Equol production is associated with bone mass in young women

Equol production is associated with bone mass in young women | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Equol production is associated with bone mass in young women Hiromi Hanano, Takumi Aoki, Shota Sasaki, Hiroyoshi Fuzikawa, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3855918/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Dec, 2025 Read the published version in BMC Women's Health → Version 1 posted 10 You are reading this latest preprint version Abstract Background Osteoporosis, a disease characterized by decreased bone strength and increased risk of fracture, represents a significant health concern in older adults. Primary osteoporosis prevention requires increasing bone mass (BM) to its peak at a young age. The estrogen-like effect of equol has been reported to suppress bone loss in postmenopausal women. This study aimed to investigate the relationship between BM, body mass, skeletal muscle mass, exercise habits, menstrual abnormalities, and equol production in younger women. Methods Of a total of 395 female university students recruited, 275 who were not taking any hormonal medications and had no deficiencies in any of the measurement items we evaluated, were included in the analysis. BM was measured in the right calcaneus using an ultrasonic bone densitometer. Body composition was measured via the bioelectrical impedance method, using a multifrequency body composition analyzer. Hormone use, menstrual cycle, current exercise habits, and daily soy intake were assessed using self-administered questionnaires. Equol production was measured using a Soy-Check system. Multiple regression analysis, using the forced-entry method, was performed with BM as the objective variable; and age, body mass index, skeletal muscle mass index, soy intake, exercise habits, menstrual cycle, and equol production as the explanatory variables. Results In our multiple regression analysis with osteo-sonoassessment indexas the objective variable, the significantly associated factors were determined to be the amount of equol production (β = 0.11, p < 0.05), skeletal muscle mass index (β = 0.29, p < 0.01), and current exercise habits (β = 0.31, p < 0.01). By contrast, age, body mass index, soy intake, and menstrual cycle were not found to be significantly associated with osteo-sonoassessment index. Conclusions Young women with higher equol production, exercise habits, and skeletal muscle mass indexshad higher levels of BM. The acquisition of maximal BM at a young age is protective against osteoporosis; therefore, increased equol production at a young age may protect against osteoporosis. Women’s health Osteoporosis Prevention University students Figures Figure 1 Background Osteoporosis, a disease characterized by decreased bone strength and an increased risk of fracture [1], is an important health problem in older adults. Falls and fractures account for 13.9% of cases requiring nursing care in Japan [2], and can significantly impact quality of life (QOL) [3]. In particular, women are at a higher risk of fractures following menopause when estrogen secretion declines [4], causing bone loss. Therefore, preventive measures against osteoporosis are important for women. To prevent osteoporosis, it is important to increase maximum bone mass (BM) in adolescence and minimize bone loss later in life [5,6]. Lifestyle factors, such as nutrition and exercise during adolescence, have a significant impact on the acquisition of sufficient maximum BM. In addition, as age-related loss of muscle mass also increases the risk of falls and fractures [7], increasing muscle mass at a young age can help prevent falls and fractures in old age as well. Equol has been shown to be effective at preventing bone loss in postmenopausal women. Equol is converted from the soy-derived isoflavone daidzein, via the metabolisms of certain gut bacteria [8], and its production varies among individuals [9]. Following one year of soy food consumption by postmenopausal women, one study found that the BM of the women who were capable of producing equol was less reduced than that of the non-producers [10]. Equol has properties that are similar to estrogen—a female hormone [11,12]. Decreased estrogen levels are believed to affect bone and calcium metabolism, leading to bone loss and osteoporosis [13]. Therefore, equol, with its female hormone-like effects, may be effective for maintaining and increasing BM. However, the relationship between BM and the ability of young women to produce equol at the time of maximal BM remains unclear. Furthermore, nutrition, exercise, menstruation, and other factors may affect maximal BM, and should therefore be included in any studies regarding the effect of equol on BM. This study aimed to investigate how BM, body mass, skeletal muscle mass, exercise habits, and menstrual abnormalities affect the ability of young women to produce equol. Methods 1. Participants Between 2021 and 2022, 395 female university students aged 18–25 years from Doshisha University, Sonoda Women's University, and Miyagi Gakuin Women's University were surveyed using measurements and questionnaires. The purpose of this study was explained both orally and in writing, and written informed consent was obtained from all participants. The study was approved by the Doshisha University Human Subjects Research Ethics Committee (approval number: 20049). The final analysis included 275 participants—excluding those taking hormonal agents, those who did not undergo an equol test, and those who did not respond to the questionnaire (Figure 1). 