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3 Department of Community and Family Medicine, Chinese University of Hong Kong, Hong Kong SAR; 4 Department of Public Health Sciences, University of Toronto, Toronto, Canada M5G 2L7; and 5 Department of Mathematics and Statistics, University of Guelph, Guelph, Canada N1G 2W1
* To whom correspondence should be addressed. E-mail: sieugaen2003{at}yahoo.com.
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ABSTRACT |
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 TOP ABSTRACT IntroductionMaterials and MethodsResultsDiscussionLITERATURE CITED |
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90% of the total isoflavone intake. Soft tofu alone accounted for 21% of the isoflavone intake, followed by bean curd skin (7.1%), name-brand soybean milk (6.3%), homemade soybean milk (6.2%), and generic soybean milk (5.8%). Combined, these 5 food items contributed 46% of the total dietary isoflavones. Multiple linear regression analysis indicated dialect group, self-reported health, and age group were significant independent predictors of soy isoflavone consumption. The data provide the basis for elucidating the patterns, determinants, and assessment of dietary soy isoflavone intake in Asian women.
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Introduction |
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TOPABSTRACTIntroductionMaterials and MethodsResultsDiscussionLITERATURE CITED |
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Yet little is known about the habitual dietary intake of soy isoflavones in Asian populations due to the absence of reliable data on isoflavone concentrations in various foods in these localities. Even less is known about the patterns and determinants of soy consumption in these populations.
Hong Kong is a unique place where the East meets the West. Many of the midlife or older residents were immigrants from Mainland China. Eating practices are, to a large extent, influenced by the place of origin or dialect groups they belong to. Though exposed to the western eating culture due to the previous British ruling, traditional diet, including soy food intake, is largely retained. In 2001, a validation study of a 47-item FFQ was conducted to estimate the habitual soy isoflavone intake in 145 midlife women. As part of the study, multiple dietary recalls (DR)6 were collected from the participants over a 12-mo period. Food items included in the FFQ were also analytically determined via he HPLC method for total isoflavones. This article reports on the dietary soy isoflavone intake in the study population, the major food sources of soy isoflavones, and the determinants influencing the intakes of soy isoflavones.
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Materials and Methods |
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TOPABSTRACTIntroductionMaterials and MethodsResultsDiscussionLITERATURE CITED |
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Subjects included in this study were selected from participants in the Hong Kong Perimenopausal Osteoporosis Study (HKPOST), an ancillary study to the 1996 cross-sectional survey of women's health at midlife. Descriptions of the study design, sampling methods, and inclusion criteria of the survey have previously been reported (5–7). Briefly, 1903 women aged 45–55 y were identified from telephone dialing of a random sample of directory-listed residential telephone numbers. An additional 290 women of similar age were identified and recruited from the University Family Medicine Teaching Clinic. All were interviewed by telephone using a structured questionnaire regarding women's health and menopausal symptoms. The participants were also invited to join a longitudinal study on bone mass and bone changes. Among the 949 eligible women identified from these sources, 438 women were recruited into the HKPOST study. Women with medical conditions or medication intake affecting bone mass were considered ineligible. Assessments of bone mineral density were made at baseline and at 9-, 18-, 30-, 47-, 74-, and 86-mo follow-up.
In July 2001, 247 HKPOST members who completed the 47-mo follow-up study were invited to participate in the present soy questionnaire validation study, which aimed to validate soy isoflavone intake estimated by the soy FFQ against multiple 24-h DR collected over a 12-mo period.
Of the 247 women, the first 145 who agreed to participate were enrolled in the study between September 2001 and February 2002. To be included in the analysis, participants had to have completed 12 or more DR. A total of 141 participants (97%) with 3217 DR were included in the analysis. The validation study was approved by the Health Sciences I Research Ethics Board of the University of Toronto and the Ethical Committee of the Chinese University of Hong Kong (CU).
