Advertisement

Canadian Journal of Public Health

, Volume 101, Issue 1, pp 56–60 | Cite as

The Epidemiology of Weight Perception: Perceived Versus Self-reported Actual Weight Status among Albertan Adults

  • Jordana Linder
  • Lindsay McLaren
  • Geraldine Lo Siou
  • Ilona Csizmadi
  • Paula J. Robson
Quantitative Research

Abstract

Background

To understand, prevent, and manage weight-related health issues, researchers and clinicians rely on the ability to identify those at risk. Prevention and management strategies may also rely on accurate self-perception of weight and body composition in the general population.

Methods

We analyzed data from The Tomorrow Project® (n=7,436), a prospective cohort study enrolling adults aged 35–69 years, in Alberta, Canada. Weight perception accuracy was defined based on body mass index (BMI), waist circumference (WC), and a combined (BMI and WC) risk profile.

Results

The majority of participants correctly perceived themselves as overweight. Women were more accurate than men in identifying themselves as overweight. In terms of inaccuracy, more normal-weight women than men perceived themselves to be overweight, while more overweight men than women perceived themselves as about the right weight. When using the combined risk profile, all men with normal weight (BMI) but higher risk WC perceived their weight as about right whereas just under half of men who were overweight (BMI) but lower risk WC perceived their weight as about right. For women, a much higher proportion recognized their weight status as overweight when only BMI was elevated compared to when only WC indicated higher risk.

Discussion

Adults in our sample showed reasonable accuracy in weight perception. Gender differences reveal that women were more accurate than men in identifying themselves as overweight. Incongruence between weight status indicators was noted, indicating the importance of using both BMI and waist circumference as health status measures.

Keywords

Weight perception body mass index waist circumference obesity 

Résumé

Contexte

Pour comprendre, prévenir et gérer les problèmes de santé liés au poids, les chercheurs et les cliniciens doivent pouvoir identifier les personnes à risque. Les stratégies de prévention et de gestion peuvent aussi faire appel à l’autoperception correcte du poids et de la composition corporelle dans la population générale.

Méthode

Nous avons analysé les données du projet The Tomorrow Project® (n=7 436), une étude prospective de cohortes d’adultes de 35 à 69 ans menée en Alberta, au Canada. Nous avons défini l’exactitude de la perception du poids d’après l’indice de masse corporelle (IMC), le périmètre ombilical (PO) et le profil de risque combiné (IMC et PO).

Résultats

La majorité des participants se percevaient correctement comme ayant une surcharge pondérale. Les femmes étaient plus précises que les hommes à cet égard. Pour ce qui est de l’imprécision, davantage de femmes que d’hommes de poids normal se percevaient comme faisant de l’embonpoint, et davantage d’hommes que de femmes ayant un excès de poids se percevaient comme ayant un poids normal. Avec l’utilisation du profil de risque combiné, tous les hommes de poids normal (IMC) mais dont le PO constituait un risque plus élevé se percevaient comme ayant un poids normal, tandis qu’un peu moins de la moitié des hommes ayant une surcharge pondérale (IMC) mais dont le PO constituait un moindre risque considéraient avoir un poids normal. Chez les femmes, une proportion beaucoup plus grande reconnaissait faire de l’embonpoint lorsque seul l’IMC était élevé, comparativement aux femmes dont seul le PO constituait un risque plus élevé.

Discussion

Les adultes de notre échantillon avaient une perception raisonnablement exacte de leur poids. Les différences entre les sexes montrent que les femmes s’identifiaient plus correctement que les hommes comme ayant une surcharge pondérale. Nous avons cerné une incompatibilité entre les indicateurs de statut pondéral, ce qui dénote l’importance d’utiliser à la fois l’IMC et le périmètre ombilical comme mesures de l’état de santé.

