Journal of physical activity & health最新文献

Background: Limited evidence exists for the role of parent-child coparticipation in physical activity (joint light, moderate, or vigorous physical activities involving at least 1 child and a parent) in parents' and children's overall physical activity. This study examined the association of parent-child coparticipation in physical activity with parental and children's daily physical activity and explored correlates of coparticipation.

Methods: Data were from 149 participants (41 families: 67 parents [30-55 y, 57% female] and 82 children [4-16 y, 40% girls]) in the Families Reporting Every Step to Health pilot study. Families Reporting Every Step to Health was a 3-armed, parallel-group, randomized controlled pilot trial. Participants' physical activity and location were measured simultaneously with accelerometers and Global Positioning System monitors. Data from 3 data collection points (baseline and 2 follow-ups) were analyzed cross-sectionally using multivariable linear mixed models with random intercepts at the family and participant levels.

Results: At baseline, children and parents accumulated an average of 70 and 36 minutes per day, respectively, of parent-child coparticipation in physical activity, which contributed 33% and 17% of their daily total physical activity, respectively. For both parents and children, coparticipation was positively associated with daily total physical activity (β = 0.37; 95% CI, 0.19-0.55 min/d) and daily moderate- to vigorous-intensity physical activity (β = 0.10; 95% CI, 0.03-0.16 min/d). Coparticipation in physical activity was on average 28.80 (11.23-46.37) minutes per day lower among parents than among children.

Conclusion: Parent-child coparticipation in physical activity might be a promising component of family-based interventions to promote physical activity among children and parents.

Background: Steps4Health, an mHealth tool for promoting physical activity and optimizing the 24-hour movement behaviors in long-term conditions, was implemented into a regional multidisciplinary clinical weight management service. This service evaluation reports uptake, usage, linkage with wearable devices, and impact on stepping behavior.

Methods: Service users were adults living with severe obesity (body mass index ≥40 kg/m2 or ≥35 kg/m2 with a comorbidity) referred to a regional weight management service from November 2023 to August 2024. Those without physical activity contraindications were offered Steps4Health during their initial consultation. Steps4Health provides personalized goal-setting and feedback on stepping and other 24-hour behaviors alongside educational material and enables linkage to wearable activity devices incorporating baseline physical activity levels. Data extraction allowed for at least 6 weeks of follow-up, assessing uptake, demographic characteristics, usage patterns, and longitudinal stepping data.

Results: Of 559 service users, 307 (54.9%) were eligible for Steps4Health. A total of 290 (94.5% of those eligible) individuals completed registration and logged into Steps4Health, an average of 28 times (8.3 min/login) over a 6-week period. The most popular features of Steps4Health were educational resources providing information on physical activity and chronic conditions. At baseline users averaged 4079 (95% confidence interval [CI], 2628 to 4531) steps/day. One hundred and thirty-nine (24.9%) logged at least 2 days of stepping data. Over the first 6 weeks, an average clinically meaningful increase of 974 (581, 1366; P < .001) steps/day was observed.

Conclusions: Steps4Health, a bespoke digital tool promoting increased physical activity in inactive clinical populations, was used by half of all individuals within a regional weight management service with half again regularly self-monitoring daily physical activity with a clinically meaningful increase observed over the first 6 weeks. Steps4Health shows promise as part of a broader strategy to enhance physical activity engagement within clinical weight management services.

Background: The optimal moment to deliver digital prompts for reducing sedentary behavior (SB) is when individuals are susceptible to prolonged SB (vulnerability) and open to behavior change (opportunity). This study aims to examine both vulnerability and opportunity.

Methods: A 14-day ecological momentary assessment study was conducted with 105 older adults. Participants wore a Fitbit activity tracker and an ActivPAL accelerometer and used a smartphone-based ecological momentary assessment app. Sensor-triggered questionnaires were delivered via the app after 30 minutes of SB to capture participants' activity, physical, social, and temporal contexts; feelings of pain and fatigue; and willingness to interrupt SB. Descriptive statistics identified states of vulnerability, whereas linear mixed models examined when participants are willing to interrupt prolonged SB, shedding light on states of opportunity.

Results: Ecological momentary assessment data (n = 2580) showed that older adults were most vulnerable to prolonged SB while watching TV (36.3%) and using digital devices (14.7%). Prolonged SB predominantly occurred at home (91.2%), in the evening (46.4%), when feeling fatigue (52.2%), and when experiencing mild pain (21.1%). The willingness to interrupt SB varied by activity, physical and social context, perceived pain, and level of fatigue, but not by time of day. Specifically, participants were more willing to interrupt their SB when engaging in mentally active SB and when indoors, alone, or with close relatives.

