101 resultados para Multilevel SEM


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BACKGROUND: Seasonal variations may influence children's physical activity patterns. The aim of this study was to examine how children's objectively-measured physical activity differed across seasons, and whether different seasonal patterns were observed for boys and girls. METHODS: Three hundred and twenty-six children aged 8-11 years from nine primary schools in Melbourne, Australia, participated in the study. Physical activity was measured every 15-s using hip-mounted GT3X+ ActiGraph accelerometers for seven consecutive days in the Winter (n = 249), Spring (n = 221), Summer (n = 174) and Autumn (n = 152) school terms. Time spent in moderate (MPA), vigorous (VPA) and moderate- to vigorous-intensity physical activity (MVPA) at each time point was derived using age-specific cut-points. Meteorological data (maximum temperature, precipitation, daylight hours) were obtained daily during each season. Longitudinal data were analysed using multilevel analyses, adjusted for age, sex, accelerometer wear time, number of valid days, and meteorological variables. RESULTS: Compared to Winter, children engaged in significantly less MPA (-5.0 min) and MVPA (-7.8 min) in Summer. Girls engaged in less MVPA in Spring (-18 min) and Summer (-9.2 min) and more MVPA in Autumn (9.9 min) compared to Winter. Significant changes in MPA and VPA bout frequency and duration were also observed. Significant decreases in VPA bout frequency (3.4 bouts) and duration (2.6 min) were observed for girls in Spring compared to Winter. No significant seasonal changes were observed for boys for all intensities and physical activity accumulation. CONCLUSIONS: Physical activity decreased in Summer compared to Winter, contrasting previous research that typically reports that children are most active in summer. Greater fluctuations were observed for girls' activity levels. In addition, girls' activity duration and bouts appeared to be more susceptible to seasonal changes compared to boys. The results suggest that strategies to promote physical activity may be needed in Australia during the hot summer months, particularly for girls.

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BACKGROUND: Low fruit and vegetable consumption is a risk factor for poor health. Studies have shown consumption varies across neighbourhoods, with lower intakes in disadvantaged neighbourhoods. However, findings are inconsistent, suggesting that socio-spatial inequities in diet could be context-specific, highlighting a need for international comparisons across contexts. This study examined variations in fruit and vegetable consumption among adults from neighbourhoods of varying socioeconomic status (SES) across seven countries (Australia, Canada, Netherlands, New Zealand, Portugal, Scotland, US). METHODS: Data from seven existing studies, identified through literature searches and knowledge of co-authors, which collected measures of both neighbourhood-level SES and fruit and vegetable consumption were used. Logistic regression was used to examine associations between neighbourhood-level SES and binary fruit and vegetable consumption separately, adjusting for neighbourhood clustering and age, gender and education. As much as possible, variables were treated in a consistent manner in the analysis for each study to allow the identification of patterns of association within study and to examine differences in the associations across studies. RESULTS: Adjusted analyses showed evidence of an association between neighbourhood-level SES and fruit consumption in Canada, New Zealand and Scotland, with increased odds of greater fruit intake in higher SES neighbourhoods. In Australia, Canada, New Zealand and Portugal, those residing in higher SES neighbourhoods had increased odds of greater vegetable intake. The other studies showed no evidence of a difference by neighbourhood-level SES. CONCLUSIONS: Acknowledging discrepancies across studies in terms of sampling, measures, and definitions of neighbourhoods, this opportunistic study, which treated data in a consistent manner, suggests that associations between diet and neighbourhood-level socioeconomic status vary across countries. Neighbourhood socioeconomic disadvantage may differentially impact on access to resources in which produce is available in different countries. Neighbourhood environments have the potential to influence behaviour and further research is required to examine the context in which these associations arise.

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Background: The objective of this study was to examine whether increased levels of sitting time and physical activity in one period (within-day) or on one day (between-day) were predictive of lower levels in these behaviours in the following period or day among children. Methods: Children aged 8-11 years from 8 primary schools located in Melbourne, Australia, wore an activPAL for 7 consecutive days (n = 235; 53 % boys). Sitting, standing and stepping time were derived for each day and for specific periods on weekdays and weekend days. Multilevel analyses were conducted using generalised linear latent and mixed models to estimate associations between temporally adjacent values (i.e. pairs of days; pairs of periods within-days) between the outcome variables. Results: Significant associations were observed between temporally adjacent days and periods of the day. On any given day, an additional 10 min of stepping was associated with fewer minutes of stepping (~9 min; 95 % CI: -11.5 to -6.2 min) and standing (15 min; 95 % CI: -18.8 to -11.1 min) the following day. Greater time spent sitting during one period, regardless of being a weekday or weekend day, was associated with less time sitting and more time standing and stepping in the following period. Conclusions: The direction of the results suggest that children appeared to compensate for increased sitting, standing, and stepping time both within- and between-days. The implications of such associations for the design and delivery of interventions require consideration.

