Clustering of Physical Activity, Sedentary Behavior, and Diet Associated With Social Isolation Among Brazilian Adolescents

Clustering of Physical Activity, Sedentary Behavior, and Diet Associated With Social Isolation Among Brazilian Adolescents | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clustering of Physical Activity, Sedentary Behavior, and Diet Associated With Social Isolation Among Brazilian Adolescents THIAGO SOUSA MATIAS, Julianne Fic Alves, Gislaine Terezinha Amaral Nienov, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2378867/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Mar, 2023 Read the published version in BMC Public Health → Version 1 posted 8 You are reading this latest preprint version Abstract Backgound: Although obesogenic behaviors have been found to be related to social isolation, evidence-based person-centered approaches are lacking. This study investigated the association between clusters of obesogenic behavior – derived from a data-driven process – and social isolation among Brazilian adolescents. Methods: Data from the National Adolescent School-based Health Survey (PeNSE) 2015 Cohort were analyzed. A total of 100,794 9 th -grade students (51.3% females; 14.3 ± 0.1 years old) enrolled in 3,040 public and private high schools participated in the study. Social isolation was assessed by two outcomes (i.e., perceived loneliness and lack of close friends). A two-step cluster analysis was conducted to identify patterns of obesogenic behaviors with the input of leisure-time physical activity (PA), sitting time as a proxy of sedentary behavior (SB), and the weekly consumption of healthy and unhealthy food. Crude and adjusted binary logistic regression models were applied to evaluate the associations between the clusters of obesogenic behaviors and social isolation variables in adolescents. Results: Three clusters were identified. Adolescents in the “Health-promoting SB and diet” (32.6%; OR = 0.69; 95% CI=0.62-0.76) and “Health-promoting PA and diet” (44.9%; OR = 0.73; 95% CI = 0.67-0.79) clusters had lower odds of loneliness compared to those in the “Health-risk” cluster (22.5%). Those belonging to the “Health-promoting PA and diet” cluster were more likely to report having close friends (OR=1.19; 95% CI = 1.00-1.41) than those in the “Health-risk” cluster. Conclusion: Adolescents in clusters where positive behaviors outweighed negative ones were less likely to perceive themselves as lonely and without close connections. Healthy Lifestyle Loneliness Mental Health Health Surveys Motor Activity Figures Figure 1 1. Introduction Regular practice of physical activity (PA) and reduced time in sedentary behaviors (SB) have been positively associated with mental health in adolescence [ 1 , 2 ]. This benefit includes favoring socialization and avoiding social isolation [ 3 , 4 ]. Thus, recent evidence has shown that both high PA and low SB are associated with lower loneliness [ 5 ]. Active adolescents can be more socially integrated [ 4 ], while having friends help them to overcome barriers associated with a less active lifestyle [ 6 ]. It is important to consider that PA and SB do not occur in isolation in adolescents’ lives. These behaviors carry synergies with other behaviors such as diet, for example, which can (synergically speaking) influence socialization [ 6 ]. This influence might depend on the extention of adolescents' lifestyle have more favorable than unfavorable behaviors coexisting [ 7 , 8 ]. These behaviors can be more or less obesogenic depending on the different profiles observed [ 3 ]. The problem that arises is that: (a) being in an obesogenic cluster can make socialization difficult, increasing social isolation [ 9 , 10 ]; and (b) clusters that combine positive and negative behaviors can still favor better socialization and psychological disposition in adolescents when compared to clusters that mostly combine risk behaviors [ 2 , 11 ]. Few studies have examined the relationship between clusters of obesogenic behaviors and psychosocial variables, such as social isolation. However, the synergistic movements between obesogenic behaviors should be considered, as adolescents do not possess isolated virtues in their lifestyle. There is an interaction between essentially positive or essentially negative behaviors, which can influence health in many ways. Therefore, this study investigates the association between clusters of obesogenic behaviors and social isolation in a population-based study of Brazilian adolescents. 2. Methods 2.1. Study design and participants A cross-sectional study using data from the National Adolescent School-based Health Survey (PeNSE) was conducted in 2015 by the Brazilian Institute of Geographic and Statistics and the Ministry of Health of Brazil. PeNSE relates to World Health Organization recommendations for health surveys among students. The study investigates adolescents’ health and lifestyle behaviors among a nationally-representative sample of students enrolled in the 9th grade of elementary school from public and private schools. PeNSE sampling process was planned to represent all geographical areas of Brazil. A total of 102,301 students among 3,040 schools were initially assessed; 229 students declined to participate or did not report their age or sex. The sampling strategy included geographical stratification and the multi-stage selection that can be seen elsewhere (Oliveira et al., 2017). Ethical approval was obtained, and the participation of all subjects was approved by the National Committee of Ethics in Research number 1.006.467/2015. The present survey is in its third edition. The questionnaire used for data collection is based on the Global School-Based Student Health Survey and Youth Risk Behavior Surveillance System and has been tested and adjusted [ 12 ]. 2.2. Clusters Formation To cluster formation, leisure-time physical activity (PA), sedentary behavior (SB), and diet were analyzed. Students’ PA was assessed using the question: In the past 7 days, without considering physical education class, how many days did you practice some physical activity like sports, dance, gym exercises, combat sports or other activity? The answers ranged from none to seven days in a week. SB was reasonable during the sitting time using the question: In a regular day, how much time do you spend watching television, playing video games, talking with friends or other sitting activities? The response options ranged from one to nine hour a day. Diet was assessed as continuous scores related to the weekly consumption of healthy (green salads or vegetables and fruits) and unhealthy food (deep-fried empanadas, candies, soda, fast foods, and ultra-processed food). Details on measurement, clusters formation procedure, and description have been provided elsewhere [ 8 ]. Briefly, a two-step cluster analysis was employed using the log-likelihood as the distance measure (to account for the congruency between clusters). Leisure-time PA, SB, and both healthy and unhealthy diet scores were independently included as inputs in the model. The low Schwarz’s Bayesian Criterion (BIC), the high ratio of distance measures, and the high ratio of BIC changes were used to determine the number of clusters. The theoretical assumption regarding the acceptability of the profiles was taken into account. The analysis was replicated among younger and older adolescents to check clusters’ acceptability [ 8 ]. Adolescents that have incomplete or missing data for PA, SB, or diet were not analyzed (n = 1,507, < 1.5% of the total sample). 100,794 adolescent students were distributed into three different profiles: The “Health-promoting SB and diet,” comprising 32.6% of the sample; the “Health-promoting PA and diet” (44.9% of the sample), the “Health-risk” cluster containing 22.5% of the sample. The two health-promoting clusters are those where positive behaviors prevail over the negative ones, and the health-risk cluster combines a negative profile for all variables (see Fig. 1 ). A detailed description of the clusters can be seen elsewhere [ 8 ]. 2.3. Social isolation Participants were asked about two aspects: (a) “In the past 12 months, how often have you felt alone”. A five-point Likert scale ranging from never to always was the response option. Those who responded always or most of the time were considered lonely; (b) “How many close friends do you have?”