National Adolescent School-based Health Survey - PeNSE 2015: Sedentary behavior and its correlates
To investigate the association between sedentary behavior (SB) and sociodemographic, social support, behavioral, and health variables among Brazilian adolescents. The 2015 National Adolescent School-based Health Survey (PeNSE) was a cross-sectional study consisting of 102,072 Brazilian ninth-graders...
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| creator | Silva, Roberta Mendes Abreu Andrade, Amanda Cristina de Souza Caiaffa, Waleska Teixeira Medeiros, Danielle Souto de Bezerra, Vanessa Moraes |
| description | To investigate the association between sedentary behavior (SB) and sociodemographic, social support, behavioral, and health variables among Brazilian adolescents.
The 2015 National Adolescent School-based Health Survey (PeNSE) was a cross-sectional study consisting of 102,072 Brazilian ninth-graders (mainly aged 13-15 years). SB was defined as the time (in hours) watching television, using a computer, playing video games, talking to friends, or doing other activities in a sitting position. For analysis purposes, SB was categorized into different cut-offs as per the sample distribution quartiles: >2 versus 4 versus 6 versus 2, >4 and >6 hours, respectively. The following characteristics were positively and significantly associated with each SB cut-off point in the final models: females, current employment, higher household economic status and higher maternal schooling, lower levels of parents checking homework, tobacco and alcohol use, soft drink and fruit consumption, and regular, poor or very poor self-assessed health status. Conversely, students who self-declared brown were less likely to be classified as a SB cut-off point. Significant associations with age, report of close friends, and physical activity varied by different SB cut-off points.
Understanding the SB correlates in their different dimensions contributes to the identification of subgroups of adolescents with higher SB prevalence, which is crucial in the development and improvement of public policies. The demographic and behavioral characterization of these groups can guide the development of future intervention strategies, considering the school and family contexts of these adolescents. |
| doi_str_mv | 10.1371/journal.pone.0228373 |
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The 2015 National Adolescent School-based Health Survey (PeNSE) was a cross-sectional study consisting of 102,072 Brazilian ninth-graders (mainly aged 13-15 years). SB was defined as the time (in hours) watching television, using a computer, playing video games, talking to friends, or doing other activities in a sitting position. For analysis purposes, SB was categorized into different cut-offs as per the sample distribution quartiles: >2 versus <2 (25th percentile); >4 versus <4 (50th 26 percentile) and >6 versus <6 (75th 27 percentile). We employed Poisson univariate and multivariate regression analyses with robust variance and hierarchical entry of variables for each cut-off point.
The prevalence rates of each SB cut-off point were 68.15% (CI: 67.44-68.86), 44.15% (CI: 43.40-44.90) and 24.97% (CI:24.37-25.57) for >2, >4 and >6 hours, respectively. The following characteristics were positively and significantly associated with each SB cut-off point in the final models: females, current employment, higher household economic status and higher maternal schooling, lower levels of parents checking homework, tobacco and alcohol use, soft drink and fruit consumption, and regular, poor or very poor self-assessed health status. Conversely, students who self-declared brown were less likely to be classified as a SB cut-off point. Significant associations with age, report of close friends, and physical activity varied by different SB cut-off points.
Understanding the SB correlates in their different dimensions contributes to the identification of subgroups of adolescents with higher SB prevalence, which is crucial in the development and improvement of public policies. The demographic and behavioral characterization of these groups can guide the development of future intervention strategies, considering the school and family contexts of these adolescents.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0228373</identifier><identifier>PMID: 31999792</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adolescent ; Adolescent Behavior ; Adolescent Health ; Adolescents ; Alcohol use ; Behavior ; Biology and Life Sciences ; Brazil - epidemiology ; Characterization ; Computer & video games ; Consumption ; Cross-Sectional Studies ; Demographics ; Drinking (Alcoholic beverages) ; Economic conditions ; Economic models ; Electronic & video games ; Electronic games ; Exercise ; Female ; Females ; Health ; Health Surveys ; Homework ; Households ; Humans ; Internet access ; Investigations ; Male ; Medicine and Health Sciences ; Metabolism ; Observatories ; People and Places ; Physical activity ; Physical fitness ; Polls & surveys ; Public policy ; Quartiles ; Questionnaires ; Regression analysis ; Robustness (mathematics) ; Schools ; Screen time ; Sedentary Behavior ; Sitting position ; Smartphones ; Social behavior ; Social interactions ; Social Sciences ; Social Support ; Sociodemographics ; Socioeconomic Factors ; Soft drinks ; Students ; Subgroups ; Surveys ; Teenagers ; Television ; Time ; Tobacco ; Variance analysis ; Video games ; Youth</subject><ispartof>PloS one, 2020-01, Vol.15 (1), p.e0228373-e0228373</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Silva et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Silva et al 2020 Silva et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-cde31823499ac252bf2dfa8c5f42b6c7bfe1764742eee42654bbb147d716c013</citedby><cites>FETCH-LOGICAL-c692t-cde31823499ac252bf2dfa8c5f42b6c7bfe1764742eee42654bbb147d716c013</cites><orcidid>0000-0001-5057-1643</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6991995/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6991995/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31999792$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Foo, Leng Huat</contributor><creatorcontrib>Silva, Roberta Mendes Abreu</creatorcontrib><creatorcontrib>Andrade, Amanda Cristina de Souza</creatorcontrib><creatorcontrib>Caiaffa, Waleska Teixeira</creatorcontrib><creatorcontrib>Medeiros, Danielle Souto de</creatorcontrib><creatorcontrib>Bezerra, Vanessa Moraes</creatorcontrib><title>National Adolescent School-based Health Survey - PeNSE 2015: Sedentary behavior and its correlates</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>To investigate the association between sedentary behavior (SB) and sociodemographic, social support, behavioral, and health variables among Brazilian adolescents.
