A comparison between conventional and holistic exercise interventions on physiological function in the elderly

Aging is characterised by a decline in physiological function. The rate of this decline can depend on certain lifestyle factors, genetics, and the environment. Although life expectancy is slowly increasing, there is a need to reduce the time spent in debilitated, and non-independent states by elderly individuals. Preventive measures need to be implemented to reduce dependency and improve the quality of life for elderly individuals. One such preventive and remedial measure is the use of exercise and physical activity. Because limited exercise prescription exists for the elderly population, there is a need to determine the effectiveness of exercise interventions that are more desirable for elderly individuals. Hence, the purpose of this pilot study was to implement and compare two types of exercise interventions, a holistic exercise intervention (Range of Motion Dance method or ROM) and a Conventional Exercise intervention commonly performed in the community by aged individuals. Forty-three elderly individuals over 65-years of age were randomly allocated to the two intervention groups and a control group. The exercise interventions were performed for 10-weeks and included baseline and post-intervention testing. The groups were compared using Analysis of Covariance on the following variables; muscular strength (grip strength, isokinetic knee flexion and extension); postural stability (Berg Balance Scale, and Center of Pressure): and functionality (Timed \u27up\u27 and \u27go\u27 and Physical Performance Test). T-tests were performed to compare the two intervention groups on attrition and compliance. The Conventional Exercise and the ROM exercise groups generally showed similar results on all physiological parameters when compared to each other. However, some statistically significant differences were observed between the intervention groups and the control group for isokinetic knee flexor and extensor strength, grip strength and the Physical Performance Test. Mean differences between post-intervention and baseline results for knee extensor and flexor strength measures ranged between 0.97 to 5.78 Newton meters for the Conventional Exercise group; -6.00 to 5.73 Newton meters for\u27 the ROM group and; 8.74 to 5.36 Newton meters for the Control group. Both intervention groups showed improvement of approximately 1.5 units for the Physical Performance Test, while the Control group showed no change. No statistically significant differences were found between the groups for any balance measures or for the Timed Up and Go . The two interventions groups showed similar average attendance rates, with 85.4% of sessions performed by the Conventional Exercise group and 88.9% of sessions performed by the ROM group. The performance of low-intensity exercise intervention, of either a conventional or holistic nature, may provide positive physiological benefits for elderly participants, such as maintaining or improving knee flexor and extensor strength and enhancing functionality. Thus this study provides evidence that low-intensity exercise interventions in the short term can cause physiological change while at the same time maintaining relatively high rates of participation

In search of causality: a systematic review of the relationship between the built environment and physical activity among adults

<p>Abstract</p> <p>Background</p> <p>Empirical evidence suggests that an association between the built environment and physical activity exists. This evidence is mostly derived from cross-sectional studies that do not account for other causal explanations such as neighborhood self-selection. Experimental and quasi-experimental designs can be used to isolate the effect of the built environment on physical activity, but in their absence, statistical techniques that adjust for neighborhood self-selection can be used with cross-sectional data. Previous reviews examining the built environment-physical activity relationship have not differentiated among findings based on study design. To deal with self-selection, we synthesized evidence regarding the relationship between objective measures of the built environment and physical activity by including in our review: 1) cross-sectional studies that adjust for neighborhood self-selection and 2) quasi-experiments.</p> <p>Method</p> <p>In September 2010, we searched for English-language studies on built environments and physical activity from all available years in health, leisure, transportation, social sciences, and geographical databases. Twenty cross-sectional and 13 quasi-experimental studies published between 1996 and 2010 were included in the review.</p> <p>Results</p> <p>Most associations between the built environment and physical activity were in the expected direction or null. Land use mix, connectivity and population density and overall neighborhood design were however, important determinants of physical activity. The built environment was more likely to be associated with transportation walking compared with other types of physical activity including recreational walking. Three studies found an attenuation in associations between built environment characteristics and physical activity after accounting for neighborhood self-selection.</p> <p>Conclusion</p> <p>More quasi-experiments that examine a broader range of environmental attributes in relation to context-specific physical activity and that measure changes in the built environment, neighborhood preferences and their effect on physical activity are needed.</p

Constructing indices representing supportiveness of the physical environment for walking using the Rasch measurement model

