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Salma S.S. Hernández, Paula F. Sandreschi, Franciele C. da Silva, Beatriz A.V. Arancibia, Rudney da Silva, Paulo J.B. Gutierres and Alexandro Andrade

To identify and characterize the scientific literature on the effects of exercise on Alzheimer’s disease, research was conducted in the following databases: MEDLINE, CINAHL, Web of Science, and Scopus. These MeSH terms—“exercise”, “motor activity”, “physical fitness”, “Alzheimer disease”, and its synonyms in English—were used in the initial search to locate studies published between 2003 and 2013. After reading the 12 final articles in their entirety, two additional articles, found by a manual search, were included. Of these, 13 had beneficial results of exercise in Alzheimer’s disease. Given the results discussed here, the exercise may be important for the improvement of functionality and performance of daily life activities, neuropsychiatric disturbances, cardiovascular and cardiorespiratory fitness, functional capacity components (flexibility, agility, balance, strength), and improvements in some cognitive components such as sustained attention, visual memory, and frontal cognitive function in patients with AD.

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Rebekka Pomiersky, Bastian Abel, Christian Werner, André Lacroix, Klaus Pfeiffer, Martina Schäufele and Klaus Hauer

(RCTs) including solely study participants with dementia ( Eggermont, Blankevoort, & Scherder, 2010 ) or Alzheimer’s disease ( Suttanon et al., 2013 ) showed that intervention approaches led to an adequate training adherence; however, these programs did not significantly or sustainably enhance or even

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Marj Moodie, Michelle M. Haby, Boyd Swinburn and Robert Carter

Background:

To assess from a societal perspective the cost-effectiveness of a school program to increase active transport in 10- to 11-year-old Australian children as an obesity prevention measure.

Methods:

The TravelSMART Schools Curriculum program was modeled nationally for 2001 in terms of its impact on Body Mass Index (BMI) and Disability-Adjusted Life Years (DALYs) measured against current practice. Cost offsets and DALY benefits were modeled until the eligible cohort reached age 100 or died. The intervention was qualitatively assessed against second stage filter criteria (‘equity,’ ‘strength of evidence,’ ‘acceptability to stakeholders,’ ‘feasibility of implementation,’ ‘sustainability,’ and ‘side-effects’) given their potential impact on funding decisions.

Results:

The modeled intervention reached 267,700 children and cost $AUD13.3M (95% uncertainty interval [UI] $6.9M; $22.8M) per year. It resulted in an incremental saving of 890 (95%UI −540; 2,900) BMI units, which translated to 95 (95% UI −40; 230) DALYs and a net cost per DALY saved of $AUD117,000 (95% UI dominated; $1.06M).

Conclusions:

The intervention was not cost-effective as an obesity prevention measure under base-run modeling assumptions. The attribution of some costs to nonobesity objectives would be justified given the program’s multiple benefits. Cost-effectiveness would be further improved by considering the wider school community impacts.

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Jeanne M. Gabriele, Diane L. Gill and Claire E. Adams

Background:

Several theories and models have been proposed to explain decisions in changing and adopting behavior but few address the intricacies of behavioral maintenance. The current study assesses the utility of the Investment Model, which identifies satisfaction, investments, and involvement alternatives as predictors of commitment and continued behavior, in predicting physical activity behavior.

Methods:

Participants (N = 267) completed questionnaires about physical activity and commitment. Structural equation modeling assessed relationships among 2 types of exercise commitment (want to or enthusiastic commitment, have to or obligatory commitment), 3 commitment determinants (satisfaction, investments, and alternatives), and physical activity (minutes of physical activity, stage of behavior change).

Results:

Want to commitment, but not have to commitment, was related to stage of exercise behavior change and time spent in physical activity. Satisfaction and investments were positively related to want to commitment; whereas, satisfaction, investments, and alternatives were positively related to have to commitment. The model explained 68% and 23% of the variance in time spent in physical activity and stage of behavior change, respectively.