. The option of response was zero/one/two/three or more. Those who responded “zero” were considered to having no close friends. 2.4. Covariates The covariates were: sex, skin color, age, live with mother, live with father, mother's schooling, residents of the house, cigarette smoking, alcohol consumption, drugs, physically aggression by an adult at home, involved in a fight with a firearm, involved in a fight with a melee weapon, suffered physical aggression, got involved in a fight, body satisfaction, health perception, type of school. 2.5. Statistical analysis The participants’ characteristics were described using absolute and relative frequency with 95% confidence intervals (95%CI) for nominal variables and means with standard deviations (SD) for numerical variables. Crude and adjusted binary logistic regression models were applied to evaluate the associations between exposure (the clusters) and social isolation variables (perceived loneliness and having close friends). For each model, a set of covariates was selected based on empirical and theoretical evidence (see tables notes); Bivariate analyses were performed to evaluate the association of each covariate and both outcomes of social isolation. Significant predictors at p-value < .2 were retained and included in the adjusted models. The “Health-risk” cluster was the reference category in the regression models. The results were expressed in odds ratios (OR) and the respective (95% CI). All inferential procedures included the survey design and weighting. Data were analyzed using STATA 15 software (Stata Inc., College Station, TX, USA), except for cluster procedures. The significance level was defined as p < .05. 3. Results Table 1 shows the characteristics of the participants. A total of 100,794 students with a mean age of 14.28 years old (SD = 0.013) were observed. Regarding social isolation, 16.39% of the adolescents experienced loneliness (95% CI = 15.93-16.85) and 4.29% reported not having any close friends (95% CI = 4.05-4.54). Other individual aspects such as behavioral characteristics, victimization, and health outcomes, are presented in the supplemental material. INSERT TABLE 1 NEAR HERE Table 1. Characteristics of the sample. PENSE, Brazil 2015 (n= 100,794). Variables n % 95% IC* School-level covariates Type of school Municipal 288 0.1 0.04 - 0.26 State 49,462 48.35 45.05 - 51.66 Federal 31,404 37.09 34.15 - 40.13 Private 20,918 14.46 12.53 - 16.63 Full-time school Yes 22,854 22.07 21.19 - 22.98 No 78,715 77.93 77.02 - 78.81 Boarding school Yes 3,846 4.085 3.748 - 4.451 No 97,942 95.92 95.55 - 96.25 Household-level covariates Computer at home Yes 69,822 69.56 68.51 - 70.6 No 32,144 30.44 29.4 - 31.49 Internet at home Yes 78,395 77.55 76.69 - 78.38 No 23,572 22.45 21.62 - 23.31 Household residents (mean) – 4.49 4.47 - 4,52 Sociodemographic factors Sex Male 49,290 48.72 48.09 - 49.34 Female 52,782 51.28 50.66 - 51.91 Skin Color White 33,775 36.15 35.12 - 37.18 Black 12,849 13.39 12.88 - 13.92 Yellow 4,580 4.11 3.87 - 4.36 Pardo 46,935 43.05 42.17 - 43.94 Indigenous 3,825 3.29 3.07 - 3.53 Age, mean – 14.29 14.26 - 14.31 Mother's schooling Did not studied 5,531 5.38 5.089 - 5.695 Incomplete elementary school 18,217 19.38 18.8 - 19.97 Elementary School 6,024 6.465 6.167 - 6.775 Incomplete high school 6,275 6.05 5.78 - 6.33 High school 17,903 18.01 17.47 - 18.57 Incomplete college 5,456 4.54 4.27 - 4.83 College 17,232 13.26 12.34 - 14.23 Do not know 25,183 26.9 26.25 - 27.56 Live with mother Yes 90,458 89.94 89.57 - 90.3 No 11,543 10.06 9.7 - 10.43 Live with father Yes 63,600 63.71 63.01 - 64.41 No 38,341 36.29 35.59 - 36.99 Has a cell phone Yes 88,978 87.38 86.87 - 87.87 No 13,012 12.62 12.13 - 13.13 n = absolute frequency; %=prevalence; IC95%= confidence interval 95%. Table 2 shows the association between clusters and social isolation variables among adolescents. In the adjusted analysis, adolescents in the Health-promoting SB and diet (OR = 0.69; 95% CI=0.62-0.76) and in the Health-promoting PA and diet (OR = 0.73; 95% CI = 0.67-0.79) clusters showed reduced odds of loneliness compared to those in the Health-risk cluster. Those belonging to the Health-promoting PA and diet cluster were more likely to have close friends (OR=1.19; 95% CI = 1.00-1.41) compared to those in the health-risk cluster. INSERT TABLE 2 NEAR HERE Table 2 . Associations between the clusters and the perception of loneliness and friendships among the adolescents. PeNSE, Brazil 2015. Perceived loneliness (n=98,485) Friendship (n=97,898) Crude Adjusted* Crude Adjusted** OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) Clusters Health-risk Ref Ref Ref Ref Health-promoting SB and diet 0.50 (0.46 - 0.55) 0.69 (0.62 - 0.76) 0.89 (0.76 - 1.03) 0.86 (0.74 - 1.02) Health-promoting PA and diet 0.50 (0.46 - 0.55) 0.73 (0.67 - 0.79) 1.23 (1.04 - 1.45) 1.19 (1.002 - 1.41) Notes: OR, Odds Ratio; CI, Confidence Intervals; Estimates were weighted according to the sampling design; *Adjusted for sex, skin color, age, live with mother, live with father, mother's schooling, residents of the house, cigarette smoking, alcohol consumption, drugs, physically aggression by an adult at home, involved in a fight with a firearm, involved in a fight with a melee weapon, suffered physical aggression, got involved in a fight, body satisfaction, health perception, type of school. **Adjusted for sex, skin color, age, live with mother, live with father, mother's schooling, residents of the house, cigarette smoking, drugs, physically aggression by an adult at home, involved in a fight with a firearm, involved in a fight with a melee weapon, suffered physical aggression, got involved in a fight, body satisfaction, health perception, computer at home, internet at home, full school, boarding school, have a cell phone, type of school. 4. Discussion The present study investigated the association between clusters of obesogenic behaviors and social isolation in a population-based sample of Brazilian adolescents. We observed that the likelihood of loneliness and having close friends varied across the clusters, and adolescents from both healthier groups seem to have lower odds of loneliness. The literature has shown that some psychosocial outcomes of adolescents can be influenced by obesogenic behaviors such as PA, diet, and SB [ 2 , 11 , 13 ]. In addition, there is evidence that adolescents with healthier obesogenic behavior profiles have better socialization, with lower chances of loneliness [ 5 , 9 , 10 ]. Our findings also highlight the fact that many adolescents have lifestyles defined by the coexistence of favorable and unfavorable health behaviors [ 14 ]. Thus, adolescents in clusters that include an active lifestyle seem to have more prosocial attitudes in their life, such as talking to friends and going for a walk more often [ 15 ], improving friendship quality and decreasing the chances of being socially isolated [ 4 ]. A systematic review investigating the relationship between friendship and PA analyzing cross-sectional, longitudinal, and experimental studies with adolescents in the United States showed that peers and friends play an important role in adolescents' PA levels. This association was positive in terms of peer support, presence of peers and/or friends, peer norms, friendship quality, peer acceptance and affiliation, and negative for peer victimization [ 16 ]. Despite the inverse chain to our proposed analyses, having friends helps to provide intrapersonal and interpersonal psychological support, favoring better psychological disposition for the maintenance of PA behavior during adolescence. In addition, being active favor socialization, evidencing a cyclical relationship between behaviors—socialization—behavior. Some mediators have been hypothesized to help explain our findings. For instance, increasing self-confidence and supporting greater problem-solving ability were observed in the univariate relationships between PA and social isolation [ 15 ] and between SB and social isolation [ 5 ]. We hypothesize that PA and SB may share psychosocial mediators, and one behavior “supplies” the other in maintaining more prosocial attitudes. In other words, a cluster that lacks PA but the adolescent has a reduced time in sedentary behavior can still provide some benefits and vice-versa. Furthermore, obese adolescents report more loneliness, have fewer friends, and are more bullied [ 17 ]. In this case, it is suggested that healthier clusters can favor both better