876 survey respondents, 89% perceived their general well-being as good, very good, or excellent, despite 90% reporting at least moderate (to extreme) concern about the pandemic, with 18.2% reporting increased PA levels, 27.1% reporting no changes, and 54.7% reporting decreased PA levels. Top priorities “in the midst of the COVID-19 outbreak” were staying in touch with family/friends (21%) and taking care of one’s body (20%). Among priorities related to physical well-being, staying active was selected most frequently (33%). Support for maintaining PA in older populations should be a priority during a pandemic and similarly disruptive events.

Activity Energy Expenditure Predicts Clinical Average Levels of Physical Activity in Older Population: Results from Salus in Apulia Study.

Self-report questionnaires are a valuable method of physical activity measurement in public health research; however, accuracy is often lacking. Resolving the differences between self-reported and objectively measured physical activity is an important surveillance challenge currently facing population health experts. The present work aims at providing the relationship between activity energy expenditure estimated from wrist-worn accelerometers and intensity of self-reported physical activity (InCHIANTI structured interview questionnaire) in a sub-cohort of a population-based study on aging in Southern Italy. Linear regression was used to test the association between measured and reported physical activity. We found that activity energy expenditure predicted clinical average levels of PA assessed through InCHIANTI classification.

PANGeA and AHA.SI project knowledge transfer for successful implementation of optimal nutrition and physical activity in older population

PANGeA and AHA.SI project knowledge transfer for successful implementation of optimal nutrition and physical activity in older population

Assessing Daily Physical Activity in Older Adults: Unraveling the Complexity of Monitors, Measures, and Methods.

At the 67th Gerontological Society of America Annual Meeting, a preconference workshop was convened to discuss the challenges of accurately assessing physical activity in older populations. The advent of wearable technology (eg, accelerometers) to monitor physical activity has created unprecedented opportunities to observe, quantify, and define physical activity in the real-world setting. These devices enable researchers to better understand the associations of physical activity with aging, and subsequent health outcomes. However, a consensus on proper methodological use of these devices in older populations has not been established. To date, much of the validation research regarding device type, placement, and data interpretation has been performed in younger, healthier populations, and translation of these methods to older populations remains problematic. A better understanding of these devices, their measurement properties, and the data generated is imperative to furthering our understanding of daily physical activity, its effects on the aging process, and vice versa. The purpose of this article is to provide an overview of the highlights of the preconference workshop, including properties of the different types of accelerometers, the methodological challenges of employing accelerometers in older study populations, a brief summary of ongoing aging-related research projects that utilize different types of accelerometers, and recommendations for future research directions.

Static or dynamic predictors of physical activity (PA)? A tracking study based on 12- and 38-month follow-ups in older adults

Studies that investigated stability of PA in older populations are scarce. Moreover, no studies used dynamic indicators to predict PA trajectories. The purpose of the present study were to investigate PA stability overtime, and to examine if changes in self-reported physical function (dynamic indicator) are better predictors of trajectories of PA than baseline measures of physical function (static indicator). This is a prospective postal survey with two time-point follow-ups: 12 and 38 months. Participants were older adults aged ≥60 years, and members of the medical insurance scheme of the French national education system. They responded to a self-report questionnaire on PA and general health status at three different times: baseline, 12- and 38-month follow-ups (n=243 for the 12-month follow-up; n=164 for the 38-month follow-up). Overtime analyses of PA showed a moderate-to-good stability with regard to both duration and volume of PA; however, a decrease in stability for vigorous PA was found between 12- and 38-month follow-ups. Both baseline measure and changes in physical function predicted PA trajectories, but magnitudes of associations were stronger for the dynamic indicator. Moreover, change in physical function was the only predictor of both becoming active compared with Inactive (reduced probability) and becoming inactive compared to Active (increased probability). In conclusion, a dynamic indicator of physical function is a better predictor of PA variation than static indicators.