Conclusions:

This study provides support for the application of the Investment Model to physical activity and suggests that want to commitment may be important for explaining and predicting sustained physical activity behavior.

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Sarah M. Camhi, Susan B. Sisson, William D. Johnson, Peter T. Katzmarzyk and Catrine Tudor-Locke

Background:

Objective physical activity data analyses focus on moderate-to-vigorous physical activity (MVPA) without considering lower intensity lifestyle-type activities (LA). We describe 1) quantity of LA (minutes and steps per day) across demographic groups, 2) proportion of LA to total physical activity, and 3) relationships between LA and MVPA using NHANES 2005−2006 accelerometer adult data (n = 3744).

Methods:

LA was defined as 760 to 2019 counts per minute (cpm) and MVPA as ≥2020 cpm. LA was compared within gender, ethnicity, age, and BMI groups. Regression analyses examined independent effects. Correlations were evaluated between LA and MVPA. All analyses incorporated sampling weights to represent national estimates.

Results:

Adults spent 110.4 ± 1.6 minutes and took 3476 ± 54 steps per day in LA. Similar to MVPA, LA was highest in men, Mexican Americans, and lowest in adults ≥60 years or obese. When LA was held constant, ethnic differences no longer predicted MVPA minutes, and age no longer predicted MVPA steps. LA and MVPA minutes (r = .84) and steps per day (r = .72) were significantly correlated, but attenuated with MVPA modified bouts (≥10 minutes sustained activity).

Conclusions:

LA accumulation differs between demographic subgroups and is related to MVPA: adults who spend more minutes and steps in MVPA also spend them in LA.

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Maciej S. Buchowski, Leena Choi, Karen M. Majchrzak, Sari Acra, Charles E. Matthews and Kong Y. Chen

Background:

Environmental factors including seasonal changes are important to guide physical activity (PA) programs to achieve or sustain weight loss. The goal was to determine seasonal variability in the amount and patterns of free-living PA in women.

Methods:

PA was measured in 57 healthy women from metropolitan Nashville, TN, and surrounding counties (age: 20 to 54 years, body mass index: 17 to 48 kg/m2) using an accelerometer for 7 consecutive days during 3 seasons within 1 year. PA counts and energy expenditure (EE) were measured in a whole-room indirect calorimeter and used to model accelerometer output and to calculate daily EE and intensity of PA expressed as metabolic equivalents (METs).

Results:

PA was lower in winter than in summer (131 ± 45 vs. 144 ± 54 × 103 counts/d; P = .025) and in spring/fall (143 ± 48 × 103 counts/d; P = .027). On weekends, PA was lower in winter than in summer by 22,652 counts/d (P = .008). In winter, women spent more time in sedentary activities than in summer (difference 35 min/d; P = .007) and less time in light activities (difference −29 min/d, P = .018) and moderate or vigorous activities (difference −6 min/d, P = .051).

Conclusions:

Women living in the southeastern United States had lower PA levels in winter compared with summer and spring/fall, and the magnitude of this effect was greater on weekends than weekdays.

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Kate Heelan, H. Jason Combs, Bryce M. Abbey, Paul Burger and Todd Bartee

Background:

The decline in active commuting to and from school in the United States is, in part, due to urban design standards and public policies that promote automobile travel and discourage pedestrian activity.

Purpose:

The current investigation examines active commuting at neighborhood schools and how it is altered by distance to school, student age and its potential impact on Body Mass Index.

Methods:

Demographic and transportation datasets were obtained for 5367 elementary students (K−5th grade) and middle school students (6th−8th grade) in 2 Midwestern communities.

Results:

4379 (81.6%) students were successfully geocoded and 21.9% actively commute to school at least half of the time meeting the Healthy People 2010 objective 22−14. Of those students who could potentially actively commute to school (0.5 mile for grades K−5 and 1 mile for grades 6−8) 36.6% are passive commuters. No significant negative associations were found between BMI z-score or BMI percentile with accumulation of activity through active commuting (frequency × distance) for elementary (r = −0.04, P = .27) or middle school students (r = .027, P = .56).