Data collection
An interviewer-administered soy FFQ was conducted at the Prince of Wales Hospital at 0 and 13 mo. Information on current marital and occupational status and place of origin (or ancestry) were obtained during the baseline FFQ interview. Self-reported health status was obtained (at the first DR) with the question, "In general, would you say your health is excellent, very good, good, fair, or poor?" Anthropometric measurements were taken while the participants wore light clothing and no shoes. We measured body weight and height to the nearest 0.1 kg and 0.1 cm, respectively, and BMI was calculated using the formula weight (kg)/height2 (m2).
Following the initial visit to the hospital for the baseline FFQ, a set of visual aids, including a page-numbered food photo album, and a set of common household containers were given to the participants to take home for reference for the DR interview. Twenty-four-hour DR were then collected from the participants for 23 d over the telephone by trained interviewers. The DR were conducted over a period of 12 mo and included 7 weekend days and 16 weekdays to account for variabilities of food consumption over the seasons and between weekends and weekdays. Two nonconsecutive DR were randomly selected monthly for a consecutive 12 mo. Participants received no prior announcements of the days when the DR would be conducted. The DR were conducted using the USDA Multiple Pass Method (8). Details about each reported food were gathered using standardized food probes listed in the Food Instruction Booklet for the Continuing Survey of Food Intakes by Individuals (CSFII) 1998 (9,10).
Isoflavone content of foods
The CU Soy Isoflavone Database was used to assign food codes and calculate the isoflavone content of soy foods reported. The database contains average analyzed values for total isoflavones of 48 edible soy products commonly consumed in Hong Kong (S. Chan, P. Murphy, S. Ho, N. Kreiger, G. Darlington, K. So, P. Chong, unpublished data). Mixed dishes and multicomponent foods were disaggregated into the corresponding components for food coding of soy products. For foods not included in the CU Soy Isoflavone Database, isoflavone values were estimated based on either published data (2 items) (11) or on values for similar foods (4 items).
Statistical analysis
Food contributions to isoflavone intake. The method described by Block et al. (12,13) was used to determine the major food sources of soy isoflavones in the study population. The percentage contribution of isoflavones from a given consumed soy product was derived from the total amount of intake from that food divided by the total isoflavone intake from all soy products. These soy products were then listed in descending order of percentage contribution to the total intake. Food items that contributed up to 90% of the total isoflavone intake were identified.
Determinants of soy isoflavone intake.
Dietary intake of total soy isoflavones for individual participants was derived from completed DR and calculated as the daily intake of isoflavones (mg aglucon equivalents/d). Descriptive results were expressed as mean ± SD or number and percentage. Differences between groups were examined by Student's t test or nonparametric Mann-Whitney test, as appropriate. Comparisons of proportions were performed using a Pearson chi-square test. Except where explicitly stated, data in tables and graphs are presented in the original scale of measurement. Because the distribution of isoflavone intake was right-skewed, it was power transformed (
) to improve distribution normality prior to statistical analysis.
To identify predictors of soy consumption, we performed simple linear regression. Variables associated with soy isoflavone intake (power transformed) in bivariate analyses at P < 0.20 and those that were considered a priori predictors were entered simultaneously into the multiple linear regression model. Two-way interactions between predictor variables were examined and regression diagnostics were performed to assess the adequacy of the multiple linear regression model. Outliers and influential observations were identified by the PRESS residuals, HAT and Cook's D statistics. Four non-Cantonese participants had high Cook's D and/or high leverage value. The stability of the regression parameter estimates and their associated SE were evaluated by performing multiple linear regression analysis without the outliers and influential observations. Because the differences observed did not change the conclusions, the outliers and influential observations were retained in the final model. Plots of PRESS residuals from the multiple linear regressions were inspected for possible violations of the assumption of normality and homoscedasticity. Normality of the residuals was further evaluated using the Shapiro-Wilk statistics. Regression analyses were repeated, confined to participants with 23 24-h DR. Because the results were similar, only those obtained in the whole sample are presented. We used the Statistical Analysis System for Windows (version 6.12, SAS Institute) to perform all statistical analyses. All tests were 2-sided and P < 0.05 was considered significant.
