Association between Lifetime Endogenous Estrogen Exposure and Body Composition Metrics in Postmenopausal Women: Findings from the Tehran Lipid and Glucose Study

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This cross-sectional study aimed to investigate the association between EEE and body composition indices among postmenopausal women. Methods Data were obtained from the Tehran Lipid and Glucose Study (TLGS), including 960 women aged over 40 years. EEE was calculated based on reproductive events, and participants were categorized into tertiles. Anthropometric measurements and body composition were assessed using standardized protocols. Linear regression models were employed to evaluate associations, adjusting for potential confounders. Results It was revealed significant differences in body composition indices across EEE tertiles, with increasing EEE associated with decreased fat mass, skeletal muscle mass, and fat-free mass. Moreover, women with higher EEE exhibited lower anthropometric and body composition measurements compared to those with lower EEE, even after adjusting for confounding factors. Specifically, for each year of increasing EEE, fat mass decreased by 0.12 kg, skeletal muscle mass by 0.04 kg, fat-free mass by 0.07 kg, and fat mass ratio decreased by 0.003. Comparing tertiles, women with the highest EEE demonstrated significantly lower anthropometric and body composition measurements compared to those with the lowest EEE. Conclusion These findings suggest a link between EEE and favorable changes in body composition, highlighting the importance of considering reproductive history in health assessment. Endogenous estrogen exposure Body composition Postmenopausal women Fat mass Skeletal muscle mass Figures Figure 1 1. Introduction The body composition has been proposed as an indicator of cardiometabolic health status in numerous studies ( 1 , 2 ). Body composition parameters reflect the difference in fat mass, muscle mass and lean mass, so compared to anthropometric measures, they provide more precise predictors of individuals' health status ( 2 ). In addition to known factors affecting body fat levels such as gender, age, genetics and lifestyle, there is increasing evidence suggesting that estradiol is an important regulator of body composition and bioenergetics. The widespread distribution of estrogen receptors (ERs), their involvement in genomic and non-genomic signaling pathways suggest that the loss of estradiol in menopause likely has prominent effects beyond reproduction. The expression of ERs in brain, adipose tissue, and skeletal muscle highlights the potential role of estradiol in regulating body weight and other metabolic processes ( 3 ). In addition, the presence of mitochondrial ERs suggests the role of estradiol in the regulation of cellular bioenergetics. There is consistent evidence in basic and preclinical studies that disruption of estradiol signaling through genetic manipulations (such as estrogen receptor deletion) or surgical interventions (such as ovariectomy) leads to accelerated fat accumulation, accompanied by disproportionate increase in abdominal fat ( 4 , 5 ). However, the clinical evidence for the regulation of body composition and biological energy by estradiol is contradictory, so that there is evidence both for and against menopause as a mediator of changes in body composition ( 6 ). Moreover, controlled trials evaluating changes in body composition in response to hormone therapy in postmenopausal women or ovarian suppression using GnRH agonists in premenopausal women do not always reveal the same role for estrogens ( 7 , 8 ). Furthermore, in studies conducted regarding the relationship between reproductive history and anthropometric measurements as well as body composition, the findings have shown inconsistency ( 9 – 11 ). Women's reproductive period - menarche to menopause - can be a proxy for premenopausal exposure to endogenous estrogen (estradiol) throughout life, although in addition to the age at menarche and menopause, other reproductive events include the number and duration of pregnancies, breastfeeding duration, and oral contraceptives use, determines the duration and level of exposure to endogenous estrogen ( 12 ). The index of endogenous estrogen exposure (EEE) was first proposed in 2002 in a study by Kleijn et al. ( 12 ). To quantify the premenopausal endogenous estrogen exposure -considering the counteractive effects of progesterone dominant periods, they combined data related to reproductive events including age of menarche, age of menopause, number and duration of pregnancy, duration of breastfeeding, and use oral contraceptives. Later studies have shown that EEE are associated with various aspects of women's health, including the risk of cardiovascular diseases, kidney failure, fractures, and Alzheimer's disease ( 13 – 16 ). However, to our knowledge, there is no study that has examined the relationship between EEE and body composition, and research on the relationship between reproductive events and body composition measures is limited and more have dealt with anthropometric measures, and often conflicting. Therefore, this study aims to explore the association of endogenous exposure and body composition as an indicator of cardiometabolic health using the EEE index, which encompasses all reproductive event dimensions, postmenopausal women. 2. Materials and methods This study is a population-based cross-sectional study that was conducted in the Tehran Lipid and Glucose Study (TLGS), an ongoing prospective study that began in 1998 with the aim of identifying the prevalence of non-communicable disease risk factors and outcomes among 15,000 individuals aged ≥ 3 years, residents of District 13 of Tehran. Individuals are followed up at three-year interval. So far, 7 phases of TLGS have been done. The data of the present study were extracted from the 7th phase of TLGS (2018–2023). The TLGS details have been previously published on its design, reasoning, data collection methods, and sampling approach ( 17 ). 2.1. Subjects The total number of women who had participated in the 7th phase of the TLGS and had available body composition data was 3953. Of these, 2411 women were over 40 years of age, and among them, information on reproductive events was available for 1363 postmenopausal women to calculate endogenous estrogen exposure. Considering the exclusion criteria, individuals with a history of irregular menstruation (n = 89), surgical menopause (n = 78), hormone replacement therapy (n = 62), corticosteroid use (n = 24), diuretic use (n = 114), malignancy (n = 20), chronic lung disease (n = 1), heart failure (n = 1), kidney failure (n = 1), and a history of bariatric surgery (n = 2) were excluded from the study. Finally, the study included 960 postmenopausal women aged over 40 years (Fig. 1 ). This study complied with the Declaration of Helsinki and was approved by the Ethics Committee of the Research Institute for Endocrine Sciences (RIES) at the Shahid Beheshti University of Medical Sciences (code: IR.SBMU.ENDOCRINE.REC.1402.134). All participants provided written informed consent prior to participating in the study. 