Predictors of Food and Physical Activity Tracking Among Young Adults
Background: Monitoring food intake and physical activity (PA) using tracking applications may support behavior change. However, few longitudinal studies identify the characteristics of young adults who track their behavior, findings that could be useful in designing tracking-related interventions. O...
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| Veröffentlicht in: | Health education & behavior 2023-10, Vol.50 (5), p.647-657 |
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| creator | O’Loughlin, Erin K. Marashi, Maryam Sabiston, Catherine M. Lucibello, Kristen M. Sylvestre, Marie-Pierre O’Loughlin, Jennifer L. |
| description | Background:
Monitoring food intake and physical activity (PA) using tracking applications may support behavior change. However, few longitudinal studies identify the characteristics of young adults who track their behavior, findings that could be useful in designing tracking-related interventions. Our objective was to identify predictors of past-year food and PA tracking among young adults.
Methods:
Data were available for 676 young adults participating in the ongoing longitudinal Nicotine Dependence in Teens Study. Potential predictors were measured in 2017–2020 at age 31, and past-year food and PA tracking were measured in 2021–2022 at age 34. Each potential predictor was studied in a separate multivariable logistic regression model controlling for age, sex, and educational attainment.
Results:
One third (37%) of participants reported past-year PA tracking; 14% reported past-year food, and 10% reported both. Nine and 11 of 41 potential predictors were associated with food and PA tracking, respectively. Compensatory behaviors after overeating, trying to lose weight, self-report overweight, reporting a wide variety of exercise behaviors, and pressure to lose weight predicted both food and PA tracking.
Conclusion:
Food and PA tracking are relatively common among young adults. If the associations observed herein between compensatory behavior after overeating and tracking (among other observed associations) are replicated and found to be causal, caution may need to be exercised in making “blanket” recommendations to track food intake and/or PA to all young adults seeking behavior change. |
| doi_str_mv | 10.1177/10901981231159679 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10492434</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ericid>EJ1392374</ericid><sage_id>10.1177_10901981231159679</sage_id><sourcerecordid>2890023345</sourcerecordid><originalsourceid>FETCH-LOGICAL-c522t-13e4d22a831c3d70a5761a5752c3507a9e2833d844d152756b534821786810923</originalsourceid><addsrcrecordid>eNqFkUlvFDEQhVsIRBb4ARxALXHh0omrvJ_QKGQBRSKHcOBkObZn4tDTTuzuSPPv8WjChEURl7Kl99XzK1fTvAFyACDlIRBNQCtACsC1kPpZswucYycA5fN6r3q3BnaavVJuCCFCE_6y2aFCM6TIdptPFzn46MaUS5vm7UlKvrWDby-uVyU627czN8b7OK7ay2zdjzgs2tky1fo9Teu7n_qxvGpezG1fwuuHc7_5dnJ8eXTWnX89_Xw0O-8cRxw7oIF5RKsoOOolsVwKqIWjo5xIqwMqSr1izANHycUVp0whSCVUHQXpfvNx43s7XS2Dd2EYs-3NbY5Lm1cm2Wj-VIZ4bRbp3gBhGhll1eHDg0NOd1Moo1nG4kLf2yGkqRhUmhCklPH_o1LVSBypruj7v9CbNOWhfkU1FChRMEorBRvK5VRKDvNtcCBmvU_zzz5rz7vfJ952_FpgBd5ugJCj28rHX4DWcHKtH2z0YhfhMdbTL_4Et4Wtvw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2862726433</pqid></control><display><type>article</type><title>Predictors of Food and Physical Activity Tracking Among Young Adults</title><source>Access via SAGE</source><source>Applied Social Sciences Index & Abstracts (ASSIA)</source><source>Alma/SFX Local Collection</source><creator>O’Loughlin, Erin K. ; Marashi, Maryam ; Sabiston, Catherine M. ; Lucibello, Kristen M. ; Sylvestre, Marie-Pierre ; O’Loughlin, Jennifer L.</creator><creatorcontrib>O’Loughlin, Erin K. ; Marashi, Maryam ; Sabiston, Catherine M. ; Lucibello, Kristen M. ; Sylvestre, Marie-Pierre ; O’Loughlin, Jennifer L.</creatorcontrib><description>Background:
Monitoring food intake and physical activity (PA) using tracking applications may support behavior change. However, few longitudinal studies identify the characteristics of young adults who track their behavior, findings that could be useful in designing tracking-related interventions. Our objective was to identify predictors of past-year food and PA tracking among young adults.
