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Physical activity and resting pulse rate in older adults: findings from a randomized controlled trial.

ABSTRACT: Elevated resting pulse rate (RPR) is a well-recognized risk factor for adverse outcomes. Epidemiological evidence supports the beneficial effects of regular exercise for lowering RPR, but studies are mainly confined to persons younger than 65 years. We set out to evaluate the utility of a physical activity (PA) intervention for slowing RPR among older adults.A total of 424 seniors (ages 70-89 years) were randomized to a moderate intensity PA intervention or an education-based "successful aging" health program. Resting pulse rate was assessed at baseline, 6 months, and 12 months. Longitudinal differences in RPR were evaluated between treatment groups using generalized estimating equation models, reporting unstandardized ? coefficients with robust SEs.Increased frequency and duration of aerobic training were observed for the PA group at 6 and 12 months as compared with the successful aging group (P < .001). In both groups, RPR remained unchanged over the course of the 12-month study period (P = .67). No significant improvement was observed (? [SE] = 0.58 [0.88]; P = .51) for RPR when treatment groups were compared using the generalized estimating equation method. Comparable results were found after omitting participants with a pacemaker, cardiac arrhythmia, or who were receiving ?-blockers.Twelve months of moderate intensity aerobic training did not improve RPR among older adults. Additional studies are needed to determine whether PA of longer duration and/or greater intensity can slow RPR in older persons.

SUBMITTER: O'Hartaigh B

PROVIDER: S-EPMC4180058 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Physical activity and resting pulse rate in older adults: findings from a randomized controlled trial.

O'Hartaigh Bríain B Pahor Marco M Buford Thomas W TW Dodson John A JA Forman Daniel E DE Gill Thomas M TM

American heart journal 20140730 4

<h4>Background</h4>Elevated resting pulse rate (RPR) is a well-recognized risk factor for adverse outcomes. Epidemiological evidence supports the beneficial effects of regular exercise for lowering RPR, but studies are mainly confined to persons younger than 65 years. We set out to evaluate the utility of a physical activity (PA) intervention for slowing RPR among older adults.<h4>Methods</h4>A total of 424 seniors (ages 70-89 years) were randomized to a moderate intensity PA intervention or an ...[more]

PMID: 25262271

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Project description:Obesity can limit physical capacity and lower physical activity levels in elderly people. Low physical activity levels may be mediated by autonomic dysfunction with decreased heart rate variability (HRV). However, the relationship between autonomic dysfunction and low physical capability remains unclear. This cross-sectional study investigated the association of low physical capability with HRV in older adults with obesity.We recruited 231 old man and 210 old women with a mean (range) age of 65.5 (51-78) and 62.9 (52-76) years, respectively. Physical capability was measured using mobility tasks, including functional reach, single-leg stance (SLS), gait speed (GS), timed up and go, and timed chair rise (TCR), and the scores on these tasks were merged and transformed into a global physical capability score (GPCS). HRV was measured using a 7-min resting pulse-based technique, and the time- and frequency-domain indices of HRV were obtained including standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences at rest (rMSSD), and high-frequency (HF) power. All HRV indices were natural log (ln) transformed for analysis. Participants were divided into high, moderate, and low physical-capability groups according to their physical performance. Multivariate analysis of covariance was performed to test differences in HRV indices among physical-capability groups with participants' characteristics serving as covariates. A stepwise regression model was established to identify the determinants of HRV indices. We used hierarchical regression analysis to identify the association of the GPCS with HRV indices.In both men and women, the low physical-capability group exhibited significantly increased heart rate (P <0.05) and decreased HRV in terms of a decreased ln[SDNN] (P <0.001), ln[rMSSD] (P <0.05) and ln[HF] (P <0.05), compared with the high physical-capability group. GS positively predicted ln[SDNN], whereas SLS, GS, and TCR were determinants of ln[HF], regardless of gender. The GPCS in older men and women independently accounted for 29.9% (P <0.001) and 23.7% (P <0.001), respectively, in variance in ln[SDNN].A low physical-capability level is an independent determinant of decreased HRV in older adults with obesity.

Project description:BackgroundMore people are living longer lives leading to a growth in the population of older adults, many of whom have comorbidities and low levels of physical function. Physical activity in later life can prevent or delay age-related disability. Identifying a cost-effective means of increasing physical activity in older adults therefore remains an important public health priority.Physical Activity Facilitation (PAF) is an intervention shown to increase physical activity in adults with depression. The PAF model was modified for a population of older adults at risk of disability. This study aimed to assess the feasibility of undertaking a definitive RCT of the PAF intervention in the target population.MethodsA pilot randomised controlled trial (RCT) was delivered through primary care. Patients at risk of disability and who were not meeting recommended levels of physical activity were recruited through postal invitation and direct approach in the practice waiting room. Those meeting eligibility criteria were enrolled and randomised at a 2:1 ratio to the PAF intervention and control. Behaviour change techniques were used by facilitators with participants over the telephone and face-to-face for 6 months. Outcome measures including physical function, physical activity, depression, social support, and quality of life were collected at baseline and at 6 months.ResultsA high proportion of patients responded to the initial invitation (68%), yet many were ineligible due to high levels of self-reported physical activity and baseline physical function. Fifty-one participants were recruited to the trial, with an average age of 74 years (range 65-89), and there were high rates of adherence and retention to the study (94% follow-up at 6 months). The majority of outcome data collected from participants was complete; however, the validated scale used to measure self-reported physical activity was associated with high levels of missing data.ConclusionsThe findings of this pilot RCT suggest that it is feasible to deliver a definitive RCT of the PAF intervention in this population. Further work is required to improve the efficiency of recruitment and to minimise missing data from self-reported physical activity measures.Trial registrationCurrent controlled trials ISRCTN80470273. Registered 25 October 2013.