2.2. Measurements Basic data was collected by trained interviewers through face-to-face interviews using demographic information questionnaires, disease records questionnaire, Food Frequency Questionnaire (FFQ) ( 17 ), and fertility history questionnaires. During the anthropometric measurements, the participants were attired in light clothing and without shoes. Weight and height were assessed using a digital electronic weighing scale (Seca 707; range 0.1–150 kg; Seca, Hanover, MD) with a precision of up to 100 g and a tape meter stadiometer, respectively. Body mass index (BMI) was calculated by dividing weight (in kilograms) by the square of height (in meters). Waist circumference (WC) was measured in centimeters at the level of the umbilicus. Body composition was assessed using a portable multi-frequency bioelectrical impedance analyzer (BIA) device (Model: InBody 570, InBody Co., Ltd. Seoul, KOREA) using the standard protocol ( 18 ). The precision and reproducibility of these measurements in TLGS were appraised through ICC (intraclass correlation coefficient) analysis ( 18 ). The ICC values with 95% confidence interval for PBF and FFM indices were 0.996-0.991-0.998 and 0.998 − 0.997, respectively, with an average difference of (0.04) for two measurements. This demonstrates the reliability and reproducibility of the results, with values of 1.1 ± 0) and 1.04 ± 0.10. 2.3. Endogenous Estrogen Exposure Endogenous estrogen exposure duration was initially defined as the time interval between age at menarche and age at menopause. Cumulative duration of progesterone dominant (luteal) phases of menstrual cycles (2 weeks for each menstrual cycle), pregnancy (40 weeks for each birth or 20 weeks for each miscarriage), breastfeeding (ie, number of months per child) and use of contraceptives were subtracted from the primary EEE variable to include only E2-dominant (follicular) phases of the menstrual cycle. 2.4. Data analysis The statistical analysis involved descriptive statistics to summarize participant characteristics, including mean and standard deviation for continuous variables and frequencies for categorical variables. One-way ANOVA and the Kruskal-Wallis test were used to compare tertiles of EEE for normally and skewed distributed continuous variables, respectively, with post hoc tests for significant differences. The Pearson correlation coefficient was calculated to evaluate the correlation between the body composition indices and EEE duration. Linear regression models, including an unadjusted model and two adjusted models for age and confounding factors, explored the association between EEE duration and body composition. Statistical significance was set at P < 0.05 for all analyses, conducted using IBM SPSS Statistics version 20. 3. Results The mean (SD) age of the participants was 63.3 (7.8) years. The mean (SD) duration of EEE was 14.4 (3.1) years in T1, 25.3 (3.07) years in T2, and 35.17 (4.5) years in T3. There was a statistically significant difference between the age groups of T2 compared to T1 and T3 (p<0.001). Education level was significantly higher in T3 compared to other tertiles (P<0.001). No significant differences were observed in calorie intake, physical activity, and smoking across groups. The mean (SD) age of menarche and menopause were 12.8 (1.5) and 49.1 (5.1), respectively. The mean (SD) gestational weeks was 149 (63) weeks, with a median (IQR) of 20 (12-48) weeks for breastfeeding duration. Participants in different groups had significant differences in terms of fertility events, also use of hormonal contraceptive in the T3 was notably shorter than in T1 and T2 (p<0.001). Time after menopause was significantly longer in T3 compared to T2 and T3 (p<0.001) (Table 1). The mean (SD) weight and BMI in the study population were 71.3 (12) (kg) and 29.7 (4.8) (kg/m 2 ), respectively. In general, the mean (SD) of FM, SMM, FFM and FMR were 31.5 (9.05) kg, 21.6 (2.8) kg, 40.2 (4.8) kg and 1.45 (0.36). There were significant differences in all anthropometric and body composition indices among the different tertiles of endogenous estrogen exposure. According to the results of the ANOVA test and post hoc test, there was a significant difference between T1 and T3 in all anthropometric and body composition indices, and it was always lower in T3 (Table 2) (Supplementary 1 and 2). There was a significant negative correlation between anthropometric and body composition indices (except for the fat mass-to-muscle mass ratio) and endogenous estrogen exposure duration (Table 3). According to the results of the linear regression model in model 1 (unadjusted model) and in model 2 (adjusted for age), there were a significant relationship between all anthropometric and body composition indices (except for FMR) and duration of EEE, and the increase in EEE was associated with a decrease in anthropometric indices and body composition (except for FMR). After adjusting for all possible confounding factors (model 3) including age, education, calorie intake, physical activity, smoking, and duration after menopause, a significant relationship was observed in all indices, and as shown in model 3, for each year of increasing exposure to endogenous estrogen, FM decreases by 0.12 kg, SMM by 0.04 kg, FFM by 0.07 kg, and FMR decreased by 0.003, which suggests a further reduction of fat mass and preservation of muscle mass with EEE (Table 4). To compare the relationship between EEE and anthropometric and body composition indices between different tertiles, T1, which had the lowest EEE, was used as the reference group. Accordingly, all anthropometric and body composition indices in women in T3, who had the highest EEE (35.1 ± 5.4 years), compared to T1 (14.4 ± 3.1) year) was significantly less. After adjusting for confounding factors, it remained significant (Table 5). 4. Discussion The findings of this cross-sectional study in 960 postmenopausal women revealed that- following adjustments for confounding factors- for each year of increasing exposure to endogenous estrogen, fat mass decrease by 0.12 kg, skeletal muscle mass by 0.04 kg, fat free mass by 0.07 kg and the ratio of fat mass to muscle mass by 0.003. Moreover, the research showed that women in T3 with the highest EEE (35.1 ± 5.4 years) demonstrated a decrease in all anthropometric and body composition measurements, such as weight, waist circumference, BMI, FM, SMM, FMM, and FMR, compared to those in T1 with the lowest exposure (14.4 ± 3.1 years). Several previous studies have shown conflicting results regarding the relationship between the age of menarche and menopause, number and duration of pregnancy and breastfeeding on anthropometric indices and body composition. What stands out in these studies is that the collective influence of all fertility events has not been examined as a single variable. Instead, each reproductive event has been individually assessed in relation to anthropometric indicators and body composition. This approach may partially explain the