2. Bone mass measurement BM was measured using the AOS-100SA ultrasound bone densitometer (FUJIFILM Co., Ltd., Tokyo, Japan), which is simple to operate and does not expose the patient to radiation exposure. The osteo-sonoassessment index (OSI) of the right calcaneus was used as the main evaluation item. It was calculated from the speed of sound (SOS) and transmission index (TI) of the bone, using the equation: OSI = TI × SOS [2]. A higher SOS indicates higher bone density and a higher TI indicates higher BM [14]. 3. Measurement of Equol Production Participants were given the "Soy Check” equol test kit (Healthcare Systems Co., Ltd., Aichi, Japan). All of the participants consumed soy foods equivalent to approximately 100 mg of isoflavone between dinner and bedtime the day before the measurement and collected their first urine sample the following morning at home, using a tube from the kit [15]. Specifically, the participants recruited in 2021 consumed two 125 mL bottles of the soy beverage "Sugoi Daizu Original” (Otuka Food Co., Ltd., Osaka, Japan), and the participants recruited in 2022 consumed the soy supplement "Nature Made Soy Isoflavone” (Otuka Food Co., Ltd.). Following urine sample collection, each participant sent their test kit to a contracted laboratory (Health Care Systems Co., Ltd.) for analysis. Urinary equol production was calculated using creatinine-corrected values (μmol/g cre). 4. Questionnaire The participants self-reported their date of birth, current exercise habits, menstrual cycle, soy intake, and hormone medication. Current exercise habits were evaluated by asking the participants whether they belonged to an athletic club. The normal range for menstrual cycles was considered to be 25–38 days [16–18]. Soy intake was calculated using the Food Frequency Questionnaire Based on Food Groups (FFQ [ver. 6]) (KENPAKUSHA Co., Ltd., Tokyo, Japan). The FFQ can be used to estimate nutrient intake for each food group, based on standard intakes and number of intakes per meal [19]. Its validity as a method for estimating nutrient intake has been confirmed previously [20]. 5. Body measurements and body composition Height, weight, and appendicular skeletal muscle mass (ASM) were also measured. Body mass index (BMI) and skeletal muscle mass index (SMI) were measured via bioelectrical impedance analysis, using a Tanita MC-780A body composition analyzer (Tanita Co., Ltd., Tokyo, Japan). BMI was calculated from height and weight, and SMI [21] was calculated from ASM and height. 6. Statistical Analysis Univariate regression analysis was performed using OSI as the objective variable and equol production as the explanatory variable. Multiple regression analysis using the forced-entry method was also performed to examine factors related to BM—using equol production, current exercise habits, normal menstruation, soy intake, BMI, and SMI as explanatory variables. All analyses were performed using IBM SPSS Statistics version 29.0 (IBM Japan Co., Ltd., Tokyo, Japan), and statistical significance level was set at p < 0.05. Results Table 1 lists the characteristics of the 275 participants. The mean of OSI was 3.14 ± 0.42. Table 2 shows the results of the univariate and multiple regression analyses with OSI as the objective variable. In the univariate analysis, the amount of equol production had a significant positive relationship with OSI (B = 0.01, p < 0.05; Model a). In the multiple regression analysis with OSI as the objective variable, the significant associated factors were the amount of equol production (β = 0.11, p < 0.05), SMI (β = 0.29, p < 0.01), and current exercise habits (β = 0.31, p < 0.01; Model b). By contrast, age, BMI, soy intake, and menstrual cycle were not found to be significantly associated with OSI. Table 1. Characteristics of study participants (n=275) OSI 3.14 ± 0.42 Age (years) 20.09 ± 1.11 BMI 21.00 ± 2.62 SMI 7.10 ± 0.83 Soy intake (g/day) 50.47 ± 40.41 Equol production (µmol/g cre) 1.66 ± 4.67 Exercise habit (Yes/No) 118 (43%) / 157 (57%) Menstrual cycle (normal/abnormal) 206 (74%) / 71 (26%) Mean ± SD, or number of persons (%). OSI: Osteo-Sonoassessment Index. BMI: body mass index. SMI: muscle mass index. SD: standard deviation. Table 2 Univariate and multiple regression analysis with OSI as the objective variable Model a Model b B SE B SE β Equol production (µmol/g cre) 0.01 * 0.01 0.01 0.01 0.11 * Age (years) –0.02 0.02 –0.06 BMI 0.01 0.01 0.05 SMI 0.14 0.04 0.29 ** Soy intake (g/day) 0.00 0.00 –0.03 Exercise habit (Yes/No) 0.26 0.07 0.31 ** Menstrual cycle (normal/abnormal) –0.02 0.05 –0.02 *p<0.05. ** p<0.01. R 2 =0.322 (model b). F༝18.139** (model b). Model a indicates univariate regression analysis. Model b indicates multiple regression analysis. B: partial regression coefficient. SE: standard error. β: standardized partial regression coefficient. Discussion This study aimed to investigate the relationship between BM, body mass, skeletal muscle mass, exercise habits, menstrual abnormalities, and the ability of young women to produce equol. Higher SMI and exercise habits, as well as higher levels of equol production, were found to be associated with higher BM in young women. It has been previously reported that bone resorption was suppressed and bone loss was reduced in a cohort of postmenopausal women who were unable to produce equol when given an equol supplement [ 22 ]. Equol production in this study was also significantly associated with BM, although exercise habits and SMI were entered together into our multiple regression analysis. SMI and exercise habits are necessary for maximizing BM, and the ability to produce equol at a young age may help prevent osteoporosis and the need for assistance in older ages. On the othe hands,there are individual differences in equol production [ 9 ], and a comparison of the percentages of equol producers in different countries indicates that the percentage of equol production is higher in Asian populations than in Western ones [ 23 ]. However, in recent years, equol production in young Japanese women has declined compared to that in middle-aged and elderly women [ 24 ]. This decline has been attributed to a decrease in soy food intake, owing to a general Westernization of the Japanese diet [ 25 ]. However, it has also been reported that equol production may also be related to factors other than soy food intake [ 26 , 27 ]. The reasons for the decreased level of equol production observed recently in young Japanese women therefore remain unclear. Our results from this study indicate that BM in youth is related to equol production. However, it is also clear that even women with low equol production can compensate for the equol-related benefits to BM if they exercise regularly and have high SMI. The OSI of the participants in this study was higher than the OSI reference value [ 28 ] (2.71 for the same age group, 20 years). Exercise habits and muscle mass influence increases in BM. Bones have sensors that detect mechanical stresses such as strain. Exercise and other factors have been shown to increase BM when the bone strain exceeds a certain threshold. This is known as the mechanostat theory [ 29 ]. The present study also suggests that the association between exercise habits and BM is due to the mechanostat theory. Increases in BM involve not only mechanical stimuli during exercise, but also a number of other interactions between muscle and bone tissues [ 30 ]. Muscle and bone interaction means that when muscle mass increases or decreases, BM increases or decreases as well. A positive correlation has been reported between muscle mass and BM in a number of previous studies [ 31 , 32 ]. Moreover, an increase in muscle mass stimulates an increase in BM, even during the developmental period [ 33 ]. Our results were also influenced by the interaction between muscle and bone, with higher SMI values indicating higher BM. Nevertheless, this study had several key limitations worth noting. It was cross-sectional in design, and therefore not investigate effects and causal relationships. Second, the questionnaire was based on self-reporting; therefore, our results were susceptible to recall bias. Third, the participation rate for equol measurements may have decreased. The participants in this study were required to consume the equivalent of 100 mg of soy foods for the equol measurement, before collecting their first urine samples the following morning, which may have represented a cumbersome task for university students. However, we were able to clarify the relationship between BM and equol production at a young age, which is useful for the prevention of osteoporosis and the need for additional assistance in older ages. In a previous study that investigated equol production capacity, participants in their 20s were recruited at a gynecology clinic [ 34 ]. One of the major advantages of this study was that we recruited healthy female university students from a non-medical institution. Conclusion Young women with higher equol production, exercise habits, and SMI had higher BM. Achieving maximal BM at a young age is protective against osteoporosis; therefore, increased equol production at a young age may protect against osteoporosis. Declarations Acknowledgements We thank Nozomi Otani for her participation in the measurement of this study. And we thank the university students from Doshisha, Miyagi Gakuin, and Sonoda who participated in this study and those who helped with it. Author contributions H.H. and K.I. conceptualized the study. H.H., T.A., S.S., H.F., K.O., Y.Y., T.M. and H.Y. were responsible for date collection. H.H. drafted the manuscript; K.O., Y.Y., T.M., H.Y. and K.I. revised it critically for important intellectual content. All authors read and approved the final manuscript. Funding This study has not received any funding. Aavailability of data andmaterials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was approved by the Doshisha University Human Subjects Research Ethics Committee (approval number: 20049). Consent for publication Not applicable. Competing interests The authors declare no competing interests. References The North American Menopause Society. Management of osteoporosis in postmenopausal women: the 2021 position statement of The North American Menopause Society. Menopause. 