521 resultados para Physical activity and inactivity


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Background Physical activity in children with intellectual disabilities is a neglected area of study, which is most apparent in relation to physical activity measurement research. Although objective measures, specifically accelerometers, are widely used in research involving children with intellectual disabilities, existing research is based on measurement methods and data interpretation techniques generalised from typically developing children. However, due to physiological and biomechanical differences between these populations, questions have been raised in the existing literature on the validity of generalising data interpretation techniques from typically developing children to children with intellectual disabilities. Therefore, there is a need to conduct population-specific measurement research for children with intellectual disabilities and develop valid methods to interpret accelerometer data, which will increase our understanding of physical activity in this population. Methods Study 1: A systematic review was initially conducted to increase the knowledge base on how accelerometers were used within existing physical activity research involving children with intellectual disabilities and to identify important areas for future research. A systematic search strategy was used to identify relevant articles which used accelerometry-based monitors to quantify activity levels in ambulatory children with intellectual disabilities. Based on best practice guidelines, a novel form was developed to extract data based on 17 research components of accelerometer use. Accelerometer use in relation to best practice guidelines was calculated using percentage scores on a study-by-study and component-by-component basis. Study 2: To investigate the effect of data interpretation methods on the estimation of physical activity intensity in children with intellectual disabilities, a secondary data analysis was conducted. Nine existing sets of child-specific ActiGraph intensity cut points were applied to accelerometer data collected from 10 children with intellectual disabilities during an activity session. Four one-way repeated measures ANOVAs were used to examine differences in estimated time spent in sedentary, moderate, vigorous, and moderate to vigorous intensity activity. Post-hoc pairwise comparisons with Bonferroni adjustments were additionally used to identify where significant differences occurred. Study 3: The feasibility on a laboratory-based calibration protocol developed for typically developing children was investigated in children with intellectual disabilities. Specifically, the feasibility of activities, measurements, and recruitment was investigated. Five children with intellectual disabilities and five typically developing children participated in 14 treadmill-based and free-living activities. In addition, resting energy expenditure was measured and a treadmill-based graded exercise test was used to assess cardiorespiratory fitness. Breath-by-breath respiratory gas exchange and accelerometry were continually measured during all activities. Feasibility was assessed using observations, activity completion rates, and respiratory data. Study 4: Thirty-six children with intellectual disabilities participated in a semi-structured school-based physical activity session to calibrate accelerometry for the estimation of physical activity intensity. Participants wore a hip-mounted ActiGraph wGT3X+ accelerometer, with direct observation (SOFIT) used as the criterion measure. Receiver operating characteristic curve analyses were conducted to determine the optimal accelerometer cut points for sedentary, moderate, and vigorous intensity physical activity. Study 5: To cross-validate the calibrated cut points and compare classification accuracy with existing cut points developed in typically developing children, a sub-sample of 14 children with intellectual disabilities who participated in the school-based sessions, as described in Study 4, were included in this study. To examine the validity, classification agreement was investigated between the criterion measure of SOFIT and each set of cut points using sensitivity, specificity, total agreement, and Cohen’s kappa scores. Results Study 1: Ten full text articles were included in this review. The percentage of review criteria met ranged from 12%−47%. Various methods of accelerometer use were reported, with most use decisions not based on population-specific research. A lack of measurement research, specifically the calibration/validation of accelerometers for children with intellectual disabilities, is limiting the ability of researchers to make appropriate and valid accelerometer use decisions. Study 2: The choice of cut points had significant and clinically meaningful effects on the estimation of physical activity intensity and sedentary behaviour. For the 71-minute session, estimations for time spent in each intensity between cut points ranged from: sedentary = 9.50 (± 4.97) to 31.90 (± 6.77) minutes; moderate = 8.10 (± 4.07) to 40.40 (± 5.74) minutes; vigorous = 0.00 (± .00) to 17.40 (± 6.54) minutes; and moderate to vigorous = 8.80 (± 4.64) to 46.50 (± 6.02) minutes. Study 3: All typically developing participants and one participant with intellectual disabilities completed the protocol. No participant met the maximal criteria for the graded exercise test or attained a steady state during the resting measurements. Limitations were identified with the usability of respiratory gas exchange equipment and the validity of measurements. The school-based recruitment strategy was not effective, with a participation rate of 6%. Therefore, a laboratory-based calibration protocol was not feasible for children with intellectual disabilities. Study 4: The optimal vertical axis cut points (cpm) were ≤ 507 (sedentary), 1008−2300 (moderate), and ≥ 2301 (vigorous). Sensitivity scores ranged from 81−88%, specificity 81−85%, and AUC .87−.94. The optimal vector magnitude cut points (cpm) were ≤ 1863 (sedentary), ≥ 2610 (moderate) and ≥ 4215 (vigorous). Sensitivity scores ranged from 80−86%, specificity 77−82%, and AUC .86−.92. Therefore, the vertical axis cut points provide a higher level of accuracy in comparison to the vector magnitude cut points. Study 5: Substantial to excellent classification agreement was found for the calibrated cut points. The calibrated sedentary cut point (ĸ =.66) provided comparable classification agreement with existing cut points (ĸ =.55−.67). However, the existing moderate and vigorous cut points demonstrated low sensitivity (0.33−33.33% and 1.33−53.00%, respectively) and disproportionately high specificity (75.44−.98.12% and 94.61−100.00%, respectively), indicating that cut points developed in typically developing children are too high to accurately classify physical activity intensity in children with intellectual disabilities. Conclusions The studies reported in this thesis are the first to calibrate and validate accelerometry for the estimation of physical activity intensity in children with intellectual disabilities. In comparison with typically developing children, children with intellectual disabilities require lower cut points for the classification of moderate and vigorous intensity activity. Therefore, generalising existing cut points to children with intellectual disabilities will underestimate physical activity and introduce systematic measurement error, which could be a contributing factor to the low levels of physical activity reported for children with intellectual disabilities in previous research.

