Leisure-time physical activity, inactivity and sedentary behaviours

Assesses the relationship between leisure-time physical activity and sedentary behaviours in two cross-sectional studies of adults. Behavioural choice theory was applied to gain a better understanding of people's time allocation in these behaviours. The findings show that preference, reinforcement, and barriers are potentially important factors to consider in the study of the increasing population prevalence of sedentary lifestyles.

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) ‘walkable’ 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 ≥15000 steps/day for boys and ≥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 ± 3136 steps/day (boys: 12270 ± 3350 vs. girls: 10681 ± 2745 steps/day; p < 0.001) and 25.9% (boys: 19.1 vs. girls: 31.6%; p < 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 < 0.05) with being male (OR = 0.42), parent self-reported number of different destinations in the neighborhood (OR 0.93), and a friend’s (OR 0.62) or relative’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 < 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’s grade (for each 500 step/day increase: OR 1.29), and living further than a 10-minute walk from a relative’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.

Don't worry, be active : positive affect and habitual physical activity

Objective: The aim of ths study was to examine the association between habitual physical activity and positive and negative affect.

Method: This cross-sectional study included 276 women aged 20 +, from the Geelong Osteoporosis Study. Habitual physical activity and other lifestyle exposures were assessed by questionnaire, concurrent with anthropometric assessments. Physical activity was categorized as very active, moderately active or sedentary. Positive and negative affect scores were derived from the validated 20 item Positive and Negative Affect Schedule (PANAS) self-report and were categorized into tertiles.

Results: There was a pattern of lower positive affect scores for lower levels of physical activity. With very active as the reference category, the odds for having a positive affect score in the highest tertile were sequentially lower for those who were moderately active (OR = 0.53, 95%CI 0.28–1.01) and sedentary (OR = 0.28, 95%CI 0.10–0.75). Associations were sustained after adjusting for body mass index and polypharmacy (OR = 0.50, 95%CI 0.26–0.96 and OR = 0.25, 95%CI 0.09–0.72, respectively). These associations were not explained by age, negative affect score or other exposures. No association was detected between physical activity and negative affect scores.

Conclusions: This study reports that higher positive affect scores, encompassing emotions such as interest, excitement, enthusiasm and alertness, are associated with higher levels of habitual physical activity. These observations warrant further investigations into possible mechanistic interplay between neurobiological and psychosocial factors that underpin this association.

Promoting fit bodies, healthy eating and physical activity among Indigenous Australian men : a study protocol

Background: Overall the physical health of Indigenous men is among the worst in Australia. Research has indicated that modifiable lifestyle factors, such as poor nutrition and physical inactivity, appear to contribute strongly to these poor health conditions. To effectively develop and implement strategies to improve the health of Australia’s Indigenous peoples, a greater understanding is needed of how Indigenous men perceive health, and how they view and care for their bodies. Further, a more systematic understanding of how sociocultural factors affect their health attitudes and behaviours is needed. This article presents the study protocol of a communitybased investigation into the factors surrounding the health and body image of Indigenous Australian men.
Methods and design: The study will be conducted in a collaborative manner with Indigenous Australian men using a participatory action research framework. Men will be recruited from three locations around Australia (metropolitan, regional, and rural) and interviewed to understand their experiences and perspectives on a number of issues related to health and health behaviour. The information that is collected will be analysed using modified grounded theory and thematic analysis. The results will then be used to develop and implement community events in each location to provide feedback on the findings to the community, promote health enhancing strategies, and determine future action and collaboration.
Discussion: This study will explore both risk and protective factors that affect the health of Indigenous Australian men. This knowledge will be disseminated to the wider Indigenous community and can be used to inform future health promotion strategies. The expected outcome of this study is therefore an increased understanding of health and health change in Indigenous Australian men, the development of strategies that promote healthy eating and positive patterns of physical activity and, in the longer term, more effective and culturally-appropriate interventions to improve health.