Project description:BACKGROUND:The beneficial effects of physical activity (PA) for older adults are well known. However, few older adults reach the health guideline of 150 min per week of moderate-to-vigorous PA (MVPA). Electronic health (eHealth) interventions are effective in increasing PA levels in older adults in the short term but, rarely, intermediate-term effects after a period without the support of a website or an app have been examined. Furthermore, current theory-based interventions focus mainly on preintentional determinants, although postintentional determinants should also be included to increase the likelihood of successful behavior change. OBJECTIVE:This study aimed to investigate the effect of the theory-based eHealth intervention, MyPlan 2.0, focusing on pre- and postintentional determinants on both accelerometer-based and self-reported PA levels in older Belgian adults in the short and intermediate term. METHODS:This study was a randomized controlled trial with three data collection points: baseline (N=72), post (five weeks after baseline; N=65), and follow-up (three months after baseline; N=65). The study took place in Ghent, and older adults (aged ?65 years) were recruited through a combination of random and convenience sampling. At all the time points, participants were visited by the research team. Self-reported domain-specific PA was assessed using the International Physical Activity Questionnaire, and accelerometers were used to objectively assess PA. Participants in the intervention group got access to the eHealth intervention, MyPlan 2.0, and used it independently for five consecutive weeks after baseline. MyPlan 2.0 was based on the self-regulatory theory and focused on both pre- and postintentional processes to increase PA. Multilevel mixed-models repeated measures analyses were performed in R (R Foundation for Statistical Computing). RESULTS:Significant (borderline) positive intervention effects were found for accelerometer-based MVPA (baseline-follow-up: intervention group +5 min per day and control group -5 min per day; P=.07) and for accelerometer-based total PA (baseline-post: intervention group +20 min per day and control group -24 min per day; P=.05). MyPlan 2.0 was also effective in increasing self-reported PA, mainly in the intermediate term. A positive intermediate-term intervention effect was found for leisure-time vigorous PA (P=.02), moderate household-related PA (P=.01), and moderate PA in the garden (P=.04). Negative intermediate-term intervention effects were found for leisure-time moderate PA (P=.01) and cycling for transport (P=.07). CONCLUSIONS:The findings suggest that theory-based eHealth interventions focusing on pre- and postintentional determinants have the potential for behavior change in older adults. If future studies including larger samples and long-term follow-up can confirm and clarify these findings, researchers and practitioners should be encouraged to use a self-regulation perspective for eHealth intervention development. TRIAL REGISTRATION:Clinicaltrials.gov NCT03194334; https://clinicaltrials.gov/ct2/show/NCT03783611.

Project description:BackgroundPervasive games aim to create more fun and engaging experiences by mixing elements from the real world into the game world. Because they intermingle with players' lives and naturally promote more casual gameplay, they could be a powerful strategy to stimulate physical activity among older adults. However, to use these games more effectively, it is necessary to understand how design elements of the game affect player behavior.ObjectiveThe aim of this study was to evaluate how the presence of a specific design element, namely social interaction, would affect levels of physical activity.MethodsParticipants were recruited offline and randomly assigned to control and intervention groups in a single-blind design. Over 4 weeks, two variations of the same pervasive game were compared: with social interaction (intervention group) and with no social interaction (control group). In both versions, players had to walk to physical locations and collect virtual cards, but the social interaction version allowed people to collaborate to obtain more cards. Changes in the weekly step counts were used to evaluate the effect on each group, and the number of places visited was used as an indicator of play activity.ResultsA total of 20 participants were recruited (no social interaction group, n=10; social interaction group, n=10); 18 participants remained active until the end of the study (no social interaction group, n=9; social interaction group, n=9). Step counts during the first week were used as the baseline level of physical activity (no social interaction group: mean 46,697.2, SE 7905.4; social interaction group: mean 45,967.3, SE 8260.7). For the subsequent weeks, changes to individual baseline values (absolute/proportional) for the no social interaction group were as follows: 1583.3 (SE 3108.3)/4.6% (SE 7.2%) (week 2), 591.5 (SE 2414.5)/2.4% (SE 4.7%) (week 3), and -1041.8 (SE 1992.7)/0.6% (SE 4.4%) (week 4). For the social interaction group, changes to individual baseline values were as follows: 11520.0 (SE 3941.5)/28.0% (SE 8.7%) (week 2), 9567.3 (SE 2631.5)/23.0% (SE 5.1%) (week 3), and 7648.7 (SE 3900.9)/13.9% (SE 8.0%) (week 4). The result of the analysis of the group effect was significant (absolute change: ?2=0.31, P=.04; proportional change: ?2=0.30, P=.03). Correlations between both absolute and proportional change and the play activity were significant (absolute change: r=0.59, 95% CI 0.32 to 0.77; proportional change: r=0.39, 95% CI 0.08 to 0.64).ConclusionsThe presence of social interaction design elements in pervasive games appears to have a positive effect on levels of physical activity.Trial registrationJapan Medical Association Clinical Trial Registration Number JMA-IIA00314; https://tinyurl.com/y5nh6ylr (Archived by WebCite at http://www.webcitation.org/761a6MVAy).

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Physical activity and resting pulse rate in older adults: findings from a randomized controlled trial.

Publications

Physical activity and resting pulse rate in older adults: findings from a randomized controlled trial.

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