Multicontextual correlates of adolescent sugar-sweetened beverage intake.

Allison W Watts, Jon Miller, Nicole I Larson, Marla E Eisenberg, Mary T Story, Dianne Neumark-Sztainer
Author Information
  1. Allison W Watts: Division of Epidemiology and Community Health, University of Minnesota, 1300 South 2(nd) Street, Suite 300, Minneapolis, MN 55454, USA. Electronic address: awwatts@umn.edu.
  2. Jon Miller: Division of Epidemiology and Community Health, University of Minnesota, 1300 South 2(nd) Street, Suite 300, Minneapolis, MN 55454, USA.
  3. Nicole I Larson: Division of Epidemiology and Community Health, University of Minnesota, 1300 South 2(nd) Street, Suite 300, Minneapolis, MN 55454, USA.
  4. Marla E Eisenberg: Department of Pediatrics and Adolescent Health, University of Minnesota, 717 Delaware St SE, Minneapolis, MN 55414, USA.
  5. Mary T Story: Community and Family Medicine and Global Health, Duke University, Duke Global Health Institute, Box 90519, Durham, NC 27708, USA.
  6. Dianne Neumark-Sztainer: Division of Epidemiology and Community Health, University of Minnesota, 1300 South 2(nd) Street, Suite 300, Minneapolis, MN 55454, USA.

Abstract

PURPOSE: To examine personal, home, peer, school, neighborhood, and media correlates of sugar-sweetened beverage (SSB) intake in a diverse sample of adolescents.
METHODS: Cross-sectional, population-based study (EAT 2010: Eating and Activity in Teens) of 2793 adolescents (54% female, mean age [SD] = 14.5 [2.0], 80% nonwhite) attending public secondary schools in Minneapolis-St. Paul, Minnesota. Adolescents completed a food frequency questionnaire and answered survey questions about their diet/health perceptions and behaviors. Socio-environmental data were collected from parents/caregivers, peers, school personnel, Geographic Information Systems (e.g., distance to food outlet), and a content analysis of favorite TV shows. Individual and mutually adjusted mixed-effects regression models examined associations between multi-contextual factors and estimated daily servings of SSB, controlling for relevant covariates.
RESULTS: The contextual factors examined accounted for 24% of the variance in adolescents' SSB consumption. The proportion of variance explained by each context was 13% personal, 16% home/family, 3% peer, 1% school, 0.1% media, and 0% neighborhood. The strongest correlate of SSB intake was home soda availability (adjusted for covariates: β = 0.26, p < 0.01; adjusted for all multi-contextual factors: β = 0.18, p < 0.01). Other significant correlates of SSB intake included personal behaviors (e.g., fast food intake, sleep), home/family factors (e.g., parent modeling) and peer influences (e.g., friends' SSB intake).
CONCLUSIONS: Public health policies and programs to reduce adolescent SSB intake should target personal behaviors (e.g., limit fast food, encourage adequate sleep), address the home setting (e.g., help parents to reduce SSB availability and model healthy eating habits) and involve peers (e.g., identify and enable peers to model healthy eating behaviors).