results for biological outcomes, such as decreasing overweight and obesity and minimizing interpersonal and intrapersonal vulnerabilities in adolescence [ 2 ]. Some limitations can be observed in this study. First, the cross-sectional nature of the data does not allow for a causal relationship to be established between adolescents' behaviors and our selected outcomes. The causal chain of these relationships between behavior and health outcomes is well established. However, it is plausible that the observed associations are bidirectional. Although obesity seems to influence social isolation, we ask for caution when interpreting our findings, as there was no control for this variable in our adjusted analysis. Feeling lonely and having fewer friends can keep adolescents away from healthier behaviors, such as PA during leisure time. The social isolation construct is self-reported based on two indicators that may not represent the phenomenon's complexity; therefore, caution in interpreting the results is necessary. Nevertheless, the observed research problem is substantial. It has an analytical approach centered on the individual (clusters analysis); the clusters observed in this population were validated in previous research and involve a representative sample. To the authors’ knowledge this is the first study to assess the relationship between clusters of obesogenic behaviors and social isolation. In addition, this study draws attention to a less obvious association between lifestyle and health outcomes. Schools, administrators, and policymakers can look beyond obesity and realize that opportunities, attitudes, and choices (in non-particular order) about adolescent lifestyle can impact the social life and the mental health of young people. Therefore, multicomponent interventions are required, considering the synergies between lifestyle behaviors. 5. Conclusions Adolescents in clusters where health-favorable behaviors outweighed unfavorable ones were less likely to perceive themselves as lonely and without close friends. Clusters of obesogenic behaviors seem to share mediators that expose or protect adolescents not only to obesity but also to critical psychosocial outcomes for social life, such as having more friends. Declarations Acknowledgements The authors would like to thank the Ministry of Health and the Institute of Geographic and Statistics (IBGE) of Brazil who conducted the survey. Funding No funding was received. Availability of data and materials The original PeNSE data set is publicly available in: https://www.ibge.gov.br/estatisticas/sociais/educacao/9134-pesquisa-nacional-de-saude-do-escolar.html?=&t=downloads Author information Authors and Affiliations Department of Physical Education, Federal University of Santa Catarina, Florianópolis, 88040-900, Brazil. Thiago Sousa Matias, Julianne Fic Alves, Gislaine Terezinha Amaral Nienov and Marcus Vinicius Veber Lopes. Australian Catholic University, Institute for Positive Psychology and Education. Diego Itibere Cunha Vasconcellos. Contributions The study was designed and drafted by TSM, with contributions from JFA and GTAN. MVVL conducted the analysis, interpreted the results, and supported the conduction of the manuscript. TSM supported the analysis. JFA and GTAN supported analysis interpretation. DICV revised and supported the conduction of the manuscript. All authors have revised the manuscript and approved the submission. All authors have agreed to be personally accountable for the author's contributions and ensured that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. The author(s) read and approved the final manuscript. Corresponding author Correspondence to Thiago Sousa Matias. Ethics declarations Ethics approval and consent to participate This study was approved by the National Commission on Research Ethics (Comissão Nacional de Ética em Pesquisa – CONEP), n° 1.006.467/2015. Informed consent was obtained from all participants thought an electronic consent form. The informed consent form was placed on the front page of the questionnaire and participant’s agreement was obtained prior to data collection. The right to refuse to participate was guaranteed. The consent to participate was not obtained from the parents/guardians. According to PeNSE report, the Brazilian legislation concerning the protection of the child and adolescent (Brazilian Statute of the Child and the Adolescent - Law n° 8069, 13 July 1990) allows the adolescent to take initiatives, such as responding to a questionnaire that does not represent a risk to their health and aims to promote health protection policies [12]. The consent procedure was approved by the National Commission on Research Ethics. Consent for publication Not applicable. Competing interests TSM, JFA, GTAN, MVVL and DICV declare no competing interests. References Biddle SJH, Ciaccioni S, Thomas G, Vergeer I. Physical activity and mental health in children and adolescents: An updated review of reviews and an analysis of causality. Psychol Sport Exerc. 2019;42:146–55. Matias TS, Lopes MVV, de Mello GT, Silva KS. Clustering of obesogenic behaviors and association with body image among Brazilian adolescents in the national school-based health survey (PeNSE 2015). Prev Med Rep. 2019;16:101000. Boone-Heinonen J, Gordon-Larsen P, Adair LS. Obesogenic Clusters: Multidimensional Adolescent Obesity-related Behaviors in the U.S. ann behav med. 2008;36:217–30. Yi X, Liu Z, Qiao W, Xie X, Yi N, Dong X, et al. Clustering effects of health risk behavior on mental health and physical activity in Chinese adolescents. Health Qual Life Outcomes. 2020;18:211. Werneck AO, Collings PJ, Barboza LL, Stubbs B, Silva DR. Associations of sedentary behaviors and physical activity with social isolation in 100,839 school students: The Brazilian Scholar Health Survey. Gen Hosp Psychiatry. 2019;59:7–13. Hoare E, Skouteris H, Fuller-Tyszkiewicz M, Millar L, Allender S. Associations between obesogenic risk factors and depression among adolescents: a systematic review: Obesogenic risk and depression: a review. Obes Rev. 2014;15:40–51. Leech RM, McNaughton SA, Timperio A. The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review. Int J Behav Nutr Phys Act. 2014;11:4. Matias TS, Silva KS, Silva JA, da, Mello GT de, Salmon J. Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school - based health survey (PeNSE 2015). BMC Public Health. 2018;18:1283. Hoare E, Milton K, Foster C, Allender S. The associations between sedentary behaviour and mental health among adolescents: a systematic review. Int J Behav Nutr Phys Act. 2016;13:108. Padial-Ruz R, González-Campos G, Zurita-Ortega F, Puga-González ME. Associations between Feelings of Loneliness and Attitudes towards Physical Education in Contemporary Adolescents According to Sex, and Physical Activity Engagement. IJERPH. 2020;17:5525. Iannotti RJ, Wang J. Patterns of Physical Activity, Sedentary Behavior, and Diet in U.S. Adolescents. J Adolesc Health. 2013;53:280–6. Instituto Brasileiro de. Geografia e Estatística I. Pesquisa Nacional de Saúde do Escolar – 2015. 2016. Liberali R, Del Castanhel F, Kupek E, Assis MAA de. Latent Class Analysis of Lifestyle Risk Factors and Association with Overweight and/or Obesity in Children and Adolescents. Syst Rev Child Obes. 2021;17:2–15. Mello GT de, Lopes MVV, Minatto G, Costa RM da, Matias TS, Guerra PH, et al. Clustering of Physical Activity, Diet and Sedentary Behavior among Youth from Low-, Middle-, and High-Income Countries: A Scoping Review. IJERPH. 2021;18:10924. Ferrar K, Chang C, Li M, Olds TS. Adolescent Time Use Clusters: A Systematic Review. J Adolesc Health. 2013;52:259–70. Fitzpatrick C, Burkhalter R, Asbridge M. Adolescent media use and its association to wellbeing in a Canadian national sample. Prev Med Rep. 2019;14:100867. Waasdorp TE, Mehari K, Bradshaw CP. Obese and overweight youth: Risk for experiencing bullying victimization and internalizing symptoms. Am J Orthopsychiatry. 2018;88:483–91. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2378867","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":163162931,"identity":"8bf46ece-7835-4e1a-bd3f-4d7b5667618c","order_by":0,"name":"THIAGO SOUSA MATIAS","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIie2SPQrCMBhAvyDUpeKakoJX0FnBg7jYyal7B5FIIV6hg+gVdHFWAnHJAXSUnqDg0OLiF1BxMXUUzJte4HvkhwA4HL8IJfxhRhJoo3nWwn8lnhENAa9PnmbmiPgiGbJ0XlwTGLXXKNVK0s5i7+WJbZfwkLJQQ5wpkrLWTtKuHjd72nqwiLNAQMwV4Yzs5KxLwQu4PUlvJlnjLlW1xINl9YkICkw2igja4pLCqS45RaIPmsZbheKrCd4lWvRsSTOb5OcyGcQreUSZ9vHFpLrYEkPDB/q+fv2Hz5CydsThcDj+mjvZKkyF/DELPAAAAABJRU5ErkJggg==","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"THIAGO","middleName":"SOUSA","lastName":"MATIAS","suffix":""},{"id":163162935,"identity":"8cabc124-48e0-460b-b976-aeb167b0a78f","order_by":1,"name":"Julianne Fic Alves","email":"","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Julianne","middleName":"Fic","lastName":"Alves","suffix":""},{"id":163162938,"identity":"d1d4bf30-a94a-4dab-817f-6068f6d07abb","order_by":2,"name":"Gislaine Terezinha Amaral Nienov","email":"","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gislaine","middleName":"Terezinha Amaral","lastName":"Nienov","suffix":""},{"id":163162942,"identity":"f933aa5c-d8f3-4f53-bee6-a755e0746be9","order_by":3,"name":"Marcus Vinicius Veber Lopes","email":"","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marcus","middleName":"Vinicius Veber","lastName":"Lopes","suffix":""},{"id":163162945,"identity":"92508557-6bb6-42b0-b455-2386a7a8a985","order_by":4,"name":"Diego Itibere Cunha Vasconcellos","email":"","orcid":"","institution":"Australian Catholic University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Diego","middleName":"Itibere Cunha","lastName":"Vasconcellos","suffix":""}],"badges":[],"createdAt":"2022-12-14 17:14:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2378867/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2378867/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-023-15444-x","type":"published","date":"2023-03-25T20:07:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":31047334,"identity":"5b77a4c9-bcd6-4e64-aaeb-fcb5313099f8","added_by":"auto","created_at":"2023-01-03 18:03:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30223,"visible":true,"origin":"","legend":"\u003cp\u003ePhysical activity (PA), sedentary behavior (SB), unhealthy diet, and healthy diet in each of the three clusters. National School-Based Health Survey among ninth-grade students - PeNSE, Brazil 2015 (sample 1).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2378867/v1/6cf56c1a356152cdaa63b0f6.png"},{"id":44723416,"identity":"3951507c-bad5-408a-a3c7-fb4e1c27fdab","added_by":"auto","created_at":"2023-10-16 20:16:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":399169,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2378867/v1/2ec73c0b-7d9f-457b-8fe2-ff9deefa171c.pdf"},{"id":31047335,"identity":"b2b9de09-26d1-444d-9eec-b2e34202cf0d","added_by":"auto","created_at":"2023-01-03 18:03:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":25211,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPORTINGINFORMATION.docx","url":"https://assets-eu.researchsquare.com/files/rs-2378867/v1/5acc635bbc17bf67a2d9cf57.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eClustering of Physical Activity, Sedentary Behavior, and Diet Associated With Social Isolation Among Brazilian Adolescents\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eRegular practice of physical activity (PA) and reduced time in sedentary behaviors (SB) have been positively associated with mental health in adolescence [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This benefit includes favoring socialization and avoiding social isolation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Thus, recent evidence has shown that both high PA and low SB are associated with lower loneliness [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Active adolescents can be more socially integrated [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], while having friends help them to overcome barriers associated with a less active lifestyle [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is important to consider that PA and SB do not occur in isolation in adolescents\u0026rsquo; lives. These behaviors carry synergies with other behaviors such as diet, for example, which can (synergically speaking) influence socialization [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This influence might depend on the extention of adolescents' lifestyle have more favorable than unfavorable behaviors coexisting [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These behaviors can be more or less obesogenic depending on the different profiles observed [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe problem that arises is that: (a) being in an obesogenic cluster can make socialization difficult, increasing social isolation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]; and (b) clusters that combine positive and negative behaviors can still favor better socialization and psychological disposition in adolescents when compared to clusters that mostly combine risk behaviors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFew studies have examined the relationship between clusters of obesogenic behaviors and psychosocial variables, such as social isolation. However, the synergistic movements between obesogenic behaviors should be considered, as adolescents do not possess isolated virtues in their lifestyle. There is an interaction between essentially positive or essentially negative behaviors, which can influence health in many ways. Therefore, this study investigates the association between clusters of obesogenic behaviors and social isolation in a population-based study of Brazilian adolescents.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study design and participants\u003c/h2\u003e \u003cp\u003eA cross-sectional study using data from the National Adolescent School-based Health Survey (PeNSE) was conducted in 2015 by the Brazilian Institute of Geographic and Statistics and the Ministry of Health of Brazil. PeNSE relates to World Health Organization recommendations for health surveys among students. The study investigates adolescents\u0026rsquo; health and lifestyle behaviors among a nationally-representative sample of students enrolled in the 9th grade of elementary school from public and private schools. PeNSE sampling process was planned to represent all geographical areas of Brazil. A total of 102,301 students among 3,040 schools were initially assessed; 229 students declined to participate or did not report their age or sex. The sampling strategy included geographical stratification and the multi-stage selection that can be seen elsewhere (Oliveira et al., 2017). Ethical approval was obtained, and the participation of all subjects was approved by the National Committee of Ethics in Research number 1.006.467/2015.\u003c/p\u003e \u003cp\u003eThe present survey is in its third edition. The questionnaire used for data collection is based on the Global School-Based Student Health Survey and Youth Risk Behavior Surveillance System and has been tested and adjusted [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Clusters Formation\u003c/h2\u003e \u003cp\u003eTo cluster formation, leisure-time physical activity (PA), sedentary behavior (SB), and diet were analyzed. Students\u0026rsquo; PA was assessed using the question: In the past 7 days, without considering physical education class, how many days did you practice some physical activity like sports, dance, gym exercises, combat sports or other activity? The answers ranged from none to seven days in a week. SB was reasonable during the sitting time using the question: In a regular day, how much time do you spend watching television, playing video games, talking with friends or other sitting activities? The response options ranged from one to nine hour a day. Diet was assessed as continuous scores related to the weekly consumption of healthy (green salads or vegetables and fruits) and unhealthy food (deep-fried empanadas, candies, soda, fast foods, and ultra-processed food). Details on measurement, clusters formation procedure, and description have been provided elsewhere [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBriefly, a two-step cluster analysis was employed using the log-likelihood as the distance measure (to account for the congruency between clusters). Leisure-time PA, SB, and both healthy and unhealthy diet scores were independently included as inputs in the model. The low Schwarz\u0026rsquo;s Bayesian Criterion (BIC), the high ratio of distance measures, and the high ratio of BIC changes were used to determine the number of clusters. The theoretical assumption regarding the acceptability of the profiles was taken into account. The analysis was replicated among younger and older adolescents to check clusters\u0026rsquo; acceptability [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Adolescents that have incomplete or missing data for PA, SB, or diet were not analyzed (n\u0026thinsp;=\u0026thinsp;1,507, \u0026lt; 1.5% of the total sample).