Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Parental optimism about childhood obesity-related disease risks

International Journal of Obesity volume 41, pages 1467–1472 (2017)Cite this article

Subjects

Abstract

Objectives:

Most parents believe childhood obesity is a problem for society, but not for their own children. We sought to understand whether parents’ risk assessment was skewed by optimism, the tendency to overestimate one’s chances of experiencing positive events.

Methods:

We administered a national web-based survey to 502 parents of 5–12-year-old children. Parents reported the chances that (a) their child and (b) ‘a typical child in their community’ would be overweight or obese, and develop hypertension, heart disease, type 2 diabetes and depression in adulthood. Respondents self-reported demographic and health information, and we obtained demographic and health information about the typical child using zip code-level census and lifestyle data. We used regression models with fixed effects to evaluate whether optimism bias was present in parent predictions of children’s future health outcomes.

Results:

Parents had 40 times lower adjusted odds (OR=0.025, P<0.001, 99% CI: 0.006, 0.100) of predicting that their child (versus a typical child) would be overweight or obese in adulthood. Of the 20% of parents who predicted their child would be overweight in adulthood, 93% predicted the typical child would also be overweight in adulthood. Controlling for health and demographic characteristics, parents estimated that their children’s chances of developing obesity-related comorbidities would be 12–14 percentage points lower those that of a typical child.

Conclusions:

Parent risk assessment is skewed by optimism, among other characteristics. More accurate risk perception could motivate parents to engage in behavior change.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. Moore LC, Harris CV, Bradlyn AS . Exploring the relationship between parental concern and the management of childhood obesity. Matern Child Health J 2012; 16: 902–908.

    Article  Google Scholar 

  2. Chen HY, Lemon SC, Pagoto SL, Barton BA, Lapane KL, Goldberg RJ . Personal and parental weight misperception and self-reported attempted weight loss in US children and adolescents, National Health and Nutrition Examination Survey, 2007-2008 and 2009-2010. Prev Chronic Dis 2014; 11: E132.

    Article  Google Scholar 

  3. Doolen J, Alpert PT, Miller SK . Parental disconnect between perceived and actual weight status of children: a metasynthesis of the current research. J Am Acad Nurse Pract 2009; 21: 160–166.

    Article  Google Scholar 

  4. Katz DL . Oblivobesity: looking over the overweight that parents keep overlooking. Child Obes 2015; 11: 225–226.

    Article  Google Scholar 

  5. Parry LL, Netuveli G, Parry J, Saxena S . A systematic review of parental perception of overweight status in children. J Ambul Care Manage 2008; 31: 253–268.

    Article  Google Scholar 

  6. Rietmeijer-Mentink M, Paulis WD, van Middelkoop M, Bindels PJ, van der Wouden JC . Difference between parental perception and actual weight status of children: a systematic review. Matern Child Nutr 2013; 9: 3–22.

    Article  Google Scholar 

  7. Weinstein MC, Torrance G, McGuire A . QALYs: the basics. Value Health 2009; 12 (Suppl 1): S5–S9.

    Article  Google Scholar 

  8. Wright DR, Lozano P, Dawson-Hahn E, Christakis DA, Haaland WL, Basu A . Parental predictions and perceptions regarding long-term childhood obesity-related health risks. Acad Pediatr 2016; 16: 475–481.

    Article  Google Scholar 

  9. RWJF, NPR, Harvard School of Public Health. A Poll about children and weight: crunch time during the American work and school week—3 pm to bed 2013.

  10. Vedantam S Your child's fat, mine's fine: rose-colored glasses and the obesity epidemic. In: NPR Shots: Health News from NPR. National Public Radio: Washington, DC, 2013.

  11. Becker GS, Tomes N . Human capital and the rise and fall of families. J Labor Econ 1986; 4 (3 Pt. 2): 1–47.

    Article  CAS  Google Scholar 

  12. Becker GS . Health as human capital: synthesis and extensions. Oxford Econ Pap 2007; 59: 379–401.

    Article  Google Scholar 

  13. Weinstein N . Unrealistic optimism about future life events. J Pers Soc Psychol 1980; 39: 806–820.

    Article  Google Scholar 

  14. Sharot T . The optimism bias. Curr Biol 2011; 21: R941–R945.

    Article  CAS  Google Scholar 

  15. Barry CL, Gollust SE, McGinty EE, Niederdeppe J . Effects of messages from a media campaign to increase public awareness of childhood obesity. Obesity 2014; 22: 466–473.

    Article  Google Scholar 

  16. Barry CL, Brescoll VL, Brownell KD, Schlesinger M . Obesity metaphors: how beliefs about the causes of obesity affect support for public policy. Milbank Q 2009; 87: 7–47.