contradictory findings in previous research. However, this study utilizes the variable of EEE, encompassing all reproductive events ( 9 – 11 , 19 – 21 ). According to prior research, there is compelling evidence indicating that estrogen plays a significant role in the regulation of adipogenesis. Animal studies have shown that complete removal of the Estrogen Receptor α (Erα) or the aromatase enzyme - essential in estrogen production - via genetic manipulation results in a substantial increase (50–180%) in the number of fat cells ( 22 , 23 ). In clinical observations, mutations in CYP19A1 (gene encoding aromatase enzyme) and ESR1 (gene encoding ERα) have been linked to increased fat tissue ( 24 , 25 ). Estrogen mainly inhibits the recruitment of Peroxisome Proliferator-Activated Receptor gamma (PPARɣ) activators including Steroid Receptor Coactivator-1 (SRC-1) and CREB-Binding Protein (CBP), thereby impacting adipocyte proliferation ( 26 ). It may also activate Cyclin-Dependent Kinase Inhibitors (CDKIs) p21 and p27 to influence fat mass. Additionally, estrogen impacts appetite, food intake, and fat distribution ( 27 , 28 ). In a cohort study with a 10-year follow-up of the UK Biobank in 2021, it has been shown that FM has a strong linear relationship with cardiovascular disease (CVD) in men and women. Specifically, for every standard deviation increase in fat mass in women (8.29 kg), there is 25% higher risk of CVD (HR = 1.25, 95% CI: 1.23–1.27). Similarly, for each standard deviation increase in FM in men (6.75 kg), there is a 20% higher risk of CVD (risk ratio = 1.20, 95% CI: 1.19–1.22) ( 29 ). According to the study by Farahmand et al. in the frame of the TLGS cohort, it was discovered that a shorter EEE is linked to increased CVD incidence (HR = 2.2, 95% CI: 2.6–6.1) ( 15 ). In our study, increasing the duration of EEE is associated with a decrease in FM. Considering the findings of these studies together, it can be suggested that the direction of our study is consistent with the Biobank study ( 29 ) and Farahmand's study ( 15 ), and one possible explanation for the impact of EEE on CVD could be its influence on fat mass levels. Estrogen's impact on skeletal muscle mass remains incompletely understood, with conflicting study findings ( 30 ). In vitro research indicates estrogen can influence myoblast cell growth and reduce inflammation post muscle injury ( 31 ). In some in vivo studies, estrogen has been associated with an increase in muscle size in female mice and a decrease in inflammation following muscle damage ( 32 , 33 ). However, in other studies following ovariectomy in adult female rats, an increase in skeletal muscle mass due to elevated collagen and/or non-protein content has been observed ( 34 , 35 ). Moreover, the increase in muscle weight after daily estradiol treatment has shown a decrease ( 35 , 36 ). In humans, the effects of estrogen on muscle are also poorly understood. For example, while some studies have shown that hormone replacement therapy with estrogen may reduce or even reverse the age-related loss of lean muscle mass and size in postmenopausal women ( 37 , 38 ), other studies have not shown an effect of estradiol on muscle mass, size or cross-sectional area following hormone replacement therapy in postmenopausal women ( 39 , 40 ). It seems that understanding the effects of estrogen and its mechanisms on skeletal muscle mass compared to fat mass is more complex and more research is needed in this field. Strengths of this study include its novelty in exploring the association between lifetime EEE and body composition metrics in postmenopausal women, employing a comprehensive index of EEE encompassing various reproductive events, a large sample size of 960 postmenopausal women, standardized protocols for anthropometric measurements and body composition assessment, and adjustment for potential confounders. However, limitations include the cross-sectional design, which precludes establishing causality or temporal relationships, retrospective data collection methods that may introduce recall bias, the possibility of residual confounding from unmeasured variables or unaccounted lifestyle factors influencing the observed associations, such as complete data on nutrition intake, including macronutrient composition, which could impact body composition outcomes. Bioelectrical impedance analysis is not the gold standard for determining body composition, but it has been shown in various studies that it is closely related to DEXA - the gold standard for determining body composition - and since it is cheap and available, its use is practical. To estimate the follicular phase, the same duration was used for all participants, which may be considered as a limitation of the present study. Conclusion In conclusion, our study elucidates a significant association between lifetime EEE and body composition metrics in postmenopausal women, revealing that increasing EEE is linked to favorable changes in body composition, including decreased fat mass and preserved skeletal muscle mass. Through comprehensive analysis encompassing various reproductive events, our findings underscore the importance of considering reproductive history in health assessments, particularly in understanding cardiometabolic health implications. This study contributes novel insights into the role of EEE in shaping body composition, emphasizing the need for further research to elucidate causal mechanisms and long-term implications, particularly in the context of cardiovascular disease risk and metabolic health in postmenopausal women. Declarations Acknowledgments None. Competing interests None. Data Availability Statement The data that support the findings of this study are available on request from the corresponding author, FH. Funding None. Author Contributions E.R., F.H., and F.RT. conceived and designed the study. M.M., E.R., M.N., B.A., and M.F. contributed to the interpretation of the results and wrote the first draft of the manuscript. M.V., F.H., F.A., and F.RT. critically revised the manuscript. All authors have read and approved the final manuscript. Ethics approval and consent to participate This study complied with the Declaration of Helsinki and was approved by the Ethics Committee of the Research Institute for Endocrine Sciences (RIES) at Shahid Beheshti University of Medical Sciences (code IR.SBMU.ENDOCRINE.REC.1402.134). All participants provided written informed consent. Consent for publication All authors have given consent for the paper to be published by the corresponding author. References Zeng Q, Dong SY, Sun XN, Xie J, Cui Y. 