A Multidisciplinary Approach to Weight Management and Reproductive Care: A Retrospective Cohort Study on Weight Loss through Personalized and Patient-Centered Care

A Multidisciplinary Approach to Weight Management and Reproductive Care: A Retrospective Cohort Study on Weight Loss through Personalized and Patient-Centered Care | 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Multidisciplinary Approach to Weight Management and Reproductive Care: A Retrospective Cohort Study on Weight Loss through Personalized and Patient-Centered Care Samantha Schon, Jocelyn Spizman, Daria Stelmak, Mark Chames, Stacey Pilarz, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6017583/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jun, 2025 Read the published version in Reproductive Biology and Endocrinology → Version 1 posted 8 You are reading this latest preprint version Abstract Background Obesity is a highly prevalent chronic disease with a significant and complex impact on reproduction. National guidelines recommend weight loss prior to pregnancy for patients with obesity to mitigate complications and increase fertility; however, targeted, personalized interventions are limited. The objectives of this study are to describe the implementation of a multidisciplinary program designed specifically for women with reproductive disorders and obesity and to report differences in baseline characteristics and weight loss outcomes between women willing vs not willing to defer pregnancy attempts to focus on weight loss. Methods Retrospective cohort study at a university multidisciplinary program for women with reproductive disorders and obesity. All participants from program initiation (November 2021) through July 2023 were included in the analysis. Primary outcome was percent body weight loss at 3 months. Secondary outcomes included weight loss at 6 months and achievement of > 5% and > 10% weight loss at each time point. Results A total of 237 participants were included in the analysis. The majority of participants (88.2%) desired pregnancy. 63.2% of participants who desired pregnancy were willing to postpone pregnancy attempts/fertility treatments so that they could focus on weight loss for at least 3 months. Participants willing to defer pregnancy attempts achieved a significantly greater weight loss at 3 months compared to those who continued pregnancy attempts (mean − 4.8% vs -2.5%, p = 0.004) and were more likely to achieve > 10% body weight loss at 3 months (14.0% vs 2.20%, p = 0.031). Those who achieved > 5% weight loss by 6 months were more likely to achieve pregnancy within the first 6 months of trying to conceive (34.1% vs 7.7%, p = 0.004). Conclusions We describe the development and implementation of a multidisciplinary program for women with reproductive disorders and obesity seeking weight management. An individualized approach to weight management and reproductive care results in clinically significant weight loss especially among women willing to defer pregnancy attempts and focus on weight loss for at least 3 months. Trial Registration: Clinical trial number: not applicable. Weight loss obesity infertility PCOS anti-obesity medication weight navigation reproduction Figures Figure 1 Figure 2 Background Obesity is a highly prevalent chronic disease, affecting over 40% of US adults ( 1 ). While men and women experience similar overall rates of obesity (defined as a BMI ≥ 30 kg/m²), the rate of severe obesity (BMI ≥ 40 kg/m²) is nearly double in women compared with men (12.1% vs. 6.7%) ( 1 ). Obesity affects nearly one-third of reproductive-aged women before pregnancy ( 2 ). The impact of obesity on reproduction is both significant and complex. Clinically, women with obesity often experience menstrual irregularities, anovulation, and longer time to pregnancy ( 3 – 8 ). Infertility rates are higher in women with obesity, and fertility treatments are less successful ( 3 , 9 – 11 ). During pregnancy, obesity is also associated with an increased risk of miscarriage, hypertensive disorders of pregnancy, gestational diabetes, cesarean section, and stillbirth ( 12 ). Given the impact of obesity on fertility as well as associated maternal and fetal risks, national societies recommend weight loss for women with obesity prior to pregnancy ( 12 ). Despite broad recommendations for weight loss, interventions to achieve this goal are usually