50 resultados para Health-enhancing physical activity (HEPA)


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BACKGROUND: Recent public health initiatives have promoted accumulating 10,000 steps per day. Little previous research has evaluated its effects in young adults. The aim of this study was to determine the effects of taking 10,000 steps per day on fitness and cardiovascular risk factors in sedentary university students. METHODS: Healthy, sedentary students (mean age 21.16 ± SD 6.17) were randomly allocated to take 10,000 steps per day or to a control group who maintained their habitual activity. Members of the 10,000 step group wore a pedometer and reported daily step count in a diary. Outcome measurements (20-meter multistage shuttle run, BMI, and blood pressure) were measured before and after 6 weeks. RESULTS: There were no significant differences between the groups at baseline. After 6 weeks, the 10,000 steps group were taking significantly more steps (8824.1 ± SD 5379.3 vs. 12635.9 ± SD 6851.3; P = .03).No changes were observed in fitness, or BMI (P > .05). Significant reductions in blood pressure (P = .04) in the 10,000 step group. CONCLUSIONS: A daily target of 10,000 steps may be an appropriate intervention in sedentary university students to increase their physical activity levels. The positive health benefits of simple everyday physical activity should be promoted among health professionals.

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Abstract
Background Physical inactivity is a major public health concern, and more innovative approaches are urgently needed to address it. The UK Government supports the use of incentives and so-called nudges to encourage healthy behaviour changes, and has encouraged business sector involvement in public health through the Public Health Responsibility Deal. To test the effectiveness of provision of incentives to encourage adults to increase their physical activity, we
recruited 406 adults from a workplace setting (office-based) to take part in an assessor-blind randomised controlled trial.
Methods
We developed the physical activity loyalty card scheme, which integrates a novel physical activity tracking system with web-based monitoring (palcard). Participants were recruited from two buildings at Northern Ireland’s main
government offices and were randomly allocated (grouped by building [n=2] to reduce contamination) to either incentive group (n=199) or no incentive group (n=207). We included participants aged 16–65 years, based at the worksite 4 days or more per week and for 6 h or more per day, and able to complete 15 min of moderate-paced walking (self-report). Exclusion criteria included having received specific advice by a general practitioner not to exercise. A statistician not involved in administration of the trial prepared a computer-generated random allocation sequence. Random assignments were placed in individually numbered, sealed envelopes by the statistician to ensure concealment of allocation. Only the assessor was masked to assignment. Sensors were placed along footpaths and the gym in the workplace. Participants scanned their loyalty card at the sensor when undertaking physical activity (eg, walking), which logged activity. Participants in the incentive group monitored their physical activity, collected points, and received rewards (retail vouchers) for minutes of physical activity completed over the 12-week intervention. Rewards were vouchers sponsored by local retailers. Participants in the no incentive group used their loyalty card to self-monitor their physical activity but were not able to earn points or receive rewards. The primary outcome was change in minutes of moderate to vigorous physical activity with the Global Physical Activity Questionnaire, measured at baseline, week 12, and 6 months. Activity was objectively measured with the tracking system over the 12-week intervention. Mann Whitney U tests were done to assess change between groups.
Findings
The mean age of participants was 43·32 years (SD 9·37), and 272 (67%) were women. We obtained follow-up data from 353 (87%) participants at week 12 and 341 (84%) at 6 months. At week 12, participants in the incentive group increased moderate to vigorous physical activity by a median of 60 min per week (IQR –10 to 120) compared with 30 min per week (–60 to 90) in the no incentive group (p=0·05). At 6 months, participants in the incentive group had
increased their moderate to vigorous physical activity by 30 min per week (–60 to 100) from baseline compared with 0 min per week (–115 to 1110) in the no incentive group (p=0·099). We noted no significant differences between groups
for use of loyalty card (p=0·18). Participants in the incentive group recorded a mean of 60·22 min (95% CI 50·90–69·55) of physical activity per week with their loyalty card on week 1 and 23·56 min (17·06–30·06) at week 12, which was similar to that for those in the no incentive group (59·74 min, 51·24–68·23, at week 1; 20·25 min, 14·45–26·06, at week 12; p=0·94 for differences between groups at week 1; p=0·45 for differences between groups at week 12).
Interpretation:
Financial incentives showed a short-term behaviour change in physical activity. This innovative study contributes to the necessary evidence base, and has important implications for physical activity promotion and business engagement in health. The optimum incentive-based approach needs to be established. Results should be interpreted with some caution as the analyses of secondary outcomes were not adjusted for multiple comparisons.