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Results |
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TOPABSTRACTIntroductionMaterials and MethodsResultsDiscussionLITERATURE CITED |
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90% of the total isoflavone intake in the study population (Table 2). Soft tofu alone accounted for 21% of the total isoflavone intake, followed by bean curd skin (7.1%), and then different types of soybean milk: commercial brand-name regular soybean milk (6.3%), homemade soybean milk (6.2%), and commercial generic regular soybean milk without (5.8%). Combined, these 5 food items contributed 46% of the total isoflavones consumed in the diet. When the individual foods were aggregated based on broad types of soy products, the category of bean curd (grouped from 9 products) accounted for 43.2% of the total intake, soybean milk (5 products) accounted for 22.6%, bean curd skin (5 products) accounted for 18.9%, and other soy products (3 products) accounted for 6.0%. The 3 most frequently consumed foods were bean curd skin, soft tofu, and bean curd puff, whereas the 2 specific types of soybean milk (Calciplus and low-sugar soybean milk) and vegetarian "duck" were the 3 most infrequently consumed soy products.
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70% of the total isoflavones in the diet, with soft tofu as the leading contributor (Table 3). Different rankings of major food sources among the dialect groups were also observed. Whereas the non-Cantonese subjects derived most of the isoflavones from the bean curd category (48.4%), the Cantonese participants had more diversified contributions from bean curd (31.5%), soybean milk (21.9%), and bean curd skin (16.9%).
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Discussion |
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TOPABSTRACTIntroductionMaterials and MethodsResultsDiscussionLITERATURE CITED |
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90% of the total isoflavone intake. The intake of soy isoflavones, as in other nutrients or phytochemicals, is a composite measure reflecting the nutrient density, frequency, and amount of foods consumed in a specific timeframe by the population group of interest (14). For example, although vegetarian duck was rich in isoflavones, containing 60 mg aglucon equivalents per 100 g, its intake was ranked low because of low consumption in the study population. On the other hand, although regular soybean milk contained only 60 mg aglucon isoflavones/L, the commonly consumed form of soybean milk was the 3rd highest contributor to the overall isoflavone intake.
The rank order of food contributors depends in part on the methods used to combine single ingredient foods or mixed dishes into abridged food categories (15,16). If soybean milk with similar isoflavone values (Table 2, rank no. 3–5, 11) were combined, the expanded soybean milk category would contribute 21% of the total soy isoflavone intake and obtain a similar top ranking as soft tofu in the total study population, and was even the top contributor among the Cantonese.
Our results revealed that the self-reported consumption levels of both dialect groups were lower than those of adult women in other Asian countries such as Japan, Singapore, and China (17). Possible explanations included differing food habits specific to dialect groups, diversification, and westernization of food consumption patterns. A population-based cross-sectional study of 1010 Chinese adults in Hong Kong (18) reported that 36% of women had a higher cholesterol intake level and 40% of women had a higher fat intake level than that recommended by dietary guidelines. The intake of traditional soy foods might have recently decreased with increasing Westernization in Hong Kong.
Our study has attempted to identify the demographic and health predictors of dietary soy isoflavone intake. The non-Cantonese had higher isoflavone intake and this finding is consistent with those previously reported by Wakai et al. (19) and Liu et al. (20) showing some regional differences in soy intake. Dialect group reflects the regional-specific food consumption preferences for certain nutrient-dense soy products and thus plays an influential role in the determinants of soy isoflavone intake.
Women aged 55–57 y had the lowest soy isoflavone intake. Our finding of a nonlinear association of age with isoflavone intake is also consistent with that observed by Liu et al. (20). Decline in total caloric intake with age may partially explain the age-related decrease in isoflavone intake levels (21). Mackerras (22) further suggested that an alteration in food choice might substantially change the amount of micronutrients and phytochemicals obtained, despite similar intakes of carbohydrates or energy. Of the participants reported making dietary change in the past 12 mo before the baseline interview, healthy eating (50%) and weight problems (25%) were the major reported reasons. However, the lower intake in the older age group could also be due to a cohort effect.
