Research Original Research: Brief| Volume 120, ISSUE 9, P1557-1567, September 2020

Download started.


Using a Socioecological Approach to Identify Factors Associated with Adolescent Sugar-Sweetened Beverage Intake

Published:April 22, 2020DOI:



      Adolescents are among the highest consumers of sugar-sweetened beverages (SSBs) in the United States. More research is needed to understand the relationship of multiple levels of influence on adolescent SSB intake across the socioecological model in a nationally representative sample.


      This secondary analysis of cross-sectional data aims to explain variance in adolescent SSB intake by exploring the associations of adolescent demographic (ie, age, race/ethnicity, and parent socioeconomic status), intrapersonal (ie, behavioral intention, self-efficacy, and media perception), interpersonal (ie, social norms and perceived parenting practices), and home availability variables.


      This study included 1,560 adolescents who participated in the 2014 National Cancer Institute-sponsored cross-sectional Family, Life, Activity, Sun, Health, and Eating study. Descriptive statistics, analyses of variance, and stepwise multiple linear regression models were used to explore factors associated with SSB intake. In the stepwise regression, a 4-step model was analyzed with each subsequent step adding variables from different socioecological model levels.


      The final step that included 14 variables individually associated with SSB intake significantly predicted 16.5% of the variance in SSB intake. Four variables were associated with higher SSB intake in the final step when controlling for all other variables: male sex (β=.066), non-Hispanic black vs non-Hispanic white (β=.123), adolescent’s report of having parents allow them to have SSBs on a bad day (β=.150), and home SSB availability (β=.263). Race/ethnicity other than Hispanic and/or non-Hispanic black vs non-Hispanic white was associated with lower intake (β= –.092).


      When considering potential targets for multilevel behavioral interventions aimed at reducing adolescent SSB intake, emphasis on reducing SSB availability at home may be especially important. Furthermore, although adolescence is a period of increasing independence, parent influence on adolescent’s health behaviors may also be a key intervention target. Home and parental SSB factors may be more important than targeting intrapersonal factors and social norms among adolescents.