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Background and Study Rationale Being physically active is a major contributor to both physical and mental health. More specifically, being physically active lowers risk of coronary heart disease, high blood pressure, stroke, metabolic syndrome (MetS), diabetes, certain cancers and depression, and increases cognitive function and wellbeing. The physiological mechanisms that occur in response to physical activity and the impact of total physical activity and sedentary behaviour on cardiometabolic health have been extensively studied. In contrast, limited data evaluating the specific effects of daily and weekly patterns of physical behaviour on cardiometabolic health exist. Additionally, no other study has examined interrelated patterns and minute-by-minute accumulation of physical behaviour throughout the day across week days in middle-aged adults. Study Aims The overarching aims of this thesis are firstly to describe patterns of behaviour throughout the day and week, and secondly to explore associations between these patterns and cardiometabolic health in a middle-aged population. The specific objectives are to: 1 Compare agreement between the International Physical Activity Questionnaire-Short Form (IPAQ-SF) and GENEActiv accelerometer-derived moderate-to-vigorous (MVPA) activity and secondly to compare their associations with a range of cardiometabolic and inflammatory markers in middle-aged adults. 2 Determine a suitable monitoring frame needed to reliably capture weekly, accelerometer-measured, activity in our population. 3 Identify groups of participants who have similar weekly patterns of physical behaviour, and determine if underlying patterns of cardiometabolic profiles exist among these groups. 4 Explore the variation of physical behaviour throughout the day to identify whether daily patterns of physical behaviour vary by cardiometabolic health. Methods All results in this thesis are based on data from a subsample of the Mitchelstown Cohort; 475 (46.1% males; mean aged 59.7±5.5 years) middle-aged Irish adults. Subjective physical activity levels were assessed using the IPAQ-SF. Participants wore the wrist GENEActiv accelerometer for 7 consecutive days. Data was collected at 100Hz and summarised into a signal magnitude vector using 60s epochs. Each time interval was categorised based on validated cut-offs. Data on cardiometabolic and inflammatory markers was collected according to standard protocol. Cardiometabolic outcomes (obesity, diabetes, hypertension and MetS) were defined according to internationally recognised definitions by World Health Organisation (WHO) and Irish Diabetes Federation (IDF). Results The results of the first chapter suggest that the IPAQ-SF lacks the sensitivity to assess patterning of activity and guideline adherence and assessing the relationship with cardiometabolic and inflammatory markers. Furthermore, GENEActiv accelerometer-derived MVPA appears to be better at detecting relationships with cardiometabolic and inflammatory markers. The second chapter examined variations in day-to-day physical behaviour levels between- and within-subjects. The main findings were that Sunday differed from all other days in the week for sedentary behaviour and light activity and that a large within-subject variation across days of the week for vigorous activity exists. Our data indicate that six days of monitoring, four weekdays plus Saturday and Sunday, are required to reliably estimate weekly habitual activity in all activity intensities. In the next chapter, latent profile analysis of weekly, interrelated patterns of physical behaviour identified four distinct physical behaviour patterns; Sedentary Group (15.9%), Sedentary; Lower Activity Group (28%), Sedentary; Higher Activity Group (44.2%) and a Physically Active Group (11.9%). Overall the Sedentary Group had poorer outcomes, characterised by unfavourable cardiometabolic and inflammatory profiles. The remaining classes were characterised by healthier cardiometabolic profiles with lower sedentary behaviour levels. The final chapter, which aimed to compare daily cumulative patterns of minute-by-minute physical behaviour intensities across those with and without MetS, revealed significant differences in weekday and weekend day MVPA. In particular, those with MetS start accumulating MVPA later in the day and for a shorted day period. Conclusion In conclusion, the results of this thesis add to the evidence base regards an optimal monitoring period for physical behaviour measurement to accurately capture weekly physical behaviour patterns. In addition, the results highlight whether weekly and daily distribution of activity is associated with cardiometabolic health and inflammatory profiles. The key findings of this thesis demonstrate the importance of daily and weekly physical behaviour patterning of activity intensity in the context of cardiometabolic health risk. In addition, these findings highlight the importance of using physical behaviour patterns of free-living adults observed in a population-based study to inform and aid health promotion activity programmes and primary care prevention and treatment strategies and development of future tailored physical activity based interventions.

