Tags

Type your tag names separated by a space and hit enter

Measurement error and results from analytic epidemiology: dietary fat and breast cancer.

Abstract

BACKGROUND

International correlational analyses have suggested a strong positive association between fat consumption and breast cancer incidence, especially among post-menopausal women. However, case-control studies have been taken to indicate a weaker association, and a recent, pooled cohort analysis reported little evidence of an association. Differences among study results could be due to differences in the populations studied, differences in the control for total energy intake, recall bias in the case-control studies, and dietary measurement error biases. Existing measurement error models assume either that the sample data used to validate dietary self-report instruments are without measurements error or that any such error is independent of both the true dietary exposure and other study subject characteristics. However, growing evidence indicates that total energy and, presumably, both total fat and percent energy from fat are increasingly underreported as percent body fat increases.

PURPOSE

A relaxed dietary measurement model is introduced that allows all measurement error parameters to depend on body mass index (weight in kilograms divided by the square of height in meters) and incorporates a random underreporting quantity that applies to each dietary self-report instrument. The model was applied to results from international correlational analyses to determine whether the differing associations between dietary fat and postmenopausal breast cancer can be explained by measurement errors in dietary assessment.

METHODS

The relaxed measurement model was developed by use of data on total fat intake and percent energy from fat from 4-day food records (4DFRs) and food-frequency questionnaires (FFQs) from the original Women's Health Trial. This trial was a randomized, controlled, feasibility study of a low-fat dietary intervention carried out from 1985 through 1988 in Cincinnati (OH), Houston (TX), and Seattle (WA) among 303 women (184 intervention and 119 control) who were 45-69 years of age. The relaxed model was used to project results from the international correlational analyses onto 4DFR and FFQ fat-intake categories.

RESULTS AND CONCLUSIONS

If measurement errors in dietary assessment are overlooked entirely, the projected relative risks (RRs) for breast cancer based on the international data vary substantially across percentiles of total fat intake. The projected RR for the 90% versus the 10% fat-intake percentile is 3.08 with the 4DFR and 4.00 with the FFQ. If random (i.e., noise) aspects of measurement error are acknowledged, the projected RR for the same comparison is reduced to 1.54 with the 4DFR and 1.42 with the FFQ. If both systematic and noise aspects of measurement error are acknowledged, the projected RR is reduced to about 1.10 with either instrument. Acknowledgment of measurement error also leads to a projected RR of about 1.10 for the 90% versus the 10% percentile of percent energy from fat with either dietary instrument.

IMPLICATIONS

Dietary self-report instruments may be inadequate for analytic epidemiologic studies of dietary fat and disease risk because of measurement error biases.

Links

  • Publisher Full Text
  • Authors+Show Affiliations

    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98104, USA.

    Source

    Journal of the National Cancer Institute 88:23 1996 Dec 04 pg 1738-47

    MeSH

    Aged
    Body Mass Index
    Breast Neoplasms
    Diet Records
    Dietary Fats
    Energy Intake
    Feasibility Studies
    Female
    Humans
    Middle Aged
    Postmenopause

    Pub Type(s)

    Clinical Trial
    Journal Article
    Randomized Controlled Trial
    Research Support, U.S. Gov't, P.H.S.

    Language

    eng

    PubMed ID

    8944004

    Citation

    Prentice, R L.. "Measurement Error and Results From Analytic Epidemiology: Dietary Fat and Breast Cancer." Journal of the National Cancer Institute, vol. 88, no. 23, 1996, pp. 1738-47.
    Prentice RL. Measurement error and results from analytic epidemiology: dietary fat and breast cancer. J Natl Cancer Inst. 1996;88(23):1738-47.
    Prentice, R. L. (1996). Measurement error and results from analytic epidemiology: dietary fat and breast cancer. Journal of the National Cancer Institute, 88(23), pp. 1738-47.
    Prentice RL. Measurement Error and Results From Analytic Epidemiology: Dietary Fat and Breast Cancer. J Natl Cancer Inst. 1996 Dec 4;88(23):1738-47. PubMed PMID: 8944004.
    * Article titles in AMA citation format should be in sentence-case
    TY - JOUR T1 - Measurement error and results from analytic epidemiology: dietary fat and breast cancer. A1 - Prentice,R L, PY - 1996/12/4/pubmed PY - 1996/12/4/medline PY - 1996/12/4/entrez SP - 1738 EP - 47 JF - Journal of the National Cancer Institute JO - J. Natl. Cancer Inst. VL - 88 IS - 23 N2 - BACKGROUND: International correlational analyses have suggested a strong positive association between fat consumption and breast cancer incidence, especially among post-menopausal women. However, case-control studies have been taken to indicate a weaker association, and a recent, pooled cohort analysis reported little evidence of an association. Differences among study results could be due to differences in the populations studied, differences in the control for total energy intake, recall bias in the case-control studies, and dietary measurement error biases. Existing measurement error models assume either that the sample data used to validate dietary self-report instruments are without measurements error or that any such error is independent of both the true dietary exposure and other study subject characteristics. However, growing evidence indicates that total energy and, presumably, both total fat and percent energy from fat are increasingly underreported as percent body fat increases. PURPOSE: A relaxed dietary measurement model is introduced that allows all measurement error parameters to depend on body mass index (weight in kilograms divided by the square of height in meters) and incorporates a random underreporting quantity that applies to each dietary self-report instrument. The model was applied to results from international correlational analyses to determine whether the differing associations between dietary fat and postmenopausal breast cancer can be explained by measurement errors in dietary assessment. METHODS: The relaxed measurement model was developed by use of data on total fat intake and percent energy from fat from 4-day food records (4DFRs) and food-frequency questionnaires (FFQs) from the original Women's Health Trial. This trial was a randomized, controlled, feasibility study of a low-fat dietary intervention carried out from 1985 through 1988 in Cincinnati (OH), Houston (TX), and Seattle (WA) among 303 women (184 intervention and 119 control) who were 45-69 years of age. The relaxed model was used to project results from the international correlational analyses onto 4DFR and FFQ fat-intake categories. RESULTS AND CONCLUSIONS: If measurement errors in dietary assessment are overlooked entirely, the projected relative risks (RRs) for breast cancer based on the international data vary substantially across percentiles of total fat intake. The projected RR for the 90% versus the 10% fat-intake percentile is 3.08 with the 4DFR and 4.00 with the FFQ. If random (i.e., noise) aspects of measurement error are acknowledged, the projected RR for the same comparison is reduced to 1.54 with the 4DFR and 1.42 with the FFQ. If both systematic and noise aspects of measurement error are acknowledged, the projected RR is reduced to about 1.10 with either instrument. Acknowledgment of measurement error also leads to a projected RR of about 1.10 for the 90% versus the 10% percentile of percent energy from fat with either dietary instrument. IMPLICATIONS: Dietary self-report instruments may be inadequate for analytic epidemiologic studies of dietary fat and disease risk because of measurement error biases. SN - 0027-8874 UR - https://www.unboundmedicine.com/medline/citation/8944004/Measurement_error_and_results_from_analytic_epidemiology:_dietary_fat_and_breast_cancer_ L2 - https://academic.oup.com/jnci/article-lookup/doi/10.1093/jnci/88.23.1738 DB - PRIME DP - Unbound Medicine ER -