BACKGROUND: The objectives of this study were to use the Rasch model to 1) assess the psychometric properties of a physical environmental audit instrument and 2) to develop indices of interrelated environmental attributes that summarize environmental supportiveness for walking. METHODS: A set of items were derived representing two conceptual physical environmental constructs: 1) functional/safety, and; 2) aesthetics. Ad hoc criteria based on point-biserial and Rasch-based fit statistics were used to examine the construct validity and internal reliability of the two constructs. RESULTS: The Rasch-based fit statistics assisted in identifying 12 items that belonged to the functional/safety construct and 4 items that belonged to the aesthetic construct. The reliability of the two constructs were low to moderate (functional/safety r(β )= 0.19 and aesthetics r(β )= 0.35). CONCLUSION: Given the vast number of built environmental attributes, a means of developing summary indices is essential. Future studies should assess the reliability and validity of indices that summarize physical environmental characteristics conducive to walking before testing them in predictive models of physical activity. More research examining procedures for measuring the built environment and techniques for analyzing environmental data are needed to guide future research in this area

The relationship between destination proximity, destination mix and physical activity behaviors

Background. The presence and mix of destinations is an important aspect of the built environment that may encourage or discourage physical activity. This study examined the association between the proximity and mix of neighbourhood destinations and physical activity. Methods. Secondary analysis was undertaken on physical activity data from Western Australian adults (n=1394). These data were linked with geographical information systems (GIS) data including the presence and the mix of destinations located within 400 and 1500 m from respondents' homes. Associations with walking for transport and recreation and vigorous physical activity were examined. Results. Access to post boxes, bus stops, convenience stores, newsagencies, shopping malls, and transit stations within 400 m (OR 1.63–5.00) and schools, transit stations, newsagencies, convenience stores and shopping malls within 1500 m (OR 1.75–2.38) was associated with participation in regular transport-related walking. A dose–response relationship between the mix of destinations and walking for transport was also found. Each additional destination within 400 and 1500 m resulted in an additional 12 and 11 min/fortnight spent walking for transport, respectively. Conclusion. Proximity and mix of destinations appears strongly associated with walking for transport, but not walking for recreation or vigorous activity. Increasing the diversity of destinations may contribute to adults doing more transport-related walking and achieving recommended levels of physical activity

The associations between objectively-determined and self-reported urban form characteristics and neighborhood-based walking in adults

BACKGROUND: Self-reported and objectively-determined neighborhood built characteristics are associated with physical activity, yet little is known about their combined influence on walking. This study: 1) compared self-reported measures of the neighborhood built environment between objectively-determined low, medium, and high walkable neighborhoods; 2) estimated the relative associations between self-reported and objectively-determined neighborhood characteristics and walking and; 3) examined the extent to which the objectively-determined built environment moderates the association between self-reported measures of the neighborhood built environment and walking. METHODS: A random cross-section of 1875 Canadian adults completed a telephone-interview and postal questionnaire capturing neighborhood walkability, neighborhood-based walking, socio-demographic characteristics, walking attitudes, and residential self-selection. Walkability of each respondent’s neighborhood was objectively-determined (low [LW], medium [MW], and high walkable [HW]). Covariate-adjusted regression models estimated the associations between weekly participation and duration in transportation and recreational walking and self-reported and objectively-determined walkability. RESULTS: Compared with objectively-determined LW neighborhoods, respondents in HW neighborhoods positively perceived access to services, street connectivity, pedestrian infrastructure, and utilitarian and recreation destination mix, but negatively perceived motor vehicle traffic and crime related safety. Compared with residents of objectively-determined LW neighborhoods, residents of HW neighborhoods were more likely (p < .05) to participate in (odds ratio [OR] = 3.06), and spend more time, per week (193 min/wk) transportation walking. Perceived access to services, street connectivity, motor vehicle safety, and mix of recreational destinations were also significantly associated with transportation walking. With regard to interactions, HW x utilitarian destination mix was positively associated with participation, HW x physical barriers and MW x pedestrian infrastructure were positively associated with minutes, and HW x safety from crime was negatively associated with minutes, of transportation walking. Neither neighborhood type nor its interactions with perceived measures of walkability were associated with recreational walking, although perceived aesthetics was associated with participation (OR = 1.18, p < .05). CONCLUSIONS: Objectively-determined and self-reported built characteristics are associated with neighborhood-based transportation walking. The objectively-determined built environment might moderate associations between perceptions of walkability and neighborhood-based transportation walking. Interventions that target perceptions in addition to modifications to the neighborhood built environment could result in increases in physical activity among adults

Associations between neighborhood walkability and walking following residential relocation: Findings from Alberta's Tomorrow Project