Motsclés

perception du poids indice de masse corporelle périmètre ombilical obésité 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lau D, Douketis J, Morrison K, Hramiak I, Sharma A, Ur E. 2006 Canadian clinical practice guidelines on the management and prevention of obesity in adults and children. CMAJ 2007;176(8):1–13.CrossRefGoogle Scholar
  2. 2.
    Stein J. Fact sheet: Major causes of death in Canada, 1993–1995. Chron Dis Can 1997;18:91–92.Google Scholar
  3. 3.
    McLaren L, Beck CA, Patten SB, Fick GH, Adair CE. The relationship between body mass index and mental health: A population-based study of the effects of the definition of mental health. Soc Psychiatry Psychiatr Epidemiol 2008;43:63–71.CrossRefGoogle Scholar
  4. 4.
    Wardle J, Johnson F. Weight and dieting: Examining levels of weight concern in British adults. Int J Obes 2002;26:1144–49.CrossRefGoogle Scholar
  5. 5.
    Strauss RS. Self-reported weight status and dieting in a cross-sectional sample of young adolescents. Arch Pediatr Adolesc Med 1999;153:741–47.CrossRefGoogle Scholar
  6. 6.
    Kaltiala-Heino R, Kautiainen S, Virtanen SM, Rimpela A, Rimpela M. Has the adolescents’ weight concern increased over 20 years? Eur J Public Health 2003;13:4–10.CrossRefGoogle Scholar
  7. 7.
    Blokstra A, Burns CM, Seidell JC. Perception of weight status and dieting behaviour in Dutch men and women. Int J Obes 1999;23:7–18.CrossRefGoogle Scholar
  8. 8.
    Villaneva E. The validity of self-reported weight in US adults: A population based cross-sectional study. BMC Public Health 2002;1:11.Google Scholar
  9. 9.
    Paeratakul S, White MA, Williamson DA, Ryan DH, Bray GA. Sex, race/ethnicity, socioeconomic status, and BMI in relation to self-perception of overweight. Obes Res 2002;10(5):345–50.CrossRefGoogle Scholar
  10. 10.
    Whisenhunt BL, Williamson DA. Perceived weight status in normal weight and overweight women. Eat Behav 2002;3:229–38.CrossRefGoogle Scholar
  11. 11.
    Mack KA, Anderson L, Galuska D, Zablotsky D, Holtzman D, Ahluwalia I. Health and sociodemographic factors associated with body weight and weight objectives for women: Behavioural risk factor surveillance system. J Wom Health 2004;13(9):1019–32.CrossRefGoogle Scholar
  12. 12.
    Befort CA, Greiner KA, Hall S, Pulvers KM, Nollen NL, Charbonneau A, et al. Weight-related perceptions among patients and physicians: How well do physicians judge patients’ motivation to lose weight? J Gen Intern Med 2006;21:1086–90.CrossRefGoogle Scholar
  13. 13.
    Lean MEJ, Han TS, Morrison CE. Waist circumference as a measure for indicating need for weight management. Br Med J 1995;311:158–61. Available at: https://doi.org/www.bmj.com/cgi/content/full/311/6998/158 (Accessed March 15, 2009).CrossRefGoogle Scholar
  14. 14.
    Zhu S, Wang Z, Heshka S, Heo M, Faith MS, Heymsfield SB. Waist circumference and obesity-associated risk factors among whites in the third National Health and Nutrition Examination Survey: Clinical action thresholds. Am J Clin Nutr 2002;76:743–49.CrossRefGoogle Scholar
  15. 15.
    Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004;79:279–84.CrossRefGoogle Scholar
  16. 16.
    Murray S. Is waist-to-hip ratio a better marker of cardiovascular risk than body mass index? CMAJ 2006;174:308.Google Scholar
  17. 17.
    Pischon T, Boeing H, Hoffmann K, Bergmann M, Schulze MB, Overvad K, et al. General and abdominal adiposity and risk of death in Europe. NEJM 2008;359:2105–20.CrossRefGoogle Scholar
  18. 18.
    Bryant H, Robson PJ, Ullman R, Friedenreich C, Dawe U. Population-based cohort development in Alberta, Canada: A feasibility study. CDIC 2006;27(2):55–63.Google Scholar
  19. 19.
    Robson PJ, Lo Siou G, Ullman R, Bryant HE. Sociodemographic, health and lifestyle characteristics reported by discrete groups of adult dietary supplement users in Alberta, Canada: Findings from The Tomorrow Project. Public Health Nutr 2008;11(12):1238–47.CrossRefGoogle Scholar
  20. 20.
    Health Canada. Canadian Guidelines for Body Weight Classification in Adults, 2003. Available at: https://doi.org/www.hc-sc.gc.ca/fn-an/nutrition/weights-poids/guide-ld-adult/qa-qr-pub_e.html (Accessed January 7, 2008).Google Scholar
  21. 21.
    Collett D. Modelling Binary Data. London, UK: Chapman & Hall, 1991.CrossRefGoogle Scholar
  22. 22.
    Leemis LM, Trivedi KS. A comparison of approximate interval estimators for the Bernoulli Parameter. Am Statistician 1996;50(1):63–68.Google Scholar
  23. 23.
    Blaak E. Gender differences in fat metabolism. Curr Opin Clin Nutr Metab Care 2001;4(6);499-502.Google Scholar
  24. 24.
    Chang VW, Christakis NA. Self-perception of weight appropriateness in the United States. Am J Prev Med 2003;24(4):332–39.CrossRefGoogle Scholar
  25. 25.
    Bigaard J, Tjonneland A, Thomsen BL, Overvad K, Heitmann BL, Sorensen TI. Waist circumference, BMI, smoking, and mortality in middle-aged men and women. Obes Res 2003;11(7):895–903.CrossRefGoogle Scholar
  26. 26.
    Hojgaard B, Gyrd-Hansen D, Olsen KR, Sogaard J, Sorensen T. Waist circumference and body mass index as predictors of health care costs. Plos ONE 2008;3(7):e2619.Google Scholar
  27. 27.
    Zhang C, Rexrode KM, van Dam RM, Li TY, Hu FB. Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: Sixteen years of follow-up in US women. Circ 2008;117:1658–67.CrossRefGoogle Scholar
  28. 28.
    Orpana HM, Berthelot JM, Kaplan MS, Feeny DH, McFarland B, Ross NA. BMI and mortality: Results from a national longitudinal study of Canadian adults. Obes 2009;1:214–18.Google Scholar
  29. 29.
    Flegal KM, Graubard BI, Williamson DF, Gail MH. Excess deaths associated with underweight, overweight, and obesity. JAMA 2005;293:1861–67.CrossRefGoogle Scholar
  30. 30.
    Sharma AM, Kushner RF. A proposed clinical staging system for obesity. Int J Obes 2009; advance online publication:1–7.Google Scholar

Copyright information

© The Canadian Public Health Association 2010

Authors and Affiliations

  • Jordana Linder
    • 1
  • Lindsay McLaren
    • 1
  • Geraldine Lo Siou
    • 2
  • Ilona Csizmadi
    • 2
  • Paula J. Robson
    • 2
  1. 1.Department of Community Health SciencesUniversity of CalgaryCalgaryCanada
  2. 2.Alberta Health Services - Cancer CarePopulation Health ResearchCalgaryCanada

Personalised recommendations