Clustering of South Korean Adolescents' Health-Related Behaviors by Gender: Using a Latent Class Analysis
Health-related behaviors during adolescence could influence adolescents' health outcomes, leading to either advantageous or deteriorative conditions. Clustering of adolescents' health-related behaviors by gender identifies the target groups for intervention and informs the strategies to be...
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Veröffentlicht in: | International journal of environmental research and public health 2021-03, Vol.18 (6), p.3129 |
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description | Health-related behaviors during adolescence could influence adolescents' health outcomes, leading to either advantageous or deteriorative conditions. Clustering of adolescents' health-related behaviors by gender identifies the target groups for intervention and informs the strategies to be implemented for behavioral changes.
Data from 1807 adolescents in grades 7 and 10 in a city in South Korea were used. Health-related behaviors including eating habits, physical activity, hand washing, brushing teeth, drinking alcohol, smoking, and Internet use were examined. Latent class analysis (LCA) was used to identify subgroups of adolescents with regard to their health-related behaviors.
A four-class model was the most adequate grouping classification across genders: adolescents with (1) healthy behaviors, (2) neither health-promoting nor health-risk behaviors, (3) good hygiene behaviors, and (4) unhealthy behaviors. The majority of both male and female adolescents were classified into the healthy group. Male adolescents belonging to the healthy group were more likely to engage in vigorous physical activities, while vigorous physical activity was not important for female adolescents. The smallest group was the unhealthy group, regardless of gender; however, the proportion of boys in the unhealthy group was almost twice that of girls. Only female adolescents engaged in excessive Internet use, especially the group with neither health-promoting nor health-risk behaviors.
To improve adolescents' health-related behaviors, it would be more effective to develop tailored interventions considering the behavioral profiles of the target groups. |
doi_str_mv | 10.3390/ijerph18063129 |
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Data from 1807 adolescents in grades 7 and 10 in a city in South Korea were used. Health-related behaviors including eating habits, physical activity, hand washing, brushing teeth, drinking alcohol, smoking, and Internet use were examined. Latent class analysis (LCA) was used to identify subgroups of adolescents with regard to their health-related behaviors.
A four-class model was the most adequate grouping classification across genders: adolescents with (1) healthy behaviors, (2) neither health-promoting nor health-risk behaviors, (3) good hygiene behaviors, and (4) unhealthy behaviors. The majority of both male and female adolescents were classified into the healthy group. Male adolescents belonging to the healthy group were more likely to engage in vigorous physical activities, while vigorous physical activity was not important for female adolescents. The smallest group was the unhealthy group, regardless of gender; however, the proportion of boys in the unhealthy group was almost twice that of girls. Only female adolescents engaged in excessive Internet use, especially the group with neither health-promoting nor health-risk behaviors.
To improve adolescents' health-related behaviors, it would be more effective to develop tailored interventions considering the behavioral profiles of the target groups.</description><identifier>ISSN: 1660-4601</identifier><identifier>ISSN: 1661-7827</identifier><identifier>EISSN: 1660-4601</identifier><identifier>DOI: 10.3390/ijerph18063129</identifier><identifier>PMID: 33803595</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Adolescent ; Adolescent Behavior ; Adolescents ; Alcohol ; Child development ; Childrens health ; Cluster Analysis ; Clustering ; Dairy products ; Drinking behavior ; Eating behavior ; Exercise ; Female ; Fruits ; Gender ; Gender differences ; Health Behavior ; Health promotion ; Health risks ; Humans ; Hygiene ; Internet ; Latent Class Analysis ; Male ; Milk ; Physical activity ; Republic of Korea ; Risk taking ; Smoking ; Subgroups ; Target groups ; Teenagers ; Vegetables</subject><ispartof>International journal of environmental research and public health, 2021-03, Vol.18 (6), p.3129</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c418t-f94ece96bebf3d69cec95641e9cda2fffd48beddb9bee84529b5953cd2f634d63</citedby><cites>FETCH-LOGICAL-c418t-f94ece96bebf3d69cec95641e9cda2fffd48beddb9bee84529b5953cd2f634d63</cites><orcidid>0000-0002-3767-8638 ; 0000-0003-1511-1785</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/PMC8003105/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003105/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33803595$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chae, Myungah</creatorcontrib><creatorcontrib>Chung, Sophia Jihey</creatorcontrib><title>Clustering of South Korean Adolescents' Health-Related Behaviors by Gender: Using a Latent Class Analysis</title><title>International journal of environmental research and public health</title><addtitle>Int J Environ Res Public Health</addtitle><description>Health-related behaviors during adolescence could influence adolescents' health outcomes, leading to either advantageous or deteriorative conditions. Clustering of adolescents' health-related behaviors by gender identifies the target groups for intervention and informs the strategies to be implemented for behavioral changes.