2021;28(9):973-997. Ministry of Health, Labour and Welfare: Comprehensive Survey of Living Conditions. 2022; https://www.mhlw.go.jp/toukei/saikin/hw/k-tyosa/k-tyosa22/dl/05.pdf Guirguis-Blake JM, Michael YL, Perdue LA, Coppola EL, Beil TL. Interventions to Prevent Falls in Older Adults: Updated Evidence Report and Systematic Review for the -US Preventive Services Task Force. 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Association of Serum Phytoestrogen Concentration and Dietary Habits in a Sample Set of the JACC Study. J Epidemiol. 2005;15(Suppl 2):S196-202. Osteoporosis Japan. Use of QUS during measurement (QUS shiyou no zissai). Life Science.2005;13(1):OJ01-3.ec5’Ó (josteo.com) Frost HM. Muscle, bone, and the Utah paradigm: a 1999 overview. Med Sci Sports Exerc. 2000;32(5):911-917. Kaji H. Interaction between Muscle and Bone. J Bone Metab. 2014;21(1):29-40. Nakaoka D, Sugimoto T, Kaji H, Kanzawa M, Yano S, Yamauchi M, et al. Determinants of bone mineral density and spinal fracture risk in postmenopausal Japanese women. Osteoporos Int. 2001;12(7):548-554. Kaji H, Kosaka R, Yamauchi M, Kuno K, Chihara K, Sugimoto T. Effects of age, grip strength and smoking on forearm volumetric bone mineral density and bone geometry by peripheral quantitative computed tomography: comparisons between female and male. Endocr J. 2005;52(6):659-666. Sharir A, Stern T, Rot C, Shahar R, Zelzer E. Muscle force regulates bone shaping for optimal load-bearing capacity during embryogenesis. 2011;138(15):3247-3259. Yuan JP, Wang JH, Liu X. Metabolism of dietary soy isoflavones to equol by human intestinal microflora--implications for health. Mol Nutr Food Res. 2007;51(7):765-781. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Dec, 2025 Read the published version in BMC Women's Health → Version 1 posted Editorial decision: Revision requested 24 Jan, 2025 Reviews received at journal 05 Sep, 2024 Reviewers agreed at journal 04 Sep, 2024 Reviews received at journal 02 Sep, 2024 Reviewers agreed at journal 20 Aug, 2024 Reviewers invited by journal 31 Jan, 2024 Editor assigned by journal 31 Jan, 2024 Editor invited by journal 17 Jan, 2024 Submission checks completed at journal 17 Jan, 2024 First submitted to journal 12 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":19482,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant selection.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3855918/v1/4901aba1530dbb03ecba7441.png"},{"id":97723774,"identity":"55dcf879-7dee-43a3-9207-9e11e0d25757","added_by":"auto","created_at":"2025-12-08 16:05:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":412178,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3855918/v1/33fb8dff-5780-458a-a3ba-0cee731617d6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Equol production is associated with bone mass in young women","fulltext":[{"header":"Background","content":"\u003cp\u003eOsteoporosis, a disease characterized by decreased bone strength and\u0026nbsp;an increased risk of fracture [1], is an important health problem in older adults. Falls and fractures account for 13.9% of cases requiring nursing care in Japan [2], and can significantly impact quality of life (QOL) [3]. In particular, women are at\u0026nbsp;a higher risk\u0026nbsp;of fractures following menopause when estrogen secretion declines [4], causing bone loss. Therefore, preventive measures against osteoporosis are important for women. To prevent osteoporosis, it is important to increase\u0026nbsp;maximum bone mass (BM) in adolescence and\u0026nbsp;minimize bone loss later in life [5,6]. Lifestyle factors, such as nutrition and exercise during adolescence, have a significant impact on the acquisition of sufficient maximum BM.\u0026nbsp;In addition, as age-related loss of muscle mass also increases the risk of falls and fractures [7], increasing muscle mass at a young age can help prevent falls and fractures in old age as well.