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Does dog acquisition improve physical activity, sedentary behaviour and biological markers of cardiometabolic health? Results from a three-arm controlled study.

ABSTRACT: Objectives:Dog ownership has been associated with improved cardiometabolic risk factors, including physical activity. Most of the evidence originates from cross-sectional studies or populations with established disease. This study investigated changes in physical activity and other cardiometabolic risk factors following dog acquisition in a sample of 71 community-dwelling adults. Methods:Participants self-allocated to three groups: 17 individuals acquired a dog within 1?month of baseline (dog acquisition), 29 delayed dog acquisition until study completion (lagged control) and 25 had no interest in dog acquisition (community control). Self-reported and thigh-worn accelerometer-based physical activity patterns, systolic and diastolic blood pressures, resting heart rate and VO2max were measured three times: baseline, 3?months and 8?months. Data were analysed using repeated measures analysis of covariance with owner age, season, sex and education included as covariates. Post hoc between-group tests were performed where there were significant overall effects (p<0.05). Results:We found significant effects in mean daily steps (F(4,64)=3.02, p=0.02) and sit-to-stand transitions (F(4,66)=3.49, p=0.01). The dog acquisition group performed an additional 2589 steps (p=0.004) and 8.2 sit-to-stand transitions (p=0.03) per day at 3?months, although these effects were not maintained at 8?months. We found a significant effect in self-reported weekly walking duration (F(4,130)=2.84, p=0.03) among the lagged control group with an 80?min increase between 3?and 8?months (p=0.04). Other cardiometabolic risk factors were unchanged following dog acquisition. Conclusion:Our study provides encouraging results that suggest a positive influence of dog acquisition on physical activity in the short term but larger and more generalisable controlled studies are needed. Trial registration number:ACTRN12617000967381.

SUBMITTER: Powell L

PROVIDER: S-EPMC7254141 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Does dog acquisition improve physical activity, sedentary behaviour and biological markers of cardiometabolic health? Results from a three-arm controlled study.

Powell Lauren L Edwards Kate M KM Bauman Adrian A McGreevy Paul P Podberscek Anthony A Neilly Brendon B Sherrington Catherine C Stamatakis Emmanuel E

BMJ open sport & exercise medicine 20200408 1

<h4>Objectives</h4>Dog ownership has been associated with improved cardiometabolic risk factors, including physical activity. Most of the evidence originates from cross-sectional studies or populations with established disease. This study investigated changes in physical activity and other cardiometabolic risk factors following dog acquisition in a sample of 71 community-dwelling adults.<h4>Methods</h4>Participants self-allocated to three groups: 17 individuals acquired a dog within 1 month of b ...[more]

PMID: 32518673

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Project description:ObjectiveThe aim of this study was to examine the associations between sedentary behavior and different intensities of physical activity with cardiometabolic risk, and to analyze the simultaneous effect of excess sedentary behavior and recommended levels of physical activity on cardiometabolic risk markers in older adults.MethodsWe conducted a population-based cross-sectional study on a sample of older adults (60+) living in Florianopolis, Brazil. The objectively measured predictors were sedentary time, light physical activity and moderate to vigorous physical activity, and the outcomes were markers of cardiometabolic risk. Data were considered valid when the participant had used the accelerometer for at least four days per week.ResultsThe sample included 425 older adults (59.8% women), with a mean age of 73.9 years (95%CI: 73.5-74.4). Sedentary behavior was associated with lower systolic blood pressure levels (? = -0.03; 95%CI: -0.05; -0.01) and lower HDL cholesterol (? = -0.02; 95%CI: -0.02; -0.01). Light physical activity was not associated with any cardiovascular risk markers after adjustment. Each minute spent in moderate to vigorous physical activity was associated with lower waist circumference (? = -0.15; 95%CI: -0.24; -0.05), systolic blood pressure (? = -0.18; 95%CI: -0.32; -0.04) and plasma glucose (? = -0.18; 95%CI: -0.33;-0.02), and with higher HDL cholesterol (? = 0.10; 95%CI: 0.01; 0.18). Moreover, physically inactive and sedentary individuals had a greater mean waist circumference and lower HDL cholesterol than physically active and non-sedentary subjects.ConclusionThe results suggest that moderate to vigorous physical activity have a positive impact on cardiometabolic risk markers in older adults. Light physical activity does not appear to have a beneficial effect on the cardiometabolic markers, and despite the benefits provided by the different intensities of physical activity, the simultaneous presence of sedentary behavior and low physical activity level was associated with poor cardiometabolic risk markers.