\u003c/p\u003e \u003cp\u003e100,794 adolescent students were distributed into three different profiles: The \u0026ldquo;Health-promoting SB and diet,\u0026rdquo; comprising 32.6% of the sample; the \u0026ldquo;Health-promoting PA and diet\u0026rdquo; (44.9% of the sample), the \u0026ldquo;Health-risk\u0026rdquo; cluster containing 22.5% of the sample. The two health-promoting clusters are those where positive behaviors prevail over the negative ones, and the health-risk cluster combines a negative profile for all variables (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A detailed description of the clusters can be seen elsewhere [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Social isolation\u003c/h2\u003e \u003cp\u003eParticipants were asked about two aspects: (a) \u0026ldquo;In the past 12 months, how often have you felt alone\u0026rdquo;. A five-point Likert scale ranging from never to always was the response option. Those who responded always or most of the time were considered lonely; (b) \u0026ldquo;How many close friends do you have?\u0026rdquo;. The option of response was zero/one/two/three or more. Those who responded \u0026ldquo;zero\u0026rdquo; were considered to having no close friends.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Covariates\u003c/h2\u003e \u003cp\u003eThe covariates were: sex, skin color, age, live with mother, live with father, mother's schooling, residents of the house, cigarette smoking, alcohol consumption, drugs, physically aggression by an adult at home, involved in a fight with a firearm, involved in a fight with a melee weapon, suffered physical aggression, got involved in a fight, body satisfaction, health perception, type of school.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe participants\u0026rsquo; characteristics were described using absolute and relative frequency with 95% confidence intervals (95%CI) for nominal variables and means with standard deviations (SD) for numerical variables. Crude and adjusted binary logistic regression models were applied to evaluate the associations between exposure (the clusters) and social isolation variables (perceived loneliness and having close friends). For each model, a set of covariates was selected based on empirical and theoretical evidence (see tables notes); Bivariate analyses were performed to evaluate the association of each covariate and both outcomes of social isolation. Significant predictors at p-value\u0026thinsp;\u0026lt;\u0026thinsp;.2 were retained and included in the adjusted models. The \u0026ldquo;Health-risk\u0026rdquo; cluster was the reference category in the regression models. The results were expressed in odds ratios (OR) and the respective (95% CI). All inferential procedures included the survey design and weighting. Data were analyzed using STATA 15 software (Stata Inc., College Station, TX, USA), except for cluster procedures. The significance level was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eTable 1 shows the characteristics of the participants. A total of 100,794 students with a mean age of 14.28 years old (SD = 0.013) were observed. Regarding social isolation, 16.39% of the adolescents experienced loneliness (95% CI = 15.93-16.85) and 4.29% reported not having any close friends (95% CI = 4.05-4.54). Other individual aspects such as behavioral characteristics, victimization, and health outcomes, are presented in the supplemental material.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 1 NEAR HERE\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Characteristics of the sample. PENSE, Brazil 2015 (n= 100,794).\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"566\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.80918727915194%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e95% IC*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.80918727915194%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSchool-level covariates\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eType of school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eMunicipal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e0.04 - 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eState\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e49,462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e48.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e45.05 - 51.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eFederal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e31,404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e37.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e34.15 - 40.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e20,918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e14.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e12.53 - 16.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eFull-time school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e22,854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e22.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e21.19 - 22.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e78,715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e77.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e77.02 - 78.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eBoarding school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e3,846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e4.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e3.748 - 4.451\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e97,942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e95.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e95.55 - 96.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.80918727915194%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHousehold-level covariates\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eComputer at home\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e69,822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e69.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e68.51 - 70.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e32,144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e30.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e29.4 - 31.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eInternet at home\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e78,395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e77.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e76.69 - 78.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e23,572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e22.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e21.62 - 23.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eHousehold residents (mean)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e4.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e4.47 - 4,52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.80918727915194%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSociodemographic factors\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e49,290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e48.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e48.09 - 49.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e52,782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e51.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e50.66 - 51.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eSkin Color\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e33,775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e36.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e35.12 - 37.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e12,849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e13.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e12.88 - 13.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eYellow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e4,580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e3.87 - 4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003e\u003cem\u003ePardo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e46,935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e43.