limited to encouragement of general behavioral modification and/or referral to comprehensive weight management programs ( 12 ), rather than treatments designed specifically for this unique and underrepresented population. Furthermore, long wait times for specialty clinics may pose challenges for women of advanced reproductive age who wish to conceive ( 13 ). In addition to a lack of personalized interventions, women with obesity and reproductive disorders may face significant barriers to receiving comprehensive and sensitive care. Individuals with obesity face pervasive society-wide stigma which adversely affects the quality of healthcare provided ( 14 , 15 ). Fear of judgment along with internalized weight bias may also result in delay of care with studies demonstrating a direct correlation between an increase in body weight and subsequent delay or avoidance of healthcare ( 16 , 17 ). Thus, many women with obesity may struggle to even present for care and upon presentation they may face additional barriers such as BMI restrictions for fertility treatment ( 18 , 19 ). These obstacles create a major gap in clinical care where women are instructed to lose weight or are denied reproductive care entirely until a specific BMI is achieved, yet they are often not provided with concrete guidance and support to achieve the recommended weight loss. To fill this gap, we report the development of a multidisciplinary weight management program aimed at providing comprehensive weight loss counselling and obesity treatment that also considers reproductive and gynecologic history, reproductive age, family building goals, and obstetrical risks. The overall objectives of this study are to 1) describe the design and implementation of a multidisciplinary program for women with reproductive disorders and obesity 2) report baseline characteristics, treatment selection, and weight loss outcomes of participants and 3) understand differences in baseline characteristics and weight loss outcomes between women who were willing vs not willing to defer pregnancy attempts to focus on weight loss. Methods Program Design The Michigan Interdisciplinary Clinic for Obesity and Reproduction (MICOR) is designed specifically for women interested in current or future pregnancy who also have a reproductive disorder such as infertility, Polycystic Ovary Syndrome (PCOS), endometriosis, or abnormal uterine bleeding. The program provides weight management counseling and individualized weight loss plans as well as comprehensive counselling regarding current obstetrical and reproductive risks while also considering ideal family size, age and fertility status. MICOR patients work with a multidisciplinary team including a nutritionist, social worker, and physicians specializing in Maternal Fetal Medicine (MFM), Obesity Medicine (American Board of Obesity Medicine (ABOM) diplomate) and REI (also ABOM diplomate). Personalized weight loss plans are developed utilizing all university weight loss resources and modelled after the Weight Navigation Program ( 20 ). The Weight Navigation Program utilizes American Board of Obesity Medicine-certified primary care physicians to provide weight-focused visits and guide weight management treatments based off patient preference. Weight navigation includes a discussion of available weight management options throughout the university including individualized nutrition plans and registered dietician support, a supervised very low-calorie meal-replacement program, bariatric surgery, endoscopic bariatric therapy, and incorporation of anti-obesity medications (AOMs). MICOR expands on this model by also incorporating reproductive and obstetrical assessment and risk counseling. Specifically, weight loss plans consider family building, age, ovarian reserve, and current/future plans for fertility treatments. MFM preconception counseling includes evaluation of current medical co-morbidities and medications, risks during pregnancy, the need for additional testing and evaluation prior to pregnancy, counseling on physical activity recommendations (prior to and during pregnancy), and weight gain recommendations during pregnancy. During their encounter with REI, participants discuss planned fertility treatments and/or pregnancy attempts as well as the risk/benefits of delaying conception for more focused weight management. As most weight loss options (except for a