Data from 1807 adolescents in grades 7 and 10 in a city in South Korea were used. Health-related behaviors including eating habits, physical activity, hand washing, brushing teeth, drinking alcohol, smoking, and Internet use were examined. Latent class analysis (LCA) was used to identify subgroups of adolescents with regard to their health-related behaviors.
A four-class model was the most adequate grouping classification across genders: adolescents with (1) healthy behaviors, (2) neither health-promoting nor health-risk behaviors, (3) good hygiene behaviors, and (4) unhealthy behaviors. The majority of both male and female adolescents were classified into the healthy group. Male adolescents belonging to the healthy group were more likely to engage in vigorous physical activities, while vigorous physical activity was not important for female adolescents. The smallest group was the unhealthy group, regardless of gender; however, the proportion of boys in the unhealthy group was almost twice that of girls. Only female adolescents engaged in excessive Internet use, especially the group with neither health-promoting nor health-risk behaviors.
To improve adolescents' health-related behaviors, it would be more effective to develop tailored interventions considering the behavioral profiles of the target groups.</description><subject>Adolescent</subject><subject>Adolescent Behavior</subject><subject>Adolescents</subject><subject>Alcohol</subject><subject>Child development</subject><subject>Childrens health</subject><subject>Cluster Analysis</subject><subject>Clustering</subject><subject>Dairy products</subject><subject>Drinking behavior</subject><subject>Eating behavior</subject><subject>Exercise</subject><subject>Female</subject><subject>Fruits</subject><subject>Gender</subject><subject>Gender differences</subject><subject>Health Behavior</subject><subject>Health promotion</subject><subject>Health risks</subject><subject>Humans</subject><subject>Hygiene</subject><subject>Internet</subject><subject>Latent Class Analysis</subject><subject>Male</subject><subject>Milk</subject><subject>Physical activity</subject><subject>Republic of Korea</subject><subject>Risk taking</subject><subject>Smoking</subject><subject>Subgroups</subject><subject>Target groups</subject><subject>Teenagers</subject><subject>Vegetables</subject><issn>1660-4601</issn><issn>1661-7827</issn><issn>1660-4601</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpdkc1rGzEQxUVpaBK31x6LoIfmsom00gqph4JrkjjEEGibs9CuRlkZeeVKuwH_95HJB0lOMzC_ecybh9BXSk4ZU-TMryFteyqJYLRWH9ARFYJUXBD68VV_iI5zXhPCJBfqEzpkTBLWqOYI-UWY8gjJD3c4Ovw3TmOPr2MCM-C5jQFyB8OYf-AlmDD21R8IZgSLf0Nv7n1MGbc7fAmDhfQT3-a9jMGrggwjXgSTM54PJuyyz5_RgTMhw5enOkO3F-f_FstqdXN5tZivqo5TOVZOcehAiRZax6xQHXSqEZyC6qypnXOWyxasbVULIHlTq7YYYZ2tnWDcCjZDvx51t1O7Abs_P5mgt8lvTNrpaLx-Oxl8r-_ivZblP5Q0ReDkSSDF_xPkUW98-UIIZoA4ZV03RDaSUcYL-v0duo5TKoYLJWpJBeW8LtTpI9WlmHMC93IMJXqfon6bYln49trCC_4cG3sAWSCbnQ</recordid><startdate>20210318</startdate><enddate>20210318</enddate><creator>Chae, Myungah</creator><creator>Chung, Sophia Jihey</creator><general>MDPI AG</general><general>MDPI</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-3767-8638</orcidid><orcidid>https://orcid.org/0000-0003-1511-1785</orcidid></search><sort><creationdate>20210318</creationdate><title>Clustering of South Korean Adolescents' Health-Related Behaviors by Gender: Using a Latent Class Analysis</title><author>Chae, Myungah ; Chung, Sophia Jihey</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c418t-f94ece96bebf3d69cec95641e9cda2fffd48beddb9bee84529b5953cd2f634d63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adolescent</topic><topic>Adolescent Behavior</topic><topic>Adolescents</topic><topic>Alcohol</topic><topic>Child development</topic><topic>Childrens health</topic><topic>Cluster Analysis</topic><topic>Clustering</topic><topic>Dairy products</topic><topic>Drinking