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Aim To further elucidate the relationship between physical activity and several risk factors for development of diabetes (glucose, C-peptide and obesity) over time. Methods A prospective longitudinal study where physical activity was measured on 199 children from Kalmar and Linköping at age 8, and the same 107 children from Linköping again at age 12. Anthropometric data was collected and blood was analyzed for C-peptide and f-glucose. The children in the study were representative for the general Swedish child population, and on an average lean. Results High physical activity was related to lower C-peptide at age 8 and 12. This correlation was especially pronounced in boys, who also were more physically active than girls at both time points. The association seen at 8 years of age was similar at age 12 in most children. Children with higher BMI Z-Score had a higher fasting C-peptide (age 12) but linear regression showed that children with more steps per day were less likely to have a higher fasting C-peptide irrespective of BMI. Longitudinal follow-up showed that a decrease in physical activity increased insulin resistance and β-cell load. Conclusions Already in young children, physical activity improves insulin sensitivity and decreases the need of C-peptide over time. This seems to become even more pronounced with increasing age when children are followed longitudinally. Low physical activity increases the load on insulin producing β-cells, might increase the risk for both type 1- and 2 diabetes.

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Background: This article describes the procedures and development of the rst Portuguese Report Card on Physical Activity in Children and Adolescents. Methods: Comprehensive searches for data related to indicators of physical activity (PA) were completed by a committee of physical activity and sports specialists. Grades were assigned to each indicator consistent with the process and methodology outlined by the Active Healthy Kids Canada Report Card model. Results: Nine indicators of PA were graded. The following grades were assigned: Overall Physical Activity Levels, D; Organized Sport Participation, B; Active Play, D; Active Transportation, C; Sedentary Behaviors, D; Family and Peers, C; Schools, B; Community and the Built Environment, D; and Government, C. Conclusions: Portuguese children and adolescents do not reach suf cient physical activity levels and spend larger amounts of time spent in sedentary behaviors compared with recommendations. Effective policies of PA promotion and implementation are needed in different domains of young people’s daily lives.