more general pregnancy-safe nutrition plan) require avoidance of pregnancy, contraception is also discussed as appropriate for selected treatment option. Social work visits assess current mental health, provide resources and support, and consider how prior experiences with external and internalized stigma/bias may influence motivation and weight management. Following initial consultation with the entire team and selection of a weight management plan, individuals follow longitudinally with REI, social work, and nutrition (unless directly referred into a meal replacement program or bariatric surgery). Future visits assess weight loss, pharmacotherapy adjustment, and pregnancy planning. Study Design This was a retrospective cohort study of all patients who presented to the Michigan Interdisciplinary Clinic for Obesity and Reproduction between November 2021 (clinic establishment) and July 2023. Data was abstracted from the electronic medical record. Demographic and clinical data, including past medical history, weight management selection, weight loss, and pregnancy outcomes, was abstracted. Information on utilization of anti-obesity medications (AOMs) was also collected including use of any of the following FDA approved medications: Liraglutide, Semaglutide, Tirzepatide, Phentermine with or without Topiramate ER, and Naltrexone/Bupropion. Individuals were further characterized based on their willingness to delay pregnancy and/or fertility treatments to focus on weight management. The primary outcome of the study was percent body weight loss at 3 months. Secondary outcomes included weight loss at 6 months and achievement of > 5% and > 10% weight loss at each time point. Ethical approval of this study was granted by the University of Michigan Institutional Review Board (HUM00227298). Informed consent was waived as this is a retrospective review of existing data included in the standard care of patients. Data Analysis Baseline descriptive statistics were assessed via calculation of means, medians and proportions as appropriate. Comparisons between continuous variables were analyzed using a Kruskal-Wallis test as normality assumptions were not met; categorical variables were compared with chi-squared tests; ordinal categorical variables were compared with a Mantel-Haenszel chi-squared test. Bonferonni correction was performed in subgroup analyses as appropriate. Power calculations for comparison of baseline characteristics and medical history between those individuals desiring pregnancy who were not willing vs willing to defer pregnancy attempts demonstrated power values between 65–89%. For comparison of individuals who did vs did not achieve > 5% total body weight loss at 6 months, power values were between 63–98%. Linear and logistic regression were also performed to assess for predictors of overall weight loss and > 5% weight loss respectively. Results A total of 237 patients were seen in MICOR between November 2021 and July 2023 and included in the analysis. Follow-up data was available on 167 individuals at 3 months and 80 individuals at 6 months. Baseline characteristics and medical history of all individuals who participated in MICOR are shown in Table 1 . The mean age was 32.9 ± 5.5 years and mean BMI was 43.5 ± 7.3 kg/m2. Upon presentation to the clinic, 64.6% of patients had at least one metabolic co-morbidity, such as hypertension (16.9%), hyperlipidemia (31.6%), pre-diabetes (Hemoglobin A1C between 5.7–6.4%) (29.5%), or diabetes mellitus (14.8%). In terms of obstetrical and gynecologic history, 51.9% of individuals reported a prior pregnancy, while about half of those individuals (26.6%) reported a prior live birth (Table 1 ). 61.6% had a diagnosis of infertility, and 51.9% had a diagnosis of PCOS at time of presentation. The majority of participants (88.2%) desired pregnancy at time of their first MICOR visit. Differences in baseline characteristics and medical history between those not interested vs interested in pregnancy are shown in Supplemental Table 1. Those who presented to MICOR and were not interested in pregnancy had a lower starting BMI (40.6 ± 7.69 vs 43.8 ± 7.23, p = 0.030), were more likely to identify as Black or African American (50.0% vs 23.4%, p = 0.040), were more likely to have a history of fibroids (28.6% vs 9.6%, p = 0.003) and were less likely to have a history of infertility (0% vs 69.9%, p < 0.001). Table 