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\"The positive benefits of physical activity for physical and mental health are now widely acknowledged, yet levels of physical inactivity continue to increase throughout the developed world. Understanding the psychology of physical activity has therefore become an important concern for scientists, health professionals and policy-makers alike. Psychology of Physical Activity is a comprehensive and in-depth introduction to the fundamentals of exercise psychology, from theories of motivation and adherence to the design of successful interventions for increasing participation. Now in a fully revised, updated and expanded third edition, Psychology of Physical Activity is still the only textbook to offer a full survey of the evidence-base for theory and practice in exercise psychology, and the only textbook that explains how to interpret the quality of the research evidence. With international cases, examples and data included throughout, the book also provides a thoroughly detailed examination of the relationship between physical activity and mental health. A full companion website offers useful features to help students and lecturers get the most out of the book during their course, including multiple-choice revision questions, flashcards, PowerPoint slides, an instructors' guide and a test bank of additional short answer and essay questions. Psychology of Physical Activity is the most authoritative, engaging and up-to-date introduction to exercise psychology currently available. It is essential reading for all students working in exercise and health sciences\"-- Provided by publisher.

Background Sedentary behaviour (sitting time) has becoming a very popular topic for research and translation since early studies on TV viewing in children in the 1980s. The most studied area for sedentary behaviour health outcomes has been adiposity in young people. However, the literature is replete with inconsistencies. Methods We conducted a systematic review of systematic reviews and meta-analyses to provide a comprehensive analysis of evidence and state-of-the-art synthesis on whether sedentary behaviours are associated with adiposity in young people, and to what extent any association can be considered ‘causal’. Searches yielded 29 systematic reviews of over 450 separate papers. We analysed results by observational (cross-sectional and longitudinal) and intervention designs. Results Small associations were reported for screen time and adiposity from cross-sectional evidence, but associations were less consistent from longitudinal studies. Studies using objective accelerometer measures of sedentary behaviour yielded null associations. Most studies assessed BMI/BMI-z. Interventions to reduce sedentary behaviour produced modest effects for weight status and adiposity. Accounting for effects from sedentary behaviour reduction alone is difficult as many interventions included additional changes in behaviour, such as physical activity and dietary intake. Analysis of causality guided by the classic Bradford Hill criteria concluded that there is no evidence for a causal association between sedentary behaviour and adiposity in youth, although a small dose-response association exists. Conclusions Associations between sedentary behaviour and adiposity in children and adolescents are small to very small and there is little to no evidence that this association is causal. This remains a complex field with different exposure and outcome measures and research designs. But claims for ‘clear’ associations between sedentary behaviour and adiposity in youth, and certainly for causality, are premature or misguided.

BACKGROUND: The efficacy of high-intensity interval training for a broad spectrum of cardio-metabolic health outcomes is not in question. Rather, the effectiveness of this form of exercise is at stake. In this paper we debate the issues concerning the likely success or failure of high-intensity interval training interventions for population-level health promotion. DISCUSSION: Biddle maintains that high-intensity interval training cannot be a viable public health strategy as it will not be adopted or maintained by many people. This conclusion is based on an analysis of perceptions of competence, the psychologically aversive nature of high-intensity exercise, the affective component of attitudes, the less conscious elements of motivated behaviour that reflect our likes and dislikes, and analysis using the RE-AIM framework. Batterham argues that this appraisal is based on a constrained and outmoded definition of high-intensity interval training and that truly practical and scalable protocols have been - and continue to be - developed. He contends that the purported displeasure associated with this type of exercise has been overstated. Biddle suggests that the way forward is to help the least active become more active rather than the already active to do more. Batterham claims that traditional physical activity promotion has been a spectacular failure. He proposes that, within an evolutionary health promotion framework, high-intensity interval training could be a successful population strategy for producing rapid physiological adaptations benefiting public health, independent of changes in total physical activity energy expenditure. Biddle recommends that we focus our attention elsewhere if we want population-level gains in physical activity impacting public health. His conclusion is based on his belief that high-intensity interval training interventions will have limited reach, effectiveness, and adoption, and poor implementation and maintenance. In contrast, Batterham maintains that there is genuine potential for scalable, enjoyable high-intensity interval exercise interventions to contribute substantially to addressing areas of public health priority, including prevention and treatment of Type 2 diabetes and cardiovascular disease.