\u003c/p\u003e\n\u003cp\u003eEquol has been shown to be effective at preventing bone loss in postmenopausal women. Equol is converted from the soy-derived isoflavone daidzein, via the metabolisms of certain gut bacteria [8], and its production varies among individuals [9]. Following one year of soy food consumption by postmenopausal women, one study found that\u0026nbsp;the BM of the women who were capable of producing\u0026nbsp;equol was less reduced than that of the non-producers [10]. Equol has properties that are similar to estrogen\u0026mdash;a female hormone [11,12]. Decreased estrogen levels are believed to affect bone and calcium metabolism, leading to bone loss and osteoporosis [13]. Therefore, equol, with its female hormone-like effects, may be effective for maintaining and increasing BM. However, the relationship between BM and the ability\u0026nbsp;of young women to produce\u0026nbsp;equol at the time of maximal BM remains unclear. Furthermore, nutrition, exercise, menstruation, and other factors may affect\u0026nbsp;maximal BM, and should therefore be included in\u0026nbsp;any studies regarding the effect of equol on BM. This study aimed to investigate how BM, body mass, skeletal muscle mass, exercise habits, and menstrual abnormalities affect the ability of young women\u0026nbsp;to produce equol.\u003c/p\u003e\n"},{"header":"Methods","content":"\u003cp\u003e1. Participants\u003c/p\u003e\n\u003cp\u003eBetween 2021 and 2022, 395 female university students aged 18\u0026ndash;25 years from Doshisha University, Sonoda Women\u0026apos;s University, and Miyagi Gakuin Women\u0026apos;s University were surveyed using measurements and questionnaires. The purpose of this study was explained both orally and in writing, and written informed consent was obtained from all participants. The study was approved by the Doshisha University Human Subjects Research Ethics Committee (approval number: 20049). The final analysis included 275 participants\u0026mdash;excluding those taking hormonal agents, those who did not undergo an equol test, and those who did not respond to the questionnaire (Figure 1).\u003c/p\u003e\n\u003cp\u003e2. Bone mass measurement\u003c/p\u003e\n\u003cp\u003eBM was measured using the AOS-100SA ultrasound bone densitometer (FUJIFILM Co., Ltd., Tokyo, Japan), which is simple to operate and does not expose the patient to radiation exposure. The osteo-sonoassessment index (OSI) of the right calcaneus was used as the main evaluation item.\u0026nbsp;It\u0026nbsp;was calculated from\u0026nbsp;the speed\u0026nbsp;of sound (SOS) and transmission index (TI) of the bone, using the equation: OSI = TI \u0026times; SOS [2]. A higher SOS indicates higher bone density and\u0026nbsp;a higher TI indicates higher BM [14].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;3. Measurement of Equol Production\u003c/p\u003e\n\u003cp\u003eParticipants were given the \u0026quot;Soy Check\u0026rdquo; equol test kit (Healthcare Systems Co., Ltd., Aichi, Japan). All of the participants consumed soy foods equivalent to approximately 100 mg of isoflavone between dinner and bedtime the day before the measurement and collected their first urine sample the following morning at home, using a tube from the kit [15]. Specifically, the participants recruited in 2021 consumed two 125 mL bottles of the soy beverage \u0026quot;Sugoi Daizu Original\u0026rdquo; (Otuka Food Co., Ltd., Osaka, Japan), and the participants recruited in 2022 consumed the soy supplement \u0026quot;Nature Made Soy Isoflavone\u0026rdquo; (Otuka Food Co., Ltd.). Following urine sample collection, each participant sent their test kit to a contracted laboratory (Health Care Systems Co., Ltd.) for analysis. Urinary\u0026nbsp;equol production was calculated using creatinine-corrected values (\u0026mu;mol/g cre).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;4. Questionnaire\u003c/p\u003e\n\u003cp\u003eThe participants self-reported their date of birth, current exercise habits, menstrual cycle, soy intake, and hormone medication. Current exercise habits were evaluated by asking the participants whether they belonged to an athletic club. The normal range for menstrual cycles was considered to be 25\u0026ndash;38 days [16\u0026ndash;18]. Soy intake was calculated using the Food Frequency Questionnaire Based on Food Groups (FFQ [ver. 6]) (KENPAKUSHA Co., Ltd., Tokyo, Japan). The FFQ can be used to estimate nutrient intake for each food group, based on\u0026nbsp;standard intakes\u0026nbsp;and number of intakes per meal [19]. Its validity\u0026nbsp;as a method for estimating nutrient intake\u0026nbsp;has been confirmed\u0026nbsp;previously [20].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;5. Body measurements and body composition\u003c/p\u003e\n\u003cp\u003eHeight, weight, and appendicular skeletal muscle mass (ASM) were\u0026nbsp;also measured. Body mass index (BMI) and skeletal muscle mass index (SMI) were measured via\u0026nbsp;bioelectrical impedance analysis,\u0026nbsp;using\u0026nbsp;a Tanita MC-780A body composition analyzer\u0026nbsp;(Tanita Co., Ltd., Tokyo, Japan). BMI was calculated from height and weight, and SMI [21] was calculated from ASM and height.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;6. Statistical Analysis\u003c/p\u003e\n\u003cp\u003eUnivariate regression analysis was performed using OSI as the objective variable and equol production as the explanatory variable. Multiple regression analysis using the forced-entry method was also performed to examine factors related to BM\u0026mdash;using equol production, current exercise habits, normal menstruation, soy intake, BMI, and SMI as explanatory variables. All analyses were performed using IBM SPSS Statistics version 29.0 (IBM Japan Co., Ltd., Tokyo, Japan), and statistical significance level was set at p \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;1 lists the characteristics of the 275 participants. The mean of OSI was 3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eshows the results of the univariate and multiple regression analyses with OSI as the objective variable. In the univariate analysis, the amount of equol production had a significant positive relationship with OSI (B\u0026thinsp;=\u0026thinsp;0.