Methods:
Data were available for 676 young adults participating in the ongoing longitudinal Nicotine Dependence in Teens Study. Potential predictors were measured in 2017–2020 at age 31, and past-year food and PA tracking were measured in 2021–2022 at age 34. Each potential predictor was studied in a separate multivariable logistic regression model controlling for age, sex, and educational attainment.
Results:
One third (37%) of participants reported past-year PA tracking; 14% reported past-year food, and 10% reported both. Nine and 11 of 41 potential predictors were associated with food and PA tracking, respectively. Compensatory behaviors after overeating, trying to lose weight, self-report overweight, reporting a wide variety of exercise behaviors, and pressure to lose weight predicted both food and PA tracking.
Conclusion:
Food and PA tracking are relatively common among young adults. If the associations observed herein between compensatory behavior after overeating and tracking (among other observed associations) are replicated and found to be causal, caution may need to be exercised in making “blanket” recommendations to track food intake and/or PA to all young adults seeking behavior change.</description><identifier>ISSN: 1090-1981</identifier><identifier>EISSN: 1552-6127</identifier><identifier>DOI: 10.1177/10901981231159679</identifier><identifier>PMID: 36942324</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Adolescents ; Adults ; Age ; Behavior ; Behavior change ; Behavior Modification ; Body Weight ; Change agents ; Compensation ; Compensatory behaviour ; Drug dependence ; Eating Habits ; Educational attainment ; Exercise ; Food ; Food intake ; Health Behavior ; Individual Characteristics ; Life Style ; Longitudinal studies ; Measurement Equipment ; Multivariable control ; Nicotine ; Obesity ; Physical activity ; Physical Activity Level ; Predictor Variables ; Regression models ; Self report ; Social Influences ; Tracking ; Weight loss ; Young Adults ; Youth Health</subject><ispartof>Health education & behavior, 2023-10, Vol.50 (5), p.647-657</ispartof><rights>The Author(s) 2023</rights><rights>The Author(s) 2023 2023 Society for Public Health Education</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c522t-13e4d22a831c3d70a5761a5752c3507a9e2833d844d152756b534821786810923</citedby><cites>FETCH-LOGICAL-c522t-13e4d22a831c3d70a5761a5752c3507a9e2833d844d152756b534821786810923</cites><orcidid>0000-0002-3104-3148 ; 0000-0001-7240-7588</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/10901981231159679$$EPDF$$P50$$Gsage$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/10901981231159679$$EHTML$$P50$$Gsage$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,21819,27924,27925,30999,43621,43622</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ1392374$$DView record in ERIC$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36942324$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>O’Loughlin, Erin K.</creatorcontrib><creatorcontrib>Marashi, Maryam</creatorcontrib><creatorcontrib>Sabiston, Catherine M.</creatorcontrib><creatorcontrib>Lucibello, Kristen M.</creatorcontrib><creatorcontrib>Sylvestre, Marie-Pierre</creatorcontrib><creatorcontrib>O’Loughlin, Jennifer L.</creatorcontrib><title>Predictors of Food and Physical Activity Tracking Among Young Adults</title><title>Health education & behavior</title><addtitle>Health Educ Behav</addtitle><description>Background:
Monitoring food intake and physical activity (PA) using tracking applications may support behavior change. However, few longitudinal studies identify the characteristics of young adults who track their behavior, findings that could be useful in designing tracking-related interventions. Our objective was to identify predictors of past-year food and PA tracking among young adults.
Methods:
Data were available for 676 young adults participating in the ongoing longitudinal Nicotine Dependence in Teens Study. Potential predictors were measured in 2017–2020 at age 31, and past-year food and PA tracking were measured in 2021–2022 at age 34. Each potential predictor was studied in a separate multivariable logistic regression model controlling for age, sex, and educational attainment.
Results:
One third (37%) of participants reported past-year PA tracking; 14% reported past-year food, and 10% reported both. Nine and 11 of 41 potential predictors were associated with food and PA tracking, respectively. Compensatory behaviors after overeating, trying to lose weight, self-report overweight, reporting a wide variety of exercise behaviors, and pressure to lose weight predicted both food and PA tracking.