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Background: This article describes the procedures and development of the first Portuguese Report Card on Physical Activity in Children and Adolescents. Methods: Comprehensive searches for data related to indicators of physical activity (PA) were completed by a committee of physical activity and sports specialists. Grades were assigned to each indicator consistent with the process and methodology outlined by the Active Healthy Kids Canada Report Card model. Results: Nine indicators of PA were graded. The following grades were assigned: Overall Physical Activity Levels, D; Organized Sport Participation, B; Active Play, D; Active Transportation, C; Sedentary Behaviors, D; Family and Peers, C; Schools, B; Community and the Built Environment, D; and Government, C. Conclusions: Portuguese children and adolescents do not reach sufficient physical activity levels and spend larger amounts of time spent in sedentary behaviors compared with recommendations. Effective policies of PA promotion and implementation are needed in different domains of young people’s daily lives.

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Type II diabetes mellitus is a highly prevalent disease among the adult Brazilian population, and one that can be controlled by interventions such as physical activity, among others. The aim of this randomized controlled study was to evaluate the impact of a traditional motivational strategy, associated with the activation of intention theory, on adherence to physical activity in patients with type II, diabetes mellitus who are part of the Unified Health System (SUS). Participants were divided into a control group (CG) and an intervention group (IG). In both groups, the traditional motivational strategy was applied, but the activation of intention strategy was only applied to the IG Group. After a two-month follow-up, statistically significant differences were verified between the groups, related to the practice of walking (p = 0.0050), number of days per week (p = 0.0076), minutes per day (p = 0.0050) and minutes walking per week (p = 0.0015). At the end of the intervention, statistically significant differences in abdominal circumference (p = 0.0048) between the groups were observed. The conclusion drawn is that the activation of intention strategy had greater impact on adherence to physical activity and reduction in abdominal circumference in type II diabetics, than traditional motivational strategy.

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Background: Determinants of public healthcare expenditures in type 2 diabetics are not well investigated in developing nations and, therefore, it is not clear if higher physical activity decreases healthcare costs. The purpose of this study was to analyze the relationship between physical activity and the expenditures in public healthcare on type 2 diabetes mellitus treatment. Methods: Cross-sectional study carried out in Brazil. A total of 121 type 2 diabetics attended to in two Basic Healthcare Units were evaluated. Public healthcare expenditures in the last year were estimated using a specific standard table. Also evaluated were: socio-demographic variables; chronological age; exogenous insulin use; smoking habits; fasting glucose test; diabetic neuropathy and anthropometric measures. Habitual physical activity was assessed by questionnaire. Results: Age (r = 0.20; p = 0.023), body mass index (r = 0.33; p = 0.001) and waist-to-hip ratio (r = 0.20; p = 0.025) were positively related to expenditures on medication for the treatment of diseases other than diabetes. Insulin use was associated with increased expenditures. Higher physical activity was associated with lower expenditure, provided medication for treatment of diseases other than diabetes (OR = 0.19; p = 0.007) and medical consultations (OR = 0.26; p = 0.029). Conclusions: Type 2 diabetics with higher enrollment in physical activity presented consistently lower healthcare expenditures for the public healthcare system.

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Endothelial dysfunction is an early key event of atherogenesis. Both fitness level and exercise intervention have been shown to positively influence endothelial function. In a cross-sectional study of 47 children, the relationship between habitual physical activity and flow-mediated dilation (FMD) of the brachial artery was explored. Habitual physical activity levels (PALs) were assessed using a validated stable isotope technique, and FMD of the brachial artery was measured via high-resolution ultrasound. The results showed that habitual physical activity significantly correlated with FMD (r=0.39, P=0.007), and remained the most influential variable on dilation in multivariate analysis. Although both fitness level and exercise intervention have previously been shown to positively influence FMD, this is the first time that a relationship with normal PALs has been investigated, especially, at such a young age. These data support the concept that physical activity exerts its protective effect on cardiovascular health via the endothelium and add further emphasis to the importance of physical activity in childhood.