1 Baseline characteristics and medical history of all individuals participating in MICOR All participants n = 237 Age (years) - mean ± SD, [CI] 32.9 ± 5.54, [32.2–33.6] BMI (kg/m 2 ) - mean ± SD, [CI] 43.5 ± 7.34, [42.5–44.4] Race n (%) Asian American (Chinese, Indian, Japanese, Korean, etc.) 9 (3.8%) Black or African American 63 (26.6%) Native Hawaiian or Other Pacific Islander 1 (0.4%) White/Caucasian 149 (62.9%) Other 14 (5.9%) Ethnicity n (%) Hispanic/Latino/Latina/Latinx 20 (8.4%) Non-Hispanic/Non-Latino 214 (90.3%) Medical History Diabetes Mellitus n (%) 35 (14.8%) Pre-Diabetes Mellitus n (%) 70 (29.5%) Hypertension n (%) 40 (16.9%) Hyperlipidemia n (%) 75 (31.6%) At least 1 metabolic co-morbidity n (%) 153 (64.6%) At least 2 metabolic co-morbidities n (%) 59 (24.9%) Depression n (%) 66 (27.8%) Anxiety n (%) 66 (27.8%) Obstetric and Gynecologic History Prior Pregnancy n (%) 123 (51.9%) Prior Live Birth n (%) 63 (26.6%) Currently Desires Pregnancy n (%) 209 (88.2%) History of Infertility n (%) 146 (61.6%) History of PCOS n (%) 123 (51.9%) History of Fibroids n (%) 28 (11.8%) AMH (ng/mL) - mean ± SD, [CI] 4.18 ± 3.708, [3.63–4.73] Following initial counselling with the multidisciplinary team and discussion of available weight management options, participants selected a treatment plan based on shared decision making. Figure 1 demonstrates initial treatment selection. The majority of participants (86.4%) elected to work with the MICOR dietician, while 45.6% were also started on an anti-obesity medication (AOM) in conjunction with nutritional support. Selection of a specific pharmacotherapy was based on anticipated break from pregnancy attempts, medical contraindications, and insurance coverage. 7.2% of participants elected to enroll in a supervised very low-calorie meal replacement program run through the Michigan Metabolism, Endocrinology & Diabetes division. A small percentage of individuals (3.4%) elected for a referral to bariatric surgery. To understand patient motivation and decision making, participants were next analyzed by their willingness to defer pregnancy for at least 3 months to focus on weight loss. Differences in baseline characteristic and medical history are demonstrated in Table 2 . A total of 209 participants desired pregnancy at time of presentation. 132 of those individuals (63.2%) were willing to postpone pregnancy attempts/fertility treatments to focus on weight loss. Participants willing to defer pregnancy attempts were less likely to have a diagnosis of Diabetes Mellitus (10.6% willing to defer pregnancy vs 22.1% not willing to defer pregnancy, p = 0.024) and anxiety (20.5% willing to defer pregnancy vs 36.4% not willing to defer pregnancy, p = 0.012). There were no statistically significant differences in age, BMI, race, or presence of other medical co-morbidities. In terms of obstetric and gynecologic history, Anti-Mullerian Hormone (AMH) was higher in the group willing to defer pregnancy (mean 4.80ng/mL willing to defer pregnancy vs mean 3.24ng/mL not willing to defer pregnancy, p = 0.004). There were no other differences noted between groups, including prior pregnancy history or current diagnosis of infertility or PCOS. Table 2 Differences in baseline characteristics and medical history between those individuals desiring pregnancy who are not willing vs willing to defer pregnancy attempts All participants (n = 209) No (n = 77) Yes (n = 132) p-value 1 Age (years) - mean ± SD, CI 33.0 ± 5.27 33.2 ± 5.85, [31.9–34.5] 32.9 ± 4.92, [32.0-33.7 0.793 BMI (kg/m 2 ) - mean ± SD, CI 43.8 ± 7.23 43.5 ± 7.64, [41.8–45.3] 44.0 ± 7.01, [42.8–45.2] 0.667 Race n (%) 0.162 Asian American (Chinese, Indian, Japanese, Korean, etc.) 7 (3.3%) 1 (1.3%) 6 (4.5%) Black or African American 49 (23.4%) 19 (24.7%) 30 (22.7%) Native Hawaiian or Other Pacific Islander 1 (0.5%) 1 (1.3%) 0 (0.0%) White/Caucasian 137 (65.6%) 47 (61.0%) 90 (68.2%) Other 14 (6.7%) 8 (10.4%) 6 (4.5%) Ethnicity n (%) 0.884 Hispanic/Latino/Latina/Latinx 18 (8.6%) 6 (7.8%) 12 (9.1%) Non-Hispanic/Non-Latino 189 (90.4%) 70 (90.9%) 119 (90.2%) Medical History Diabetes Mellitus n (%) 31 (14.8%) 17 (22.1%) 14 (10.6%) 0.024 Pre-Diabetes Mellitus n (%) 62 (29.7%) 18 (23.4%) 44 (33.3%) 0.128 Hypertension n (%) 37 (17.7%) 11 (14.3%) 26 (19.7%) 0.323 Hyperlipidemia n (%) 64 (30.6%) 20 (26.0%) 44 (33.3%) 0.266 At least 1 metabolic co-morbidity n (%) 134 (64.1%) 