Conclusion:
Food and PA tracking are relatively common among young adults. If the associations observed herein between compensatory behavior after overeating and tracking (among other observed associations) are replicated and found to be causal, caution may need to be exercised in making “blanket” recommendations to track food intake and/or PA to all young adults seeking behavior change.</description><subject>Adolescents</subject><subject>Adults</subject><subject>Age</subject><subject>Behavior</subject><subject>Behavior change</subject><subject>Behavior Modification</subject><subject>Body Weight</subject><subject>Change agents</subject><subject>Compensation</subject><subject>Compensatory behaviour</subject><subject>Drug dependence</subject><subject>Eating Habits</subject><subject>Educational attainment</subject><subject>Exercise</subject><subject>Food</subject><subject>Food intake</subject><subject>Health Behavior</subject><subject>Individual Characteristics</subject><subject>Life Style</subject><subject>Longitudinal studies</subject><subject>Measurement Equipment</subject><subject>Multivariable control</subject><subject>Nicotine</subject><subject>Obesity</subject><subject>Physical activity</subject><subject>Physical Activity Level</subject><subject>Predictor Variables</subject><subject>Regression models</subject><subject>Self report</subject><subject>Social Influences</subject><subject>Tracking</subject><subject>Weight loss</subject><subject>Young Adults</subject><subject>Youth Health</subject><issn>1090-1981</issn><issn>1552-6127</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>7QJ</sourceid><recordid>eNqFkUlvFDEQhVsIRBb4ARxALXHh0omrvJ_QKGQBRSKHcOBkObZn4tDTTuzuSPPv8WjChEURl7Kl99XzK1fTvAFyACDlIRBNQCtACsC1kPpZswucYycA5fN6r3q3BnaavVJuCCFCE_6y2aFCM6TIdptPFzn46MaUS5vm7UlKvrWDby-uVyU627czN8b7OK7ay2zdjzgs2tky1fo9Teu7n_qxvGpezG1fwuuHc7_5dnJ8eXTWnX89_Xw0O-8cRxw7oIF5RKsoOOolsVwKqIWjo5xIqwMqSr1izANHycUVp0whSCVUHQXpfvNx43s7XS2Dd2EYs-3NbY5Lm1cm2Wj-VIZ4bRbp3gBhGhll1eHDg0NOd1Moo1nG4kLf2yGkqRhUmhCklPH_o1LVSBypruj7v9CbNOWhfkU1FChRMEorBRvK5VRKDvNtcCBmvU_zzz5rz7vfJ952_FpgBd5ugJCj28rHX4DWcHKtH2z0YhfhMdbTL_4Et4Wtvw</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>O’Loughlin, Erin K.</creator><creator>Marashi, Maryam</creator><creator>Sabiston, Catherine M.</creator><creator>Lucibello, Kristen M.</creator><creator>Sylvestre, Marie-Pierre</creator><creator>O’Loughlin, Jennifer L.</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AFRWT</scope><scope>7SW</scope><scope>BJH</scope><scope>BNH</scope><scope>BNI</scope><scope>BNJ</scope><scope>BNO</scope><scope>ERI</scope><scope>PET</scope><scope>REK</scope><scope>WWN</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QJ</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-3104-3148</orcidid><orcidid>https://orcid.org/0000-0001-7240-7588</orcidid></search><sort><creationdate>20231001</creationdate><title>Predictors of Food and Physical Activity Tracking Among Young Adults</title><author>O’Loughlin, Erin K. ; Marashi, Maryam ; Sabiston, Catherine M. ; Lucibello, Kristen M. ; Sylvestre, Marie-Pierre ; O’Loughlin, Jennifer L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c522t-13e4d22a831c3d70a5761a5752c3507a9e2833d844d152756b534821786810923</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Adolescents</topic><topic>Adults</topic><topic>Age</topic><topic>Behavior</topic><topic>Behavior change</topic><topic>Behavior Modification</topic><topic>Body Weight</topic><topic>Change agents</topic><topic>Compensation</topic><topic>Compensatory behaviour</topic><topic>Drug dependence</topic><topic>Eating Habits</topic><topic>Educational attainment</topic><topic>Exercise</topic><topic>Food</topic><topic>Food intake</topic><topic>Health Behavior</topic><topic>Individual Characteristics</topic><topic>Life Style</topic><topic>Longitudinal studies</topic><topic>Measurement Equipment</topic><topic>Multivariable control</topic><topic>Nicotine</topic><topic>Obesity</topic><topic>Physical activity</topic><topic>Physical Activity Level</topic><topic>Predictor Variables</topic><topic>Regression models</topic><topic>Self report</topic><topic>Social Influences</topic><topic>Tracking</topic><topic>Weight loss</topic><topic>Young Adults</topic><topic>Youth Health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>O’Loughlin, Erin K.