Conclusions: Contextual factors significantly influence older adults' vulnerability to prolonged SB and their willingness to interrupt it. This empirical information can guide the design of just-in-time adaptive interventions that deliver strategically timed prompts to reduce prolonged SB in older adults.

Background: The aim is to investigate whether integrating a therapeutic program, focused on concurrent training combined with neuromuscular exercises (CNET), within a multidisciplinary approach can positively impact body composition, muscular fitness, and quality of life in adults with obesity compared with a single-mode intervention.

Methods: Three-arm randomized controlled trial design. Ninety-one outpatients (54.7 [7.6] y) were randomly assigned into CNET, resistance training, or aerobic training groups. The interventions lasted 10 weeks with a frequency of 2 days per week. Pre-post assessments were conducted in body mass index, waist circumference, fat mass (FM%), fat-free mass, functional movement screen, modified version of the Balance Error Scoring System, handgrip strength test, handgrip strength test asymmetry, five-repetition sit-to-stand power, and quality of life (EuroQol Five-dimensional Visual Analog Scale).

Results: A significant time × group interaction, main effect of group and time were detected in all outcomes. CNET exhibited significant ameliorations compared with resistance training in functional movement screen (56%), modified version of the Balance Error Scoring System (86%), and FM% (70%), respectively. When compared with the aerobic training group, CNET showed enhancements in functional movement screen (62%), modified version of the Balance Error Scoring System (59%), five-repetition sit-to-stand power (4%), handgrip strength test (73%), handgrip strength test asymmetry (99%), FM% (60%), and fat-free mass (84%). Finally, resistance training outperformed aerobic training only in five-repetition sit-to-stand power (24%), handgrip strength test (73%), FM% (32%), and fat-free mass (79%) outcomes.

Conclusion: CNET showed positive responses across all measured outcomes over 10 weeks compared to the other interventions, except for body mass index, waist circumference, and EuroQol Five-dimensional Visual Analog Scale. This exercise mode could be a feasible option to adopt when prescribing physical exercise to counteract obesity.

Background: Maintaining physical activity (PA) is critical for reducing disease risk. Yet, lack of consensus on how to define and operationalize PA maintenance has hindered surveillance efforts. We used longitudinal accelerometer data to compare how different ways of operationalizing PA maintenance impact PA maintenance prevalence estimates.

Methods: Young adults (N = 173, ages 18-29) provided up to 12 months of PA data via smartwatch accelerometers. Nonsleep movement data were processed into 7-day moving averages of Monitor-Independent Movement Summary units. PA maintenance was operationalized using combinations of 3 accelerometer-based indicators: (1) threshold (ie, level of PA required: [5.0-20.0 Monitor-Independent Movement Summary-units/min], (2) duration (ie,  time required above a threshold [7-70 d]), and (3) allowance (ie, time allowed below a threshold [0-40 d]). Outcomes included the prevalence of days, episodes, and number of participants classified into PA maintenance.

Results: Increasing PA thresholds led to larger changes in PA maintenance prevalence outcomes than increasing durations or allowances. Greater changes in PA maintenance outcomes were observed when increasing thresholds up to about 12 Monitor-Independent Movement Summary-units/minute and allowances up to 7 days than when increasing above those points. Changes in PA maintenance outcomes were consistent across the entire range of durations.

Conclusions: Threshold emerged as a more influential determinant of PA maintenance prevalence than duration or allowance, with greater changes across the lower range of thresholds. Validating these accelerometer-based indicators is a critical next step for establishing consensus regarding PA maintenance classification that can guide population-level surveillance.

The development of lymphedema (LE) is a major concern in breast cancer treatment, and it is crucial to understand the best ways to prevent and treat it. Physical activity has shown to be effective, safe, and feasible in controlling complications arising from treatments, as well as improving function and quality of life in breast cancer survivors. This study aimed to investigate the relationship between physical activity with grip strength and LE development in breast cancer survivors. A cross-sectional analytical study was conducted and women who had survived breast cancer between 1 and 5 years after surgery were selected. Participants completed the International Physical Activity Questionnaire Short Form, the volume of upper limb (UL) was measured by perimetry, handgrip strength was assessed with the JAMAR dynamometer, and the Actigraph accelerometer was placed on the waist. It was found that 50% of the sample was overweight, 28.3% were obese, and 52% of the participants had grip strength below the recommended level. They had an average energy expenditure of 1.2 (0.1) metabolic equivalents, 8.3 (1.8) hours/day of sedentary activity, and spent an average of 61% of their awake time in sedentary activity per day. Significant correlations were found between grip strength on the affected side and the difference in volume between the UL (rp = -.303, P = .041) as well as between body mass index (BMI) and the difference in volume between the UL (rp = .341; P = .020). Moreover, a significant correlation between BMI and the volume of the affected UL was found (rp = .848, P = .000). BMI and grip strength of the affected side were identified as significant predictors of LE, both with P values less than .05. Although physical activity cannot directly prevent LE, it may contribute by helping to control BMI and promote higher levels of grip strength, both of which are important factors in the prediction of LE.