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e42.17 - 43.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eIndigenous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e3,825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e3.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e3.07 - 3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eAge, mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e14.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e14.26 - 14.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eMother\u0026apos;s schooling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eDid not studied\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e5,531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e5.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e5.089 - 5.695\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eIncomplete elementary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e18,217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e19.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e18.8 - 19.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eElementary School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e6,024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e6.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e6.167 - 6.775\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eIncomplete high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e6,275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e6.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e5.78 - 6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e17,903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e18.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e17.47 - 18.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eIncomplete college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e5,456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e4.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e4.27 - 4.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eCollege\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e17,232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e13.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e12.34 - 14.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eDo not know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e25,183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e26.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e26.25 - 27.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eLive with mother\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e90,458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e89.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e89.57 - 90.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e11,543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e10.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e9.7 - 10.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eLive with father\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e63,600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e63.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e63.01 - 64.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e38,341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e36.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e35.59 - 36.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eHas a cell phone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e88,978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e87.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e86.87 - 87.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"37.80918727915194%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"23.674911660777386%\"\u003e\n \u003cp\u003e13,012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.25441696113074%\"\u003e\n \u003cp\u003e12.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"22.261484098939928%\"\u003e\n \u003cp\u003e12.13 - 13.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003en = absolute frequency; %=prevalence; IC95%= confidence interval 95%.\u003c/p\u003e\n\u003cp\u003eTable 2 shows the association between clusters and social isolation variables among adolescents. In the adjusted analysis, adolescents in the Health-promoting SB and diet (OR = 0.69; 95% CI=0.62-0.76) and in the Health-promoting PA and diet (OR = 0.73; 95% CI = 0.67-0.79) clusters showed reduced odds of loneliness compared to those in the Health-risk cluster. Those belonging to the Health-promoting PA and diet cluster were more likely to have close friends (OR=1.19; 95% CI = 1.00-1.41) compared to those in the health-risk cluster.\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 2 NEAR HERE\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. Associations between the clusters and the perception of loneliness and friendships among the adolescents. PeNSE, Brazil 2015.\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"574\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.0801393728223%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" width=\"39.02439024390244%\"\u003e\n \u003cp\u003ePerceived loneliness\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n=98,485)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" width=\"39.89547038327526%\"\u003e\n \u003cp\u003eFriendship\u003c/p\u003e\n \u003cp\u003e(n=97,898)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.0801393728223%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.337979094076655%\"\u003e\n \u003cp\u003eCrude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.686411149825783%\"\u003e\n \u003cp\u003eAdjusted*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.337979094076655%\"\u003e\n \u003cp\u003eCrude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.557491289198605%\"\u003e\n \u003cp\u003eAdjusted**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.0801393728223%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.337979094076655%\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.686411149825783%\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.337979094076655%\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.557491289198605%\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.0801393728223%\"\u003e\n \u003cp\u003e\u003cstrong\u003eClusters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.337979094076655%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.686411149825783%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.337979094076655%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.557491289198605%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"21.0801393728223%\"\u003e\n \u003cp\u003eHealth-risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.337979094076655%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.686411149825783%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.337979094076655%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"20.557491289198605%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"21.0801393728223%\"\u003e\n \u003cp\u003eHealth-promoting SB and diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.337979094076655%\"\u003e\n \u003cp\u003e0.50 (0.46 - 0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.686411149825783%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.69 (0.62 - 0.76)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.337979094076655%\"\u003e\n \u003cp\u003e0.89 (0.76 - 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.557491289198605%\"\u003e\n \u003cp\u003e0.86 (0.74 - 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"21.0801393728223%\"\u003e\n \u003cp\u003eHealth-promoting PA and diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.337979094076655%\"\u003e\n \u003cp\u003e0.50 (0.46 - 0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.686411149825783%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.73 (0.67 - 0.79)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.337979094076655%\"\u003e\n \u003cp\u003e1.23 (1.04 - 1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.557491289198605%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.19 (1.002 - 1.41)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: OR, Odds Ratio; CI, Confidence Intervals; Estimates were weighted according to the sampling design; *Adjusted for sex, \u0026nbsp;skin color, age, live with mother, live with father, mother\u0026apos;s schooling, residents of the house, cigarette smoking, alcohol consumption, \u0026nbsp;drugs, physically aggression by an adult at home, involved in a fight with a firearm, involved in a fight with a melee weapon, suffered physical aggression, \u0026nbsp; got involved in a fight, body satisfaction, \u0026nbsp;health perception, type of school. **Adjusted for sex, skin color, age, live with mother, live with father, mother\u0026apos;s schooling, residents of the house, cigarette smoking, drugs, physically aggression by an adult at home, involved in a fight with a firearm, involved in a fight with a melee weapon, suffered physical aggression, got involved in a fight, body satisfaction, health perception, computer at home, internet at home, full school, boarding school, have a cell phone, type of school.