Journal of physical activity & health最新文献

Background: Built environments are excellent places/opportunities for sports and recreational practice. However, research on this topic is scarce and unclear in Latin America, especially in Uruguay. This study aimed to analyze the features of resources for sport and recreational physical activity and their association with use in the city of Rivera, Uruguay.

Methods: This observational, cross-sectional study analyzed all available public open spaces (POS) from Rivera city in Uruguay the Physical Activity Resource Assessment checklist to evaluate the presence and quality of resources, and the System for Observation of Play and Recreation in Communities to evaluate the use. Each space was visited 9 times: mornings, afternoons, and evenings on 2 nonconsecutive weekdays and weekend days. A negative binomial regression model was used to analyze the association between POS quality and their use.

Results: Twenty-nine POS were assessed, the squares (58.1%) and sports facilities (22.6%) were the most frequent of resource. A total of 7920 scans were performed in 88 target areas; 808 users were observed, and the highest frequency of use was identified in men on the weekdays (66.4%) and on the weekend (66.7%). Was observed a positive and significant association between the features (P = .028), incivilities (P = .042), and total quality (P = .001) with the number, but there was no association between the amenities (P = .155) and the number users.

Conclusion: Our findings provide relevant information at the local level and suggest promoting intervention policies that help maintain renovated and accessible POS for the physical activity, sports, and outdoor recreation.

Background: Mental health is a serious concern among US adolescents. We examined the role of a combined running/mentorship program, Teens Run DC (TRDC), on self-reported indicators of mental health in high-school students (N = 291) living in Washington, DC.

Methods: The TRDC program was offered in 10 high schools across 7 DC wards between 2010 and 2018. We used a quasi-experimental design within each school to determine the relation between dose of the TRDC program, and indicators of depression, and social connectedness in students who did and did not participate in the program. Data were collected at the beginning and end of each school year, using the Center for Epidemiological Studies Depression in Children scale and the Hemingway Social Connectedness scale. Mixed-effect regression modeling examined the dose-response relationship between participation dose and mental health scores.

Results: High school students who completed at least 2 years of TRDC lowered their Center for Epidemiological Studies Depression in Children scale score by 6 points (β = -5.9; 95% CI, -10.7 to -1.0) and had a 69% lower odds of developing symptoms of clinical depression (odds ratios = 0.31; 95% CI, 0.23 to 0.42), compared with students receiving less than one year. Similarly, students with 2 or more years of TRDC increased their overall Hemingway Social Connectedness score by 8 points (β = 7.9; 95% CI, 0.65 to 15.1), relative to those with less than one year of exposure. The benefits of TRDC were especially pronounced in female students.

Conclusion: These findings indicate that a running/mentoring program has substantial mental health benefits for high school students and this is particularly so for teenage girls.

Background: Sleep and eating disorders are significant global public health concerns. While physical activity (PA) has been suggested to influence these disorders, the nature of this relationship remains unclear. This study aims to investigate whether a causal link exists between PA and sleep and eating disorders.

Methods: This study uses Genome-Wide Association Study data; PA ("ebi-a-GCST90061432") is the exposure, with sleep disorders ("ukb-d-SLEEP") and eating disorders ("finn-b-F5_EATING") as outcomes variable. The study sample consists of a European population, and genetic instrumental variables are carefully selected. Two-sample Mendelian Randomization (MR) analysis is performed using inverse variance weighting, weighted median, and MR-Egger regression.

Results: MR analysis revealed a significant negative association between PA and sleep disorders (inverse variance weighting estimate β = -0.004, SE = 0.002, P = .008). Both the Weighted Median and MR-Egger methods showed negative trends, but not statistically significant (β = -0.003/-0.005, SE = 0.002/0.005, P = .191/0.346). For PA and eating disorders, the inverse variance weighting estimate was β = -0.375 (P = .153), with no significance in the other methods, suggesting a limited effect of PA on eating disorders. Sensitivity (MR-Egger, leave-one-out) and heterogeneity (Q = 29.87, P = .472; I2 = 0.004) analyses confirmed the robustness of these findings (F = 24.49).

Conclusion: This study suggests PA may reduce the risk of sleep disorders, while its impact on eating disorders appears limited. Future research should explore how different types, frequencies, and intensities of PA affect various health conditions to optimize its use in public health.

Background: Seasonality profoundly impacts older adults in rural communities, influencing daily routines, physical activity (PA), and functionality. Effective interventions require a nuanced understanding of these variations particularly for those living alone.

Methods: This longitudinal study examined 58 older adults (mean age 80.22 y) living alone in a rural community across summer and winter. Variables assessed included sociodemographics, lifestyle factors, weekly social contacts, a composite index of agricultural activity, independence in daily activities, functional status, and weather conditions. PA was measured using an ActiGraph GT9X accelerometer. Paired t tests and K-means cluster analysis were applied, followed by discriminant analysis and cluster evolution monitoring.

