Dietary misreporting characterized by implausible energy intakes is often overlooked. In the absence of objective measures of energy intake, however, indirect methods are typically used to identify implausible reporters and to evaluate how misreporting may influence associations between dietary intakes and health outcomes (16
). Recently, some researchers have proposed that pTEE equations may be better suited than previous methods to estimate energy requirements and identify implausible reporters (17
); others have suggested that the equations most frequently used to estimate BMR may be insufficiently valid among overweight and obese subjects (28
). In the present study, we assessed how these alternative methods of estimating energy needs affected estimated prevalences of implausible reporting and influenced associations between dietary factors and obesity.
Levels of under- and overreporting obtained using the traditional Goldberg method—19% and 5%, respectively, in the sample as a whole—were comparable to those reported in the literature that used diet histories or food frequency questionnaires (1
). In comparison, when we used the revised Goldberg and pTEE methods, which were highly concordant with each other, levels of underreporting were 7%–10% lower and levels of overreporting were 13%–15% higher. Nonetheless, regardless of the method used, underreporters had higher mean BMIs and overreporters had lower mean BMIs than did plausible reporters, as observed elsewhere (1
). As in earlier studies (2
), likely underreporters identified with each method reported higher intakes of healthy foods, such as fruits and vegetables, and lower intakes of energy and less-healthy foods, such as pastries, than did plausible reporters. The opposite pattern was true for overreporters. After excluding implausible reporters using each approach, coefficients for several diet-BMI associations changed in magnitude or direction, becoming more consistent with hypotheses relating energy-dense foods to obesity (14
), again consistent with several earlier reports (2
). For example, among women, initially negative associations between BMI and intakes of energy and pastries were reversed, whereas a neutral association with fruit became negative. In contrast, excluding subjects with extreme energy intakes by using recommended cutoffs (32
) had no meaningful effect. Coefficients for percentage of energy from fat were not meaningfully affected by adjustment for misreporting. Although reasons for this finding are uncertain, Huang et al. (22
) also found that associations between BMI and percentage of energy from fat were not influenced by excluding implausible reporters. Similarly, coefficients for the percentage of energy from saturated, polyunsaturated, and monounsaturated fat in the baseline multivariate model (β = −0.02 (SE, 0.01), 0.17 (SE, 0.01), and 0.04 (SE, 0.01), respectively) were consistent with those obtained excluding (β = −0.01 (SE, 0.01), 0.14 (SE, 0.01), and 0.03 (SE, 0.01), pTEE method 1.5-standard-deviation cutoffs) or adjusting for implausible reporters (not shown). In separate models, we briefly examined associations between BMI and the percentage of energy from carbohydrates. As for fat, misreporting adjustments had little effect (not shown).
Although the effects of accounting for misreporting were generally consistent across methods, the magnitude of associations observed after these adjustments was frequently stronger when using the revised Goldberg and pTEE methods to identify misreporters than when using the original Goldberg method. This was observed despite the lower prevalence of underreporting found when using these alternative methods. As observed previously, using more restrictive cutoffs to identify implausible reporters tended to strengthen associations (17
). Results also suggested that in some cases, overreporting might have been influential, as excluding or adjusting only for underreporters at times yielded associations that differed when also accounting for overreporters. Additionally, as in a previous study on a different population (2
), we found that adjusting for rather than excluding implausible reporters yielded consistent results: Relations between dietary intakes and BMI that emerged after stratifying by reporting group were similar to those observed among plausible reporters (Web Figure 1
). This suggested that adjustment—effectively summarizing across reporting groups—was a viable alternative to omitting a substantial proportion of subjects, which some researchers have suggested may lead to bias (34
). Similarly, in another recent study, de Castro et al. (35
) found that positive relations between variables such as energy density and energy intakes were preserved within reporting subgroups defined on the basis of the rEI:BMR ratio, despite the disparate levels of intake reported across these groups.
The stronger associations observed using the revised Goldberg and pTEE methods versus the original Goldberg method might be due in part to improved classification of implausible reporters, as these methods could better estimate energy requirements. pTEE equations have high R2
), and the revised BMR equations have been reported to yield better estimates across the range of BMIs (28
). It is noteworthy that these revised approaches, although based on independent equations for estimating energy needs, yielded highly concordant estimates of both under- and overreporting. It is important to keep in mind, however, that although the Goldberg method has been evaluated against doubly labeled water, the true validity of these alternative methods is uncertain. In previous studies, researchers have shown the Goldberg method with cutoffs of 2.0 standard deviations to be specific (97%–98%) and reasonably sensitive (72%–74%) for identifying underreporters (21
). Reassuringly, when 1.5-standard-deviation cutoffs were applied, the numbers of underreporters identified with these updated methods were highly concordant (94%–96% agreement) with the Goldberg method. Thus, the major discrepancy was the substantially higher level of overrreporting identified using these methods. Indeed, the validation of the original Goldberg method suggested this method had limited ability to identify overreporters (21
The substantial differences in the prevalence of implausible reporting across alternative methods highlight that in the absence of valid objective measures of habitual energy intakes, it is not possible to determine to what extent implausible rEIs reflect misreporting rather than true habitual intakes in subjects whose energy requirements may be poorly estimated (31
). However, the findings that emerge after accounting for implausible reporters are consistent with the disparity in associations observed in several studies comparing how questionnaire data versus biomarker-based markers of intake relate to obesity or related health outcomes. For example, in one recent study, urinary sugars and plasma vitamin C, but not food frequency questionnaire-based estimates of intake, were found to be associated with obesity (36
). In another population, estimates of vitamin C intake derived from plasma or food records, but not from food frequency questionnaires, were associated with ischemic heart disease (37
). In yet another study, positive associations between energy intakes and obesity-related cancers, such as breast and colon cancer, emerged only after using biomarker-calibrated measures of intake, whereas associations with non-obesity-related cancers such as lung cancer and lymphoma remained neutral (38
). The absence of objective measures of energy intake is an important limitation of this analysis. However, there are important strengths, including the large sample size with measured anthropometry, and the availability of a validated physical activity level measure to aid estimation of energy needs (21
). Nonetheless, as household activities were not included, activity levels might have been assessed with some degree of error (39
Recent literature has suggested that imprecise or biased intake reporting, often more prevalent among obese subjects, may undermine the validity of research on diet and numerous health outcomes (11
). In the absence of objective biomarkers, the updated methods used in this study, which attempted to address limitations identified with the original approach, appear to be a reasonable alternative, enabling researchers to examine the effects of accounting for likely overreporters as well as underreporters. Although its relevance may vary across populations and dietary assessment methods, additionally accounting for overreporting appeared to influence associations with some dietary factors, and this type of misreporting should be considered. Future studies to assess the sensitivity and specificity of these alternative methods against objective measures of energy intake are needed to better evaluate their ability to identify under- and overreporters compared with the Goldberg method.