Do food and physical activity environments vary between disadvantaged urban and rural areas? Findings from the READI study

Issues addressed: The presence or absence of amenities in local neighbourhood environments can either promote or restrict access to opportunities to engage in healthy and/or less healthy behaviours. Rurality is thought to constrain access to facilities and services. This study investigated whether the presence and density of environmental amenities related to physical activity and eating behaviours differs between socioeconomically disadvantaged urban and rural areas in Victoria, Australia.

Methods: We undertook cross-sectional analysis of environmental data collected in 2007-08 as part of the Resilience for Eating and Activity Despise Inequality (READI) study. These data were sourced and analysed for 40 urban and 40 rural socioeconomically disadvantaged areas. The variables examined were the presence, raw count, count/km², and count/'000 population of a range of environmental amenities (fast-food restaurants, all supermarkets (also separated by major chain and other supermarkets), greengrocers, playgrounds, gyms/leisure centres, public swimming pools and public open spaces).

Results: A greater proportion of urban areas had a fast-food restaurant and gym/leisure centre present while more rural areas contained a supermarket and public swimming pool. All amenities examined (with the exception of swimming pools) were more numerous per km² in urban areas, however rural areas had a greater number of all supermarkets, other supermarkets, playgrounds, swimming pools and public open area per '000 population.

Conclusion: Although opportunities to engage in healthy eating and physical activity exist in many rural areas, a lower density per km² suggests a greater travel distance may be required to reach these.

Change in active travel and changes in recreational and total physical activity in adults : longitudinal findings from the iConnect study

Background : To better understand the health benefits of promoting active travel, it is important to understand the relationship between a change in active travel and changes in recreational and total physical activity.

Methods : These analyses, carried out in April 2012, use longitudinal data from 1628 adult respondents (mean age 54 years; 47% male) in the UK-based iConnect study. Travel and recreational physical activity were measured using detailed seven-day recall instruments. Adjusted linear regression models were fitted with change in active travel defined as ‘decreased’ (<−15 min/week), ‘maintained’ (±15 min/week) or ‘increased’ (>15 min/week) as the primary exposure variable and changes in (a) recreational and (b) total physical activity (min/week) as the primary outcome variables.

Results : Active travel increased in 32% (n=529), was maintained in 33% (n=534) and decreased in 35% (n=565) of respondents. Recreational physical activity decreased in all groups but this decrease was not greater in those whose active travel increased. Conversely, changes in active travel were associated with commensurate changes in total physical activity. Compared with those whose active travel remained unchanged, total physical activity decreased by 176.9 min/week in those whose active travel had decreased (adjusted regression coefficient −154.9, 95% CI −195.3 to −114.5) and was 112.2 min/week greater among those whose active travel had increased (adjusted regression coefficient 135.1, 95% CI 94.3 to 175.9).

Conclusion : An increase in active travel was associated with a commensurate increase in total physical activity and not a decrease in recreational physical activity.

Study protocol for "Moving bright, eating smart"- a phase 2 clinical trial on the acceptability and feasibility of a diet and physical activity intervention to prevent recurrence in colorectal cancer survivors

