Skip to main content
×
Home
    • Aa
    • Aa

Bias in dietary-report instruments and its implications for nutritional epidemiology

  • Victor Kipnis (a1), Douglas Midthune (a1), Laurence Freedman (a2), Sheila Bingham (a3), Nicholas E Day (a4), Elio Riboli (a5), Pietro Ferrari (a5) and Raymond J Carroll (a6)...
Abstract
AbstractObjective:

To evaluate measurement error structure in dietary assessment instruments and to investigate its implications for nutritional studies, using urinary nitrogen excretion as a reference biomarker for protein intake.

Design:

The dietary assessment methods included different food-frequency questionnaires (FFQs) and such conventional dietary-report reference instruments as a series of 24-hour recalls, 4-day weighed food records or 7-day diaries.

Setting:

Six original pilot validation studies within the European Prospective Investigation of Cancer (EPIC), and two validation studies conducted by the British Medical Research Council (MRC) within the Norfolk cohort that later joined as a collaborative component cohort of EPIC.

Subjects:

A sample of approximately 100 to 200 women and men, aged 35–74 years, from each of eight validation studies.

Results:

In assessing protein intake, all conventional dietary-report reference methods violated the critical requirements for a valid reference instrument for evaluating, and adjusting for, dietary measurement error in an FFQ. They displayed systematic bias that depended partly on true intake and partly was person-specific, correlated with person-specific bias in the FFQ. Using the dietary-report methods as reference instruments produced substantial overestimation (up to 230%) of the FFQ correlation with true usual intake and serious underestimation (up to 240%) of the degree of attenuation of FFQ-based log relative risks.

Conclusion:

The impact of measurement error in dietary assessment instruments on the design, analysis and interpretation of nutritional studies may be much greater than has been previously estimated, at least regarding protein intake.

    • 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.

      Bias in dietary-report instruments and its implications for nutritional epidemiology
      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.

      Bias in dietary-report instruments and its implications for nutritional epidemiology
      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.

      Bias in dietary-report instruments and its implications for nutritional epidemiology
      Available formats
      ×
Copyright
Corresponding author
*Corresponding author: Email vk3b@nih.gov
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

20 RJ Carroll , D Ruppert , LA Stefanski . Measurement Error in Nonlinear Models. London: Chapman & Hall, 1995.

Recommend this journal

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

Public Health Nutrition
  • ISSN: 1368-9800
  • EISSN: 1475-2727
  • URL: /core/journals/public-health-nutrition
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords:

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 354 *
Loading metrics...

Abstract views

Total abstract views: 310 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 28th May 2017. This data will be updated every 24 hours.