behavior</topic><topic>Eating behavior</topic><topic>Exercise</topic><topic>Female</topic><topic>Fruits</topic><topic>Gender</topic><topic>Gender differences</topic><topic>Health Behavior</topic><topic>Health promotion</topic><topic>Health risks</topic><topic>Humans</topic><topic>Hygiene</topic><topic>Internet</topic><topic>Latent Class Analysis</topic><topic>Male</topic><topic>Milk</topic><topic>Physical activity</topic><topic>Republic of Korea</topic><topic>Risk taking</topic><topic>Smoking</topic><topic>Subgroups</topic><topic>Target groups</topic><topic>Teenagers</topic><topic>Vegetables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chae, Myungah</creatorcontrib><creatorcontrib>Chung, Sophia Jihey</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>International journal of environmental research and public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chae, Myungah</au><au>Chung, Sophia Jihey</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Clustering of South Korean Adolescents' Health-Related Behaviors by Gender: Using a Latent Class Analysis</atitle><jtitle>International journal of environmental research and public health</jtitle><addtitle>Int J Environ Res Public Health</addtitle><date>2021-03-18</date><risdate>2021</risdate><volume>18</volume><issue>6</issue><spage>3129</spage><pages>3129-</pages><issn>1660-4601</issn><issn>1661-7827</issn><eissn>1660-4601</eissn><abstract>Health-related behaviors during adolescence could influence adolescents' health outcomes, leading to either advantageous or deteriorative conditions. Clustering of adolescents' health-related behaviors by gender identifies the target groups for intervention and informs the strategies to be implemented for behavioral changes.
Data from 1807 adolescents in grades 7 and 10 in a city in South Korea were used. Health-related behaviors including eating habits, physical activity, hand washing, brushing teeth, drinking alcohol, smoking, and Internet use were examined. Latent class analysis (LCA) was used to identify subgroups of adolescents with regard to their health-related behaviors.
A four-class model was the most adequate grouping classification across genders: adolescents with (1) healthy behaviors, (2) neither health-promoting nor health-risk behaviors, (3) good hygiene behaviors, and (4) unhealthy behaviors. The majority of both male and female adolescents were classified into the healthy group. Male adolescents belonging to the healthy group were more likely to engage in vigorous physical activities, while vigorous physical activity was not important for female adolescents. The smallest group was the unhealthy group, regardless of gender; however, the proportion of boys in the unhealthy group was almost twice that of girls. Only female adolescents engaged in excessive Internet use, especially the group with neither health-promoting nor health-risk behaviors.
To improve adolescents' health-related behaviors, it would be more effective to develop tailored interventions considering the behavioral profiles of the target groups.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>33803595</pmid><doi>10.3390/ijerph18063129</doi><orcidid>https://orcid.org/0000-0002-3767-8638</orcidid><orcidid>https://orcid.org/0000-0003-1511-1785</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adolescent Behavior Adolescents Alcohol Child development Childrens health Cluster Analysis Clustering Dairy products Drinking behavior Eating behavior Exercise Female Fruits Gender Gender differences Health Behavior Health promotion Health risks Humans Hygiene Internet Latent Class Analysis Male Milk Physical activity Republic of Korea Risk taking Smoking Subgroups Target groups Teenagers Vegetables |
title | Clustering of South Korean Adolescents' Health-Related Behaviors by Gender: Using a Latent Class Analysis |
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