Conclusion:

Many elementary students living within 0.3−0.4 miles are being driven to school. Promoting pedestrian-friendly communities and making healthy and sustainable transportation choices should be priorities for community leaders and school administrators.

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Mitch J. Duncan, Hannah M. Badland and William Kerry Mummery

Background:

The aim of this study was to examine the relationship between occupational category and 3 health-related behaviors: participation in leisure-time physical activity, active transport (AT) and occupational sitting in a sample of employed Australian adults.

Methods:

A random, cross-sectional sample of 592 adults aged 18 to 71 years completed a telephone survey in October/November 2006. Reported occupations were categorized as professional (n = 332, 56.1%), white-collar (n = 181, 30.6%), and blue-collar (n = 79, 13.3%). Relationships between occupational category and AT, sufficient physical activity and occupational sitting were examined using logistic regression.

Results:

White-collar employees (OR = 0.36, 95% CI 0.14−0.95) were less likely to engage in AT and more likely to engage in occupational sitting (OR = 3.10, 95% CI 1.63−5.92) when compared with blue-collar workers. Professionals (OR = 3.04, 95% CI 1.94−4.76) were also more likely to engage in occupational sitting compared with blue-collar workers. No relationship was observed between occupational category and engagement in sufficient physical activity.

Conclusions:

No association between occupational category and sufficient physical activity levels was observed, although white-collar and professionals were likely to engage in high levels of occupational sitting. Innovative and sustainable strategies are required to reduce occupational sitting to improve health.

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Nicholas Gilson, Wendy J. Brown, Guy Faulkner, Jim McKenna, Marie Murphy, Andy Pringle, Karin Proper, Anna Puig-Ribera and Aphroditi Stathi

Background:

This paper aimed to use the Delphi technique to develop a consensus framework for a multinational, workplace walking intervention.

Methods:

Ideas were gathered and ranked from eight recognized and emerging experts in the fields of physical activity and health, from universities in Australia, Canada, England, the Netherlands, Northern Ireland, and Spain. Members of the panel were asked to consider the key characteristics of a successful campus walking intervention. Consensus was reached by an inductive, content analytic approach, conducted through an anonymous, three-round, e-mail process.

Results:

The resulting framework consisted of three interlinking themes defined as “design, implementation, and evaluation.” Top-ranked subitems in these themes included the need to generate research capacity (design), to respond to group needs through different walking approaches (implementation), and to undertake physical activity assessment (evaluation). Themes were set within an underpinning domain, referred to as the “institution” and sites are currently engaging with subitems in this domain, to provide sustainable interventions that refect the practicalities of local contexts and needs.

Conclusions:

Findings provide a unique framework for designing, implementing, and evaluating walking projects in universities and highlight the value of adopting the Delphi technique for planning international, multisite health initiatives.

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Tamara Vehige Calise and Sarah Martin

Background:

Physical inactivity is one of the top 3 risk factors associated with an increased prevalence of obesity and other chronic diseases. The public health infrastructure positions state health departments to address physical inactivity. To examine preparedness, all 50 health departments were assessed, using the 5 benchmarks developed by CDC for physical activity and public health practice, on their capacity to administer physical activity programs.

Methods:

States were scored on a 5-point scale for each benchmark. The top 2 high and low scores were combined to create 2 categories. Exact Chi-square analyses were performed.

Results:

States with CDC obesity funding scored higher on 4 benchmarks than states without. States with a state physical activity plan scored higher on all benchmarks than states without. States with a physical activity coalition scored higher on 2 benchmarks than states without.

Conclusions:

At the time of the assessment, approximately 20% of state physical activity programs could have improved in the use of evidence-based strategies and planning and evaluation approaches. Furthermore, many programs seemed to have limited sustainability. The findings of this report serve as a baseline of the capacity and infrastructure of state health department physical activity programs.