The 2015 National Adolescent School-based Health Survey (PeNSE) was a cross-sectional study consisting of 102,072 Brazilian ninth-graders (mainly aged 13-15 years). SB was defined as the time (in hours) watching television, using a computer, playing video games, talking to friends, or doing other activities in a sitting position. For analysis purposes, SB was categorized into different cut-offs as per the sample distribution quartiles: >2 versus <2 (25th percentile); >4 versus <4 (50th 26 percentile) and >6 versus <6 (75th 27 percentile). We employed Poisson univariate and multivariate regression analyses with robust variance and hierarchical entry of variables for each cut-off point.
The prevalence rates of each SB cut-off point were 68.15% (CI: 67.44-68.86), 44.15% (CI: 43.40-44.90) and 24.97% (CI:24.37-25.57) for >2, >4 and >6 hours, respectively. The following characteristics were positively and significantly associated with each SB cut-off point in the final models: females, current employment, higher household economic status and higher maternal schooling, lower levels of parents checking homework, tobacco and alcohol use, soft drink and fruit consumption, and regular, poor or very poor self-assessed health status. Conversely, students who self-declared brown were less likely to be classified as a SB cut-off point. Significant associations with age, report of close friends, and physical activity varied by different SB cut-off points.
Understanding the SB correlates in their different dimensions contributes to the identification of subgroups of adolescents with higher SB prevalence, which is crucial in the development and improvement of public policies. The demographic and behavioral characterization of these groups can guide the development of future intervention strategies, considering the school and family contexts of these adolescents.</description><subject>Adolescent</subject><subject>Adolescent Behavior</subject><subject>Adolescent Health</subject><subject>Adolescents</subject><subject>Alcohol use</subject><subject>Behavior</subject><subject>Biology and Life Sciences</subject><subject>Brazil - epidemiology</subject><subject>Characterization</subject><subject>Computer & video games</subject><subject>Consumption</subject><subject>Cross-Sectional Studies</subject><subject>Demographics</subject><subject>Drinking (Alcoholic beverages)</subject><subject>Economic conditions</subject><subject>Economic models</subject><subject>Electronic & video games</subject><subject>Electronic games</subject><subject>Exercise</subject><subject>Female</subject><subject>Females</subject><subject>Health</subject><subject>Health Surveys</subject><subject>Homework</subject><subject>Households</subject><subject>Humans</subject><subject>Internet access</subject><subject>Investigations</subject><subject>Male</subject><subject>Medicine and Health Sciences</subject><subject>Metabolism</subject><subject>Observatories</subject><subject>People and Places</subject><subject>Physical activity</subject><subject>Physical fitness</subject><subject>Polls & surveys</subject><subject>Public policy</subject><subject>Quartiles</subject><subject>Questionnaires</subject><subject>Regression analysis</subject><subject>Robustness (mathematics)</subject><subject>Schools</subject><subject>Screen time</subject><subject>Sedentary Behavior</subject><subject>Sitting position</subject><subject>Smartphones</subject><subject>Social behavior</subject><subject>Social interactions</subject><subject>Social Sciences</subject><subject>Social Support</subject><subject>Sociodemographics</subject><subject>Socioeconomic Factors</subject><subject>Soft drinks</subject><subject>Students</subject><subject>Subgroups</subject><subject>Surveys</subject><subject>Teenagers</subject><subject>Television</subject><subject>Time</subject><subject>Tobacco</subject><subject>Variance analysis</subject><subject>Video 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Adolescent School-based Health Survey - PeNSE 2015: Sedentary behavior and its correlates</title><author>Silva, Roberta Mendes Abreu ; Andrade, Amanda Cristina de Souza ; Caiaffa, Waleska Teixeira ; Medeiros, Danielle Souto de ; Bezerra, Vanessa Moraes</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-cde31823499ac252bf2dfa8c5f42b6c7bfe1764742eee42654bbb147d716c013</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adolescent</topic><topic>Adolescent Behavior</topic><topic>Adolescent Health</topic><topic>Adolescents</topic><topic>Alcohol use</topic><topic>Behavior</topic><topic>Biology and Life Sciences</topic><topic>Brazil - epidemiology</topic><topic>Characterization</topic><topic>Computer & video games</topic><topic>Consumption</topic><topic>Cross-Sectional Studies</topic><topic>Demographics</topic><topic>Drinking (Alcoholic beverages)</topic><topic>Economic 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One</addtitle><date>2020-01-30</date><risdate>2020</risdate><volume>15</volume><issue>1</issue><spage>e0228373</spage><epage>e0228373</epage><pages>e0228373-e0228373</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>To investigate the association between sedentary behavior (SB) and sociodemographic, social support, behavioral, and health variables among Brazilian adolescents.