48 (62.3%) 86 (65.2%) 0.682 At least 2 metabolic co-morbidities n (%) 53 (25.4%) 17 (22.1%) 36 (27.3%) 0.405 Depression n (%) 58 (27.8%) 26 (33.8%) 32 (24.2%) 0.138 Anxiety n (%) 55 (26.3%) 28 (36.4%) 27 (20.5%) 0.012 Obstetric and Gynecologic History Prior Pregnancy n (%) 113 (54.1%) 48 (62.3%) 65 (49.2%) 0.067 Prior Live Birth n (%) 58 (27.8%) 26 (33.8%) 32 (24.2%) 0.138 History of Infertility n (%) 146 (69.9%) 52 (67.5%) 94 (71.2%) 0.576 History of PCOS n (%) 108 (51.7%) 36 (46.8%) 72 (54.5%) 0.277 History of Fibroids n (%) 20 (9.6%) 10 (13.0%) 10 (7.6%) 0.200 AMH (ng/mL) - mean ± SD, CI 4.18 ± 3.725 3.24 ± 3.056, [2.46–4.01] 4.80 ± 3.999, [3.98–5.61] 0.004 1 Continuous variables use a Kruskal-Wallis test for comparison; categorical variables use a chi-squared test for comparison; ordinal categorical variables use a Mantel-Haenszel chi-squared test for comparison Participants willing to defer pregnancy attempts achieved a significantly greater weight loss at 3 months compared to those who continued pregnancy attempts (mean − 4.8% vs -2.5%, p = 0.004) (Fig. 2 A). Individuals willing to defer pregnancy were also more likely to achieve > 10% body weight loss at 3 months (14.0% vs 2.20%, p = 0.031) (Fig. 2 B). At 6 months those willing to defer pregnancy similarly demonstrated a greater mean weight loss (-6.5% vs -2.6%, p = 0.02) and were significantly more likely to have achieved > 5% weight loss (61.4 vs 28.6%, p = 0.024) (Fig. 2 C &D). To evaluate for participant characteristics associated with successful weight loss, we next evaluated MICOR participants at 3 months and 6 months who achieved > 5% weight loss, and assessed for differences in baseline characteristics, medical, and gynecologic history (Supplemental Tables 2 &3). There were no differences found between those who did vs did not achieve > 5% weight loss at 3 months (Supplemental Table 2). At 6 months we found that those who identified as White/Caucasian were more likely to achieve > 5% loss (p = 0.028) as were those patients who had hyperlipidemia at baseline (p = 0.022). Patients with Diabetes Mellitus were less likely to achieve > 5% weight loss at 6 months (p = 0.024). Logistic and linear regression were also performed to try and identify predictors of weight loss success, with willingness to delay pregnancy identified as the only predictor of achieving > 5% body weight loss at 6 months (OR 18.44 95%CI [1.3–256.0]). To try to understand how weight loss may impact fertility/pregnancy outcomes in this population, pregnancy (within the first 6 months of attempted conception) and miscarriage rates were also evaluated. Pregnancy rates were calculated for all individuals attempting conception, regardless of type of fertility treatment. Those individuals who elected to defer pregnancy to focus on weight loss were less likely to conceive within the first 6 months (23.5% vs 37.7%, p = 0.029), however, there was no difference in miscarriage rate between the 2 groups (24.1% vs 32.3%, p = 0.485). To further assess how successful weight may impact conception, pregnancy rates were then compared between individuals who achieved > 5% weight loss vs those who did not achieve 5% weight loss (Supplemental Tables 2 &3). There were no differences seen in pregnancy rates or miscarriage rates among those who achieved > 5% vs those who did not achieve > 5% weight loss at 3 months (Supplemental Table 2). However, those participants who achieved > 5% weight loss at 6 months were more likely to achieve pregnancy within the first 6 months of trying to conceive (34.1% vs 7.7%, p = 0.004), and achieve any conception (including beyond initial 6 months of attempted conception) (56.1% vs 15.4%, p 5% weight loss (Supplemental Table 2). There was no difference in miscarriage rates (7.7% vs 14.6%, p = 0.326). Discussion Here we report the successful establishment of a multidisciplinary weight management program for women with reproductive disorders and obesity. We found that when offered personalized weight management strategies, many women (63.2%) elected to postpone pregnancy/fertility treatments for at least 3 months to focus on weight management and ultimately achieved greater weight loss than those women not deferring pregnancy attempts. Weight loss strategies were diverse and tailored per patient preference. This is important as recent data suggests that personalized diet and activity treatments