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe present study investigated the association between clusters of obesogenic behaviors and social isolation in a population-based sample of Brazilian adolescents. We observed that the likelihood of loneliness and having close friends varied across the clusters, and adolescents from both healthier groups seem to have lower odds of loneliness.\u003c/p\u003e \u003cp\u003eThe literature has shown that some psychosocial outcomes of adolescents can be influenced by obesogenic behaviors such as PA, diet, and SB [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In addition, there is evidence that adolescents with healthier obesogenic behavior profiles have better socialization, with lower chances of loneliness [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Our findings also highlight the fact that many adolescents have lifestyles defined by the coexistence of favorable and unfavorable health behaviors [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Thus, adolescents in clusters that include an active lifestyle seem to have more prosocial attitudes in their life, such as talking to friends and going for a walk more often [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], improving friendship quality and decreasing the chances of being socially isolated [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA systematic review investigating the relationship between friendship and PA analyzing cross-sectional, longitudinal, and experimental studies with adolescents in the United States showed that peers and friends play an important role in adolescents' PA levels. This association was positive in terms of peer support, presence of peers and/or friends, peer norms, friendship quality, peer acceptance and affiliation, and negative for peer victimization [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Despite the inverse chain to our proposed analyses, having friends helps to provide intrapersonal and interpersonal psychological support, favoring better psychological disposition for the maintenance of PA behavior during adolescence. In addition, being active favor socialization, evidencing a cyclical relationship between behaviors\u0026mdash;socialization\u0026mdash;behavior.\u003c/p\u003e \u003cp\u003eSome mediators have been hypothesized to help explain our findings. For instance, increasing self-confidence and supporting greater problem-solving ability were observed in the univariate relationships between PA and social isolation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and between SB and social isolation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. We hypothesize that PA and SB may share psychosocial mediators, and one behavior \u0026ldquo;supplies\u0026rdquo; the other in maintaining more prosocial attitudes. In other words, a cluster that lacks PA but the adolescent has a reduced time in sedentary behavior can still provide some benefits and vice-versa. Furthermore, obese adolescents report more loneliness, have fewer friends, and are more bullied [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In this case, it is suggested that healthier clusters can favor both better results for biological outcomes, such as decreasing overweight and obesity and minimizing interpersonal and intrapersonal vulnerabilities in adolescence [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSome limitations can be observed in this study. First, the cross-sectional nature of the data does not allow for a causal relationship to be established between adolescents' behaviors and our selected outcomes. The causal chain of these relationships between behavior and health outcomes is well established. However, it is plausible that the observed associations are bidirectional. Although obesity seems to influence social isolation, we ask for caution when interpreting our findings, as there was no control for this variable in our adjusted analysis. Feeling lonely and having fewer friends can keep adolescents away from healthier behaviors, such as PA during leisure time. The social isolation construct is self-reported based on two indicators that may not represent the phenomenon's complexity; therefore, caution in interpreting the results is necessary. Nevertheless, the observed research problem is substantial. It has an analytical approach centered on the individual (clusters analysis); the clusters observed in this population were validated in previous research and involve a representative sample. To the authors\u0026rsquo; knowledge this is the first study to assess the relationship between clusters of obesogenic behaviors and social isolation. In addition, this study draws attention to a less obvious association between lifestyle and health outcomes. Schools, administrators, and policymakers can look beyond obesity and realize that opportunities, attitudes, and choices (in non-particular order) about adolescent lifestyle can impact the social life and the mental health of young people. Therefore, multicomponent interventions are required, considering the synergies between lifestyle behaviors.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eAdolescents in clusters where health-favorable behaviors outweighed unfavorable ones were less likely to perceive themselves as lonely and without close friends. Clusters of obesogenic behaviors seem to share mediators that expose or protect adolescents not only to obesity but also to critical psychosocial outcomes for social life, such as having more friends.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Ministry of Health and the Institute of Geographic and Statistics (IBGE) of Brazil who conducted the survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original PeNSE data set is publicly available in: https://www.ibge.gov.br/estatisticas/sociais/educacao/9134-pesquisa-nacional-de-saude-do-escolar.html?=\u0026amp;t=downloads\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Physical Education, Federal University of Santa Catarina, Florianópolis, 88040-900, Brazil.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThiago Sousa Matias, Julianne Fic Alves, Gislaine Terezinha Amaral Nienov and Marcus Vinicius Veber Lopes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAustralian Catholic University, Institute for Positive Psychology and Education.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiego Itibere Cunha Vasconcellos.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was designed and drafted by TSM, with contributions from JFA and GTAN. MVVL conducted the analysis, interpreted the results, and supported the conduction of the manuscript. TSM supported the analysis. JFA and GTAN supported analysis interpretation. DICV revised and supported the conduction of the manuscript. All authors have revised the manuscript and approved the submission. All authors have agreed to be personally accountable for the author's contributions and ensured that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. The author(s) read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Thiago Sousa Matias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the National Commission on Research Ethics (Comissão Nacional de Ética em Pesquisa – CONEP), n° 1.006.467/2015. Informed consent was obtained from all participants thought an electronic consent form. The informed consent form was placed on the front page of the questionnaire and participant’s agreement was obtained prior to data collection. The right to refuse to participate was guaranteed. The consent to participate was not obtained from the parents/guardians. According to PeNSE report, the Brazilian legislation concerning the protection of the child and adolescent (Brazilian Statute of the Child and the Adolescent - Law n° 8069, 13 July 1990) allows the adolescent to take initiatives, such as responding to a questionnaire that does not represent a risk to their health and aims to promote health protection policies [12]. The consent procedure was approved by the National Commission on Research Ethics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTSM, JFA, GTAN, MVVL and DICV declare no competing interests.