Self-reported health, a common proxy indicator of overall health and general well being (23), reflects an array of health, psychological, and social factors (24) that might exert their influences on dietary intake. Similar to previous studies reporting a positive association between self-rated health and vegetable consumption (25), participants with good self-rated health had significantly greater daily intake of soy isoflavones than those reporting poor health. At a follow-up interview and bone mineral density measurement of the HKPOST study participants (from which the participants of the present study were recruited) that followed shortly after the completion of baseline FFQ of this validation study, a menopausal symptoms checklist (5) revealed a higher number of symptoms in women with poor health compared with those with good to excellent health. Menopausal symptoms might play a role influencing the dietary intake of soy isoflavones, or healthier dietary pattern might also be associated with better self-rated health status.
This study has a number of limitations. The isoflavone intake levels of the study participants were probably underestimated, because the estimation was based on the CU Soy Isoflavone Database comprising mainly traditional soybean products. The isoflavone content of some modern processed foods containing protein (e.g. white breads) could not be estimated because the ingredients and composition were not available. Many previous studies assessing dietary isoflavone intake (19,26,27) also had similar constraints.
We found dialect group a predictor of soy intake. However, the small number of non-Cantonese subjects might have slightly reduced the stability of the regression coefficient estimates of predictors in the regression analysis. As the study participants were women at midlife in a narrow age range, the results may not be generalizable to other age groups or women in the general population. Nevertheless, within these limitations, our study was based on 3217 DR conducted on random days of the month over a 12-mo period. The estimation of soy isoflavones is also based on a soy isoflavone database constructed from local soy foods. In conclusion, this study identified the patterns and determinants of dietary isoflavone intake among midlife Hong Kong women. It forms the basis to further assess dietary soy exposure and the soy-health association.
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FOOTNOTES |
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2 Author disclosures: S. G. Chan, S. C. Ho, N. Kreiger, G. Darlington, K. F. So, and P. Y. Y. Chong, no conflicts of interest.
6 Abbreviations used: CU, Chinese University of Hong Kong; DR, dietary recall; HKPOST, Hong Kong Perimenopausal Osteoporosis Study.
Manuscript received 15 March 2007. Initial review completed 10 April 2007. Revision accepted 27 August 2007.
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LITERATURE CITED |
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1. Adlercreutz H. Western diet and Western diseases: some hormonal and biochemical mechanisms and associations. Scand J Clin Lab Invest Suppl. 1990;201:3–21.[Medline]
2. Adlercreutz H, Hamalainen E, Gorbach S, Goldin B. Dietary phytoestrogens and the menopause in Japan. Lancet. 1992;339:1233.[Medline]
3. Anderson JJ, Garner SC. Phytoestrogens and bone. Baillieres Clin Endocrinol Metab. 1998;12:543–57.[Medline]
4. Erdman JW Jr. AHA Science Advisory: soy protein and cardiovascular disease: a statement for healthcare professionals from the Nutrition Committee of the AHA. Circulation. 2000;102:2555–9.
5. Ho SC, Chan SG, Yip YB, Cheng A, Yi Q, Chan C. Menopausal symptoms and symptom clustering in Chinese women. Maturitas. 1999;33:219–27.[Medline]
6. Chan C, Ho SC, Chan SG, Yip YB, Wong FC, Cheng F. Factors affecting uptake of cervical and breast cancer screening among perimenopausal women in Hong Kong. Hong Kong Med J. 2002;8:334–41.[Medline]
7. Yip YB, Ho SC, Chan SG. Socio-psychological stressors as risk factors for low back pain in Chinese middle-aged women. J Adv Nurs. 2001;36:409–16.[Medline]
8. Guenther PM, Cleveland LE, Ingwersen LA. Questionnaire development and data collection procedures. In: Tippett, Katherine S. and Yasmin S. Cypel, editors. 1997. Design and Operation: The Continuing Survey of Food Intakes by Individuals and the Diet and Health Knowledge Survey, 1994–96. U.S. Department of Agriculture, Agricultural Research Service, Nationwide Food Surveys Report No. 96-1, 197 pp. Available from: http://www.ars.usda.gov/SP2UserFiles/Place/12355000/pdf/DORch_4.pdf [Accessed August 31, 2005].