Results: Significant seasonal differences were observed in lifestyle, weekly contacts, agricultural activity, and PA. Engagement in agricultural activities correlated with higher PA levels during summer and lower sedentary behavior in both seasons. Cluster analysis identified 3 distinct groups each season, with unique levels of PA, functionality, and behaviors. The discriminant analysis highlighted seasonal patterns, while the bipartite graph analysis showed subject reaggregation in winter, illustrating cluster composition shifts.

Conclusion: This study demonstrates that older adults living alone in rural areas are vulnerable to seasonal variations, with higher PA, more frequent social contacts, and greater agricultural engagement in summer than in winter. Cluster analysis revealed 3 groups of older adults each season, underscoring the necessity for customized interventions that consider behavioral patterns, specific needs, and seasonal changes. The significance of suitable interventions to improve social interactions and prevent functional decline is emphasized.

Background: Characterizing interindividual differences in physical activity within schools and understanding potential drivers of these differences may support the development of improved strategies to increase in-school physical activity.

Methods: Anonymized physical activity data from a school-specific wrist-worn device were obtained from 17,043 pupils and 2555 staff from 165 primary schools in England. Additional school information included UK government school data, area-level deprivation, and estimated playground area. Descriptive statistics were calculated, and data visualizations were used to explore within- and between-school differences. Multilevel models were used to explore the associations between children's in-school physical activity and school variables, with pupils nested within schools, adjusted for individual characteristics.

Results: There was large variation in physical activity between schools. Some schools accumulated twice the amount of physical activity within the school day compared with other schools, with physical activity ranging from 4253 to 8356 steps per school day or 16 to 39 minutes of moderate to vigorous physical activity per school day. School-level data, such as playground space and government school ratings, did not explain between-school variance. Although boys were generally more active than girls in most schools, some schools had more equitable physical activity, and in a small number of schools (∼5%), girls were more active than boys.

Conclusions: There is considerable heterogeneity in physical activity levels between English primary schools. Technology-enabled surveillance from wearable devices can be used to identify schools needing greater support and facilitate learning from those with higher and more equitable physical activity among pupils.

Background: Evidence on the long-term implementation and sustainability of whole-school physical activity programs remains limited. The Creating Active Schools (CAS) program incorporated the CAS Framework to support schools to focus on organizational and cultural change for physical activity. This study evaluates the medium-term implementation of CAS, after 2 academic years.

Methods: A qualitative descriptive approach was employed. After 2 years of implementation, 35 participants from 30 Bradford schools, including school staff, CAS Champions, and Bradford CAS locality leads took part in semistructured focus groups. Thematic analysis followed a codebook method, combining inductive, data-driven insights with deductive themes based on McKay et al's implementation evaluation roadmap, and aligned to the Consolidated Framework Implementation Research.

Results: The program increased the reach compared with the first year, with more staff buying into CAS and gaining confidence as advocates of physical activity. Schools shifted from creating new initiatives to embedding and sustaining previous efforts, and some schools required repeated doses to reinstate CAS as a priority where there had been high staff turnover or superficial initial buy-in. Core components of CAS that mitigated negative influences from the wider educational system, included peer-to-peer learning, and inter and intraknowledge exchange arising from the communities of practice. Collectively, these factors contributed to the combined agency within the school to implement CAS.

Conclusions: The medium-term implementation of whole-school physical activity programs is contingent on understanding the broader educational context and system influences. This study underscores the importance of communities of practice and supportive structures in sustaining school-based physical activity initiatives.

Background: Exercise reduces falls in older people, and the benefits are stronger with greater exercise adherence. This review summarized adherence and behavior change techniques in fall prevention supervised exercise interventions and investigated the association between adherence, participants' characteristics, and intervention components.

Methods: A secondary analysis of trials from the previous 2019 Cochrane Review and its associated updates, investigating fall prevention exercises in community-dwelling people aged 60+ years. We dichotomized the interventions based on adherence, using the threshold of ≥75% of the sessions provided, or ≥75% of the participants attended ≥75% of sessions. Logistic regression examined the associations between adherence and participant characteristics, and intervention components.

Results: One hundred and two studies investigated 136 supervised exercise interventions, of which 116 interventions (85%) reported adherence. The median proportion of exercise sessions attended was 78% (range: 38%-100%). Adherence was associated with exercise frequency with the odds of adherence increased by 167% (95% CI, 12%-536%) for interventions conducted ≥2 times/week, compared to those <2 times/week; 72% higher (95% CI, 12%-85%) for supervised programs without home exercise component, compared to those with 4% more for 1 week less in exercise intervention conducted in trials (2%-7%), and 33% higher (95% CI, 11%-50%) for each behavior change technique not used.

Conclusion: Higher adherence was observed in interventions that were shorter, did not have home exercise components, had more weekly sessions (≥2 times/wk), and used fewer behavior change techniques. Clinicians should consider these factors to optimize adherence to supervised programs.