Project description:BackgroundSmartphone apps are increasingly used to deliver physical activity and sedentary behaviour interventions for people with cardiovascular disease. However, the active components of these interventions which aim to change behaviours are unclear.AimsTo identify behaviour change techniques used in smartphone app interventions for improving physical activity and sedentary behaviour in people with cardiovascular disease. Secondly, to investigate the association of the identified techniques on improving these behaviours.MethodsSix databases (Medline, CINAHL Plus, Cochrane Library, SCOPUS, Sports Discus, EMBASE) were searched from 2007 to October 2020. Eligible studies used a smartphone app intervention for people with cardiovascular disease and reported a physical activity and/or sedentary behaviour outcome. The behaviour change techniques used within the apps for physical activity and/or sedentary behaviour were coded using the Behaviour Change Technique Taxonomy (v1). The association of behaviour change techniques on physical activity outcomes were explored through meta-regression.ResultsForty behaviour change techniques were identified across the 19 included app-based interventions. Only two studies reported the behaviour change techniques used to target sedentary behaviour change. The most frequently used techniques for sedentary behaviour and physical activity were habit reversal and self-monitoring of behaviour respectively. In univariable analyses, action planning (β =0.42, 90%CrI 0.07-0.78) and graded tasks (β =0.33, 90%CrI -0.04-0.67) each had medium positive associations with increasing physical activity. Participants in interventions that used either self-monitoring outcome(s) of behaviour (i.e. outcomes other than physical activity) (β = - 0.47, 90%CrI -0.79--0.16), biofeedback (β = - 0.47, 90%CrI -0.81--0.15) and information about health consequences (β = - 0.42, 90%CrI -0.74--0.07) as behaviour change techniques, appeared to do less physical activity. In the multivariable model, these predictors were not clearly removed from zero.ConclusionThe behaviour change techniques action planning and graded tasks are good candidates for causal testing in future experimental smartphone app designs.

Project description:BACKGROUND:With approximately 8 hours of one's waking day spent at work, occupational tasks and environments are important influencers on an individual's physical activity (PA) and sedentary behaviours. Little research has compared device-measured physical activity, sedentary behaviour and cardiometabolic outcomes between occupational groups. OBJECTIVE:To compare device-measured movement (sedentary time [ST], light intensity physical activity [LPA], moderate-to-vigorous intensity physical activity [MVPA], and steps) across occupations. The secondary objective was to examine whether cardiometabolic and fitness outcomes differed by occupation. METHODS:Five bibliographic databases were searched to identify all studies which included working age, employed adults from high-income countries, and reported on device-measured movement within occupations. Risk of bias within and across studies was assessed. Results were synthesized using meta-analyses and narrative syntheses. RESULTS:The review includes 132 unique studies with data from 15,619 participants. Working adults spent ~ 60% of their working and waking time engaged in sedentary behaviour; a very small proportion (~ 4%) of the day included MVPA. On average, workers accumulated 8124 steps/day. Office and call center workers' steps/day were among the lowest, while those of postal delivery workers were highest. Office workers had the greatest ST and the lowest time in LPA both at work and during wakeful time. However, office workers had the greatest minutes sent in MVPA during wakeful hours. Laborers had the lowest ST and spent a significantly greater proportion of their work time in LPA and MVPA. Healthcare and protective services workers had higher levels of LPA at work compared to other occupations. Workers in driving-based occupations tended to have a higher body mass index and blood pressure. CONCLUSION:This review identifies that occupational and wakeful time PA and ST differed between occupations. Future studies are needed to assess whether patterns differ by age and sex, describe leisure-time movement and movement patterns, and the relationship with cardiometabolic health. SYSTEMATIC REVIEW REGISTRATION:PROSPERO CRD42017070448 .

Project description:BackgroundThe number of commercial apps to improve health behaviours in children is growing rapidly. While this provides opportunities for promoting health, the content and quality of apps targeting children and adolescents is largely unexplored. This review systematically evaluated the content and quality of apps to improve diet, physical activity and sedentary behaviour in children and adolescents, and examined relationships of app quality ratings with number of app features and behaviour change techniques (BCTs) used.MethodsSystematic literature searches were conducted in iTunes and Google Play stores between May-November 2016. Apps were included if they targeted children or adolescents, focused on improving diet, physical activity and/or sedentary behaviour, had a user rating of at least 4+ based on at least 20 ratings, and were available in English. App inclusion, downloading and user-testing for quality assessment and content analysis were conducted independently by two reviewers. Spearman correlations were used to examine relationships between app quality, and number of technical app features and BCTs included.ResultsTwenty-five apps were included targeting diet (n = 12), physical activity (n = 18) and sedentary behaviour (n = 7). On a 5-point Mobile App Rating Scale (MARS), overall app quality was moderate (total MARS score: 3.6). Functionality was the highest scoring domain (mean: 4.1, SD: 0.6), followed by aesthetics (mean: 3.8, SD: 0.8), and lower scoring for engagement (mean: 3.6, SD: 0.7) and information quality (mean: 2.8, SD: 0.8). On average, 6 BCTs were identified per app (range: 1-14); the most frequently used BCTs were providing 'instructions' (n = 19), 'general encouragement' (n = 18), 'contingent rewards' (n = 17), and 'feedback on performance' (n = 13). App quality ratings correlated positively with numbers of technical app features (rho = 0.42, p < 0.05) and BCTs included (rho = 0.54, p < 0.01).ConclusionsPopular commercial apps to improve diet, physical activity and sedentary behaviour in children and adolescents had moderate quality overall, scored higher in terms of functionality. Most apps incorporated some BCTs and higher quality apps included more app features and BCTs. Future app development should identify factors that promote users' app engagement, be tailored to specific population groups, and be informed by health behaviour theories.