may be more effective in achieving weight loss compared to standard recommendations ( 21 ). Among all patients seen in MICOR (including those not desiring pregnancy), we found that most women elected to proceed with nutritional interventions (86.4%). Nutritional plans were created by a registered dietician with macronutrient and calorie recommendations based on whether a patient was actively trying to conceive. Among those women trying to conceive, a gentle low carbohydrate plan was usually suggested (approximately 100-130gm of carbohydrates per day with a focus on weight-based protein intake) ( 22 ). For individuals who were not actively attempting pregnancy, nutritional plans included low carbohydrate (50-130gm carbohydrate per day), very low carbohydrate interventions (< 50gm of carbohydrate per day), and low-calorie interventions (generally 1200-1500kcal per day) ( 22 , 23 ). Individuals interested in very low-calorie options were directly referred into a supervised meal-replacement program managed by the department of endocrinology which incorporates meal replacements and targets 800kcal per day ( 24 ). Anti-obesity medications (AOMs) were utilized in 45.6% of individuals. It is notable that in the general US population, AOMs are severely underutilized with only 1–3% of eligible patients with obesity receiving prescriptions ( 25 , 26 ). There are several short and long-term medications currently FDA approved for weight loss. Short-term sympathomimetics (phentermine, benzphetamine, diethylpropion, and phendimetrazine) are approved for 3 months of use, with phentermine being the most widely prescribed ( 27 ). AOMs approved for long-term use include the oral medications Orlistat (Xenical and Alli), Phentermine/Topiramate extended release (Qsymia), and Naltrexone/Bupropion extended release (Contrave). Injectable Glucagon-like peptide agonist (GLP-1) receptor agonists (RA) include Liraglutide (Saxenda) and Semaglutide (Wegovy) and the combination GLP-1/GIP agonist Tirzepatide (Zepbound). It should be noted that all anti-obesity medications are contraindicated in women attempting pregnancy. Thus, in our population, AOMs were only utilized among women electing to defer pregnancy attempts and utilize contraception. The recommendations for cessation of AOMs prior to pregnancy attempts varies based on the half-life of the medication. In the setting of longer-acting GLP1 RAs, the recommended wash-out period may require several months. For example, the manufacturer for Semaglutide advises waiting at least 2 months after stopping the medication to attempt pregnancy and it is suggested to wait at least 1 month following Tirzepatide ( 28 ). Given that Semaglutide and Tirzepatide are titrated once monthly (maximum dose achieved after 5–6 months) and there is a 1-2-month waiting period following cessation of the medication prior to pregnancy attempts, these medications were generally only utilized in individuals willing to defer pregnancy for at least 6–12 months. MICOR uniquely offers medication counseling, management, and monitoring for women in the program on AOMs with goals of future fertility and childbearing. As mentioned above, after taking the time to discuss the complex interaction between fertility, obesity and pregnancy outcomes, many women elected to defer pregnancy/fertility treatments to focus on weight loss. When we assessed for differences between those women who were willing vs not willing to focus on weight loss, we found women willing to defer pregnancy attempts were less likely to have a diagnosis of diabetes or anxiety. They also had a higher AMH. It is logical that baseline ovarian reserve status would factor into the decision to postpone pregnancy attempts. Surprisingly, there was no difference in other medical or gynecologic factors such as presence of other metabolic conditions such as hypertension, hyperlipidemia, prior pregnancy, history of infertility, or other gynecologic diagnoses such as PCOS. While the authors originally hypothesized that metabolic co-morbidities may provide an impetus for focused weight loss prior to pregnancy, women who did not defer pregnancy attempts still elected to engage in tailored nutrition and physical activity plans aimed at gentle weight loss and weight maintenance. Indeed, the average weight loss at 3 months among those women who did not desire to postpone pregnancy attempts was − 