Based on our study of women in NHANES, BMI categories based on self-reported height and weight had substantial agreement with measured categories among non-pregnant women. Agreement between BMI category based on self-reported and measured height and weight was significantly related to age and race, with less agreement found for older, black and Hispanic women. Strength of agreement was unrelated to SES, access to care or health status. However, pregnancy significantly decreased strength of agreement.
In the subset of women with discordant responses, the majority under-reported their obesity category. In particular, we found an under-reporting bias among white, non-Hispanic women with some college education. Thus, concerns, in terms of accuracy, would be greatest for studies that rely on self-reported categories for women with these characteristics. However, even in this worst case scenario, BMI categories based on self-reported height and weight still demonstrate moderate agreement with measured categories.
Behavioral and health characteristics were largely unrelated to the accuracy of BMI categories based on self-reported height and weight, except to mention that women who annually visit a physician or are diagnosed with osteoporosis were more accurate in their reporting. A sur-prising finding was that the diagnosis of osteoporosis, a condition associated with a loss in height, improved agreement among older women. Women, age 56-65 years and diagnosed with osteoporosis, may more accurately report their BMI category due to access to a physician, due to better self monitoring of physiological changes, or due to greater awareness of a potentially latent conditions.
Our findings suggest that self-reported and measured BMI categories among pregnant women are in moderate agreement, and discordant responders largely under-report their category. The possibility that pregnant women can accurately assess their weight seems highly unlikely based on this evidence, and we suggest caution in the interpretation of such data. Further studies are warranted to address issues concerning recall bias and gestational development.
Our results were similar to many studies which found that women are more likely to under-report weight [6
]. Similar to Nyholm, we found that age is related to bias in self-reported BMI [9
]. However, because we examined BMI categories, not BMI in its continuous form, we were able to examine the extent to which this bias might threaten categorical agreement. We found that while differences between self-reported and clinically measured values are statistically significant, varying by age and race, self-reported BMI categories show substantial agreement with clinical measures across all age and race subgroups.
In addition to evidence supporting the use of self-reported BMI categories, the results contribute to our understanding of clinical effects. Our results suggest that a diagnosis of osteoporosis increases the accuracy of self-reported BMI categories, particularly in women age 55-76 and presumably because these women are more aware of their true height. It is interesting that women with previous diagnoses of osteoporosis are more likely to report accurately as many geriatric studies have found self-reports to be less reliable in older women. Wada and colleagues found no significant differences in measured versus self-reported BMI in males or females with hypertension or hyperlipidemia, but did find a significant difference in diabetics, who more accurately self-reported BMI [19
Prior to our study, no study has examined the agreement between self-reported and measured BMI categories beyond the probability of agreement at random (i.e., Cohen’s kappa). Brunner Huber found that self-reported height and weight measures classified 84% of women of reproductive age into appropriate BMI categories [7
]. While this article reports percentage agreement, it excluded a measure of agreement adjusted for agreement at random (i.e., Cohen’s kappa) from the analysis. Still, Cohen’s kappa (0.77) can be computed using the data found in Table 6 of the article. Some studies have simplified the five BMI categories into a binary variable (e.g., obese and non-obese) and examined sensitivity and specificity. This simplification may facilitate explanation, because it describes the probability that an obese patient will be categorized as obese based on self-reported weight and height (true-positive rate). However, it loses descriptive power by equating underweight, normal and overweight individuals as well as equating obese and morbidly obese individuals. Furthermore, using sensitivity and specificity does not account for agreement at random. In the previous example of an anorexic population, kappa would be zero, but sensitivity of underweight (i.e., probability of agreement conditional on underweight) would be 75%, which may be erroneously interpreted as a strong association.
A key limitation of the study is that NHANES participants may have known they were going to be weighed when they consented for the study, which may have decreased tendencies to under-report weight. Any comparison of self-reported and clinically reported height and weight requires consent; therefore, this would be susceptible to experimental influences in addition to social desirability bias.