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBiddle SJH, Ciaccioni S, Thomas G, Vergeer I. Physical activity and mental health in children and adolescents: An updated review of reviews and an analysis of causality. Psychol Sport Exerc. 2019;42:146\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatias TS, Lopes MVV, de Mello GT, Silva KS. Clustering of obesogenic behaviors and association with body image among Brazilian adolescents in the national school-based health survey (PeNSE 2015). Prev Med Rep. 2019;16:101000.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoone-Heinonen J, Gordon-Larsen P, Adair LS. Obesogenic Clusters: Multidimensional Adolescent Obesity-related Behaviors in the U.S. ann behav med. 2008;36:217\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYi X, Liu Z, Qiao W, Xie X, Yi N, Dong X, et al. Clustering effects of health risk behavior on mental health and physical activity in Chinese adolescents. Health Qual Life Outcomes. 2020;18:211.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWerneck AO, Collings PJ, Barboza LL, Stubbs B, Silva DR. Associations of sedentary behaviors and physical activity with social isolation in 100,839 school students: The Brazilian Scholar Health Survey. Gen Hosp Psychiatry. 2019;59:7\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoare E, Skouteris H, Fuller-Tyszkiewicz M, Millar L, Allender S. Associations between obesogenic risk factors and depression among adolescents: a systematic review: Obesogenic risk and depression: a review. Obes Rev. 2014;15:40\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeech RM, McNaughton SA, Timperio A. The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review. Int J Behav Nutr Phys Act. 2014;11:4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatias TS, Silva KS, Silva JA, da, Mello GT de, Salmon J. Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school - based health survey (PeNSE 2015). BMC Public Health. 2018;18:1283.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoare E, Milton K, Foster C, Allender S. The associations between sedentary behaviour and mental health among adolescents: a systematic review. Int J Behav Nutr Phys Act. 2016;13:108.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePadial-Ruz R, Gonz\u0026aacute;lez-Campos G, Zurita-Ortega F, Puga-Gonz\u0026aacute;lez ME. Associations between Feelings of Loneliness and Attitudes towards Physical Education in Contemporary Adolescents According to Sex, and Physical Activity Engagement. IJERPH. 2020;17:5525.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIannotti RJ, Wang J. Patterns of Physical Activity, Sedentary Behavior, and Diet in U.S. Adolescents. J Adolesc Health. 2013;53:280\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstituto Brasileiro de. Geografia e Estat\u0026iacute;stica I. Pesquisa Nacional de Sa\u0026uacute;de do Escolar \u0026ndash; 2015. 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiberali R, Del Castanhel F, Kupek E, Assis MAA de. Latent Class Analysis of Lifestyle Risk Factors and Association with Overweight and/or Obesity in Children and Adolescents. Syst Rev Child Obes. 2021;17:2\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMello GT de, Lopes MVV, Minatto G, Costa RM da, Matias TS, Guerra PH, et al. Clustering of Physical Activity, Diet and Sedentary Behavior among Youth from Low-, Middle-, and High-Income Countries: A Scoping Review. IJERPH. 2021;18:10924.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerrar K, Chang C, Li M, Olds TS. Adolescent Time Use Clusters: A Systematic Review. J Adolesc Health. 2013;52:259\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFitzpatrick C, Burkhalter R, Asbridge M. Adolescent media use and its association to wellbeing in a Canadian national sample. Prev Med Rep. 2019;14:100867.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaasdorp TE, Mehari K, Bradshaw CP. Obese and overweight youth: Risk for experiencing bullying victimization and internalizing symptoms. Am J Orthopsychiatry. 2018;88:483\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Healthy Lifestyle, Loneliness, Mental Health, Health Surveys, Motor Activity","lastPublishedDoi":"10.21203/rs.3.rs-2378867/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2378867/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackgound:\u003c/strong\u003e Although obesogenic behaviors have been found to be related to social isolation, evidence-based person-centered approaches are lacking. This study investigated the association between clusters of obesogenic behavior – derived from a data-driven process – and social isolation among Brazilian adolescents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Data from the National Adolescent School-based Health Survey (PeNSE) 2015 Cohort were analyzed. A total of 100,794 9\u003csup\u003eth\u003c/sup\u003e-grade students (51.3% females; 14.3 ± 0.1 years old) enrolled in 3,040 public and private high schools participated in the study. Social isolation was assessed by two outcomes (i.e., perceived loneliness and lack of close friends). A two-step cluster analysis was conducted to identify patterns of obesogenic behaviors with the input of leisure-time physical activity (PA), sitting time as a proxy of sedentary behavior (SB), and the weekly consumption of healthy and unhealthy food. Crude and adjusted binary logistic regression models were applied to evaluate the associations between the clusters of obesogenic behaviors and social isolation variables in adolescents. \u003cem\u003eResults:\u003c/em\u003e Three clusters were identified. Adolescents in the “Health-promoting SB and diet” (32.6%; OR = 0.69; 95% CI=0.62-0.76) and “Health-promoting PA and diet” (44.9%; OR = 0.73; 95% CI = 0.67-0.79) clusters had lower odds of loneliness compared to those in the “Health-risk” cluster (22.5%). Those belonging to the “Health-promoting PA and diet” cluster were more likely to report having close friends (OR=1.19; 95% CI = 1.00-1.41) than those in the “Health-risk” cluster.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Adolescents in clusters where positive behaviors outweighed negative ones were less likely to perceive themselves as lonely and without close connections.\u003c/p\u003e","manuscriptTitle":"Clustering of Physical Activity, Sedentary Behavior, and Diet Associated With Social Isolation Among Brazilian Adolescents","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-03 18:03:18","doi":"10.21203/rs.3.rs-2378867/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-02-17T13:20:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-02-13T05:25:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33a10ae9-f403-44f4-88be-9a108b7593ac","date":"2023-02-02T12:22:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-01-06T15:31:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-01-06T15:28:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-12-27T13:25:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-12-27T13:23:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2022-12-14T17:08:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fc9044d1-af1b-4915-9d98-a6cf91286c2a","owner":[],"postedDate":"January 3rd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T20:14:34+00:00","versionOfRecord":{"articleIdentity":"rs-2378867","link":"https://doi.org/10.1186/s12889-023-15444-x","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2023-03-25 20:07:11","publishedOnDateReadable":"March 25th, 2023"},"versionCreatedAt":"2023-01-03 18:03:18","video":"","vorDoi":"10.1186/s12889-023-15444-x","vorDoiUrl":"https://doi.org/10.1186/s12889-023-15444-x","workflowStages":[]},"version":"v1","identity":"rs-2378867","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2378867","identity":"rs-2378867","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}