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Introduction: This paper reviews studies of physical activity interventions in health care settings to determine effects on physical activity and/or fitness and characteristics of successful interventions. Methods: Studies testing interventions to promote physical activity in health care settings for primary prevention (patients without disease) and secondary prevention (patients with cardiovascular disease [CVD]) were identified by computerized search methods and reference lists of reviews and articles. Inclusion criteria included assignment to intervention and control groups, physical activity or cardiorespiratory fitness outcome measures, and, for the secondary prevention studies, measurement 12 or more months after randomization. The number of studies with statistically significant effects was determined overall as well as for studies testing interventions with various characteristics. Results: Twelve studies of primary prevention were identified, seven of which were randomized. Three of four randomized studies with short-term measurement (4 weeks to 3 months after randomization), and two of five randomized studies with long-term measurement (6 months after randomization) achieved significant effects on physical activity. Twenty-four randomized studies of CVD secondary prevention were identified; 13 achieved significant effects on activity and/or fitness at twelve or more months. Studies with measurement at two time points showed decaying effects over time, particularly if the intervention were discontinued. Successful interventions contained multiple contacts, behavioral approaches, supervised exercise, provision of equipment, and/or continuing intervention. Many studies had methodologic problems such as low follow-up rates. Conclusion: Interventions in health care settings can increase physical activity for both primary and secondary prevention. Long-term effects are more likely with continuing intervention and multiple intervention components such as supervised exercise, provision of equipment, and behavioral approaches. Recommendations for additional research are given.

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To investigate the influence of physical activity on bone mineral accrual during the adolescent years, we analyzed 6 years of data from 53 girls and 60 boys. Physical activity, dietary intakes, and anthropometry were measured every 6 months and dual-energy X-ray absorptiometry scans of the total body (TB), lumbar spine (LS), and proximal femur (Hologic 2000, array mode) were collected annually. Distance and velocity curves for height and bone mineral content (BMC) were fitted for each child at several skeletal sites using a cubic spline procedure, from which ages at peak height velocity (PHV) and peak BMC velocity (PBMCV) were identified. A mean age- and gender-specific standardized activity (Z) score was calculated for each subject based on multiple yearly activity assessments collected up until age of PHV. This score was used to identify active (top quartile), average (middle 2 quartiles), or inactive (bottom quartile) groups. Two-way analysis of covariance, with height and weight at PHV controlled for, demonstrated significant physical activity and gender main effects (but no interaction) for PBMCV, for BMC accrued for 2 years around peak velocity, and for BMC at 1 year post-PBMCV for the TB and femoral neck and for physical activity but not gender at the LS (all p < 0.05). Controlling for maturational and size differences between groups, we noted a 9% and 17% greater TB BMC for active boys and girls, respectively, over their inactive peers 1 year after the age of PBMCV. We also estimated that, on average, 26% of adult TB bone mineral was accrued during the 2 years around PBMCV.

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Objective: To test a conceptual model linking parental physical activity orientations, parental support for physical activity, and children's self-efficacy perceptions with physical activity participation. Participants and Setting: The sample consisted of 380 students in grades 7 through 12 (mean age, 14.0 +/- 1.6 years) and their parents. Data collection took place during the fall of 1996. Main Outcome Measures: Parents completed a questionnaire assessing their physical activity habits, enjoyment of physical activity, beliefs regarding the importance of physical activity, and supportive behaviors for their child's physical activity. Students completed a 46-item inventory assessing physical activity during the previous 7 days and a 5-item physical activity self-efficacy scale. The model was tested via observed variable path analysis using structural equation modeling techniques (AMOS 4.0). Results: An initial model, in which parent physical activity orientations predicted child physical activity via parental support and child self-efficacy, did not provide an acceptable fit to the data. Inclusion of a direct path from parental support to child physical activity and deletion of a nonsignificant path from parental physical activity to child physical activity significantly improved model fit. Standardized path coefficients for the revised model ranged from 0.17 to 0.24, and all were significant at the p < 0.0001 level. Conclusions: Parental support was an important correlate of youth physical activity, acting directly or indirectly through its influence on self-efficacy. Physical activity interventions targeted at youth should include and evaluate the efficacy of individual-level and community-level strategies to increase parents' capacity to provide instrumental and motivational support for their children's physical activity.