    Article  Google Scholar 

  17. Esri. 2010 Methodology Statement: Esri Data—Tapestry Segmentation for Block Groups and ZIP+4s. Esri: Redlands, CA, 2010.

  18. Vidmar S, Carlin J, Hesketh K . Standardizing anthropometric measures in children and adolescents with new functions for egen. Stata J 2004; 4: 50–55.

    Article  Google Scholar 

  19. Centers for Disease Control and Prevention. About BMI for adults. 2015. Available at: https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/.

  20. Centers for Disease Control and Prevention. About BMI for Children and Teens. Atlanta, 2014. Available at: https://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html.

  21. Ezzati M, Martin H, Skjold S, Vander Hoorn S, Murray CJ . Trends in national and state-level obesity in the USA after correction for self-report bias: analysis of health surveys. J R Soc Med 2006; 99: 250–257.

    Article  Google Scholar 

  22. Jain RB . Regression models to predict corrected weight, height and obesity prevalence from self-reported data: data from BRFSS 1999-2007. Int J Obes 2010; 34: 1655–1664.

    Article  CAS  Google Scholar 

  23. Weden MM, Brownell PB, Rendall MS, Lau C, Fernandes M, Nazarov Z . Parent-reported height and weight as sources of bias in survey estimates of childhood obesity. Am J Epidemiol 2013; 178: 461–473.

    Article  Google Scholar 

  24. Rendall MS, Weden MM, Lau C, Brownell P, Nazarov Z, Fernandes M . Evaluation of bias in estimates of early childhood obesity from parent-reported heights and weights. Am J Public Health 2014; 104: 1255–1262.

    Article  Google Scholar 

  25. Ogden CL, Carroll MD, Kit BK, Flegal KM . Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA 2014; 311: 806–814.

    Article  CAS  Google Scholar 

  26. Zhang X, Onufrak S, Holt JB, Croft JB . A multilevel approach to estimating small area childhood obesity prevalence at the census block-group level. Prev Chronic Dis 2013; 10: E68.

    Article  Google Scholar 

  27. StataCorpStata Statistical Software: Release 12. Statacorp LP: College Station, TX, 2011.

  28. Brown AW, Allison DB . Unintended consequences of obesity-targeted health policy. Virtual Mentor 2013; 15: 339–346.

    Article  Google Scholar 

  29. Robinson E, Sutin AR . Parents' perceptions of their children as overweight and children's weight concerns and weight gain. Psychol Sci 2017; 956797616682027.

  30. Gerards SM, Gubbels JS, Dagnelie PC, Kremers SP, Stafleu A, de Vries NK et al. Parental perception of child's weight status and subsequent BMIz change: the KOALA birth cohort study. BMC Public Health 2014; 14: 291.

    Article  Google Scholar 

  31. Hunger JM, Tomiyama AJ . Weight labeling and obesity: a longitudinal study of girls aged 10 to 19 years. JAMA Pediatr 2014; 168: 579–580.

    Article  Google Scholar 

  32. Sonneville KR, Thurston IB, Milliren CE, Kamody RC, Gooding HC, Richmond TK . Helpful or harmful? Prospective association between weight misperception and weight gain among overweight and obese adolescents and young adults. Int J Obes 2016; 40: 328–332.

    Article  CAS  Google Scholar 

  33. Barlow SE . Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics 2007; 120 (Suppl 4): S164–S192.

    Article  Google Scholar 

  34. Herzberg PY, Glaesmer H, Hoyer J . Separating optimism and pessimism: a robust psychometric analysis of the revised Life Orientation Test (LOT-R). Psychol Assess 2006; 18: 433–438.

    Article  Google Scholar 

  35. Epstein RM, Korones DN, Quill TE . Withholding information from patients—when less is more. N Engl J Med 2010; 362: 380–381.

    Article  CAS  Google Scholar 

  36. Fagerlin A, Zikmund-Fisher BJ, Ubel PA . Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst 2011; 103: 1436–1443.

    Article  Google Scholar 

  37. Oettinger MD, Finkle JP, Esserman D, Whitehead L, Spain TK, Pattishall SR et al. Color-coding improves parental understanding of body mass index charting. Acad Pediatr 2009; 9: 330–338.

    Article  Google Scholar 

  38. Sheridan SL, Halpern DJ, Viera AJ, Berkman ND, Donahue KE, Crotty K . Interventions for individuals with low health literacy: a systematic review. J Health Commun 2011; 16 (Suppl 3): 30–54.

    Article  Google Scholar 

  39. Garcia-Retamero R, Galesic M . Who profits from visual aids: overcoming challenges in people's understanding of risks (corrected). Soc Sci Med 2010; 70: 1019–1025.