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Tables Table 1 to 5 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Supplementary1.docx Supplementary2.docx Tables.docx Cite Share Download PDF Status: Published Journal Publication published 21 Dec, 2024 Read the published version in BMC Women's Health → Version 1 posted Editorial decision: Revision requested 12 Aug, 2024 Reviews received at journal 10 Aug, 2024 Reviewers agreed at journal 04 Aug, 2024 Reviewers agreed at journal 01 Aug, 2024 Reviewers agreed at journal 31 Jul, 2024 Reviews received at journal 16 Jul, 2024 Reviewers agreed at journal 14 Jul, 2024 Reviewers agreed at journal 27 Jun, 2024 Reviewers invited by journal 13 Jun, 2024 Editor assigned by journal 11 Jun, 2024 Submission checks completed at journal 11 Jun, 2024 First submitted to journal 08 Jun, 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4548933","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":318429669,"identity":"5ad66b03-2897-4592-9e8b-d01ea451ab1e","order_by":0,"name":"Elahe Rashidi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Elahe","middleName":"","lastName":"Rashidi","suffix":""},{"id":318429670,"identity":"11b345b1-5528-4bb5-b739-dac24eccc7a4","order_by":1,"name":"Fahimeh Ramezani Tehrani","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Fahimeh","middleName":"Ramezani","lastName":"Tehrani","suffix":""},{"id":318429671,"identity":"a25f6573-47c4-4c01-87d9-b7a791791d9f","order_by":2,"name":"Majid Valizadeh","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Majid","middleName":"","lastName":"Valizadeh","suffix":""},{"id":318429672,"identity":"55d4c1cf-1a84-4141-ae4e-66d6fa1c17a8","order_by":3,"name":"Mahtab Niroomand","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mahtab","middleName":"","lastName":"Niroomand","suffix":""},{"id":318429673,"identity":"b0faa380-7664-427b-8e34-fe0cb08df4c8","order_by":4,"name":"Maryam Mahdavi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Mahdavi","suffix":""},{"id":318429674,"identity":"d4e9892c-53cd-4472-8f01-1510412d1eec","order_by":5,"name":"Maryam Farahmand","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Farahmand","suffix":""},{"id":318429675,"identity":"ada80b40-a347-4879-a88a-77e8925de0e7","order_by":6,"name":"Behnaz Abiri","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Behnaz","middleName":"","lastName":"Abiri","suffix":""},{"id":318429676,"identity":"db4a746d-377a-4931-85d9-6e4b55cbe7ca","order_by":7,"name":"Fereidoun Azizi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Fereidoun","middleName":"","lastName":"Azizi","suffix":""},{"id":318429677,"identity":"6f1a33de-69fe-497f-9be3-865488a59cfd","order_by":8,"name":"Farhad Hosseinpanah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYBACAySSjeEDwwEUccJaGGcQrwUC2Jh54FrwAHP29scfPhTcyeOf3fzssc2fO9EGB5gffmAouIdTi2XPGTPJGQbPiiXuHDM3zm17lrvhAJuxBINBMW6H3cgBusfgcGLDjQQz6dyGw0AtDGZA8QQ8WtIff/4D1DL/Rvo3aYs/IC3s3whoSTCQZgBq2XAjx0yagQ2khYeALWeAfukxOFxseCOnTLIX6JeZh3mKJRLwaTkODLEffw7nyd1I3ybx48+d3L7j7Rs/fPiDWwsMIKlgRuUSo2UUjIJRMApGARoAAJMbXMUDD5H4AAAAAElFTkSuQmCC","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Farhad","middleName":"","lastName":"Hosseinpanah","suffix":""}],"badges":[],"createdAt":"2024-06-08 05:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4548933/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4548933/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12905-024-03501-5","type":"published","date":"2024-12-21T15:57:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59525054,"identity":"53ffe691-ff7a-4d7b-95f8-e8beb25fd9dc","added_by":"auto","created_at":"2024-07-02 20:50:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20363,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the study population\u003c/p\u003e","description":"","filename":"Onlinedrawingimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4548933/v1/3761cf4da917d9b21e7d0571.png"},{"id":72201839,"identity":"64f98951-a171-4393-a1e8-8522c0b11b77","added_by":"auto","created_at":"2024-12-23 16:10:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":424002,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4548933/v1/7844abd6-aac9-47e1-911d-a53eb67cabf3.pdf"},{"id":59525055,"identity":"1a33a33f-c2a4-443d-859e-98c4368cf1d1","added_by":"auto","created_at":"2024-07-02 20:50:26","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36215,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4548933/v1/722121627e512c60045a7a33.docx"},{"id":59525056,"identity":"9ca9ffaa-5517-4bdc-a52d-321b9bae3e77","added_by":"auto","created_at":"2024-07-02 20:50:26","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":34035,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4548933/v1/233157c42eafcae3792594bc.docx"},{"id":59525050,"identity":"14fc8234-b4ef-4003-b14c-825b6c9e30b4","added_by":"auto","created_at":"2024-07-02 20:50:25","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":33711,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4548933/v1/833e8423f631c43842bf15c1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between Lifetime Endogenous Estrogen Exposure and Body Composition Metrics in Postmenopausal Women: Findings from the Tehran Lipid and Glucose Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe body composition has been proposed as an indicator of cardiometabolic health status in numerous studies (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Body composition parameters reflect the difference in fat mass, muscle mass and lean mass, so compared to anthropometric measures, they provide more precise predictors of individuals' health status (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In addition to known factors affecting body fat levels such as gender, age, genetics and lifestyle, there is increasing evidence suggesting that estradiol is an important regulator of body composition and bioenergetics. The widespread distribution of estrogen receptors (ERs), their involvement in genomic and non-genomic signaling pathways suggest that the loss of estradiol in menopause likely has prominent effects beyond reproduction. The expression of ERs in brain, adipose tissue, and skeletal muscle highlights the potential role of estradiol in regulating body weight and other metabolic processes (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In addition, the presence of mitochondrial ERs suggests the role of estradiol in the regulation of cellular bioenergetics.\u003c/p\u003e \u003cp\u003eThere is consistent evidence in basic and preclinical studies that disruption of estradiol signaling through genetic manipulations (such as estrogen receptor deletion) or surgical interventions (such as ovariectomy) leads to accelerated fat accumulation, accompanied by disproportionate increase in abdominal fat (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). However, the clinical evidence for the regulation of body composition and biological energy by estradiol is contradictory, so that there is evidence both for and against menopause as a mediator of changes in body composition (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Moreover, controlled trials evaluating changes in body composition in response to hormone therapy in postmenopausal women or ovarian suppression using GnRH agonists in premenopausal women do not always reveal the same role for estrogens (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Furthermore, in studies conducted regarding the relationship between reproductive history and anthropometric measurements as well as body composition, the