</creatorcontrib><creatorcontrib>Marashi, Maryam</creatorcontrib><creatorcontrib>Sabiston, Catherine M.</creatorcontrib><creatorcontrib>Lucibello, Kristen M.</creatorcontrib><creatorcontrib>Sylvestre, Marie-Pierre</creatorcontrib><creatorcontrib>O’Loughlin, Jennifer L.</creatorcontrib><collection>Sage Journals GOLD Open Access 2024</collection><collection>ERIC</collection><collection>ERIC (Ovid)</collection><collection>ERIC</collection><collection>ERIC</collection><collection>ERIC (Legacy Platform)</collection><collection>ERIC( SilverPlatter )</collection><collection>ERIC</collection><collection>ERIC PlusText (Legacy Platform)</collection><collection>Education Resources Information Center (ERIC)</collection><collection>ERIC</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Health education & behavior</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>O’Loughlin, Erin K.</au><au>Marashi, Maryam</au><au>Sabiston, Catherine M.</au><au>Lucibello, Kristen M.</au><au>Sylvestre, Marie-Pierre</au><au>O’Loughlin, Jennifer L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1392374</ericid><atitle>Predictors of Food and Physical Activity Tracking Among Young Adults</atitle><jtitle>Health education & behavior</jtitle><addtitle>Health Educ Behav</addtitle><date>2023-10-01</date><risdate>2023</risdate><volume>50</volume><issue>5</issue><spage>647</spage><epage>657</epage><pages>647-657</pages><issn>1090-1981</issn><eissn>1552-6127</eissn><abstract>Background:
Monitoring food intake and physical activity (PA) using tracking applications may support behavior change. However, few longitudinal studies identify the characteristics of young adults who track their behavior, findings that could be useful in designing tracking-related interventions. Our objective was to identify predictors of past-year food and PA tracking among young adults.
Methods:
Data were available for 676 young adults participating in the ongoing longitudinal Nicotine Dependence in Teens Study. Potential predictors were measured in 2017–2020 at age 31, and past-year food and PA tracking were measured in 2021–2022 at age 34. Each potential predictor was studied in a separate multivariable logistic regression model controlling for age, sex, and educational attainment.
Results:
One third (37%) of participants reported past-year PA tracking; 14% reported past-year food, and 10% reported both. Nine and 11 of 41 potential predictors were associated with food and PA tracking, respectively. Compensatory behaviors after overeating, trying to lose weight, self-report overweight, reporting a wide variety of exercise behaviors, and pressure to lose weight predicted both food and PA tracking.
Conclusion:
Food and PA tracking are relatively common among young adults. If the associations observed herein between compensatory behavior after overeating and tracking (among other observed associations) are replicated and found to be causal, caution may need to be exercised in making “blanket” recommendations to track food intake and/or PA to all young adults seeking behavior change.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>36942324</pmid><doi>10.1177/10901981231159679</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-3104-3148</orcidid><orcidid>https://orcid.org/0000-0001-7240-7588</orcidid><oa>free_for_read</oa></addata></record> |
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| source | Access via SAGE; Applied Social Sciences Index & Abstracts (ASSIA); Alma/SFX Local Collection |
| subjects | Adolescents Adults Age Behavior Behavior change Behavior Modification Body Weight Change agents Compensation Compensatory behaviour Drug dependence Eating Habits Educational attainment Exercise Food Food intake Health Behavior Individual Characteristics Life Style Longitudinal studies Measurement Equipment Multivariable control Nicotine Obesity Physical activity Physical Activity Level Predictor Variables Regression models Self report Social Influences Tracking Weight loss Young Adults Youth Health |
| title | Predictors of Food and Physical Activity Tracking Among Young Adults |
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