IntroductionCross-sectional studies consistently find that the neighborhood built environment (e.g., walkability) is associated with walking. However, findings from the few existing longitudinal residential relocation studies that have estimated associations between changes in neighborhood built characteristics and walking are equivocal. The study objective was to estimate whether changes in neighborhood walkability resulting from residential relocation were associated with leisure, transportation, and total walking levels among adults.MethodsThis study included longitudinal data from the “Alberta's Tomorrow Project”—a province-wide cohort study (Alberta, Canada). The analysis included data collected at two time points (i.e., baseline and follow-up) from 5,977 urban adults. The International Physical Activity Questionnaire (IPAQ) captured self-reported walking. We estimated neighborhood walkability, an index capturing intersection, destination, and population counts for the 400 m Euclidean buffer around participants' homes. Using household postal codes reported at baseline and follow-up, we categorized participants into three groups reflecting residential relocation (“non-movers:” n = 5,679; “movers to less walkability:” n = 164, and; “movers to more walkability:” n = 134). We used Inverse-Probability-Weighted Regression Adjustment to estimate differences [i.e., average treatment effects in the treated (ATET)] in weekly minutes of leisure, transportation, and total walking at follow-up between residential relocation groups, adjusting for baseline walking, sociodemographic characteristics, and walkability. The median time between baseline and follow-up was 2-years.ResultsThe three residential relocation groups mainly included women (61.6–67.2%) and had a mean age of between 52.2 and 55.7 years. Compared to “non-movers” (reference group), weekly minutes of transportation walking at follow-up was significantly lower among adults who moved to less walkable neighborhoods (ATET: −41.34, 95 CI: −68.30, −14.39; p &lt; 0.01). We found no other statistically significant differences in walking between the groups.DiscussionOur findings suggest that relocating to less walkable neighborhoods could have detrimental effects on transportation walking to the extent of adversely affecting health. Public health strategies that counteract the negative impacts of low walkable neighborhoods and leverage the supportiveness of high walkable neighborhoods might promote more walking

Correlates of distances traveled to use recreational facilities for physical activity behaviors

BACKGROUND: Information regarding how far people are willing to travel to use destinations for different types of recreational physical activity behaviors is limited. This study examines the demographic characteristics, neighborhood opportunity and specific-physical activity behaviors associated with distances traveled to destinations used for recreational physical activity. METHODS: A secondary analysis was undertaken of data (n = 1006) from a survey of Western Australian adults. Road network distances between respondents' homes and 1) formal recreational facilities; 2) beaches and rivers; and 3) parks and ovals used for physical activity were determined. Associations between distances to destinations and demographic characteristics, neighborhood opportunity (number of destinations within 1600 meters of household), and physical activity behaviors were examined. RESULTS: Overall, 56.3% of respondents had used a formal recreational facility, 39.9% a beach or river, and 38.7% a park or oval. The mean distance traveled to all destinations used for physical activity was 5463 ± 5232 meters (m). Distances traveled to formal recreational facilities, beaches and rivers, and parks and ovals differed depending on the physical activity undertaken. Younger adults traveled further than older adults (7311.8 vs. 6012.6 m, p = 0.03) to use beaches and rivers as did residents of socio-economically disadvantaged areas compared with those in advantaged areas (8118.0 vs. 7311.8 m, p = 0.02). Club members traveled further than non-members to use parks and ovals (4156.3 vs. 3351.6 meters, p = 0.02). The type of physical activity undertaken at a destination and number of neighborhood opportunities were also associated with distance traveled for all destination types. CONCLUSION: The distances adults travel to a recreational facility depends on the demographic characteristics, destination type, physical activity behavior undertaken at that destination, and number of neighborhood opportunities. Knowing how far adults travel to undertake physical activity will assist in designing supportive neighborhoods and designing future ecological research

A cross-sectional study of the individual, social, and built environmental correlates of pedometer-based physical activity among elementary school children