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Model a). In the multiple regression analysis with OSI as the objective variable, the significant associated factors were the amount of equol production (β\u0026thinsp;=\u0026thinsp;0.11, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), SMI (β\u0026thinsp;=\u0026thinsp;0.29, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and current exercise habits (β\u0026thinsp;=\u0026thinsp;0.31, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Model b). By contrast, age, BMI, soy intake, and menstrual cycle were not found to be significantly associated with OSI.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;1. Characteristics of study participants (n=275)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoy intake (g/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e40.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEquol production (\u0026micro;mol/g cre)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e4.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise habit (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118 (43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e157 (57%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual cycle (normal/abnormal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206 (74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e71 (26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, or number of persons (%).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eOSI: Osteo-Sonoassessment Index. BMI: body mass index.\u003c/p\u003e \u003cp\u003eSMI: muscle mass index. SD: standard deviation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multiple regression analysis with OSI as the objective variable\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eModel a\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eModel b\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEquol production (\u0026micro;mol/g cre)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoy intake (g/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise habit (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual cycle (normal/abnormal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e*p\u0026lt;0.05. ** p\u0026lt;0.01. R\u003csup\u003e2\u003c/sup\u003e=0.322 (model b). F༝18.139** (model b).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eModel a indicates univariate regression analysis. Model b indicates multiple regression analysis.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eB: partial regression coefficient. SE: standard error. β: standardized partial regression coefficient.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to investigate the relationship between BM, body mass, skeletal muscle mass, exercise habits, menstrual abnormalities, and the ability of young women to produce equol. Higher SMI and exercise habits, as well as higher levels of equol production, were found to be associated with higher BM in young women.\u003c/p\u003e \u003cp\u003eIt has been previously reported that bone resorption was suppressed and bone loss was reduced in a cohort of postmenopausal women who were unable to produce equol when given an equol supplement [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Equol production in this study was also significantly associated with BM, although exercise habits and SMI were entered together into our multiple regression analysis. SMI and exercise habits are necessary for maximizing BM, and the ability to produce equol at a young age may help prevent osteoporosis and the need for assistance in older ages.\u003c/p\u003e \u003cp\u003eOn the othe hands,there are individual differences in equol production [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and a comparison of the percentages of equol producers in different countries indicates that the percentage of equol production is higher in Asian populations than in Western ones [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, in recent years, equol production in young Japanese women has declined compared to that in middle-aged and elderly women [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This decline has been attributed to a decrease in soy food intake, owing to a general Westernization of the Japanese diet [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, it has also been reported that equol production may also be related to factors other than soy food intake [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The reasons for the decreased level of equol production observed recently in young Japanese women therefore remain unclear. Our results from this study indicate that BM in youth is related to equol production. However, it is also clear that even women with low equol production can compensate for the equol-related benefits to BM if they exercise regularly and have high SMI.