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      Clustering of risk-related modifiable behaviours and their association with overweight and obesity among a large sample of youth in the COMPASS study

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          Abstract

          Background

          Canadian youth exhibit a number of risky behaviours, some of which are associated with overweight and obesity. The purpose of this study was to examine the prevalence of 15 modifiable risk behaviours in a large sample of Canadian youth, to identify underlying subgroups based on patterns of health behaviours, and to examine the association between identified subgroups and overweight/obesity.

          Methods

          Data from 18,587 grades 9–12 students in Year 1 (2012–13) of the COMPASS study and latent class analysis were used to identify patterns and clustering among 15 health behaviours (e.g., physical inactivity, sedentary behaviour, unhealthy eating, substance use). A logistic regression model examined the associations between these clusters and overweight/obesity status.

          Results

          Four distinct classes were identified: traditional school athletes, inactive screenagers, health conscious, and moderately active substance users. Each behavioural cluster demonstrated a distinct pattern of behaviours, some with a greater number of risk factors than others. Traditional school athletes (odds ratio (OR) 1.15, 95% CI 1.03–1.29), inactive screenagers (OR 1.33; 1.19–1.48), and moderately active substance users (OR 1.27; 1.14–1.43) were all significantly more likely to be overweight/obese compared to the health conscious group.

          Conclusions

          Four distinct subpopulations of youth were identified based on their patterns of health and risk behaviours. The three clusters demonstrating poorer health behaviour were all at an increased risk of being overweight/obese compared to their somewhat healthier peers. Obesity-related public health interventions and health promotion efforts might be more effective if consideration is given to population segments with certain behavioural patterns, targeting subgroups at greatest risk of overweight or obesity.

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          Most cited references35

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          Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.

          In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013. We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down. Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene. Bill & Melinda Gates Foundation. Copyright © 2014 Elsevier Ltd. All rights reserved.
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            A review of correlates of physical activity of children and adolescents.

            Understanding the factors that influence physical activity can aid the design of more effective interventions. Previous reviews of correlates of youth physical activity have produced conflicting results. A comprehensive review of correlates of physical activity was conducted, and semiquantitative results were summarized separately for children (ages 3-12) and adolescents (ages 13-18). The 108 studies evaluated 40 variables for children and 48 variables for adolescents. About 60% of all reported associations with physical activity were statistically significant. Variables that were consistently associated with children's physical activity were sex (male), parental overweight status, physical activity preferences, intention to be active, perceived barriers (inverse), previous physical activity, healthy diet, program/facility access, and time spent outdoors. Variables that were consistently associated with adolescents' physical activity were sex (male), ethnicity (white), age (inverse), perceived activity competence, intentions, depression (inverse), previous physical activity, community sports, sensation seeking, sedentary after school and on weekends (inverse), parent support, support from others, sibling physical activity, direct help from parents, and opportunities to exercise. These consistently related variables should be confirmed in prospective studies, and interventions to improve the modifiable variables should be developed and evaluated.
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              Further analysts of the data by akaike' s information criterion and the finite corrections

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                Author and article information

                Contributors
                rlaxer@uwaterloo.ca
                rbrownson@wustl.edu
                jdubin@uwaterloo.ca
                cooke@uwaterloo.ca
                a4chaurasia@uwaterloo.ca
                sleatherdale@uwaterloo.ca
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                21 January 2017
                21 January 2017
                2017
                : 17
                : 102
                Affiliations
                [1 ]ISNI 0000 0000 8644 1405, GRID grid.46078.3d, School of Public Health and Health Systems, , University of Waterloo, ; 200 University Avenue West, Waterloo, ON N2L3G1 Canada
                [2 ]ISNI 0000 0001 2355 7002, GRID grid.4367.6, Brown School and School of Medicine, , Washington University in St. Louis, ; Campus Box 1196, One Brookings Drive, St. Louis, MO 63130-4899 USA
                [3 ]ISNI 0000 0000 8644 1405, GRID grid.46078.3d, School of Public Health and Health Systems, Department of Statistics and Actuarial Science, , University of Waterloo, ; 200 University Avenue West, Waterloo, ON N2L3G1 Canada
                [4 ]ISNI 0000 0000 8644 1405, GRID grid.46078.3d, School of Public Health and Health Systems, Department of Sociology & Legal Studies, , University of Waterloo, ; 200 University Avenue West, Waterloo, ON N2L3G1 Canada
                Article
                4034
                10.1186/s12889-017-4034-0
                5251243
                28109270
                69b78777-c91d-470a-9f39-d08b7bb320b8
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 7 September 2016
                : 13 January 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000035, Institute of Nutrition, Metabolism and Diabetes;
                Award ID: OOP-110788
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000036, Institute of Population and Public Health;
                Award ID: MOP-114876
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Public health
                obesity,adolescent,health promotion,physical activity,risk-taking,latent class analysis,diet,behaviour patterns

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