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The Institute of Public Health in Ireland recently hosted a seminar on physical activity. The seminar presentations were: Ms Teresa Lavin, IPH - Physical activity and the built environment in Ireland Prof James Sallis, Professor of Psychology at San Diego State University and Director of Active Living Research - Translating evidence from physical activity research into practice.

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‘Everybody active, every day’ is a national, evidence-based approach to support all sectors to embed physical activity into the fabric of daily life and make it an easy, cost-effective and ‘normal’ choice in every community in England.PHE has co-produced the framework with over 1,000 national and local leaders in physical activity and is calling for action from providers and commissioners in: health, social care, transportation, planning, education, sport and leisure, culture, the voluntary and community sector, as well as public and private employers.To make active lifestyles a reality for all, the framework’s 4 areas for action will:change the social ‘norm’ to make physical activity the expectationdevelop expertise and leadership within professionals and volunteerscreate environments to support active livesidentify and up-scale successful programmes nationwide‘Everybody active, every day’ is part of the cross-government ‘Moving More, Living More’ campaign for a more active nation as part of the 2012 Olympic and Paralympic Games legacy.

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OBJECTIVE: We sought to examine the relation between recommended levels of physical activity during pregnancy and pregnancy outcomes. STUDY DESIGN: We conducted an observational study with energy expenditure, aerobic fitness, and sleeping heart rate measured in 44 healthy women in late pregnancy. Medical records were examined for pregnancy outcome. RESULTS: Active women, who engaged in > or = 30 minutes of moderate physical activity per day, had significantly better fitness and lower sleeping heart rate compared to the inactive. Duration of second stage of labor was 88 and 146 minutes in the active vs inactive women, respectively (P = .05). Crude odds ratio of operative delivery in the inactive vs the active was 3.7 (95% confidence interval, 0.87-16.08). Birthweight, maternal weight gain, and parity adjusted odds ratio was 7.6 (95% confidence interval, 1.23-45.8). Neonatal condition and other obstetric outcomes were similar between groups. CONCLUSION: Active women have better aerobic fitness as compared to inactive women. The risk for operative delivery is lower in active women compared to inactive, when controlled for birthweight, maternal weight gain, and parity. Further studies with larger sample size are required to confirm the association between physical activity and pregnancy outcomes.

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OBJECTIVES: Exercise combined with nicotine therapy may help smoking cessation and minimise weight gain after quitting. Low participation in vigorous-intensity physical activity programmes precludes their population-wide applicability. In a randomised controlled trial, we tested whether a population-based moderate-intensity physical activity programme increases quit rates among sedentary smokers receiving nicotine therapy. METHODS: Participants (n=481; 57% male; mean age, 42.2 years (SD 10.1); mean cigarette consumption, 27 (SD 10.2) per day) were offered a nine-week smoking cessation programme consisting of a weekly 15-minute counselling session and the prescription of nicotine replacement therapy. In addition, participants in the physical activity group (n=229) also took part in a programme of moderate-intensity physical activity implemented at the national level, and offering nine weekly 60-minute sessions of physical activity. To ensure equal contact conditions, participants in the control group (n=252) attended weekly 60-minute health behaviour education sessions unrelated to physical activity. The primary outcome was continuous CO-verified smoking abstinence rates at 1-year follow-up. RESULTS: Continuous smoking abstinence rates were high and similar in the physical activity group and the control group at the end of the intervention (47% versus 46%, p=0.81) and at 1-year follow-up (27% versus 29%, p=0.71). The mean weight gain after one year was 4.4 kg and 6.2 kg among sustained quitters of the physical activity and control groups, respectively (p=0.06). CONCLUSION: Participation in a population-based moderate-intensity physical activity programme for 9 weeks in addition to a comprehensive smoking cessation programme did not significantly increase smoking cessation rates. A non-significant reduction in weight gain was observed among participants who quit smoking in the physical activity group. TRIAL REGISTRATION: ClinicalTrials.gov; US National Institutes for Health (available online at http://clinicaltrials.gov/; CLINICAL TRIAL REGISTRATION NUMBER: NCT00521391).