\u003c/p\u003e \u003cp\u003eThe OSI of the participants in this study was higher than the OSI reference value [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] (2.71 for the same age group, 20 years). Exercise habits and muscle mass influence increases in BM. Bones have sensors that detect mechanical stresses such as strain. Exercise and other factors have been shown to increase BM when the bone strain exceeds a certain threshold. This is known as the mechanostat theory [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The present study also suggests that the association between exercise habits and BM is due to the mechanostat theory. Increases in BM involve not only mechanical stimuli during exercise, but also a number of other interactions between muscle and bone tissues [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Muscle and bone interaction means that when muscle mass increases or decreases, BM increases or decreases as well. A positive correlation has been reported between muscle mass and BM in a number of previous studies [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Moreover, an increase in muscle mass stimulates an increase in BM, even during the developmental period [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Our results were also influenced by the interaction between muscle and bone, with higher SMI values indicating higher BM.\u003c/p\u003e \u003cp\u003eNevertheless, this study had several key limitations worth noting. It was cross-sectional in design, and therefore not investigate effects and causal relationships. Second, the questionnaire was based on self-reporting; therefore, our results were susceptible to recall bias. Third, the participation rate for equol measurements may have decreased. The participants in this study were required to consume the equivalent of 100 mg of soy foods for the equol measurement, before collecting their first urine samples the following morning, which may have represented a cumbersome task for university students.\u003c/p\u003e \u003cp\u003eHowever, we were able to clarify the relationship between BM and equol production at a young age, which is useful for the prevention of osteoporosis and the need for additional assistance in older ages. In a previous study that investigated equol production capacity, participants in their 20s were recruited at a gynecology clinic [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. One of the major advantages of this study was that we recruited healthy female university students from a non-medical institution.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eYoung women with higher equol production, exercise habits, and SMI had higher BM. Achieving maximal BM at a young age is protective against osteoporosis; therefore, increased equol production at a young age may protect against osteoporosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe thank Nozomi Otani for her participation in the measurement of this study. And we thank the university students from Doshisha, Miyagi Gakuin, and Sonoda who participated in this study and those who helped with it.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Author contributions\u003c/p\u003e\n\u003cp\u003eH.H. and K.I. conceptualized the study. H.H., T.A., S.S., H.F., K.O., Y.Y., T.M. and H.Y. were responsible for date collection. H.H. drafted the manuscript; K.O., Y.Y., T.M., H.Y. and K.I. revised it critically for important intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Funding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study has not received any funding.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Aavailability of data andmaterials \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Ethics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Doshisha University Human Subjects Research Ethics Committee (approval number: 20049).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Consent for publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Competing interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThe North American Menopause Society. 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J Epidemiol. 2000;10(2):127-135.\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"\"\u003eIino C, Shimoyama T, Iino K, Yokoyama Y, Chinda D, Sakuraba H, et al. \u003c/span\u003eDaidzein Intake Is Associated with Equol Producing Status through an Increase in the Intestinal Bacteria Responsible for Equol Production. Nutrients. 2019;11(2):433.\u003c/li\u003e\n\u003cli\u003eAkaza H, Miyanaga N, Takashima N, Naito S, Hirao Y, Tsukamoto T, et al. Comparisons of percent equol producers between prostate cancer patients and controls: case-controlled studies of isoflavones in Japanese, Korean and American residents. Jpn J Clin Oncol. 2004 ;34(2):86-89.