Overweight and obesity impose a significant health burden in Australia, predominantly the middle-aged and older adults. Studies of the association between obesity and chronic diseases are primarily based on cross-sectional data, which is insufficient to deduce a temporal relationship. Using nationally representative panel data, this study aims to investigate whether obesity is a significant risk factor for type 2 diabetes, heart diseases, asthma, arthritis, and depression in Australian middle-aged and older adults. Longitudinal data comprising three waves (waves 9, 13 and 17) of the Household, Income and Labour Dynamics in Australia (HILDA) survey were used in this study. This study fitted longitudinal random-effect logistic regression models to estimate the between-person differences in the association between obesity and chronic diseases. The findings indicated that obesity was associated with a higher prevalence of chronic diseases among Australian middle-aged and older adults. Obese adults (Body Mass Index [BMI] ≥ 30) were at 12.76, 2.05, 1.97, 2.25, and 1.96, times of higher risks of having type 2 diabetes (OR: 12.76, CI 95%: 8.88-18.36), heart disease (OR: 2.05, CI 95%: 1.54-2.74), asthma (OR: 1.97, CI 95%: 1.49-2.62), arthritis (OR: 2.25, 95% CI: 1.90-2.68) and depression (OR: 1.96, CI 95%: 1.56-2.48), respectively, compared with healthy weight counterparts. However, the study did not find any evidence of a statistically significant association between obesity and cancer. Besides, gender stratified regression results showed that obesity is associated with a higher likelihood of asthma (OR: 2.64, 95% CI: 1.84-3.80) among female adults, but not in the case of male adults. Excessive weight is strongly associated with a higher incidence of chronic disease in Australian middle-aged and older adults. This finding has clear public health implications. Health promotion programs and strategies would be helpful to meet the challenge of excessive weight gain and thus contribute to the prevention of chronic diseases.

Accumulating high volumes of sedentary behaviour is a risk factor for multiple negative health-related outcomes. The objective of this review was to synthesise the evidence on the levels of sedentary behaviour in university students. Screened records from 13 databases were included if (i) published after 2007 and (ii) reported on university students’ amount of total or domain-specific sedentary behaviour. Sub-group and meta-regression analyses were conducted to investigate potential sources of heterogeneity (moderators). A total of 125 studies met the inclusion criteria. Most studies were cross-sectional (84%) and reported screen time (61%) or total sedentary time (39%). Self-reported data indicated that university students spend 7.29 h per day being sedentary. The levels of total sedentary behaviour were significantly higher when measured with accelerometers (M = 9.82 h per day). Computer use presented significantly higher prevalence over other modalities of screen time. Among the explored factors (i.e. countries’ income, age, gender, and study’s publication date), only publication date significantly moderated sedentary behaviour. Results suggest that a considerable proportion of university students (i) engage in higher levels of sedentary time compared to the general young adult population and (ii) accumulate levels of sedentary time that have been associated with an increased risk for detrimental health outcomes. In addition, meta-regression analyses suggest that sedentary time has increased over the last 10-year period among university students. These findings may inform future initiatives and policies targeting university students’ sedentary behaviour. Further research is needed to identify the factors moderating sedentary behaviour in the university setting.