findings have shown inconsistency (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWomen's reproductive period - menarche to menopause - can be a proxy for premenopausal exposure to endogenous estrogen (estradiol) throughout life, although in addition to the age at menarche and menopause, other reproductive events include the number and duration of pregnancies, breastfeeding duration, and oral contraceptives use, determines the duration and level of exposure to endogenous estrogen (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The index of endogenous estrogen exposure (EEE) was first proposed in 2002 in a study by Kleijn et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). To quantify the premenopausal endogenous estrogen exposure -considering the counteractive effects of progesterone dominant periods, they combined data related to reproductive events including age of menarche, age of menopause, number and duration of pregnancy, duration of breastfeeding, and use oral contraceptives. Later studies have shown that EEE are associated with various aspects of women's health, including the risk of cardiovascular diseases, kidney failure, fractures, and Alzheimer's disease (\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, to our knowledge, there is no study that has examined the relationship between EEE and body composition, and research on the relationship between reproductive events and body composition measures is limited and more have dealt with anthropometric measures, and often conflicting. Therefore, this study aims to explore the association of endogenous exposure and body composition as an indicator of cardiometabolic health using the EEE index, which encompasses all reproductive event dimensions, postmenopausal women.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003eThis study is a population-based cross-sectional study that was conducted in the Tehran Lipid and Glucose Study (TLGS), an ongoing prospective study that began in 1998 with the aim of identifying the prevalence of non-communicable disease risk factors and outcomes among 15,000 individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;3 years, residents of District 13 of Tehran. Individuals are followed up at three-year interval. So far, 7 phases of TLGS have been done. The data of the present study were extracted from the 7th phase of TLGS (2018\u0026ndash;2023). The TLGS details have been previously published on its design, reasoning, data collection methods, and sampling approach (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Subjects\u003c/h2\u003e \u003cp\u003eThe total number of women who had participated in the 7th phase of the TLGS and had available body composition data was 3953. Of these, 2411 women were over 40 years of age, and among them, information on reproductive events was available for 1363 postmenopausal women to calculate endogenous estrogen exposure. Considering the exclusion criteria, individuals with a history of irregular menstruation (n\u0026thinsp;=\u0026thinsp;89), surgical menopause (n\u0026thinsp;=\u0026thinsp;78), hormone replacement therapy (n\u0026thinsp;=\u0026thinsp;62), corticosteroid use (n\u0026thinsp;=\u0026thinsp;24), diuretic use (n\u0026thinsp;=\u0026thinsp;114), malignancy (n\u0026thinsp;=\u0026thinsp;20), chronic lung disease (n\u0026thinsp;=\u0026thinsp;1), heart failure (n\u0026thinsp;=\u0026thinsp;1), kidney failure (n\u0026thinsp;=\u0026thinsp;1), and a history of bariatric surgery (n\u0026thinsp;=\u0026thinsp;2) were excluded from the study. Finally, the study included 960 postmenopausal women aged over 40 years (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e This study complied with the Declaration of Helsinki and was approved by the Ethics Committee of the Research Institute for Endocrine Sciences (RIES) at the Shahid Beheshti University of Medical Sciences (code: IR.SBMU.ENDOCRINE.REC.1402.134). All participants provided written informed consent prior to participating in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Measurements\u003c/h2\u003e \u003cp\u003eBasic data was collected by trained interviewers through face-to-face interviews using demographic information questionnaires, disease records questionnaire, Food Frequency Questionnaire (FFQ) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), and fertility history questionnaires. During the anthropometric measurements, the participants were attired in light clothing and without shoes. Weight and height were assessed using a digital electronic weighing scale (Seca 707; range 0.1\u0026ndash;150 kg; Seca, Hanover, MD) with a precision of up to 100 g and a tape meter stadiometer, respectively. Body mass index (BMI) was calculated by dividing weight (in kilograms) by the square of height (in meters).\u003c/p\u003e \u003cp\u003eWaist circumference (WC) was measured in centimeters at the level of the umbilicus. Body composition was assessed using a portable multi-frequency bioelectrical impedance analyzer (BIA) device (Model: InBody 570, InBody Co., Ltd. Seoul, KOREA) using the standard protocol (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The precision and reproducibility of these measurements in TLGS were appraised through ICC (intraclass correlation coefficient) analysis (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The ICC values with 95% confidence interval for PBF and FFM indices were 0.996-0.991-0.998 and 0.998\u0026thinsp;\u0026minus;\u0026thinsp;0.997, respectively, with an average difference of (0.04) for two measurements. This demonstrates the reliability and reproducibility of the results, with values of 1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0) and 1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Endogenous Estrogen Exposure\u003c/h2\u003e \u003cp\u003eEndogenous estrogen exposure duration was initially defined as the time interval between age at menarche and age at menopause. Cumulative duration of progesterone dominant (luteal) phases of menstrual cycles (2 weeks for each menstrual cycle), pregnancy (40 weeks for each birth or 20 weeks for each miscarriage), breastfeeding (ie, number of months per child) and use of contraceptives were subtracted from the primary EEE variable to include only E2-dominant (follicular) phases of the menstrual cycle.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Data analysis\u003c/h2\u003e \u003cp\u003eThe statistical analysis involved descriptive statistics to summarize participant characteristics, including mean and standard deviation for continuous variables and frequencies for categorical variables. One-way ANOVA and the Kruskal-Wallis test were used to compare tertiles of EEE for normally and skewed distributed continuous variables, respectively, with post hoc tests for significant differences. The Pearson correlation coefficient was calculated to evaluate the correlation between the body composition indices and EEE duration. Linear regression models, including an unadjusted model and two adjusted models for age and confounding factors, explored the association between EEE duration and body composition. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all analyses, conducted using IBM SPSS Statistics version 20.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe mean (SD) age of the participants was 63.3 (7.8) years. The mean (SD) duration of EEE was 14.4 (3.1) years in T1, 25.3 (3.07) years in T2, and 35.17 (4.5) years in T3. There was a statistically significant difference between the age groups of T2 compared to T1 and T3 (p\u0026lt;0.001). Education level was significantly higher in T3 compared to other tertiles (P\u0026lt;0.001). No significant differences were observed in calorie intake, physical activity, and smoking across groups. The mean (SD) age of menarche and menopause were 12.8 (1.5) and 49.1 (5.1), respectively. The mean (SD) gestational weeks was 149 (63) weeks, with a median (IQR) of 20 (12-48) weeks for breastfeeding duration. Participants in different groups had significant differences in terms of fertility events, also use of hormonal contraceptive in the T3 was notably shorter than in T1 and T2 (p\u0026lt;0.001). Time after menopause was significantly longer in T3 compared to T2 and T3 (p\u0026lt;0.001) (Table 1).\u003c/p\u003e\n\u003cp\u003eThe mean (SD) weight and BMI in the study population were 71.3 (12) (kg) and 29.7 (4.8) (kg/m\u003csup\u003e2\u003c/sup\u003e), respectively. In general, the mean (SD) of FM, SMM, FFM and FMR were 31.5 (9.05) kg,\u0026nbsp;21.6 (2.8)\u0026nbsp;kg, 40.2 (4.8) kg and 1.45 (0.36). There were significant differences in all anthropometric and body composition indices among the different tertiles of endogenous estrogen exposure. According to the results of the ANOVA test and post hoc test, there was a significant difference between T1 and T3 in all anthropometric and body composition indices, and it was always lower in T3 (Table 2)\u0026nbsp;(Supplementary 1 and 2).\u003c/p\u003e\n\u003cp\u003eThere was a significant negative correlation between anthropometric and body composition indices (except for the fat mass-to-muscle mass ratio) and endogenous estrogen exposure duration (Table 3).\u003c/p\u003e\n\u003cp\u003eAccording to the results of the linear regression model in model 1 (unadjusted model) and in model 2 (adjusted for age), there were a significant relationship between all anthropometric and body composition indices (except for FMR) and duration of EEE, and the increase in EEE was associated with a decrease in anthropometric indices and body composition (except for FMR). After adjusting for all possible confounding factors (model 3) including age, education, calorie intake, physical activity, smoking, and duration after menopause, a significant relationship was observed in all indices, and as shown in model 3, for each year of increasing exposure to endogenous estrogen, FM decreases by 0.12 kg, SMM by 0.04 kg, FFM by 0.07 kg, and FMR decreased by 0.003, which suggests a further reduction of fat mass and preservation of muscle mass with EEE (Table 4). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo compare the relationship between EEE and anthropometric and body composition indices between different tertiles, T1, which had the lowest EEE, was used as the reference group. Accordingly, all anthropometric and body composition indices in women in T3, who had the highest EEE (35.1 \u0026plusmn; 5.4 years), compared to T1 (14.4 \u0026plusmn; 3.1) year) was significantly less. After adjusting for confounding factors, it remained significant (Table 5).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe findings of this cross-sectional study in 960 postmenopausal women revealed that- following adjustments for confounding factors- for each year of increasing exposure to endogenous estrogen, fat mass decrease by 0.12 kg, skeletal muscle mass by 0.04 kg, fat free mass by 0.07 kg and the ratio of fat mass to muscle mass by 0.003. Moreover, the research showed that women in T3 with the highest EEE (35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4 years) demonstrated a decrease in all anthropometric and body composition measurements, such as weight, waist circumference, BMI, FM, SMM, FMM, and FMR, compared to those in T1 with the lowest exposure (14.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 years).\u003c/p\u003e \u003cp\u003eSeveral previous studies have shown conflicting results regarding the relationship between the age of menarche and menopause, number and duration of pregnancy and breastfeeding on anthropometric indices and body composition. What stands out in these studies is that the collective influence of all fertility events has not been examined as a single variable. Instead, each reproductive event has been individually assessed in relation to anthropometric indicators and body composition. This approach may partially explain the contradictory findings in previous research. However, this study utilizes the variable of EEE, encompassing all reproductive events (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to prior research, there is compelling evidence indicating that estrogen plays a significant role in the regulation of adipogenesis. Animal studies have shown that complete removal of the Estrogen Receptor α (Erα) or the aromatase enzyme - essential in estrogen production - via genetic manipulation results in a substantial increase (50\u0026ndash;180%) in the number of fat cells (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In clinical observations, mutations in CYP19A1 (gene encoding aromatase enzyme) and ESR1 (gene encoding ERα) have been linked to increased fat tissue (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Estrogen mainly inhibits the recruitment of Peroxisome Proliferator-Activated Receptor gamma (PPARɣ) activators including Steroid Receptor Coactivator-1 (SRC-1) and CREB-Binding Protein (CBP), thereby impacting adipocyte proliferation (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). It may also activate Cyclin-Dependent Kinase Inhibitors (CDKIs) p21 and p27 to influence fat mass. Additionally, estrogen impacts appetite, food intake, and fat distribution (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a cohort study with a 10-year follow-up of the UK Biobank in 2021, it has been shown that FM has a strong linear relationship with cardiovascular disease (CVD) in men and women. Specifically, for every standard deviation increase in fat mass in women (8.29 kg), there is 25% higher risk of CVD (HR\u0026thinsp;=\u0026thinsp;1.25, 95% CI: 1.23\u0026ndash;1.27). Similarly, for each standard deviation increase in FM in men (6.75 kg), there is a 20% higher risk of CVD (risk ratio\u0026thinsp;=\u0026thinsp;1.20, 95% CI: 1.19\u0026ndash;1.22) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). According to the study by Farahmand et al. in the frame of the TLGS cohort, it was discovered that a shorter EEE is linked to increased CVD incidence (HR\u0026thinsp;=\u0026thinsp;2.2, 95% CI: 2.6\u0026ndash;6.1) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In our study, increasing the duration of EEE is associated with a decrease in FM. Considering the findings of these studies together, it can be suggested that the direction of our study is consistent with the Biobank study (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) and Farahmand's study (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), and one possible explanation for the impact of EEE on CVD could be its influence on fat mass levels.