Background: Children who participate in regular physical activity obtain health benefits. Preliminary pedometerbased cut-points representing sufficient levels of physical activity among youth have been established; however limited evidence regarding correlates of achieving these cut-points exists. The purpose of this study was to identify correlates of pedometer-based cut-points among elementary school-aged children.Method: A cross-section of children in grades 5-7 (10-12 years of age) were randomly selected from the most (n = 13) and least (n = 12) &lsquo;walkable&rsquo; public elementary schools (Perth, Western Australia), stratified by socioeconomic status. Children (n = 1480; response rate = 56.6%) and parents (n = 1332; response rate = 88.8%) completed a survey, and steps were collected from children using pedometers. Pedometer data were categorized to reflect the sex-specific pedometer-based cut-points of &ge;15000 steps/day for boys and &ge;12000 steps/day for girls. Associations between socio-demographic characteristics, sedentary and active leisure-time behavior, independent mobility, active transportation and built environmental variables - collected from the child and parent surveys - and meeting pedometer-based cut-points were estimated (odds ratios: OR) using generalized estimating equations.Results: Overall 927 children participated in all components of the study and provided complete data. On average, children took 11407 &plusmn; 3136 steps/day (boys: 12270 &plusmn; 3350 vs. girls: 10681 &plusmn; 2745 steps/day; p &lt; 0.001) and 25.9% (boys: 19.1 vs. girls: 31.6%; p &lt; 0.001) achieved the pedometer-based cut-points. After adjusting for all other variables and school clustering, meeting the pedometer-based cut-points was negatively associated (p &lt; 0.05) with being male (OR = 0.42), parent self-reported number of different destinations in the neighborhood (OR 0.93), and a friend&rsquo;s (OR 0.62) or relative&rsquo;s (OR 0.44, boys only) house being at least a 10-minute walk from home. Achieving the pedometer-based cut-points was positively associated with participating in screen-time &lt; 2 hours/day (OR 1.88), not being driven to school (OR 1.48), attending a school located in a high SES neighborhood (OR 1.33), the average number of steps among children within the respondent&rsquo;s grade (for each 500 step/day increase: OR 1.29), and living further than a 10-minute walk from a relative&rsquo;s house (OR 1.69, girls only).Conclusions: Comprehensive multi-level interventions that reduce screen-time, encourage active travel to/from school and foster a physically active classroom culture might encourage more physical activity among children.<br /

Friendship networks and physical activity and sedentary behavior among youth: a systematized review

BACKGROUND: Low levels of physical activity and increased participation in sedentary leisure-time activities are two important obesity-risk behaviors that impact the health of today’s youth. Friend’s health behaviors have been shown to influence individual health behaviors; however, current evidence on the specific role of friendship networks in relation to levels of physical activity and sedentary behavior is limited. The purpose of this review was to summarize evidence on friendship networks and both physical activity and sedentary behavior among children and adolescents. METHOD: After a search of seven scientific databases and reference scans, a total of thirteen articles were eligible for inclusion. All assessed the association between friendship networks and physical activity, while three also assessed sedentary behavior. RESULTS: Overall, higher levels of physical activity among friends are associated with higher levels of physical activity of the individual. Longitudinal studies reveal that an individual’s level of physical activity changes to reflect his/her friends’ higher level of physical activity. Boys tend to be influenced by their friendship network to a greater extent than girls. There is mixed evidence surrounding a friend’s sedentary behavior and individual sedentary behavior. CONCLUSION: Friends’ physical activity level appears to have a significant influence on individual’s physical activity level. Evidence surrounding sedentary behavior is limited and mixed. Results from this review could inform effective public health interventions that harness the influence of friends to increase physical activity levels among children and adolescents

Physical activity and sedentary behavior assessment: A laboratory-based evaluation of agreement between commonly used actigraph and omron accelerometers

Different models of accelerometer have the potential to provide a different estimate of the same physical activity or sedentary behavior. Our study compared the outputs of the Active Style Pro (ASP) and ActiGraph (AG) devices in assessing predicted metabolic equivalents (METs) for specific activities under laboratory conditions. Thirty healthy young adults wore two hip accelerometers (ASP and AG), simultaneously while performing twenty-two activities (eight sedentary, eight household, and six ambulatory activities) in a controlled laboratory setting. For the AG, predicted METs for each activity was calculated using four equations based on vertical-axis and vector magnitude data. Separate paired t-tests and Bland–Altman analysis examined the difference and agreement in METs between AG using four commonly used equations and ASP measurements for each activity. AG devices using different equations calculated significantly different outcomes for most activities compared with ASP devices. The smallest differences in predicted METs estimates between ASP and AG were observed for ambulatory activities. Ambulatory activities demonstrated the best agreement between ASP and AG regardless of which AG equation was used. Our findings can be used to assist researchers in their selection of accelerometer and output estimation equations for measuring physical activity and sedentary behavior in adults