Project description:INTRODUCTION:Although studies showed that physical activity (PA) and sedentary behaviour (SB) were associated with cardiometabolic risk factors and cognitive function, both independent and combined associations among them are inconsistent. Cardiometabolic risk factors are also associated with cognitive function, but research of children is limited. Additionally, the brain level mechanisms have not been fully established. The proposed study aims to explore the associations and mechanisms of PA and SB on cognitive function and cardiometabolic risk factors in children. METHODS AND ANALYSIS:This is a school-based prospective cohort study. A total of 8324 participants of this study are primary school students aged 7-12 years old who are followed up every 2?years from January 2017 to December 2026. We used a stratified cluster random sampling to select five primary schools in Guangzhou, China. There are three phases at baseline. At phase I, we collect PA, SB and cognitive function by questionnaires and also conduct anthropometric and biochemical measurements in all participants. At phase II, PA, SB and cognitive function are measured respectively by accelerometers and cognitive tasks among participants randomly selected from four subgroups with different SB and PA levels. At phase III, event-related potentials are recorded using electroencephalogram during a cognitive task among participants randomly selected from phase II. We plan to follow-up all participants until they graduate from high school. The process applied at baseline and follow-up are approximately identical. ETHICS AND DISSEMINATION:Procedures described in this manuscript have been approved by the Ethical Review Committee for Biomedical Research, School of Public Health, Sun Yat-sen University (L2016-010). All parents or guardians of participants signed the informed consent form voluntarily before participating in the study. The findings of the study will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER:NCT03582709.

Project description:Lower levels of physical activity (PA) and sedentary behaviour (SB) have been associated with increased cardiometabolic risk among children. However, little is known about the independent and combined associations of PA and SB as well as different types of these behaviours with cardiometabolic risk in children. We therefore investigated these relationships among children.The subjects were a population sample of 468 children 6-8 years of age. PA and SB were assessed by a questionnaire administered by parents and validated by a monitor combining heart rate and accelerometry measurements. We assessed body fat percentage, waist circumference, blood glucose, serum insulin, plasma lipids and lipoproteins and blood pressure and calculated a cardiometabolic risk score using population-specific Z-scores and a formula waist circumference?+?insulin?+?glucose?+?triglycerides - HDL cholesterol?+?mean of systolic and diastolic blood pressure. We analysed data using multivariate linear regression models.Total PA was inversely associated with the cardiometabolic risk score (??=?-0.135, p?=?0.004), body fat percentage (??=?-0.155, p?<?0.001), insulin (??=?-0.099, p?=?0.034), triglycerides (??=?-0.166, p?<?0.001), VLDL triglycerides (??=?-0.230, p?<?0.001), VLDL cholesterol (??=?-0.168, p?=?0.001), LDL cholesterol (??=?-0.094, p?=?0.046) and HDL triglycerides (??=?-0.149, p?=?0.004) and directly related to HDL cholesterol (??=?0.144, p?=?0.002) adjusted for age and gender. Unstructured PA was inversely associated with the cardiometabolic risk score (??=?-0.123, p?=?0.010), body fat percentage (??=?-0.099, p?=?0.027), insulin (??=?-0.108, p?=?0.021), triglycerides (??=?-0.144, p?=?0.002), VLDL triglycerides (??=?-0.233, p?<?0.001) and VLDL cholesterol (??=?-0.199, p?<?0.001) and directly related to HDL cholesterol (??=?0.126, p?=?0.008). Watching TV and videos was directly related to the cardiometabolic risk score (??=?0.135, p?=?0.003), body fat percentage (??=?0.090, p?=?0.039), waist circumference (??=?0.097, p?=?0.033) and systolic blood pressure (??=?0.096, p?=?0.039). Resting was directly associated with the cardiometabolic risk score (??=?0.092, p?=?0.049), triglycerides (??=?0.131, p?=?0.005), VLDL triglycerides (??=?0.134, p?=?0.009), VLDL cholesterol (??=?0.147, p?=?0.004) and LDL cholesterol (??=?0.105, p?=?0.023). Other types of PA and SB had less consistent associations with cardiometabolic risk factors.The results of our study emphasise increasing total and unstructured PA and decreasing watching TV and videos and other sedentary behaviours to reduce cardiometabolic risk among children.ClinicalTrials.gov Identifier: NCT01803776.

Dataset Information

Does dog acquisition improve physical activity, sedentary behaviour and biological markers of cardiometabolic health? Results from a three-arm controlled study.

Publications

Does dog acquisition improve physical activity, sedentary behaviour and biological markers of cardiometabolic health? Results from a three-arm controlled study.

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