The prevalence of overweight and obesity has been increasing globally and has become a significant public health concern in Australia in the two past decades. This study explores the most recent national prevalence and trends of adult overweight and obesity in Australia. It will also investigate geographic remoteness as a potential risk factor for an individual being overweight or obese in adulthood. A retrospective longitudinal study that utilised 14 successive waves (wave 6 through 19) of a nationally representative linked individual-level survey. Data was obtained from the Household, Income and Labour Dynamics in Australia survey. The data on 199,675 observations from 26,713 individuals aged ≥ 15 years over the period 2006 to 2019 was analysed. Random-effects logit model was employed to estimate the association between geographic remoteness and the risk of excessive weight gain. The results reveal that the prevalence of overweight, obesity and combined overweight and obesity among Australian adults in 2019 were 34%, 26% and 60%, respectively. The analysis shows that the prevalence of overweight and obesity varies by geographic remoteness. Adults from regional city urban (OR 1.53, 95% CI 1.16–2.03) and rural areas (OR 1.32, 95% CI 1.18–1.47) were more likely to be obese compared with their counterparts from major city urban areas. The results also show that adults living in major city urban areas, regional city urban areas, and regional city rural areas in Australia were 1.53 (OR 1.53, 95% CI 1.16–2.03), 1.32 (OR 1.32, 95% CI 1.18–1.47), and 1.18 (OR 1.18, 95% CI 1.08–1.29) times more likely to be overweight compared with their counterparts from major city urban areas in Australia. Substantial geographic variation in the prevalence of overweight and obesity exists among Australian adults and appears to be increasing. Public health measures should focus on contextual obesogenic factors and behavioural characteristics to curb the rising prevalence of adult obesity.

Background The World Health Organization’s ‘Global Recommendations on Physical Activity for Health’ state that adults should engage in regular moderate-to-vigorous intensity aerobic physical activity (MVPA; e.g. walking, running, cycling) and muscle-strengthening activity (MSA; e.g. strength/resistance training). However, assessment of both MVPA and MSA is rare in physical activity surveillance. The aim of this study is to describe the prevalence, correlates and chronic health conditions associated with meeting the combined MVPA-MSA guidelines among a population representative sample of U.S. adults. Methods In this cross-sectional study, data were drawn from the U.S. 2015 Behavioral Risk Factor Surveillance System. During telephone interviews, MVPA and MSA were assessed using validated questionnaires. We calculated the proportions meeting both the global MVPA and MSA physical activity guidelines (MVPA ≥150 min/week and MSA ≥2 sessions/week). Poisson regressions with a robust error variance were used to assess: (i) prevalence ratios (PR) for meeting both guidelines across sociodemographic factors (e.g. age, sex, education, income, race/ethnicity); and (ii) PRs of 12 common chronic health conditions (e.g. diabetes, coronary heart disease, hypertension, depression) across different categories of physical activity guideline adherence (met neither [reference]; MSA only; MVPA only; met both). Results Among 383,928 adults (aged 18–80 years), 23.5% (95% CI: 20.1, 20.6%) met the combined MVPA-MSA guidelines. Those with poorer self-rated health, older adults, women, lower education/income and current smokers were less likely to meet the combined guidelines. After adjustment for covariates (e.g. age, self-rated health, income, smoking) compared with meeting neither guidelines, MSA only and MVPA only, meeting the combined MVPA-MSA guidelines was associated with the lowest PRs for all health conditions (APR range: 0.44–0.76), and the clustering of ≥6 chronic health conditions (APR = 0.33; 95% CI: 0.31–0.35). Conclusions Eight out of ten U.S. adults do not meet the global physical activity guidelines. This study supports the need for comprehensive health promotion strategies to increase the uptake and adherence of MVPA-MSA among U.S. adults. Large-scale interventions should target specific population sub-groups including older adults, women, those with poorer health and lower education/income.