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Background: Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how specific destinations are related to activity. This study examined associations between types and mix of destinations and both walking frequency and physical activity. Method: The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Using geographic information systems, seven types of destinations were examined within three network buffers (400 meters (m), 800 m and 1200 m) of respondents' homes. Multilevel logistic regression was used to estimate effects of each destination type separately, as well as destination mix (variety) on: 1) likelihood of walking for at least 10 min ≥ 4/week; 2) likelihood of being sufficiently physically active. All models were adjusted for potential confounders. Results: All destination types were positively associated with walking frequency, and physical activity sufficiency at 1200 m. For the 800 m buffer: all destinations except transport stops and sports facilities were significantly associated with physical activity, while all except sports facilities were associated with walking frequency; at 400 m, café/takeaway food stores and transport stops were associated with walking frequency and physical activity sufficiency, and sports facilities were also associated with walking frequency. Strongest associations for both outcomes were observed for community resources and small food stores at both 800 m and 1200 m. For all buffer distances: greater mix was associated with greater walking frequency. Inclusion of walking in physical activity models led to attenuation of associations. Conclusions: The results of this analysis indicate that there is an association between destinations and both walking frequency and physical activity sufficiency, and that this relationship varies by destination type. It is also clear that greater mix of destinations positively predicts walking frequency and physical activity sufficiency.

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BACKGROUND: Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how the distribution of destinations is related to activity. Kernel density estimation is a spatial analysis technique that accounts for the location of features relative to each other. Using kernel density estimation, this study sought to investigate whether individuals who live near destinations (shops and service facilities) that are more intensely distributed rather than dispersed: 1) have higher odds of being sufficiently active; 2) engage in more frequent walking for transport and recreation. METHODS: The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Destinations within these areas were geocoded and kernel density estimates of destination intensity were created using kernels of 400m (meters), 800m and 1200m. Using multilevel logistic regression, the association between destination intensity (classified in quintiles Q1(least)-Q5(most)) and likelihood of: 1) being sufficiently active (compared to insufficiently active); 2) walking≥4/week (at least 4 times per week, compared to walking less), was estimated in models that were adjusted for potential confounders. RESULTS: For all kernel distances, there was a significantly greater likelihood of walking≥4/week, among respondents living in areas of greatest destinations intensity compared to areas with least destination intensity: 400m (Q4 OR 1.41 95%CI 1.02-1.96; Q5 OR 1.49 95%CI 1.06-2.09), 800m (Q4 OR 1.55, 95%CI 1.09-2.21; Q5, OR 1.71, 95%CI 1.18-2.48) and 1200m (Q4, OR 1.7, 95%CI 1.18-2.45; Q5, OR 1.86 95%CI 1.28-2.71). There was also evidence of associations between destination intensity and sufficient physical activity, however these associations were markedly attenuated when walking was included in the models. CONCLUSIONS: This study, conducted within urban Melbourne, found that those who lived in areas of greater destination intensity walked more frequently, and showed higher odds of being sufficiently physically active-an effect that was largely explained by levels of walking. The results suggest that increasing the intensity of destinations in areas where they are more dispersed; and or planning neighborhoods with greater destination intensity, may increase residents' likelihood of being sufficiently active for health.

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PURPOSE: Both moderate-to-vigorous physical activity (MVPA) and sedentary behavior can be associated with adult adiposity. Much of the relevant evidence is from cross-sectional studies or from prospective studies with relevant exposure measures at a single time point prior to weight gain or incident obesity. This study examined whether changes in MVPA and television (TV) viewing time are associated with subsequent changes in waist circumference, using data from three separate observation points in a large population-based prospective study of Australian adults. METHODS: Data were obtained from the Australian Diabetes, Obesity and Lifestyle study collected in 1999-2000 (baseline), 2004-05 (Wave 2), and 2011-12 (Wave 3). The study sample consisted of adults aged 25 to 74 years at baseline who also attended site measurement at three time points (n=3261). Multilevel linear regression analysis examined associations of initial five-year changes in MVPA and TV viewing time (from baseline to Wave 2) with 12-year change in waist circumference (from baseline to Wave 3), adjusting for well-known confounders. RESULTS: As categorical predictors, increases in MVPA significantly attenuated increases in waist circumference (p for trend< 0.001). TV viewing time change was not significantly associated with changes in waist circumference (p for trend =0.06). Combined categories of MVPA and TV viewing time changes were predictive of waist circumference increases; compared to those who increased MVPA and reduced TV viewing time, those who reduced MVPA and increased TV viewing time had a 2cm greater increase in waist circumference (p=0.001). CONCLUSION: Decreasing MVPA emerged as a significant predictor of increases in waist circumference. Increasing TV viewing time was also influential, but its impact was much weaker than MVPA.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially.