Background: Colorectal cancer is the second most common cancer and cancer-killer in Hong Kong with an alarming increasing incidence in recent years. The latest World Cancer Research Fund report concluded that foods low in fibre, and high in red and processed meat cause colorectal cancer whereas physical activity protects against
colon cancer. Yet, the influence of these lifestyle factors on cancer outcome is largely unknown even though cancer survivors are eager for lifestyle modifications. Observational studies suggested that low intake of a Western-pattern diet and high physical activity level reduced colorectal cancer mortality. The Theory of Planned
Behaviour and the Health Action Process Approach have guided the design of intervention models targeting a wide range of health-related behaviours.
Methods/design: We aim to demonstrate the feasibility of two behavioural interventions intended to improve colorectal cancer outcome and which are designed to increase physical activity level and reduce consumption of a Western-pattern diet. This three year study will be a multicentre, randomised controlled trial in a 2x2 factorial
design comparing the “Moving Bright, Eating Smart” (physical activity and diet) programme against usual care. Subjects will be recruited over a 12-month period, undertake intervention for 12 months and followed up for a further 12 months. Baseline, interim and three post-intervention assessments will be conducted. Two hundred and twenty-two colorectal cancer patients who completed curative treatment without evidence of recurrence will be recruited into the study. Primary outcome measure will be whether physical activity and dietary targets are met at the end of the 12-month intervention. Secondary outcome measures include the magnitude and
mechanism of behavioural change, the degree and determinants of compliance, and the additional health benefits and side effects of the intervention.
Discussion: The results of this study will establish the feasibility of targeting the two behaviours (diet and physical activity) and demonstrate the magnitude of behaviour change. The information will facilitate the design of a further larger phase III randomised controlled trial with colorectal cancer outcome as the study endpoint to determine whether this intervention model would reduce colorectal cancer recurrence and mortality.

Knowledge, attitudes and practices of clinicians in promoting physical activity to prostate cancer survivors

Objectives: 

The use of kernel density estimation to examine associations between neighborhood destination intensity and walking and physical activity

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.

Traversing myths and mountains: addressing socioeconomic inequities in the promotion of nutrition and physical activity behaviours

BACKGROUND: In developed countries, individuals experiencing socioeconomic disadvantage - whether a low education level, low income, low-status occupation, or living in a socioeconomically disadvantaged neighbourhood - are less likely than those more advantaged to engage in eating and physical activity behaviours conducive to optimal health. These socioeconomic inequities in nutrition and physical activity (and some sedentary) behaviours are graded, persistent, and evident across multiple populations and studies. They are concerning in that they mirror socioeconomic inequities in obesity and in health outcomes. Yet there remains a dearth of evidence of the most effective means of addressing these inequities. People experiencing disadvantage face multiple challenges to healthy behaviours that can appear insurmountable. With increasing recognition of the role of underlying structural and societal factors as determinants of nutrition and physical activity behaviours and inequities in these behaviours, and the limited success of behaviour change approaches in addressing these inequities, we might wonder whether there remains a role for behavioural scientists to tackle these challenges. DISCUSSION: This debate piece argues that behavioural scientists can play an important role in addressing socioeconomic inequities in nutrition, physical activity and sedentary behaviours, and that this will involve challenging myths and taking on new perspectives. There are successful models for doing so from which we can learn. Addressing socioeconomic inequities in eating, physical activity and sedentary behaviours is challenging. However, successful examples demonstrate that overcoming such challenges is possible, and provide guidance for doing so. Given the disproportionate burden of ill health carried by people experiencing socioeconomic disadvantage, all our nutrition and physical activity interventions, programs and policies should be designed to reach and positively impact these individuals at greatest need.

A machine learning approach to measure and monitor physical activity in children to help fight overweight and obesity

Physical Activity is important for maintaining healthy lifestyles. Recommendations for physical activity levels are issued by most governments as part of public health measures. As such, reliable measurement of physical activity for regulatory purposes is vital. This has lead research to explore standards for achieving this using wearable technology and artificial neural networks that produce classifications for specific physical activity events. Applied from a very early age, the ubiquitous capture of physical activity data using mobile and wearable technology may help us to understand how we can combat childhood obesity and the impact that this has in later life. A supervised machine learning approach is adopted in this paper that utilizes data obtained from accelerometer sensors worn by children in free-living environments. The paper presents a set of activities and features suitable for measuring physical activity and evaluates the use of a Multilayer Perceptron neural network to classify physical activities by activity type. A rigorous reproducible data science methodology is presented for subsequent use in physical activity research. Our results show that it was possible to obtain an overall accuracy of 96 % with 95 % for sensitivity, 99 % for specificity and a kappa value of 94 % when three and four feature combinations were used.