Keywords

References

  1. J Am Diet Assoc. 1999 Apr;99(4):436-41 [PMID: 10207395]
  2. J Am Diet Assoc. 2002 Mar;102(3 Suppl):S40-51 [PMID: 11902388]
  3. J Am Diet Assoc. 2002 Sep;102(9):1234-9 [PMID: 12792618]
  4. Prev Med. 2003 Sep;37(3):198-208 [PMID: 12914825]
  5. Int J Behav Nutr Phys Act. 2007 Dec 18;4:66 [PMID: 18088416]
  6. Crit Rev Food Sci Nutr. 2010 Mar;50(3):228-58 [PMID: 20301013]
  7. Public Health Nutr. 2010 Nov;13(11):1757-63 [PMID: 20529405]
  8. Pediatrics. 2010 Oct;126(4):e754-61 [PMID: 20876172]
  9. J Transp Land Use. 2010 Apr 1;3(1):43-65 [PMID: 21837264]
  10. Public Health Nutr. 2012 Apr;15(4):627-34 [PMID: 21929844]
  11. Appetite. 2012 Feb;58(1):1-5 [PMID: 22001023]
  12. Prev Med. 2012 Jan;54(1):77-81 [PMID: 22024221]
  13. Int J Adolesc Med Health. 2011;23(3):279-86 [PMID: 22191196]
  14. J Nutr. 2012 Feb;142(2):306-12 [PMID: 22223568]
  15. Int J Environ Res Public Health. 2012 Apr;9(4):1458-71 [PMID: 22690205]
  16. Appetite. 2013 Jan;60(1):140-147 [PMID: 23022556]
  17. Am J Prev Med. 2013 Jan;44(1):48-55 [PMID: 23253649]
  18. Prev Med. 2013 Jun;56(6):416-8 [PMID: 23480973]
  19. Obesity (Silver Spring). 2013 Sep;21(9):1858-69 [PMID: 23512596]
  20. Am J Clin Nutr. 2013 Jul;98(1):180-8 [PMID: 23676424]
  21. Appl Physiol Nutr Metab. 2013 Jul;38(7):789-94 [PMID: 23980738]
  22. JAMA Pediatr. 2014 Mar;168(3):279-86 [PMID: 24473632]
  23. J Nutr Educ Behav. 2014 Jul-Aug;46(4):277-85 [PMID: 24735768]
  24. Am J Prev Med. 2014 Jun;46(6):605-16 [PMID: 24842737]
  25. J Acad Nutr Diet. 2014 Oct;114(10):1569-1579.e1 [PMID: 25066057]
  26. Int J Eat Disord. 2015 Sep;48(6):759-66 [PMID: 25139262]
  27. Br J Nutr. 2015 Dec 14;114(11):1941-7 [PMID: 26400488]
  28. J Am Coll Cardiol. 2015 Oct 6;66(14):1615-1624 [PMID: 26429086]
  29. JAMA. 2016 Feb 2;315(5):457-8 [PMID: 26746707]
  30. Prev Med. 2016 Jun;87:194-199 [PMID: 26970036]
  31. J Adolesc Health. 2016 Jul;59(1):17-23 [PMID: 27021401]
  32. Prev Chronic Dis. 2016 May 19;13:E66 [PMID: 27197079]
  33. J Nutr. 2016 Jul;146(7):1348-55 [PMID: 27281807]
  34. Int J Behav Nutr Phys Act. 2016 Jun 14;13:68 [PMID: 27301414]
  35. Appl Physiol Nutr Metab. 2016 Jun;41(6 Suppl 3):S294-302 [PMID: 27306435]
  36. Circulation. 2017 May 9;135(19):e1017-e1034 [PMID: 27550974]
  37. J Am Diet Assoc. 1995 Mar;95(3):336-40 [PMID: 7860946]
  38. Prev Med. 1997 Nov-Dec;26(6):808-16 [PMID: 9388792]

Grants

  1. R01 HL127077/NHLBI NIH HHS
  2. T32 CA163184/NCI NIH HHS

MeSH Term

Adolescent
Beverages
Cross-Sectional Studies
Dietary Sugars
Feeding Behavior
Female
Humans
Male
Minnesota
Multivariate Analysis
Risk Factors
Social Environment
Surveys and Questionnaires
Sweetening Agents

Chemicals

Dietary Sugars
Sweetening Agents

Word Cloud

Created with Highcharts 10.0.0SSBintakeegbehaviorspersonalfoodhomepeerschoolcorrelatespeersadjustedfactorsneighborhoodmediasugar-sweetenedbeverageadolescentsEatingAdolescentsexaminedmulti-contextualvariancehome/family1%availabilityβ = 0p < 001fastsleepreduceadolescentmodelhealthyeatingPURPOSE:examinediversesampleMETHODS:Cross-sectionalpopulation-basedstudyEAT2010:ActivityTeens279354%femalemeanage[SD] = 145[20]80%nonwhiteattendingpublicsecondaryschoolsMinneapolis-StPaulMinnesotacompletedfrequencyquestionnaireansweredsurveyquestionsdiet/healthperceptionsSocio-environmentaldatacollectedparents/caregiverspersonnelGeographicInformationSystemsdistanceoutletcontentanalysisfavoriteTVshowsIndividualmutuallymixed-effectsregressionmodelsassociationsestimateddailyservingscontrollingrelevantcovariatesRESULTS:contextualaccounted24%adolescents'consumptionproportionexplainedcontext13%16%3%00%strongestcorrelatesodacovariates:26factors:18significantincludedparentmodelinginfluencesfriends'CONCLUSIONS:PublichealthpoliciesprogramstargetlimitencourageadequateaddresssettinghelpparentshabitsinvolveidentifyenableMulticontextualEnvironmentSugar-sweetenedbeverages

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