\u003c/p\u003e \u003cp\u003eEstrogen's impact on skeletal muscle mass remains incompletely understood, with conflicting study findings (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). In vitro research indicates estrogen can influence myoblast cell growth and reduce inflammation post muscle injury (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In some in vivo studies, estrogen has been associated with an increase in muscle size in female mice and a decrease in inflammation following muscle damage (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). However, in other studies following ovariectomy in adult female rats, an increase in skeletal muscle mass due to elevated collagen and/or non-protein content has been observed (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Moreover, the increase in muscle weight after daily estradiol treatment has shown a decrease (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn humans, the effects of estrogen on muscle are also poorly understood. For example, while some studies have shown that hormone replacement therapy with estrogen may reduce or even reverse the age-related loss of lean muscle mass and size in postmenopausal women (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), other studies have not shown an effect of estradiol on muscle mass, size or cross-sectional area following hormone replacement therapy in postmenopausal women (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). It seems that understanding the effects of estrogen and its mechanisms on skeletal muscle mass compared to fat mass is more complex and more research is needed in this field.\u003c/p\u003e \u003cp\u003eStrengths of this study include its novelty in exploring the association between lifetime EEE and body composition metrics in postmenopausal women, employing a comprehensive index of EEE encompassing various reproductive events, a large sample size of 960 postmenopausal women, standardized protocols for anthropometric measurements and body composition assessment, and adjustment for potential confounders. However, limitations include the cross-sectional design, which precludes establishing causality or temporal relationships, retrospective data collection methods that may introduce recall bias, the possibility of residual confounding from unmeasured variables or unaccounted lifestyle factors influencing the observed associations, such as complete data on nutrition intake, including macronutrient composition, which could impact body composition outcomes. Bioelectrical impedance analysis is not the gold standard for determining body composition, but it has been shown in various studies that it is closely related to DEXA - the gold standard for determining body composition - and since it is cheap and available, its use is practical. To estimate the follicular phase, the same duration was used for all participants, which may be considered as a limitation of the present study.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eIn conclusion, our study elucidates a significant association between lifetime EEE and body composition metrics in postmenopausal women, revealing that increasing EEE is linked to favorable changes in body composition, including decreased fat mass and preserved skeletal muscle mass. Through comprehensive analysis encompassing various reproductive events, our findings underscore the importance of considering reproductive history in health assessments, particularly in understanding cardiometabolic health implications. This study contributes novel insights into the role of EEE in shaping body composition, emphasizing the need for further research to elucidate causal mechanisms and long-term implications, particularly in the context of cardiovascular disease risk and metabolic health in postmenopausal women.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author, FH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.R., F.H., and F.RT. conceived and designed the study. M.M., E.R., M.N., B.A., and M.F. contributed to the interpretation of the results and wrote the first draft of the manuscript. M.V., F.H., F.A., and F.RT. critically revised the manuscript. All authors have read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study complied with the Declaration of Helsinki and was approved by the Ethics Committee of the Research Institute for Endocrine Sciences (RIES) at Shahid Beheshti University of Medical Sciences (code IR.SBMU.ENDOCRINE.REC.1402.134). All participants provided written informed consent.\u0026nbsp;\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have given consent for the paper to be published by the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZeng Q, Dong SY, Sun XN, Xie J, Cui Y. Percent body fat is a better predictor of cardiovascular risk factors than body mass index. Braz J Med Biol Res. 2012;45:591\u0026ndash;600.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomero-Corral A, Somers VK, Sierra-Johnson J, Thomas RJ, Collazo-Clavell ML, Korinek JE, Allison TG, Batsis JA, Sert-Kuniyoshi FH, Lopez-Jimenez F. Accuracy of body mass index in diagnosing obesity in the adult general population. Int J Obes. 2008;32(6):959\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Pelt RE, Gavin KM, Kohrt WM. 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Comprehensive evaluation of body composition in a wide age range of Iranian adults using bioelectrical impedance analysis: Tehran Lipid and Glucose Study. Public Health Nutr. 2024;27(1):e24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanellakis S, Karalexi MA, Apostolidou E, Skoufas E, Kontoe M, Bacopoulou F, Tsitsas G, Migdanis A, Boudouvi E, Canellopoulos L, Manios Y. Earlier age at menarche is associated with body fat and negative body image in adult life. Behav Med. 2023;49(2):105\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsrullah M, L\u0026rsquo;Hoir M, Feskens EJ, Melse-Boonstra A. Trend in age at menarche and its association with body weight, body mass index and non-communicable disease prevalence in Indonesia: evidence from the Indonesian Family Life Survey (IFLS). BMC Public Health. 2022;22(1):628.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcClure CK, Schwarz EB, Conroy MB, Tepper PG, Janssen I, Sutton-Tyrrell KC. Breastfeeding and subsequent maternal visceral adiposity. Obesity. 2011;19(11):2205\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeine PA, Taylor JA, Iwamoto GA, Lubahn DB, Cooke PS. Increased adipose tissue in male and female estrogen receptor-α knockout mice. Proceedings of the National Academy of Sciences. 