In recent years there has been a growing interest in the relationship between sedentary behaviour (sitting) and health outcomes. Only recently have there been studies assessing the association between time spent in sedentary behaviour and the metabolic syndrome. The aim of this study is to quantify the association between sedentary behaviour and the metabolic syndrome in adults using meta-analysis. Medline, Embase and the Cochrane Library were searched using medical subject headings and key words related to sedentary behaviours and the metabolic syndrome. Reference lists of relevant articles and personal databases were hand searched. Inclusion criteria were: (1) cross sectional or prospective design; (2) include adults ≥ 18 years of age; (3) self-reported or objectively measured sedentary time; and (4) an outcome measure of metabolic syndrome. Odds Ratio (OR) and 95% confidence intervals for metabolic syndrome comparing the highest level of sedentary behaviour to the lowest were extracted for each study. Data were pooled using random effects models to take into account heterogeneity between studies. Ten cross-sectional studies (n = 21393 participants), one high, four moderate and five poor quality, were identified. Greater time spent sedentary increased the odds of metabolic syndrome by 73% (OR 1.73, 95% CI 1.55-1.94, p<0.0001). There were no differences for subgroups of sex, sedentary behaviour measure, metabolic syndrome definition, study quality or country income. There was no evidence of statistical heterogeneity (I(2) = 0.0%, p = 0.61) or publication bias (Eggers test t = 1.05, p = 0.32). People who spend higher amounts of time in sedentary behaviours have greater odds of having metabolic syndrome. Reducing sedentary behaviours is potentially important for the prevention of metabolic syndrome.

Active video games (AVGs) have gained interest as a way to increase physical activity in children and youth. The effect of AVGs on acute energy expenditure (EE) has previously been reported; however, the influence of AVGs on other health-related lifestyle indicators remains unclear. This systematic review aimed to explain the relationship between AVGs and nine health and behavioural indicators in the pediatric population (aged 0-17 years). Online databases (MEDLINE, EMBASE, psycINFO, SPORTDiscus and Cochrane Central Database) and personal libraries were searched and content experts were consulted for additional material. Included articles were required to have a measure of AVG and at least one relevant health or behaviour indicator: EE (both habitual and acute), adherence and appeal (i.e., participation and enjoyment), opportunity cost (both time and financial considerations, and adverse events), adiposity, cardiometabolic health, energy intake, adaptation (effects of continued play), learning and rehabilitation, and video game evolution (i.e., sustainability of AVG technology). 51 unique studies, represented in 52 articles were included in the review. Data were available from 1992 participants, aged 3-17 years, from 8 countries, and published from 2006-2012. Overall, AVGs are associated with acute increases in EE, but effects on habitual physical activity are not clear. Further, AVGs show promise when used for learning and rehabilitation within special populations. Evidence related to other indicators was limited and inconclusive. Controlled studies show that AVGs acutely increase light- to moderate-intensity physical activity; however, the findings about if or how AVG lead to increases in habitual physical activity or decreases in sedentary behaviour are less clear. Although AVGs may elicit some health benefits in special populations, there is not sufficient evidence to recommend AVGs as a means of increasing daily physical activity.

To review associations between the family environment and young people's fruit and vegetable consumption. A systematic review. Published English-language (n 60) papers were identified using electronic databases and manual searches of personal files and reference lists. Observational research reporting a measure of fruit/vegetable intake for children (aged 6-11 years) and/or adolescents (aged 12-18 years) and at least one potential family correlate of dietary intake was included. Parental modelling and parental intake were consistently and positively associated with children's fruit and fruit, juice and vegetable (FJV) consumption. There were also positive associations between home availability, family rules and parental encouragement and children's fruit and vegetable consumption. Parental intake was positively associated with adolescents' fruit and vegetable consumption. There were also positive associations between parental occupational status and adolescent fruit consumption and between parental education and adolescents' FJV consumption. Our findings highlight the importance of targeting the family environment for the promotion of healthy eating behaviours among children and adolescents. Future interventions should encourage parents to be positive role models by targeting parental intake and to create a supportive home environment through increased encouragement and availability of fruits and vegetables and employing rules to govern eating behaviours. For adolescents, indicators of family circumstances (e.g. parental education) should be used to identify target groups for interventions aimed at promoting healthy eating.