The 2015 National Adolescent School-based Health Survey (PeNSE) was a cross-sectional study consisting of 102,072 Brazilian ninth-graders (mainly aged 13-15 years). SB was defined as the time (in hours) watching television, using a computer, playing video games, talking to friends, or doing other activities in a sitting position. For analysis purposes, SB was categorized into different cut-offs as per the sample distribution quartiles: >2 versus <2 (25th percentile); >4 versus <4 (50th 26 percentile) and >6 versus <6 (75th 27 percentile). We employed Poisson univariate and multivariate regression analyses with robust variance and hierarchical entry of variables for each cut-off point.
The prevalence rates of each SB cut-off point were 68.15% (CI: 67.44-68.86), 44.15% (CI: 43.40-44.90) and 24.97% (CI:24.37-25.57) for >2, >4 and >6 hours, respectively. The following characteristics were positively and significantly associated with each SB cut-off point in the final models: females, current employment, higher household economic status and higher maternal schooling, lower levels of parents checking homework, tobacco and alcohol use, soft drink and fruit consumption, and regular, poor or very poor self-assessed health status. Conversely, students who self-declared brown were less likely to be classified as a SB cut-off point. Significant associations with age, report of close friends, and physical activity varied by different SB cut-off points.
Understanding the SB correlates in their different dimensions contributes to the identification of subgroups of adolescents with higher SB prevalence, which is crucial in the development and improvement of public policies. The demographic and behavioral characterization of these groups can guide the development of future intervention strategies, considering the school and family contexts of these adolescents.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>31999792</pmid><doi>10.1371/journal.pone.0228373</doi><tpages>e0228373</tpages><orcidid>https://orcid.org/0000-0001-5057-1643</orcidid><oa>free_for_read</oa></addata></record> |
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| issn | 1932-6203 1932-6203 |
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| recordid | cdi_plos_journals_2348784943 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS); EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adolescent Adolescent Behavior Adolescent Health Adolescents Alcohol use Behavior Biology and Life Sciences Brazil - epidemiology Characterization Computer & video games Consumption Cross-Sectional Studies Demographics Drinking (Alcoholic beverages) Economic conditions Economic models Electronic & video games Electronic games Exercise Female Females Health Health Surveys Homework Households Humans Internet access Investigations Male Medicine and Health Sciences Metabolism Observatories People and Places Physical activity Physical fitness Polls & surveys Public policy Quartiles Questionnaires Regression analysis Robustness (mathematics) Schools Screen time Sedentary Behavior Sitting position Smartphones Social behavior Social interactions Social Sciences Social Support Sociodemographics Socioeconomic Factors Soft drinks Students Subgroups Surveys Teenagers Television Time Tobacco Variance analysis Video games Youth |
| title | National Adolescent School-based Health Survey - PeNSE 2015: Sedentary behavior and its correlates |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T03%3A38%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=National%20Adolescent%20School-based%20Health%20Survey%20-%20PeNSE%202015:%20Sedentary%20behavior%20and%20its%20correlates&rft.jtitle=PloS%20one&rft.au=Silva,%20Roberta%20Mendes%20Abreu&rft.date=2020-01-30&rft.volume=15&rft.issue=1&rft.spage=e0228373&rft.epage=e0228373&rft.pages=e0228373-e0228373&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0228373&rft_dat=%3Cgale_plos_%3EA612757388%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2348784943&rft_id=info:pmid/31999792&rft_galeid=A612757388&rft_doaj_id=oai_doaj_org_article_13770672834d4318841bbf074ffcc23e&rfr_iscdi=true |