2000; 97 (23):12729-34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones ME, Thorburn AW, Britt KL, Hewitt KN, Wreford NG, Proietto J, Oz OK, Leury BJ, Robertson KM, Yao S, Simpson ER. Aromatase-deficient (ArKO) mice have a phenotype of increased adiposity. 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Skeletal muscle wasting: The estrogen side of sexual dimorphism. Am J Physiology-Cell Physiol. 2022;322(1):C24\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKahlert S, Groh\u0026eacute; C, Karas RH, L\u0026ouml;bbert K, Neyses L, Vetter H. Effects of estrogen on skeletal myoblast growth. Biochem Biophys Res Commun. 1997;232(2):373\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTiidus PM, Holden D, Bombardier E, Zajchowski S, Enns D, Belcastro A. Estrogen effect on post-exercise skeletal muscle neutrophil infiltration and calpain activity. Can J Physiol Pharmacol. 2001;79(5):400\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSciote JJ, Horton MJ, Zyman Y, Pascoe G. Differential effects of diminished oestrogen and androgen levels on development of skeletal muscle fibres in hypogonadal mice. Acta Physiol Scand. 2001;172(3):179\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSitnick M, Foley AM, Brown M, Spangenburg EE. Ovariectomy prevents the recovery of atrophied gastrocnemius skeletal muscle mass. J Appl Physiol. 2006;100(1):286\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoran AL, Nelson SA, Landisch RM, Warren GL, Lowe DA. Estradiol replacement reverses ovariectomy-induced muscle contractile and myosin dysfunction in mature female mice. J Appl Physiol. 2007;102(4):1387\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcClung JM, Davis JM, Wilson MA, Goldsmith EC, Carson JA. Estrogen status and skeletal muscle recovery from disuse atrophy. J Appl Physiol. 2006;100(6):2012\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSorensen MB, Rosenfalck AM, H\u0026oslash;jgaard L, Ottesen B. Obesity and sarcopenia after menopause are reversed by sex hormone replacement therapy. Obes Res. 2001;9(10):622\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaaffe DR, Sipil\u0026auml; S, Cheng S, Puolakka J, Toivanen J, Suominen H. The effect of hormone replacement therapy and/or exercise on skeletal muscle attenuation in postmenopausal women: a yearlong intervention. Clin Physiol Funct Imaging. 2005;25(5):297\u0026ndash;304.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown M, Birge SJ, Kohrt WM. Hormone replacement therapy does not augment gains in muscle strength or fat-free mass in response to weight-bearing exercise. Journals Gerontol Ser A: Biol Sci Med Sci. 1997;52(3):B166\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaddalozzo GF, Cardinal BJ, Li F, Snow CM. The association between hormone therapy use and changes in strength and body composition in early postmenopausal women. Menopause. 2004;11(4):438\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 5 are available in the Supplementary Files section.\u003c/p\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":"Endogenous estrogen exposure, Body composition, Postmenopausal women, Fat mass, Skeletal muscle mass","lastPublishedDoi":"10.21203/rs.3.rs-4548933/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4548933/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe role of endogenous estrogen exposure (EEE) in shaping body composition and its implications for cardiometabolic health remain understudied despite its potential significance. This cross-sectional study aimed to investigate the association between EEE and body composition indices among postmenopausal women.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData were obtained from the Tehran Lipid and Glucose Study (TLGS), including 960 women aged over 40 years. EEE was calculated based on reproductive events, and participants were categorized into tertiles. Anthropometric measurements and body composition were assessed using standardized protocols. Linear regression models were employed to evaluate associations, adjusting for potential confounders.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIt was revealed significant differences in body composition indices across EEE tertiles, with increasing EEE associated with decreased fat mass, skeletal muscle mass, and fat-free mass. Moreover, women with higher EEE exhibited lower anthropometric and body composition measurements compared to those with lower EEE, even after adjusting for confounding factors. Specifically, for each year of increasing EEE, fat mass decreased by 0.12 kg, skeletal muscle mass by 0.04 kg, fat-free mass by 0.07 kg, and fat mass ratio decreased by 0.003. Comparing tertiles, women with the highest EEE demonstrated significantly lower anthropometric and body composition measurements compared to those with the lowest EEE.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese findings suggest a link between EEE and favorable changes in body composition, highlighting the importance of considering reproductive history in health assessment.\u003c/p\u003e","manuscriptTitle":"Association between Lifetime Endogenous Estrogen Exposure and Body Composition Metrics in Postmenopausal Women: Findings from the Tehran Lipid and Glucose Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-02 20:50:16","doi":"10.21203/rs.3.rs-4548933/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-12T07:04:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-10T14:12:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276363369893595881499358499295318374016","date":"2024-08-04T13:04:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110146255931704213355963853353024336920","date":"2024-08-01T12:47:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"325879703148463165721801989571360977133","date":"2024-07-31T07:56:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-16T10:16:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25903577265499976732847270817318662982","date":"2024-07-14T17:13:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211354142514002969930391174325142274509","date":"2024-06-27T19:01:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-13T17:14:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-12T03:40:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-11T23:15:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2024-06-08T05:01:16+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":"761ed606-f826-419c-866c-d6a90a15f4be","owner":[],"postedDate":"July 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:02:44+00:00","versionOfRecord":{"articleIdentity":"rs-4548933","link":"https://doi.org/10.1186/s12905-024-03501-5","journal":{"identity":"bmc-womens-health","isVorOnly":false,"title":"BMC Women's Health"},"publishedOn":"2024-12-21 15:57:46","publishedOnDateReadable":"December 21st, 2024"},"versionCreatedAt":"2024-07-02 20:50:16","video":"","vorDoi":"10.1186/s12905-024-03501-5","vorDoiUrl":"https://doi.org/10.1186/s12905-024-03501-5","workflowStages":[]},"version":"v1","identity":"rs-4548933","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4548933","identity":"rs-4548933","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}