Skip to main content
Log in

Validating self-reported food expenditures against food store and eating-out receipts

  • Original Article
  • Published:
European Journal of Clinical Nutrition Submit manuscript

Abstract

Background/Objectives:

To compare objective food store and eating-out receipts with self-reported household food expenditures.

Subjects/Methods:

The Seattle Obesity Study II was based on a representative sample of King County adults, Washington, USA. Self-reported household food expenditures were modeled on the Flexible Consumer Behavior Survey (FCBS) Module from 2007 to 2009 National Health and Nutrition Examination Survey (NHANES). Objective food expenditure data were collected using receipts. Self-reported food expenditures for 447 participants were compared with receipts using paired t-tests, Bland–Altman plots and κ-statistics. Bias by sociodemographics was also examined.

Results:

Self-reported expenditures closely matched with objective receipt data. Paired t-tests showed no significant differences between receipts and self-reported data on total food expenditures, expenditures at food stores or eating out. However, the highest-income strata showed weaker agreement. Bland–Altman plots confirmed no significant bias across both methods–mean difference: 6.4; agreement limits: −123.5 to 143.4 for total food expenditures, mean difference 5.7 for food stores and mean difference 1.7 for eating out. The κ-statistics showed good agreement for each (κ 0.51, 0.41 and 0.49 respectively. Households with higher education and income had significantly more number of receipts and higher food expenditures.

Conclusions:

Self-reported food expenditures using NHANES questions, both for food stores and eating out, serve as a decent proxy for objective household food expenditures from receipts. This method should be used with caution among high-income populations, or with high food expenditures. This is the first validation of the FCBS food expenditures question using food store and eating-out receipts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1

Similar content being viewed by others

References

  1. Centers for Disease Control and Prevention (CDC), National Center for Health Statistics About the National Health and Nutrition Exmaination Survey (NHANES). 2013. Available at http://www.cdc.gov/nchs/nhanes/about_nhanes.htm (accessed April 2014).

  2. United States Department of Agriculture Flexible Consumer Behavior Survey. 2014. Available at http://www.ers.usda.gov/topics/food-choices-health/food-consumption-demand/food-consumption/flexible-consumer-behavior-survey.aspx#.U4jCwign-aI (accessed May 2014).

  3. French SA, Wall M, Mitchell NR, Shimotsu ST, Welsh E . Annotated receipts capture household food purchases from a broad range of sources. Int J Behav Nutr Phys Act 2009; 6: 37.

    Article  Google Scholar 

  4. French SA, Wall M, Mitchell NR . Household income differences in food sources and food items purchased. Int J Behav Nutr Phys Act 2010; 7: 77.

    Article  Google Scholar 

  5. Cullen K, Baranowski T, Watson K, Nicklas T, Fisher J, O'Donnell S et al. Food category purchases vary by household education and race/ethnicity: results from grocery receipts. J Am Diet Assoc 2007; 107: 1747–1752.

    Article  Google Scholar 

  6. Martin SL, Howell T, Duan Y, Walters M . The feasibility and utility of grocery receipt analyses for dietary assessment. Nutr J 2006; 5: 10.

    Article  Google Scholar 

  7. Ransley JK, Donnelly JK, Botham H, Khara TN, Greenwood DC, Cade JE . Use of supermarket receipts to estimate energy and fat content of food purchased by lean and overweight families. Appetite 2003; 41: 141–148.

    Article  CAS  Google Scholar 

  8. Ransley JK, Donnelly JK, Khara TN, Botham H, Arnot H, Greenwood DC et al. The use of supermarket till receipts to determine the fat and energy intake in a UK population. Public Health Nutr 2001; 4: 1279–1286.

    Article  CAS  Google Scholar 

  9. Rankin JW, Winett RA, Anderson ES, Bickley PG, Moore JF, Leahy M et al. Food purchase patterns at the supermarket and their relationship to family characteristics. J Nutr Educ 1998; 30: 81–88.

    Article  Google Scholar 

  10. DeWalt KM, D'Angelo S, McFadden M, Danner FW, Noland M, Kotchen JM . The use of itemized register tapes for analysis of household food acquisition patterns prompted by children. J Am Diet Assoc 1990; 90: 559–562.

    CAS  PubMed  Google Scholar 

  11. Monsivais P, Perrigue MM, Adams SL, Drewnowski A . Measuring diet cost at the individual level: a comparison of three methods. Eur J Clin Nutr 2013; 67: 1220–1225.

    Article  CAS  Google Scholar 

  12. French SA, Shimotsu ST, Wall M, Gerlach AF . Capturing the spectrum of household food and beverage purchasing behavior: a review. J Am Diet Assoc 2008; 108: 2051–2058.

    Article  Google Scholar 

  13. Rehm CD, Moudon AV, Hurvitz PM, Drewnowski A . Residential property values are associated with obesity among women in King County, WA, USA. Soc Sci Med 2012; 75: 491–495.

    Article  Google Scholar 

  14. Bland JM, Altman DG . Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307–310.

    Article  CAS  Google Scholar 

  15. StataCorp Stata Statistical Software: Release 11, 2013, StataCorp LP: College Station, TX.

  16. United States Bureau of Labor Statistics Consumer Expenditure Survey. 2013. Available at http://www.bls.gov/cex/2012/combined/quintile.pdf (accessed 22 July 2014).

  17. United States Department of Labor, Bureau of Labor Statistics Consumer Expenditures in 2011. 2011. Available at http://www.bls.gov/cex/csxann11.pdf (accessed April 2013).

  18. King County Office of the Executive Median household income: King County and U.S. (1999–2009) http://www.kingcounty.gov/exec/PSB/BenchmarkProgram/Economy/EC02_Income/MedianIncomeChart.aspx.

  19. Drewnowski A, Specter SE . Poverty and obesity: the role of energy density and energy costs. Am J Clin Nutr 2004; 79: 6–16.

    Article  CAS  Google Scholar 

  20. Slawson DL, Fitzgerald N, Morgan KT . Position of the Academy of Nutrition and Dietetics: the role of nutrition in health promotion and chronic disease prevention. J Acad Nutr Diet 2013; 113: 972–979.

    Article  Google Scholar 

  21. Wolongevicz DM, Zhu L, Pencina MJ, Kimokoti RW, Newby PK, D'Agostino RB et al. Diet quality and obesity in women: the Framingham Nutrition Studies. Br J Nutr 2010; 103: 1223–1229.

    CAS  PubMed  Google Scholar 

  22. US Department of Agriculture, US Department of Health and Human Services Dietary Guidelines for Americans, 2010. 7th edn US Government Printing Office: Washington, DC, 2010.

  23. Drewnowski A, Darmon N . The economics of obesity: dietary energy density and energy cost. Am J Clin Nutr 2005; 82: 265s–273s.

    Article  CAS  Google Scholar 

  24. Rao M, Afshin A, Singh G, Mozaffarian D . Do healthier foods and diet patterns cost more than less healthy options? A systematic review and meta-analysis. BMJ Open 2013; 3: e004277.

    Article  Google Scholar 

Download references

Acknowledgements

This study was funded by the NIH Grants P20 RR020774-03, R01 DK076608-04 and R21 DK020774.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A Drewnowski.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tang, W., Aggarwal, A., Liu, Z. et al. Validating self-reported food expenditures against food store and eating-out receipts. Eur J Clin Nutr 70, 352–357 (2016). https://doi.org/10.1038/ejcn.2015.166

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ejcn.2015.166

  • Springer Nature Limited

This article is cited by

Navigation