Background: The most recent physical activity (PA) monitor data from the US National Health and Nutrition Examination Survey (NHANES) were processed using a novel monitor-independent movement summary (MIMS) algorithm. To date, few studies have utilized these data, likely due to a general unfamiliarity with MIMS-related metrics. The purpose of this study was to establish normative values for peak MIMS metrics as measures of free-living PA intensity and natural ambulatory effort.

Methods: Data from the National Health and Nutrition Examination Survey 2011-2012 and 2013-2014 survey cycles were used, including 8729 individuals aged 20-80+ years. MIMS data were obtained from wrist-worn accelerometers worn for at least 1 valid day (<5% nonwear time per day). Peak-1MIMS (ie, the highest 1-min MIMS value within a day) and Peak-30MIMS (ie, the average of the 30 highest 1-min MIMS values) were obtained, averaged across all valid days, and reported as sample-weighted means (95% confidence intervals), and across 5th to 95th percentiles.

Results: Mean (95% confidence interval) values for Peak-1MIMS and Peak-30MIMS were 59.9 (59.2-61.6) and 42.9 (42.4-43.3) MIMS/minute, respectively. Both peak metrics declined across the adult lifespan. Men displayed greater Peak-1MIMS, while Peak-30MIMS was similar between sexes. Both MIMS metrics trended lower with increasing body mass index.

Conclusion: We provide normative values for peak MIMS metrics which reflect PA intensity/effort. We also developed an R-Shiny App whereby users can input age, sex, body mass index category, and MIMS metrics to determine individual-specific MIMS percentile values. Given the universal nature of the MIMS algorithm, these population representative data may be useful as a reference data set for device-based PA surveillance within the United States and for comparison globally.

Background: Cognitive frailty, defined by the coexistence of physical frailty and mild cognitive impairment, can be reversed through targeted interventions. This meta-analysis evaluated the efficacy of physical activity interventions on cognitive function and well-being in older adults with frailty.

Methods: The databases (ProQuest, PubMed, CINAHL Ultimate, and Scopus) and Google Scholar were searched to identify relevant articles published from 1990 to March 2025. Our analyses included randomized controlled trials evaluating the effects of physical activity interventions on cognitive function and well-being in older adults with cognitive or physical frailty.

Results: Forty-two randomized controlled trials involving 4740 older adults were included. The meta-analysis categorized interventions into multicomponent exercise, resistance training, aerobic exercise, and mindfulness-based activities. Physical activity interventions produced small-to-moderate improvements in global cognition (g = 0.442), attention (g = 0.267), and executive function (g = 0.279). No significant effect was found for memory (g = -0.020). Moderate effects were observed for physical health-related quality of life (g = 0.600), and moderate-to-large effects were found for psychological well-being (g = 0.710).

Conclusions: Multicomponent and resistance-based programs are effective strategies to promote cognitive function, psychological well-being, and physical health-related quality of life in older adults with frailty. Tailored physical activity programs should be considered in geriatric care to optimize healthy aging.

Background: Older adults engage in the highest levels of sedentary behavior across all age groups. Yet, the extent to which sedentary time is associated with cardiometabolic health in older adults is unclear. This systematic review and meta-analysis examined associations between daily sedentary time and cardiometabolic biomarkers in older adults.

Methods: Peer-reviewed articles which studied the association between daily sedentary time and ≥1 cardiometabolic biomarker in participants aged ≥60 years were eligible. Five electronic databases (PubMed, CINAHL, MEDLINE, Web of Science, and PsycINFO) were searched. Screening, data extraction, and study quality were undertaken independently by 2 reviewers. Meta-analyses were undertaken using random-effects models based on correlation and regression coefficients. Methodological quality was assessed using the Joanna Briggs Institute checklist.

Results: Twenty-eight articles were included with sample sizes ranging from 30 to 62,754 participants. Increasing daily sedentary time was adversely associated with body mass index (Hedge g: 0.32; P = .001), waist circumference (Hedge g: 0.45; P < .001), body fat percentage (Hedge g: 0.61; P = .012), and fat mass (Hedge g: 0.30; P = .018). There were also unfavorable associations with systolic blood pressure (Hedge g: 0.37; P = .047), blood glucose (Hedge g: 0.30; P = .044), triglycerides (Hedge g: 0.36; P = .039), and high-density lipoprotein cholesterol (Hedge g: 0.34; P = .034).

Conclusions: Increased daily sedentary time is adversely associated with body composition, systolic blood pressure, and blood biomarkers in older adults. Therefore, limiting sedentary behavior should be considered an important target in this population group for improved cardiometabolic health.