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Background: There is a dearth of evidence regarding the impact of urban regeneration projects on public health, particularly the nature and degree to which urban regeneration impacts upon health-related behaviour change. Natural experiment methodology enables comprehensive large-scale evaluations of such interventions. The Connswater Community Greenway in Belfast is a major urban regeneration project involving the development of a 9 km linear park, including the provision of new cycle paths and walkways. In addition to the environmental improvements, this complex intervention involves a number of programmes to promote physical activity in the regenerated area. The project affords a unique opportunity to investigate the public health impact of urban regeneration.

Methods/Design: The evaluation framework was informed by the socio-ecological model and guided by the RE-AIM Framework. Key components include: (1) a quasi-experimental before-and-after survey of the Greenway population (repeated cross-sectional design), in tandem with data from a parallel Northern Ireland-wide survey for comparison; (2) an assessment of changes in the local built environment and of walkability using geographic information systems; (3) semi-structured interviews with a purposive sample of survey respondents, and a range of community stakeholders, before and after the regeneration project; and (4) a cost-effectiveness analysis. The primary outcome is change in proportion of individuals identified as being regularly physically active, according to the current UK recommendations. The RE-AIM Framework will be used to make an overall assessment of the impact of the Greenway on the physical activity behaviour of local residents.

Discussion: The Connswater Community Greenway provides a significant opportunity to achieve long-term, population level behaviour change. We argue that urban regeneration may be conceptualised meaningfully as a complex intervention comprising multiple components with the potential, individually and interactively, to affect the behaviour of a diverse population. The development and implementation of our comprehensive evaluation framework reflects this complexity and illuminates an approach to the empirical, rigorous evaluation of urban regeneration. More specifically, this study will add to the much needed evidence-base about the impact of urban regeneration on public health as well as having important implications for the development of natural experiment methodology.

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Background: Mental ill-health, particularly depression and anxiety, is a leading and increasing cause of disability worldwide, especially for women.

Methods: We examined the prospective association between physical activity and symptoms of mental ill-health in younger, mid-life and older working women. Participants were 26 913 women from the ongoing cohort Finnish Public Sector Study with complete data at two phases, excluding those who screened positive for mental ill-health at baseline. Mental health was assessed using the 12-item General Health Questionnaire. Self-reported physical activity was expressed in metabolic equivalent task (MET) hours per week. Logistic regression models were used to analyse associations between physical activity levels and subsequent mental health.

Results: There was an inverse dose–response relationship between physical activity and future symptoms of mental ill-health. This association is consistent with a protective effect of physical activity and remained after adjustments for socio-demographic, work-related and lifestyle factors, health and body mass index. Furthermore, those mid-life and older women who reported increased physical activity by more than 2 MET hours per week demonstrated a reduced risk of later mental ill-health in comparison with those who did not increase physical activity. This protective effect of increased physical activity did not hold for younger women.

Conclusions: This study adds to the evidence for the protective effect of physical activity for later mental health in women. It also suggests that increasing physical activity levels may be beneficial in terms of mental health among mid-life and older women. The alleviation of menopausal symptoms may partly explain age effects but further research is required.

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Objective. The aim of this study is to investigate the correlates of knowledge of the UK physical activity (PA) guidelines.

Method. A Northern Ireland-wide population survey (2010/2011) of 4653 adults provided cross-sectional data on PA, knowledge of guidelines and socio demographic characteristics. Multinomial logistic regression was used to investigate the associations between knowledge and socio-demographic characteristics (Model 1); and modifiable health behaviours (Model 2).

Results. Results showed that 47% of respondents were unaware of PA guidelines. Males who had a lower level of education (OR 5.91; 95% CI 1.67, 20.94), lived in more deprived areas (OR 4.80; 95% CI 1.87, 12.30), low income (OR 2.36; 95% CI 1.63, 3.41) and did no PA (OR 2.74; 95% CI 1.31, 5.76) were more likely to be unaware of the guidelines. Females who were younger (OR 1.03; 95% CI 1.02, 1.05) and reported poor health (OR 2.71; 95% CI 1.61, 4.58) were more likely to be unaware of the guidelines.

Conclusion. There is a lack of awareness about the levels of PA needed to promote health. An understanding of the characteristics of those who are unaware of the guidelines has important implications for the design of targeted, effective health promotion.