Motivation and barriers for leisure-time physical activity in socioeconomically disadvantaged women

INTRODUCTION: The aim of this study was to examine cross-sectional and longitudinal associations between motivation and barriers for physical activity, and physical activity behavior in women living in socioeconomic disadvantage. This study also examined whether weight control intentions moderate those associations.

METHODS: Data from 1664 women aged 18-46 years was collected at baseline and three-year follow-up as part of the Resilience for Eating and Activity Despite Inequality study. In mail-based surveys, women reported sociodemographic and neighborhood environmental characteristics, intrinsic motivation, goals and perceived family barriers to be active, weight control intentions and leisure-time physical activity (assessed through the IPAQ-L). Linear regression models assessed the association of intrinsic motivation, goals and barriers with physical activity at baseline and follow-up, adjusting for environmental characteristics and also physical activity at baseline (for longitudinal analyses), and the moderating effects of weight control intentions were examined.

RESULTS: Intrinsic motivation and, to a lesser extent, appearance and relaxation goals for being physically active were consistently associated with leisure-time physical activity at baseline and follow-up. Perceived family barriers, health, fitness, weight and stress relief goals were associated with leisure-time physical activity only at baseline. Moderated regression analyses revealed that weight control intentions significantly moderated the association between weight goals and leisure-time physical activity at baseline (β = 0.538, 99% CI = 0.057, 0.990) and between intrinsic motivation and leisure-time physical activity at follow-up (β = 0.666, 99% CI = 0.188, 1.145). For women actively trying to control their weight, intrinsic motivation was significantly associated with leisure-time physical activity at follow-up (β = 0.184, 99% CI = 0.097, 0.313).

CONCLUSIONS: Results suggest that, especially in women trying to control their weight, intrinsic motivation plays an important role in sustaining physical activity participation over time. Also, weight goals for being physically active seem to play a role regarding short-term physical activity participation in this particular population. Addressing these motivational features may be important when promoting physical activity participation in women living in socioeconomically disadvantaged neighborhoods.

Neighbourhood environment, physical activity, quality of life and depressive symptoms in Hong Kong older adults: a protocol for an observational study

INTRODUCTION: The neighbourhood environment can assist the adoption and maintenance of an active lifestyle and affect the physical and mental well-being of older adults. The psychosocial and behavioural mechanisms through which the environment may affect physical and mental well-being are currently poorly understood. AIM: This observational study aims to examine associations between the physical and social neighbourhood environments, physical activity, quality of life and depressive symptoms in Chinese Hong Kong older adults.

METHODS AND ANALYSES: An observational study of the associations of measures of the physical and social neighbourhood environment, and psychosocial factors, with physical activity, quality of life and depressive symptoms in 900 Hong Kong older adults aged 65+ years is being conducted in 2012-2016. The study involves two assessments taken 6 months apart. Neighbourhood walkability and access to destinations are objectively measured using Geographic Information Systems and environmental audits. Demographics, socioeconomic status, walking for different purposes, perceived neighbourhood and home environments, psychosocial factors, health status, social networks, depressive symptoms and quality of life are being assessed using validated interviewer-administered self-report measures and medical records. Physical functionality is being assessed using the Short Physical Performance Battery. Physical activity and sedentary behaviours are also being objectively measured in approximately 45% of participants using accelerometers over a week. Physical activity, sedentary behaviours, quality of life and depressive symptoms are being assessed twice (6 months apart) to examine seasonality effects on behaviours and their associations with quality of life and depressive symptoms.

ETHICS AND DISSEMINATION: The study received ethical approval from the University of Hong Kong Human Research Ethics Committee for Non-Clinical Faculties (EA270211) and the Department of Health (Hong Kong SAR). Data are stored in a password-protected secure database for 10 years, accessible only to the named researchers. Findings will be submitted for publication in peer-reviewed journals.