9. USDA, Agricultural Research Service. 1994–6 Continuing Survey of Food Intakes by Individuals (CSFII): food instruction booklet. 1998. Available from: http://www.ars.usda.gov/SP2UserFiles/Place/12355000/pdf/FIB.pdf. [cited 2004 Sept 21].
10. Casey PH, Goolsby SL, Lensing SY, Perloff BP, Bogle ML. The use of telephone interview methodology to obtain 24-hour dietary recalls. J Am Diet Assoc. 1999;99:1406–11.[Medline]
11. USDA, Agricultural Research Service. USDA-Iowa State University Database on the Isoflavone Content of Foods, Release 1.3–2002 [database on the Internet]. [cited 2004 Sept 21]. Available from: http://www.nal.usda.gov/fnic/foodcomp/Data/isoflav/isoflav.html.
12. Block G, Dresser CM, Hartman AM, Carroll MD. Nutrient sources in the American diet: quantitative data from the NHANES II survey. I. Vitamins and minerals. Am J Epidemiol. 1985;122:13–26.
13. Block G, Dresser CM, Hartman AM, Carroll MD. Nutrient sources in the American diet: quantitative data from the NHANES II survey. II. Macronutrients and fats. Am J Epidemiol. 1985;122:27–40.
14. Batcher OM, Nichols JM. Identifying important sources of nutrients. J Nutr Educ. 1984;16:177–81.
15. Krebs-Smith SM, Cronin FJ, Haytowitz DB, Cook DA. Food sources of energy, macronutrients, cholesterol, and fiber in diets of women. J Am Diet Assoc. 1992;92:168–74.[Medline]
16. Royo-Bordonada MA, Gorgojo L, de Oya M, Garces C, Rodriguez-Artalejo F, Rubio R, del Barrio JL, Martin-Moreno JM. Food sources of nutrients in the diet of Spanish children: the Four Provinces Study. Br J Nutr. 2003;89:105–14.[Medline]
17. Messina M, Nagata C, Wu AH. Estimated Asian adult soy protein and isoflavone intakes. Nutr Cancer. 2006;55:1–12.[Medline]
18. Woo J, Leung SS, Ho SC, Lam TH, Janus ED. Dietary intake and practices in the Hong Kong Chinese population. J Epidemiol Community Health. 1998;52:631–7.[Abstract]
19. Wakai K, Egami I, Kato K, Kawamura T, Tamakoshi A, Lin Y, Nakayama T, Wada M, Ohno Y. Dietary intake and sources of isoflavones among Japanese. Nutr Cancer. 1999;33:139–45.[Medline]
20. Liu Z, Li W, Sun J, Liu C, Zeng Q, Huang J, Yu B, Huo J. Intake of soy foods and soy isoflavones by rural adult women in China. Asia Pac J Clin Nutr. 2004;13:204–9.[Medline]
21. Beaton GH. Human nutrient requirement estimates. Food, Nutrition and Agriculture No 2/3. 1991 [cited 2005 Aug 31]. Available from: http://www.fao.org/es/esn/fna/fna-e.htm.
22. Mackerras D. Energy adjustment: the concepts underlying the debate. J Clin Epidemiol. 1996;49:957–62.[Medline]
23. Dennerstein L, Smith AM, Morse C, Burger H, Green A, Hopper J, Ryan M. Menopausal symptoms in Australian women. Med J Aust. 1993;159:232–6.[Medline]
24. Manderbacka K, Lundberg O, Martikainen P. Do risk factors and health behaviors contribute to self-ratings of health? Soc Sci Med. 1999;48:1713–20.[Medline]
25. Osler M. Social class and health behavior in Danish adults: a longitudinal study. Public Health. 1993;107:251–60.[Medline]
26. Kim J. Kwon C. Estimated dietary isoflavone intake of Korean population based on National Nutrition Survey. Nutr Res. 2001;21:947–53.[Medline]
27. Keinan-Boker L, Peeters PH, Mulligan AA, Navarro C, Slimani N, Mattisson I, Lundin E, McTaggart A, Allen NE, et al. Soy product consumption in 10 European countries: the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Public Health Nutr. 2002;5:1217–26.[Medline]
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