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It is now recognised that inactive lifestyles underpin much of the disease burden evident in the richer nations of the world. Indeed, the WHO has identified physical inactivity as a 'global public health problem' and has established minimum physical activity (PA) targets for people at different stages of the life-course. Yet, according to WHO, just under 1/3 of working age adults across the globe meet those targets and it is not at all clear how the disjunction between the recommendations of policy makers and the behaviour of ordinary people might be surmounted. Using an opportunity to examine the impact of an urban regeneration project on community residents in East Belfast (Northern Ireland) this paper examines the views of some 113 people on how to increase rates of PA in an area of multiple deprivation. The results of the analysis suggest that lay people rarely consider PA as a discrete issue, or one that centres on individuals and their motivation, but rather as one component in a complex web of concerns, processes and events that include such things as the actions of neighbours and relatives, material and political environments, vandalism, violence, and the weather. We explore and unravel the nature of those concerns using novel methods of content analysis that generate 'issue webs'. Particular attention is paid to the ways in which lay people conceptualize 'activity' and to the manner in which they point to ways of encouraging activity that are rooted in everyday life rather than in the corpocentric, agent-centred and often sport dominated strategies favoured by local policy makers. Our results support those who argue that interventions to increase rates of PA need to move beyond behavioural approaches that focus on individuals and consider the social, political and material contexts in which 'activity' occurs.

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OBJECTIVE: To investigate the characteristics of those doing no moderate-vigorous physical activity (MVPA) (0days/week), some MVPA (1-4days/week) and sufficient MVPA (≥5days/week) to meet the guidelines in order to effectively develop and target PA interventions to address inequalities in participation.

METHOD: A population survey (2010/2011) of 4653 UK adults provided data on PA and socio-demographic characteristics. An ordered logit model investigated the covariates of 1) participating in no PA, 2) participating in some PA, and 3) meeting the PA guidelines. Model predictions were derived for stereotypical subgroups to highlight important policy and practice implications.

RESULTS: Mean age of participants was 45years old (95% CI 44.51, 45.58) and 42% were male. Probability forecasting showed that males older than 55years of age (probability=0.20; 95% CI 0.11, 0.28), and both males (probability=0.31; 95% CI 0.17, 0.45) and females (probability=0.38; 95% CI 0.27, 0.50) who report poor health are significantly more likely to do no PA.

CONCLUSIONS: Understanding the characteristics of those doing no MVPA and some MVPA could help develop population-level interventions targeting those most in need. Findings suggest that interventions are needed to target older adults, particularly males, and those who report poor health.

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Health Locus of Control (HLC) classifies our beliefs about the connection between our actions and health outcomes (Skinner, 1996) into three categories: “internal control”, corresponding to health being the result of an individual's effort and habits; “control by powerful others”, whereby health depends on others, such as doctors; and “chance control”, according to which health depends on fate and chance. Using Choice Experiments we investigate the relationship between HLC and willingness to change lifestyle, in terms of eating habits, physical activity and associated cardiovascular disease risk, in a 384 person sample representative of the 40–65 aged population of Northern Ireland administered between February and July 2011. Using latent class analysis we identify three discrete classes of people based on their HLC: the first class is sceptical about their capacity to control their health and certain unhealthy habits. Despite being unsatisfied with their situation, they are reluctant to accept behaviour changes. The second is a group of individuals unhappy with their current situation but willing to change through exercise and diet. Finally, a group of healthy optimists is identified, who are satisfied with their current situation but happy to take more physical activity and improve their diet. Our findings show that any policy designed to modify people's health related behaviour should consider the needs of this sceptical class which represents a considerable proportion of the population in the region.

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Objectives: To assess the levels of physical activity and other health related behaviours of General Practitioners (GPs) and compare their reported levels of physical activity with those of the general population. Study Design: Cross sectional postal questionnaire survey. Methods: A questionnaire, which did not allow identification of individual respondents, was posted to all 1074 (GPs) in Northern Ireland. It included the validated International Physical Activity Questionnaire (IPAQ) and questions relating to smoking and alcohol consumption. A national survey of a representative sample of the general population of similar age (29-67 years; n = 3010) provided comparative data. Results: 735 GPs responded (68.4%). IPAQ data indicated that fewer GPs (43.4%) were “physically inactive” compared to the general population (56.2%) (p