\u003c/li\u003e\n\u003cli\u003eOzasa K, Nakao M, Watanabe Y, Hayashi K, Miki T, Mikami K, et al. Association of Serum Phytoestrogen Concentration and Dietary Habits in a Sample Set of the JACC Study. J Epidemiol. 2005;15(Suppl 2):S196-202.\u003c/li\u003e\n\u003cli\u003eOsteoporosis Japan. Use of QUS during measurement (QUS shiyou no zissai). 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Muscle force regulates bone shaping for optimal load-bearing capacity during embryogenesis. 2011;138(15):3247-3259.\u003c/li\u003e\n\u003cli\u003eYuan JP, Wang JH, Liu X. Metabolism of dietary soy isoflavones to equol by human intestinal microflora--implications for health. Mol Nutr Food Res. 2007;51(7):765-781.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Women’s health, Osteoporosis, Prevention, University students","lastPublishedDoi":"10.21203/rs.3.rs-3855918/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3855918/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground\u003c/p\u003e\n\u003cp\u003eOsteoporosis, a disease characterized by decreased bone strength and increased risk of fracture, represents a significant health concern in older adults. Primary osteoporosis prevention requires increasing bone mass (BM) to its peak at a young age. The estrogen-like effect of equol has been reported to suppress bone loss in postmenopausal women. This study aimed to investigate the relationship between BM, body mass, skeletal muscle mass, exercise habits, menstrual abnormalities, and equol production in younger women.\u003c/p\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003cp\u003eOf a total of 395 female university students recruited, 275 who were not taking any hormonal medications and had no deficiencies in any of the measurement items we evaluated, were included in the analysis. BM was measured in the right calcaneus using an ultrasonic bone densitometer. Body composition was measured via the bioelectrical impedance method, using a multifrequency body composition analyzer. Hormone use, menstrual cycle, current exercise habits, and daily soy intake were assessed using self-administered questionnaires. Equol production was measured using a Soy-Check system. Multiple regression analysis, using the forced-entry method, was performed with BM as the objective variable; and age, body mass index, skeletal muscle mass index, soy intake, exercise habits, menstrual cycle, and equol production as the explanatory variables.\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eIn our multiple regression analysis with osteo-sonoassessment indexas the objective variable, the significantly associated factors were determined to be the amount of equol production (β = 0.11, p \u0026lt; 0.05), skeletal muscle mass index (β = 0.29, p \u0026lt; 0.01), and current exercise habits (β = 0.31, p \u0026lt; 0.01). By contrast, age, body mass index, soy intake, and menstrual cycle were not found to be significantly associated with osteo-sonoassessment index.\u003c/p\u003e\n\u003cp\u003eConclusions\u003c/p\u003e\n\u003cp\u003eYoung women with higher equol production, exercise habits, and skeletal muscle mass indexshad higher levels of BM. The acquisition of maximal BM at a young age is protective against osteoporosis; therefore, increased equol production at a young age may protect against osteoporosis.\u003c/p\u003e","manuscriptTitle":"Equol production is associated with bone mass in young women","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-18 15:21:59","doi":"10.21203/rs.3.rs-3855918/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-24T07:20:32+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-05T10:57:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65187352602380526695759953027115068478","date":"2024-09-04T14:01:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-02T18:46:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257820200511872364543749754091658258375","date":"2024-08-20T16:32:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-31T10:40:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-31T10:39:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-01-17T09:39:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-17T09:35:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2024-01-12T06:27:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a424df56-cf99-42de-9aed-36d0e55ee513","owner":[],"postedDate":"January 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T15:59:40+00:00","versionOfRecord":{"articleIdentity":"rs-3855918","link":"https://doi.org/10.1186/s12905-025-04098-z","journal":{"identity":"bmc-womens-health","isVorOnly":false,"title":"BMC Women's Health"},"publishedOn":"2025-12-04 15:57:08","publishedOnDateReadable":"December 4th, 2025"},"versionCreatedAt":"2024-01-18 15:21:59","video":"","vorDoi":"10.1186/s12905-025-04098-z","vorDoiUrl":"https://doi.org/10.1186/s12905-025-04098-z","workflowStages":[]},"version":"v1","identity":"rs-3855918","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3855918","identity":"rs-3855918","version":["v1"]},"buildId":"itB540yAGKdqaaUR3okzg","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}