Journal of physical activity & health最新文献

Background: This study aims to elucidate the causal effect of physical activity (PA) at different times of day on the risk of cardiovascular diseases, including subtypes of stroke, heart failure, atherosclerosis (AS), myocardial infarction, hypertension, and peripheral artery disease.

Methods: Two-sample univariable and multivariable Mendelian randomization were conducted. Genetic instruments for total PA and PA across twelve 2-hour intervals were derived from UK Biobank. Summary-level data for outcomes were obtained from large consortia. We estimated causal effects using inverse variance weighted, MR-Egger, and weighted median methods. Sensitivity analyses were also conducted.

Results: Multivariable Mendelian randomization revealed independent protective effects of PA during 6 AM to 8 AM, 10 AM to 12 PM, and 4 PM to 6 PM on total and ischemic stroke. In contrast, the effect in protecting total, ischemic and large artery stroke were detected for PA during 6 PM to 8 PM in univariable MR. PA during 2 AM to 4 AM and 10 AM to 12 PM had directly protective effect of total AS, and PA during 2 PM to 4 PM for coronary AS, while univariable MR results indicated PA during 8 PM to 10 PM and 6 PM to 8 PM decreased the risk of cerebral and coronary AS, respectively. PA during 2 PM to 4 PM exhibited a total but not a direct effect of reducing risk of total and essential hypertension. No robust causal associations were observed for heart failure, myocardial infarction, or peripheral artery disease.

Conclusion: This study provides evidence that PA during specific periods is causally associated with the risk of stroke, AS, and hypertension. These findings suggest that the timing of PA should be considered for the prevention of cardiovascular diseases.

Background: Despite the benefits of physical activity (PA), evidence suggests around 25% of adults fail to meet PA guidelines, parents, and mothers in particular, and engage in less PA on average than their childless peers. This review sought to determine the correlates of parental PA, stratifying evidence by self-report and device-based measures.

Methods: Quantitative studies (cross-sectional and longitudinal) investigating associations between correlates and parental PA (ie, parents with children aged 0-18 y) were identified across 4 databases (MEDLINE, EMBASE, PsycINFO and Scopus) up to October 2024. Correlates (assessed in 3 or more studies) and direction of associations were extracted, described, and synthesized narratively according to the socioecological model (individual, interpersonal, organizational, environmental, societal).

Results: Of 4632 studies identified, 269 full texts were assessed and 105 studies included in the review. A total of 117 correlates were identified across all studies (103 for self-report measures, 55 for device-based). 53 correlates were assessed in 3/+ independent associations (n = 51 self-report, n = 14 device, n = 12 both). Consistently, partner PA was positively associated with parent PA regardless of measure used. Child PA, pet ownership, and environmental aesthetics were positively associated with (mothers') PA, whereas car ownership was negatively associated with PA. Only one policy-level factor (COVID-19 restrictions) was assessed, being negatively associated with parental PA.

Conclusions: Family-based correlates of PA were positively associated with parental PA, suggesting these may support wider family engagement in PA. Evidence from fathers and from low- and middle-income countries is needed to gain a better understanding of parental PA in these groups.

Background: The aim of this study is to present how physical activity (PA) affects life satisfaction (LS) among individuals working in small societies with stressful and sedentary work environments. This study investigates the complex pathways through which PA enhances LS among banking and insurance employees-a population facing unique occupational stressors within a small society context of 476,214 residents. Drawing on Conservation of Resources and Self-Determination theories, this study examines how work-life balance, competence satisfaction, and job motivation mediate this relationship.

Methods: Data collected from 429 banking and insurance employees in Northern Cyprus were analyzed using Hayes' PROCESS macro to test direct and indirect effects. The study employed a cross-sectional survey design with hardcopy questionnaires distributed to employees across both sectors.

Results: Results reveal that PA significantly influences LS both directly (β = 0.137, P = .004) and through multiple mediating pathways. Notably, work-life balance fully mediates the relationship between PA and competence satisfaction, supporting the resource-generation function of exercise. The significant serial mediation pathway demonstrates how regular PA initiates a positive chain reaction in professional settings. Furthermore, these findings uncover bidirectional relationships between workplace factors and LS, suggesting a more dynamic interplay than previously theorized.

Conclusions: These results provide compelling evidence that workplace wellness initiatives should integrate PA programs with supportive work-life balance policies to maximize employee well-being. Furthermore, they highlight the importance of developing evidence-based strategies to enhance employee quality of life in demanding professional environments.

Limitations have been noted for the employ of social return on investment (SROI) in physical activity and sport (PAS). A group of researchers recently produced a series of papers describing their efforts to standardize the application of SROI to PAS. Two of these papers, a systematic review and a subsequent commentary summarizing lessons learned from a Delphi study of experts, were published in the Journal of Physical Activity and Health. In this commentary, I reflect on the findings of the systematic review and respond to the lessons learned. In their lessons learned, Nieto et al conclude no causal evidence exists for relationships between PAS with crime, social capital, or the environment. Furthermore, limited evidence exists for causality between PAS and some indicators of educational attainment and subjective well-being. Given that a critical component of a properly conducted SROI is the development of a logic model describing the causal relationship between inputs, outputs, and outcomes, I argue that the lack of causal relationships for much of the key outcomes for PAS is problematic. I identify other limitations for the current body of SROIs for PAS including mostly unpublished commissioned works and a lack of regulatory mechanisms. I applaud efforts to establish consensus for good practice in the application of SROI approaches to PAS. However, an additional apparent lesson from the work of Nieto and colleagues is that most SROIs are making faulty and inflated claims about the impact of PAS on social outcomes (eg, crime).

