Skip to main content
×
Home

A health assessment tool for multiple risk factors for obesity: age and sex differences in the prediction of body mass index

  • Julie A. Chambers (a1) and Vivien Swanson (a1)
Abstract

The aim was to establish the relative importance of multiple dietary, activity and other risk factors in determining BMI. A cross-sectional survey was conducted with 322 adults (71 % female; aged 18–79 years; BMI 16·5–40·9 kg/m2) using a previously developed, psychometrically tested, seventy-three-item questionnaire covering a wide range of obesity risk factors (consisting of five dietary, five activity and seven other risk factor subscales). Outcome was self-reported weight and height for BMI, cross-validated with items on clothes size and perceived need to lose weight. Stepwise regression analysis predicted 25–55 % of the variance in BMI with physical activity participation, current and past dieting behaviour, amount eaten, and age being the most important predictors. The association of lower BMI and younger age appeared to be due to higher activity levels, as younger participants reported much less healthy eating behaviour than the older age group. Amount eaten and physical activity participation were stronger predictors of BMI than other factors including healthy eating and use of mechanised transport. Results showed that the relationship between various risk factors and obesity may differ by both sex and age group, suggesting that different interventions may need to be targeted at different groups. The higher-risk eating behaviour observed in younger participants is of concern and needs to be addressed, if the current trend of rising obesity levels is to be halted.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      A health assessment tool for multiple risk factors for obesity: age and sex differences in the prediction of body mass index
      Available formats
      ×
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about sending content to Dropbox.

      A health assessment tool for multiple risk factors for obesity: age and sex differences in the prediction of body mass index
      Available formats
      ×
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about sending content to Google Drive.

      A health assessment tool for multiple risk factors for obesity: age and sex differences in the prediction of body mass index
      Available formats
      ×
Copyright
Corresponding author
*Corresponding author: Dr Julie A. Chambers, fax +44 1786 467641, email j.a.chambers@stir.ac.uk
References
Hide All
1Jebb SA, Kopelman P & Butland B (2007) Executive summary: Foresight Tackling Obesity: Future Choices Project. Obes Rev 8, Suppl. 1, viix.
2Flegal KM, Caroll MD, Ogden CL, et al. (2002) Prevalence and trends in obesity among US adults, 1990–2000. JAMA 288, 17231727.
3Monteiro CA, Moura EC, Conde WL, et al. (2004) Socioeconomic status and obesity in adult populations of developing countries: a review. Bull World Health Organ 82, 940946.
4Patterson RE, Frank LL, Kristal AR, et al. (2004) A comprehensive examination of health conditions associated with obesity in older adults. Am J Prev Med 27, 385390.
5Guh DP, Zhang W, Bansback N, et al. (2009) The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis. BMC Public Health 9, 88.
6Whitaker RC, Wright JA, Pepe MS, et al. (1997) Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med 337, 869873.
7Whitaker RC & Dietz WH (1998) The role of the environment in the development of obesity. J Pediatr 132, 768776.
8Foresight (2007) Foresight Tackling Obesities: Future Choices Project. http://www.foresight.gov.uk (accessed September 2009).
9Hill JO, Melanson EL & Wyatt HT (2002) Dietary fat intake and regulation of energy: implications for obesity. J Nutr 130, S284S288.
10Lobstein T (2004) Obesity in children and young people: a crisis in public health. Obes Rev 5, Suppl. 1, 485.
11Ludwig DS, Peterson KE & Gortmaker SL (2001) Relation between consumption of sugar-sweetened drinks and childhood obesity: a prospective observational analysis. Lancet 357, 505508.
12Prentice AM & Jebb SA (2003) Fast foods, energy density and obesity: a possible mechanistic link. Obes Rev 4, 187194.
13Rolls BJ, Morris EL & Roe LS (2002) Portion size of food affects energy intake in normal-weight and overweight men and women. Am J Clin Nutr 76, 12071213.
14Tuomisto T, Tuomisto MT, Hetherington M, et al. (1998) Reasons for initiation and cessation of eating in obese men and women and the affective consequences of eating in everyday situations. Appetite 30, 211222.
15Ma Y, Bertone ER, Stanek EJ III, et al. (2003) Association between eating patterns and obesity in a free-living US adult population. Am J Epidemiol 158, 8592.
16French SA, Jeffrey RW, Forster JL, et al. (1994) Predictors of weight change over two years among a population of working adults: The Healthy Worker Project. Int J Obes 18, 145154.
17Gortmaker SL, Must A, Sobol AM, et al. (1996) Television viewing as a cause of increasing obesity among children in the United States, 1986–1990. Arch Pediatr Adolesc Med 150, 356362.
18Jebb SA & Moore MS (1999) Contribution of a sedentary lifestyle and inactivity to the etiology of overweight and obesity: current evidence and research issues. Med Sci Sports Exerc 31, Suppl. 11, S534S541.
19Prentice AM & Jebb SA (1995) Obesity in Britain: gluttony or sloth? Br Med J 311, 437439.
20Von Kries R, Kolezo B, Sauerweld T, et al. (1999) Breast feeding and obesity: cross sectional study. BMJ 319, 147150.
21Hasler G, Buysse DJ, Klaghofer R, et al. (2004) The association between short sleep duration and obesity in young adults: a 13-year prospective study. Sleep 27, 661666.
22Newmark-Sztainer D, Wall M, Guo J, et al. (2006) Obesity, disordered eating, and eating disorders in a longitudinal study of adolescents: how do dieters fare 5 years later? J Am Diet Assoc 106, 559568.
23Leibman M, Pelican S, Moore SA, et al. (2005) Dietary intake-, eating behaviour- and physical activity-related determinants of high body mass index in the 2003 Wellness in the Rockies cross-sectional study. Nutr Res 26, 111117.
24Chambers JA & Swanson V (2006) A health assessment tool for multiple risk factors for obesity: results from a pilot study with UK adults. Patient Educ Counsel 62, 7988.
25Chambers JA & Swanson V (2008) A health assessment tool for multiple risk factors for obesity: psychometric testing and age differences in UK adults. Obesity Facts 1, 227236.
26Office of Population and Census Surveys (OPCS) (1991) Classification of Occupations. London: HM Stationery Office.
27Wardle J, Guthrie CA, Sanderson S, et al. (2001) Development of the Children's Eating Behaviour questionnaire. J Child Psychol Psychiatry 42, 963970.
28World Health Organization (2000) Health and Health Behaviour Among Young People. WHO Policy Series: Health Policy for Children and Adolescents no. 1. Geneva: WHO.
29Flesch RF (1948) A new readability yardstick. J Appl Psychol 32, 221233.
30Heitmann BL & Lissner L (1995) Dietary underreporting by obese individuals – is it specific or non-specific? BMJ 311, 986989.
31World Health Organization (2000) Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. WHO Technical Report Series no. 894. Geneva: WHO.
32Patel SR & Hu FB (2008) Short sleep duration and weight gain: a systematic review. Obesity 16, 643653.
33Scottish Government (2008) The Scottish Health Survey 2008. Edinburgh: Blackwell.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

British Journal of Nutrition
  • ISSN: 0007-1145
  • EISSN: 1475-2662
  • URL: /core/journals/british-journal-of-nutrition
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords:

Metrics

Full text views

Total number of HTML views: 6
Total number of PDF views: 96 *
Loading metrics...

Abstract views

Total abstract views: 137 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 20th November 2017. This data will be updated every 24 hours.