    Article  Google Scholar 

  40. Rothman AJ, Bartels RD, Wlaschin J, Salovey P . The strategic use of gain- and loss-framed messages to promote healthy behavior: how theory can inform practice. J Commun 2006; 56: S202–S220.

    Article  Google Scholar 

  41. Johnson D, Fowler H . The evolution of overconfidence. Nature 2011; 477: 317–320.

    Article  CAS  Google Scholar 

  42. Rothman AJ, Salovey P . Shaping perceptions to motivate healthy behavior: the role of message framing. Psychol Bull 1997; 121: 3–19.

    Article  CAS  Google Scholar 

  43. Tversky A, Kahneman D . The framing of decisions and the psychology of choice. Science 1981; 211: 453–458.

    Article  CAS  Google Scholar 

  44. Fagerlin A, Ubel PA, Smith DM, Zikmund-Fisher BJ . Making numbers matter: present and future research in risk communication. Am J Health Behav 2007; 31 (Suppl 1): S47–S56.

    Article  Google Scholar 

  45. Witteman HO, Zikmund-Fisher BJ, Waters EA, Gavaruzzi T, Fagerlin A . Risk estimates from an online risk calculator are more believable and recalled better when expressed as integers. J Med Internet Res 2011; 13: e54.

    Article  Google Scholar 

  46. Zikmund-Fisher BJ, Witteman HO, Dickson M, Fuhrel-Forbis A, Kahn VC, Exe NL et al. Blocks, ovals, or people? Icon type affects risk perceptions and recall of pictographs. Med Decis Making 2014; 34: 443–453.

    Article  Google Scholar 

  47. Black JA, Park M, Gregson J, Falconer CL, White B, Kessel AS et al. Child obesity cut-offs as derived from parental perceptions: cross-sectional questionnaire. Br J Gen Pract 2015; 65: e234–e239.

    Article  Google Scholar 

  48. De La OA, Jordan KC, Ortiz K, Moyer-Mileur LJ, Stoddard G, Friedrichs M et al. Do parents accurately perceive their child's weight status? J Pediatr Health Care 2009; 23: 216–221.

    Article  Google Scholar 

  49. Gillespie J, Midmore C, Hoeflich J, Ness C, Ballard P, Stewart L . Parents as the start of the solution: a social marketing approach to understanding triggers and barriers to entering a childhood weight management service. J Hum Nutr Diet 2015; 28 (Suppl 1): S83–S92.

    Article  Google Scholar 

Download references

Acknowledgements

This work was funded by the University of Washington Nutrition Obesity Research Center (P30 DK035816). The research presented in this paper is that of the authors and does not reflect the official policy of the funders. The authors thank Waylon Howard, PhD (Seattle Children’s Research Institute) for his review and comments on this manuscript. Financial support for this study was provided by a grant from the University of Washington Nutrition Obesity Research Center (P30 DK035816). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing and publishing the report. ED-H’s time was supported by the Rush L. Kirschstein National Research Service Award (T32HP10002). DRW’s time was supported by The University of Washington Institute for Translational Health Sciences (UL1 TR000423) and NHLBI (K01HL130413) and WLH’s (Seattle Children’s Research Institute) time was supported by the Seattle Children’s Research Institute.

Author contributions

DRW (University of Washington & Seattle Children’s Research Institute) had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. DRW conceptualized and designed the study, obtained funding, analyzed and interpreted the data and wrote the initial manuscript. PL (Kaiser Permanente Health Research Institute), ED-H (University of Washington & Seattle Children’s Research Institute), DAC (University of Washington & Seattle Children’s Research Institute), WLH (Seattle Children’s Research Institute) and AB (University of Washington) all contributed to the study design and interpretation of data, and critically reviewed and revised the manuscript.

Author information

Authors and Affiliations

  1. Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA

    D R Wright, E Dawson-Hahn & D A Christakis

  2. Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, USA

    D R Wright, E Dawson-Hahn, D A Christakis & W L Haaland

  3. Kaiser Permanente Health Research Institute, Seattle, WA, USA

    P Lozano

  4. Department of Pharmacy, University of Washington School of Pharmacy, Seattle, WA, USA

    P Lozano & A Basu

Authors
  1. D R Wright
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P Lozano
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E Dawson-Hahn
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D A Christakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. W L Haaland
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. A Basu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to D R Wright.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies this paper on International Journal of Obesity website

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wright, D., Lozano, P., Dawson-Hahn, E. et al. Parental optimism about childhood obesity-related disease risks. Int J Obes 41, 1467–1472 (2017). https://doi.org/10.1038/ijo.2017.103

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ijo.2017.103

This article is cited by

Search

Advanced search

Quick links