Background: This review combined studies included in 3 systematic reviews of the measurement properties of physical activity (PA) questionnaires in children to explore: (1) if any questionnaire was specifically developed for or validated in children with chronic conditions or disabilities; (2) to what extent the inclusion/exclusion of these children was reported; (3) whether any specific chronic conditions or disabilities were more commonly excluded; and (4) if the percentage of papers reporting inclusion/exclusion of children with chronic conditions or disabilities changed over time.

Methods: Two independent investigators reviewed included papers (N = 216) that reported at least one psychometric property of PA questionnaires for children and extracted data, including study populations and inclusion/exclusion of children with chronic conditions or disabilities. Chi-square tests were used to assess changes in reporting about inclusion/exclusion of these children between the 3 reviews.

Results: Only 8 papers (4%) evaluated newly developed questionnaires or tested existing ones specifically in children with chronic conditions or disabilities. Forty-eight papers (22%) reported whether they included or excluded children with chronic conditions or disabilities. About 3 times more papers reported exclusion (n = 40; 19%) versus inclusion (n = 13; 6%) of children with chronic conditions or disabilities. Exclusions included either all chronic conditions or disabilities, those limiting PA participation, or specific chronic conditions or disabilities. Although more studies in the latest review reported about inclusion/exclusion (P < .05), the proportion remained low (31%).

Conclusion: More PA questionnaires should be developed and/or validated in children with chronic conditions or disabilities and studies should avoid excluding these children whenever possible.

Background: Venous thromboembolism (VTE) constitutes a significant global health burden, yet the contribution of circadian rhythm disruptions to VTE risk remains insufficiently characterized. This study investigated the independent and joint associations of rest-activity circadian rhythm and physical activity (PA) with VTE incidence in a large cohort.

Methods: A total of 89,473 UK Biobank participants were analyzed (median follow-up: 12.7 y). Rest-activity rhythm was assessed using accelerometer-derived relative amplitude (RA), and PA was measured by average daily acceleration. VTE events were ascertained via International Classification of Diseases, 10th Revision codes. Cox regression models were used to evaluate linear, nonlinear, and joint associations, adjusting for sociodemographic and clinical covariates. Sensitivity analyses, subgroup analyses, and E-value calculations further supported the robustness of the findings.

Results: Each SD increase in RA was associated with a 12% lower VTE risk (hazard ratio, 0.88; 95% CI, 0.85-0.91). Nonlinear analysis of PA identified an inflection point at 30.4mg (milligravity); PA below this level was associated with a 37% higher risk (hazard ratio, 1.37; 95% CI, 1.21-1.54). Participants with both low RA and low PA had a 54% higher VTE risk compared with those with high RA and high PA (hazard ratio, 1.54; 95% CI, 1.34-1.76). Chronotype showed no significant association with VTE.

Conclusions: This large-scale cohort study demonstrates that disrupted circadian rhythms and low PA are independently and jointly associated with elevated VTE risk. These findings suggest that circadian and activity monitoring, for example, via wearable devices, may have potential utility in future VTE risk assessment particularly among high-risk populations.

Background: The use of digital technology for supporting physical activity (PA) in older adults has increased recently despite the paucity of research exploring perceptions and age-appropriateness of these technologies.

Methods: Older adults (n = 120) residing in care homes (n = 45) and living independently (n = 75) in England and Scotland, as well as care home staff (n = 30) and young adults (n = 7) appraised a variety of different PA technologies (eg, online and digital platforms, exergames, and virtual reality headsets) through a multiphase approach. Technologies were presented as a "menu" to participants to select at interactive sessions. Feedback was collected through focus groups, interviews, codesign workshops, and field notes, all analyzed thematically. Participant characteristics including PA levels and familiarity with technology were collected via questionnaire at baseline and after appraising selected technologies.

Results: Qualitative findings explored 6 overarching themes: (1) recognizing the potential of technology, (2) suitability of PA technology, (3) barriers to using PA technology, (4) motivation to engage with digital technology, (5) content suggestions for future PA technology, and (6) preferences for PA technology delivery. PA engagement and prior experience with digital technologies varied greatly at baseline. Overall, participants' perceptions and appraisal of the PA technologies varied according to their context and setting, prior experience with technology, and PA engagement. Quantitative data were challenging to gather, with complete data available from only 18% out of those consented.

Conclusions: Older adults in this study demonstrated a keen interest in digital technologies for PA, but context- and health-related barriers for engagement with these tools need addressing.

Background: Movement behavior is inherently complex and heterogeneous, making it difficult to capture using a single indicator. To better identify meaningful movement behavior phenotypes, robust dimensionality reduction techniques are needed that integrate multiple behavioral dimensions while preserving their continuous nature. This study aimed to identify distinct movement behavior phenotypes and to investigate how variations in movement behavior phenotypes relate to cardiometabolic health biomarkers.

Methods: This cross-sectional study included 1009 Luxembourg residents aged 25-79 years, each with at least 4 valid days of triaxial accelerometry data. A reversed graph embedding method was used to reduce the complexity of movement behaviors into a 2-dimensional tree structure, enabling the identification of distinct phenotypes. Separate linear regression models were used to assess associations between the derived tree dimensions and both movement behavior indicators and cardiometabolic health biomarkers.

Results: Four distinct movement behavior phenotypes were identified: inactive, irregularly active, regularly active, and regularly low active. Both tree dimensions were favorably associated with cardiometabolic health outcomes, suggesting that higher overall activity volume, regardless of its regularity, may offer health benefits. Average 24-hour acceleration and total step count emerged as the most influential indicators contributing to phenotypic variation.

Conclusion: This study demonstrates that a novel dimensionality reduction approach effectively captures the complexity of movement behaviors, identifies key movement behavior indicators, and distinguishes between meaningful phenotypes. The findings provide new insights into behavioral heterogeneity and highlight key movement dimensions linked to cardiometabolic health.