      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Journal of the Academy of Nutrition and Dietetics
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Luger M.
        • Lafontan M.
        • Bes-Rastrollo M.
        • Winzer E.
        • Yumuk V.
        • Farpour-Lambert N.
        Sugar-sweetened beverages and weight gain in children and adults: A systematic review from 2013 to 2015 and a comparison with previous studies.
        Obesity Facts. 2017; 10: 674-693
        • Marshall T.A.
        • Curtis A.M.
        • Cavanaugh J.E.
        • Warren J.J.
        • Levy S.M.
        Child and adolescent sugar-sweetened beverage intakes are longitudinally associated with higher body mass index z scores in a birth cohort followed 17 years.
        J Acad Nutr Diet. 2019; 119: 425-434
        • Kim S.
        • Park S.
        • Lin M.
        Permanent tooth loss and sugar-sweetened beverage intake in US young adults.
        J Public Health Dent. 2017; 77: 148-154
        • Bernabé E.
        • Vehkalahti M.M.
        • Sheiham A.
        • Aromaa A.
        • Suominen A.L.
        Sugar-sweetened beverages and dental caries in adults: A 4-year prospective study.
        J Dent. 2014; 42: 952-958
        • Huang C.
        • Huang J.
        • Tian Y.
        • Yang X.
        • Gu D.
        Sugar sweetened beverages consumption and risk of coronary heart disease: A meta-analysis of prospective studies.
        Atherosclerosis. 2014; 234: 11-16
        • Imamura F.
        • O’Connor L.
        • Ye Z.
        • et al.
        Consumption of sugar sweetened beverages, artificially sweetened beverages, and fruit juice and incidence of type 2 diabetes: Systematic review, meta-analysis, and estimation of population attributable fraction.
        BMJ. 2015; 351: h3576
        • Rosinger A.
        • Herrick K.
        • Gahche J.
        • Park S.
        Sugar-sweetened beverage consumption among US youth, 2011-2014.
        National Center for Health Statistics, Washington, DC2017 (NCHS Data Brief no. 271)
        • Haughton C.F.
        • Waring M.E.
        • Wang M.L.
        • Rosal M.C.
        • Pbert L.
        • Lemon S.C.
        Home matters: Adolescents drink more sugar-sweetened beverages when available at home.
        J Pediatr. 2018; 202: 121-128
        • Vos M.B.
        • Kaar J.L.
        • Welsh J.A.
        • et al.
        Added sugars and cardiovascular disease risk in children: A scientific statement from the American Heart Association.
        Circulation. 2017; 135: e1017-e1034
        • Davison K.K.
        • Birch L.L.
        Childhood overweight: A contextual model and recommendations for future research.
        Obes Rev. 2001; 2: 159-171
        • Lane H.
        • Porter K.
        • Estabrooks P.
        • Zoellner J.
        A systematic review to assess sugar-sweetened beverage interventions for children and adolescents across the socioecological model.
        J Acad Nutr Diet. 2016; 116 (e1296): 1295-1307
        • Rimer B.K.
        • Glanz K.
        Theory at a Glance: A Guide for Health Promotion Practice.
        National Cancer Institute, Washington,DC2005
        • Kassem N.O.
        • Lee J.W.
        Understanding soft drink consumption among male adolescents using the Theory of Planned Behavior.
        J Behav Med. 2004; 27: 273-296
        • Kassem N.O.
        • Lee J.W.
        • Modeste N.N.
        • Johnston P.K.
        Understanding soft drink consumption among female adolescents using the Theory of Planned Behavior.
        Health Educ Res. 2003; 18: 278-291
        • Cervi M.M.
        • Agurs-Collins T.
        • Dwyer L.A.
        • Thai C.L.
        • Moser R.P.
        • Nebeling L.C.
        Susceptibility to food advertisements and sugar-sweetened beverage intake in non-Hispanic black and non-Hispanic white adolescents.
        J Comm Health. 2017; 42: 748-756
        • Riebl S.K.
        • MacDougal C.
        • Hill C.
        • et al.
        Beverage choices of adolescents and their parents using the Theory of Planned Behavior: A mixed methods analysis.
        J Acad Nutr Diet. 2016; 116 (e221): 226-239
        • Van der Horst K.
        • Kremers S.
        • Ferreira I.
        • Singh A.
        • Oenema A.
        • Brug J.
        Perceived parenting style and practices and the consumption of sugar-sweetened beverages by adolescents.
        Health Educ Res. 2006; 22: 295-304
        • Fleary S.A.
        • Ettienne R.
        The relationship between food parenting practices, parental diet and their adolescents’ diet.
        Appetite. 2019; 135: 79-85
        • Watts A.W.
        • Miller J.
        • Larson N.I.
        • Eisenberg M.E.
        • Story M.T.
        • Neumark-Sztainer D.
        Multicontextual correlates of adolescent sugar-sweetened beverage intake.
        Eating Behav. 2018; 30: 42-48
        • De Bruijn G.-J.
        • Kremers S.P.
        • De Vries H.
        • Van Mechelen W.
        • Brug J.
        Associations of social–environmental and individual-level factors with adolescent soft drink consumption: Results from the SMILE study.
        Health Educ Res. 2006; 22: 227-237
        • Park S.
        • Blanck H.M.
        • Sherry B.
        • Brener N.
        • O'toole T.
        Factors associated with sugar-sweetened beverage intake among United States high school students.
        J Nutr. 2012; 142: 306-312
        • Park S.
        • Sherry B.
        • Foti K.
        • Blanck H.M.
        Self-reported academic grades and other correlates of sugar-sweetened soda intake among US adolescents.
        J Acad Nutr Diet. 2012; 112: 125-131
        • Hebden L.
        • Hector D.
        • Hardy L.L.
        • King L.
        A fizzy environment: Availability and consumption of sugar-sweetened beverages among school students.
        Prev Med. 2013; 56: 416-418
      1. Family Life, Activity, Sun, Health, and Eating (FLASHE) study.
        • Oh A.Y.
        • Davis T.
        • Dwyer L.A.
        • et al.
        Recruitment, enrollment, and response of parent–adolescent dyads in the FLASHE study.
        Am J Prev Med. 2017; 52: 849-855
        • Nebeling L.C.
        • Hennessy E.
        • Oh A.Y.
        • et al.
        The FLASHE study: Survey development, dyadic perspectives, and participant characteristics.
        Am J Prev Med. 2017; 52: 839-848
        • Epidemiology and Genomics Research Program
        • National Cancer Institute
        Dietary screener questionnaire in the NHANES 2009–2010: Background.
        (Updated February 13, 2018. Accessed April 15, 2019)
        • Centers for Disease Control and Prevention
        National Youth Physical Activity and Nutrition Survey.
        (Published 2010. Accessed April 15, 2019)
        • Levesque C.S.
        • Williams G.C.
        • Elliot D.
        • Pickering M.A.
        • Bodenhamer B.
        • Finley P.J.
        Validating the theoretical structure of the Treatment Self-Regulation Questionnaire (TSRQ) across three different health behaviors.
        Health Educ Res. 2006; 22: 691-702
      2. Self-determination theory. Perceived competence scales.
        • Hagler A.S.
        • Norman G.J.
        • Radick L.R.
        • Calfas K.J.
        • Sallis J.F.
        Comparability and reliability of paper-and computer-based measures of psychosocial constructs for adolescent fruit and vegetable and dietary fat intake.
        J Acad Nutr Diet. 2005; 105: 1758-1764
        • Birch L.L.
        • Fisher J.O.
        • Grimm-Thomas K.
        • Markey C.N.
        • Sawyer R.
        • Johnson S.L.
        Confirmatory factor analysis of the Child Feeding Questionnaire: A measure of parental attitudes, beliefs and practices about child feeding and obesity proneness.
        Appetite. 2001; 36: 201-210
        • Musher-Eizenman D.
        • Holub S.
        Comprehensive feeding practices questionnaire: Validation of a new measure of parental feeding practices.
        J Pediatr Psychol. 2007; 32: 960-972
        • Wardle J.
        • Sanderson S.
        • Guthrie C.A.
        • Rapoport L.
        • Plomin R.
        Parental feeding style and the inter-generational transmission of obesity risk.
        Obesity Res. 2002; 10: 453-462
        • Darling N.
        • Cumsille P.
        • Martínez M.L.
        Individual differences in adolescents’ beliefs about the legitimacy of parental authority and their own obligation to obey: A longitudinal investigation.
        Child Dev. 2008; 79: 1103-1118
        • Neumark-Sztainer D.R.
        • Wall M.M.
        • Haines J.I.
        • Story M.T.
        • Sherwood N.E.
        • van den Berg P.A.
        Shared risk and protective factors for overweight and disordered eating in adolescents.
        Am J Prev MEd. 2007; 33 (e353): 359-369
      3. SPSS [computer program]. Version 24. Armonk, NY: IBM-SPSS Inc; 2016.

