In this study sample, soy protein intake in all subjects and among soy users fell within the range of intakes of those observed among populations in Singapore, Shanghai, North Korea, and Japan (20
). Mean urinary excretions of daidzein and genistein were higher among the soy users in our sample than in either of the populations in Singapore or Shanghai (20
). Seven percent of soy users in our sample produced >500 pmol/12 h equol.
The small sample in this analysis was chosen from the AHS-2 calibration study specifically to represent a group of individuals with a wide range of soy intake (low, medium, or high). Following this criterion, we demonstrated that mean estimates of soy protein from FFQs and recalls are not significantly different and that soy protein from FFQs moderately correlates with estimates from multiple 24-h recalls. The correlation coefficients between specific urinary IFLs (daidzein, genistein, and total IFLs) and soy protein estimates from 24-h recalls or FFQs are relatively high, especially with the use of recall values.
In comparison, another study in which soy protein from questionnaires was validated against 24-h recalls (39
) reported a Spearman correlation coefficient of 0.38 (P
< 0.05), which is lower than the Pearson correlation of 0.67 that we observed. Our findings for the correlation between soy protein from questionnaires and urinary IFLs (daidzein, genistein, and total IFLs) are within the range (0.55–0.57) of those observed in other studies that evaluated the validity of soy protein from questionnaires with total IFL excretion rates in overnight urine samples. For example, previous studies reported statistically significant correlation coefficients of 0.53 with FFQs in a sample of women in Shanghai (23
) and 0.32 or 0.61 with FFQs for the previous year or previous 24 h, respectively, from a multiethnic population (Caucasian, Native Hawaiian, Chinese, Japanese, and Filipino) of women in Hawaii (19
Many studies that validated soy intake from questionnaires against biomarkers of IFL concentration as the reference method preferentially assessed intake of isoflavones from questionnaires (40
), and few measured soy protein intake (19
). When isoflavone intake was assessed, correlation coefficients were 0.28 in a population of women in the United States (32
) and ranged from 0.21 to 0.30 in women from the European Prospective Investigation of Cancer and Nutrition-Norfolk UK study (41
). Correlations were higher in a Chinese population living in Shanghai (range: 0.42–0.54) (39
) and in a multiethnic population in Hawaii (0.31 or 0.62) (19
). The weak correlations observed in Western countries probably result from a small range of soy intake in these populations compared with that in Asian populations. That the correlations observed between urinary IFL excretion and soy protein intake (range: 0.31–0.56) are rather stronger than those between isoflavone intake and excretion (range: 0.24–0.30) suggests that current dietary assessment methods of isoflavone intake may be less accurate than for soy protein intake.
Assessment of isoflavone intake in populations represents a challenge for researchers primarily because of the paucity of data on the isoflavone content of many foods. Moreover, isoflavone databases that are available have been developed with the assumption that the isoflavone content in foods remains constant, despite the recognition that great variability exists. Setchell and Cole (43
) demonstrated that isoflavone content in the samples of soy protein isolates used in commercial foods, collected over a period of 3 y, varied markedly (by 200–300%) with time, by manufacturer, and by processing method. During the same 3-y period of sample collection, however, the authors reported only a 3% variation in the protein content of the soy protein isolates, which indicates that manufacturers have better control over the protein than the isoflavone content in soy foods. Data from the USDA-Iowa State University Database on Isoflavone Content of Foods show that total isoflavones in soy protein concentrate can vary from 102 mg/100 g of edible portion by using the aqueous wash method of extraction to 12.47 mg/100 g of product when produced by alcohol extraction (44
). Finally, isoflavone content in soybean seeds varies depending on a variety of factors such as environmental, genetic, harvesting, and processing conditions (45
). It is not surprising, therefore, that estimates of soy protein intake perform at least as well as, if not better than, estimates of isoflavone intake when correlated with IFL excretion.
US consumption of soy is increasing, and use of commercial ingredients such as soy protein concentrate, soy protein isolate, and soy flour is becoming more prevalent among manufacturers of cereals, energy bars, soy-based iced desserts, and, in particular, meat analogues. If soy proteins in these products remain more stable over time than isoflavones, studies that investigate relations between soy and disease risk should, therefore, evaluate both isoflavone and soy protein intake.
This study provides data on soy protein intake and measured biologic markers in a Western population with a wide range of intake of soy foods and at levels comparable to those of Eastern populations. In addition, we demonstrated that the AHS-2 FFQ is a valid instrument for assessing soy protein intake and that these estimates are a good index of soy isoflavone intake. Findings from this analysis may be useful in bringing greater clarity to the links between soy intake and cancer incidence in the AHS-2 cohort.