Physical activity in older population: An interesting profile of elderly in Turkey

Physical activity in older population: An interesting profile of elderly in Turkey

Expected values for pedometer-determined physical activity in older populations

The purpose of this review is to update expected values for pedometer-determined physical activity in free-living healthy older populations. A search of the literature published since 2001 began with a keyword (pedometer, "step counter," "step activity monitor" or "accelerometer AND steps/day") search of PubMed, Cumulative Index to Nursing & Allied Health Literature (CINAHL), SportDiscus, and PsychInfo. An iterative process was then undertaken to abstract and verify studies of pedometer-determined physical activity (captured in terms of steps taken; distance only was not accepted) in free-living adult populations described as ≥ 50 years of age (studies that included samples which spanned this threshold were not included unless they provided at least some appropriately age-stratified data) and not specifically recruited based on any chronic disease or disability. We identified 28 studies representing at least 1,343 males and 3,098 females ranging in age from 50–94 years. Eighteen (or 64%) of the studies clearly identified using a Yamax pedometer model. Monitoring frames ranged from 3 days to 1 year; the modal length of time was 7 days (17 studies, or 61%). Mean pedometer-determined physical activity ranged from 2,015 steps/day to 8,938 steps/day. In those studies reporting such data, consistent patterns emerged: males generally took more steps/day than similarly aged females, steps/day decreased across study-specific age groupings, and BMI-defined normal weight individuals took more steps/day than overweight/obese older adults. The range of 2,000–9,000 steps/day likely reflects the true variability of physical activity behaviors in older populations. More explicit patterns, for example sex- and age-specific relationships, remain to be informed by future research endeavors.

Correction: Expected values for pedometer-determined physical activity in older populations

Correction to Tudor-Locke C, Hart TL, Washington TL: Expected values for pedometer-determined physical activity in older populations. International Journal of Behavioral Nutrition and Physical Activity 2009, 6:59

Promoting physical activity among older adults: From ecology to the individual

The promotion of physical activity in older populations holds the promise of promoting health and reducing the risk of disablement. Individual- and community-based programs are often presented as being distinct and, in some cases, antithetical. The objective of this paper is to illustrate, through the use of an ecologic model, that individual- and community-based programs are complementary. The following topics are discussed: (1) the development of transdisciplinary theories; (2) the establishment of better measures to address the linkages across individual behavior, group behavior, the built environment, and the temporal sequence of biological, behavioral, and environmental factors; (3) the translation of research into practice and policies; and (4) the training of a new generation of scholars and practitioners to develop and execute research, practice, and policy agendas in this area. An ecologic model fosters a comprehensive agenda based on biological, behavioral, and environmental factors. The study of the interaction of the individual with the environment is challenging but potentially more important than the study of the role of the individual or the environment alone in the promotion of physical activity.

Social–Cognitive and Perceived Environment Influences Associated with Physical Activity in Older Australians

Background. Regular physical activity in older adults can facilitate healthy aging, improve functional capacity, and prevent disease. However, factors associated with physical inactivity in older populations are poorly understood. This study attempts to identify social–cognitive and perceived environmental influences associated with physical activity participation in older populations.Methods. In a randomly selected sample of 449 Australian adults age 60 and older, we assessed self-reported physical activity and a range of social–cognitive and perceived environmental factors. Respondents were classified as sufficiently active and inactive based on energy expenditure estimates (kcal/week) derived from self-reported physical activity. Two logistic regression models, with and without self-efficacy included, were conducted to identify modifiable independent predictors of physical activity.Results. Significantly more males than females were physically active. Physical activity participation was related to age with a greater proportion of those age 65–69 being active than those age 60–64 or 70 or older. High self-efficacy, regular participation of friends and family, finding footpaths safe for walking, and access to local facilities were significantly associated with being active.Conclusion. Identifying predictors of physical activity in older populations, particularly social support, facility access, and neighbourhood safety, can inform the development of policy and intervention strategies to promote the health of older people.