        • Keith T.Z.
        Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling.
        Routledge, New York, NY2019
        • Bleich S.N.
        • Vercammen K.A.
        • Koma J.W.
        • Li Z.
        Trends in beverage consumption among children and adults, 2003-2014.
        Obesity. 2018; 26: 432-441
        • Lubke G.H.
        • Muthén B.O.
        Applying multigroup confirmatory factor models for continuous outcomes to Likert scale data complicates meaningful group comparisons.
        Struct Equ Modeling. 2004; 11: 514-534
        • Han E.
        • Powell L.M.
        Consumption patterns of sugar-sweetened beverages in the United States.
        J Acad Nutr Diet. 2013; 113: 43-53
        • Ogden C.L.
        • Fryar C.D.
        • Hales C.M.
        • Carroll M.D.
        • Aoki Y.
        • Freedman D.S.
        Differences in obesity prevalence by demographics and urbanization in US children and adolescents, 2013-2016.
        JAMA. 2018; 319: 2410-2418
        • Vargas-Garcia E.
        • Evans C.
        • Prestwich A.
        • Sykes-Muskett B.
        • Hooson J.
        • Cade J.
        Interventions to reduce consumption of sugar-sweetened beverages or increase water intake: Evidence from a systematic review and meta-analysis.
        Obes Rev. 2017; 18: 1350-1363
        • Wang Y.C.
        • Bleich S.N.
        • Gortmaker S.L.
        Increasing caloric contribution from sugar-sweetened beverages and 100% fruit juices among US children and adolescents, 1988–2004.
        Pediatrics. 2008; 121: e1604-e1614
        • Flynn M.
        • McNeil D.
        • Maloff B.
        • et al.
        Reducing obesity and related chronic disease risk in children and youth: A synthesis of evidence with ‘best practice’recommendations.
        Obes Rev. 2006; 7: 7-66
        • Van Der Horst K.
        • Oenema A.
        • Ferreira I.
        • et al.
        A systematic review of environmental correlates of obesity-related dietary behaviors in youth.
        Health Educ Res. 2006; 22: 203-226
        • Scaglioni S.
        • Salvioni M.
        • Galimberti C.
        Influence of parental attitudes in the development of children eating behaviour.
        Brit J Nutr. 2008; 99: S22-S25
        • Ma Z.
        • Hample D.
        Modeling parental influence on teenagers’ food consumption: An analysis using the Family Life, Activity, Sun, Health, and Eating (FLASHE) survey.
        J Nutr Educ Behav. 2018; 50: 1005-1014


      M. Yuhas is a postdoctoral associate, Department of Public Health Sciences, University of Virginia, Christiansburg, VA.


      K. J. Porter is an assistant professor, Department of Public Health Sciences, University of Virginia, Christiansburg, VA.


      J. M. Zoellner is an associate professor, Department of Public Health Sciences, University of Virginia, Christiansburg, VA.


      V. Hedrick is an assistant professor, Department of Human Nutrition, Foods, and Exercise, Virginia Polytechnic Institute and State University, Blacksburg, VA.