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OBJECTIVE: To assess the potential benefit of a workplace physical activity program on daytime sleepiness. METHODS: A total of 685 participants of a 4-month workplace physical activity program were assessed for daytime sleepiness (Epworth Sleepiness Scale [ESS]) at baseline, 4 months (postprogram), and 12 months. Changes in ESS were analyzed using multilevel mixed linear regression. RESULTS: In the total population, no changes in ESS scores were observed; 0 to 4 months: -0.2 (95% CI: -0.5 to 0.0), 4 to 12 months: 0.1 (95% CI: -0.2 to 0.4). In participants with baseline excessive daytime sleepiness (ESS > 10, n = 109), ESS scores improved significantly by -2.2 (95% CI: -3.0 to -1.4) at 4 months, sustained at 12 months; and almost half no longer had excessive daytime sleepiness by end of program. CONCLUSIONS: This study suggests that for employees with excessive daytime sleepiness, short- and long-term improvement in daytime sleepiness may be an unforeseen benefit of workplace physical activity programs.

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OBJECTIVE: Depression has been identified as a priority disorder among children and adolescents. While numerous reviews have examined the individual and family factors that contribute to child and adolescent depressive symptoms, less is known about community-level risk and protective factors. The aim of this study was to complete a systematic review to identify community risk and protective factors for depression in school-aged children (4-18 years). METHOD: The review adopted the procedures recommended by the Cochrane Non-Randomised Studies Methods Working Group and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted to identify both observational and intervention study designs in both peer-reviewed and non-peer reviewed publications. RESULTS: A total of 21 studies met the inclusion criteria. Seventeen of the 18 community association studies and 2 of the 3 intervention studies reported one or more significant effects. Results indicated that community safety and community minority ethnicity and discrimination act as risk factors for depressive symptoms in school-aged children. Community disadvantage failed to achieve significance in meta-analytic results but findings suggest that the role of disadvantage may be influenced by other factors. Community connectedness was also not directly associated with depressive symptoms. CONCLUSION: There is evidence that a number of potentially modifiable community-level risk and protective factors influence child and adolescent depressive symptoms suggesting the importance of continuing research and intervention efforts at the community-level.

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The study's purpose was to examine age, gender, and education as potential moderators of the associations of perceived neighborhood environment variables with accelerometer-based moderate-to-vigorous physical activity (MVPA). Data were from 7273 adults from 16 sites (11 countries) that were part of a coordinated multi-country cross-sectional study. Age moderated the associations of perceived crime safety, and perceiving no major physical barriers to walking, with MVPA: positive associations were only found in older adults. Perceived land use mix-access was linearly (positive) associated with MVPA in men, and curvilinearly in women. Perceived crime safety was related to MVPA only in women. No moderating relationships were found for education. Overall the associations of adults' perceptions of environmental attributes with MVPA were largely independent of the socio-demographic factors examined. These findings are encouraging, suggesting that efforts to optimize the perceived built and social environment may act in a socially-equitable manner to facilitate MVPA.

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In this paper, a five-level cascaded H-bridge multilevel inverters topology is applied on induction motor control known as direct torque control (DTC) strategy. More inverter states can be generated by a five-level inverter which improves voltage selection capability. This paper also introduces two different control methods to select the appropriate output voltage vector for reducing the torque and flux error to zero. The first is based on the conventional DTC scheme using a pair of hysteresis comparators and look up table to select the output voltage vector for controlling the torque and flux. The second is based on a new fuzzy logic controller using Sugeno as the inference method to select the output voltage vector by replacing the hysteresis comparators and lookup table in the conventional DTC, to which the results show more reduction in torque ripple and feasibility of smooth stator current. By using Matlab/Simulink, it is verified that using five-level inverter in DTC drive can reduce the torque ripple in comparison with conventional DTC, and further torque ripple reduction is obtained by applying fuzzy logic controller. The simulation results have also verified that using a fuzzy controller instead of a hysteresis controller has resulted in reduction in the flux ripples significantly as well as reduces the total harmonic distortion of the stator current to below 4 %.

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In data science, anomaly detection is the process of identifying the items, events or observations which do not conform to expected patterns in a dataset. As widely acknowledged in the computer vision community and security management, discovering suspicious events is the key issue for abnormal detection in video surveil-lance. The important steps in identifying such events include stream data segmentation and hidden patterns discovery. However, the crucial challenge in stream data segmenta-tion and hidden patterns discovery are the number of coherent segments in surveillance stream and the number of traffic patterns are unknown and hard to specify. Therefore, in this paper we revisit the abnormality detection problem through the lens of Bayesian nonparametric (BNP) and develop a novel usage of BNP methods for this problem. In particular, we employ the Infinite Hidden Markov Model and Bayesian Nonparamet-ric Factor Analysis for stream data segmentation and pattern discovery. In addition, we introduce an interactive system allowing users to inspect and browse suspicious events.