2.5% and almost one third of women (28.2%) still achieved a > 5% weight loss. The MICOR program was designed to provide personalized weight management plans for the treatment of obesity and incorporate family building goals, treatment of reproductive disorders and mitigation of obstetrical risks; for some MICOR patient this meant electing to continue pregnancy attempts. Similarly, while national guidelines suggest that weight loss should be encouraged in all women with obesity prior to pregnancy ( 12 ), this may not be an appropriate strategy in certain populations especially those with advanced reproductive age. For example, a study examining cumulative live birth rates following 51, 959 cycles of IVF found that the age-related decline in fertility had a greater impact on cumulative live birth rates at older reproductive ages as opposed to BMI ( 29 ). In this case, the time it takes to achieve clinically significant weight loss may be more detrimental to chance of a future live birth than proceeding immediately with fertility treatments ( 3 ). Furthermore, the data regarding the impact of weight loss on fertility treatment success is mixed with most randomized-controlled trials failing to demonstrate improved live birth rates following pre-conception weight loss ( 3 , 4 , 30 , 31 ). While weight loss is consistently associated with improved rates of ovulation, the impact of weight loss on pregnancy and live birth rates among norm-ovulatory women with infertility is less clear ( 30 ). For example in the FIT-PLEASE study 379 women with unexplained infertility and obesity were randomized to either a 16-week pre-conception intensive intervention including meal replacements and pharmacotherapy (Orlistat) or a standard group with increased physical activity without targeted weight loss ( 31 ). While the intervention group achieved an average of 7% weight loss, there was no difference in the primary outcome of a healthy live birth. Most randomized controlled trials (RCTs) that have assessed weight loss prior to IVF similarly do not demonstrate improvements in live birth ( 32 – 35 ), although there are some small studies that have documented significant improvements ( 36 , 37 ). A recent systematic review and meta-analysis that included 16 studies (total n = 3,588 participants) found that while women randomized to a weight loss intervention prior to pregnancy attempts were more likely to become pregnant, they were not more likely to achieve a live birth ( 38 ). Thus, while pre-conception weight loss is important to promote healthier pregnancies, it is not clear that all women will experience an improved chance of a live birth. This complicated relationship between obesity, reproductive age, and infertility, is why more recent guidelines from national reproductive societies such as the American Society of Reproductive Medicine (ASRM), recommend against BMI cutoffs for reproductive treatment ( 3 ) . To try to understand pregnancy outcomes within the MICOR population we examined pregnancy and miscarriage rates within the first 6 months of attempted conception. While those individuals who initially elected to defer pregnancy to focus on weight management were less likely to become pregnant, women who ultimately achieved clinically significant weight loss (> 5%) by 6 months demonstrated higher pregnancy rates when compared to those who did not achieve > 5% weight loss. There was no difference in miscarriage rates. As discussed above, the data regarding improved fertility among normo-ovulatory women with obesity is conflicting. It is worth noting that some studies raise concerns about an increased risk of miscarriage in the setting of weight loss immediately prior to conception ( 28 ). For example in the FIT-PLEASE study discussed above a trend towards increased risk of first trimester spontaneous abortion (SAB) (33.3% versus 23.7%), although this did not meet statistical significance ( 31 ). When the authors pooled their results with other small studies, they did see a statistically significant increased risk of SAB, which they hypothesized may be related to vitamin or micronutrient deficiencies ( 31 ). In our study we specifically looked at women who achieved pre-pregnancy weight loss and we did not see a difference in risk of miscarriage among women with > 5% weight loss. However, it will be important to assess the correlation between weight loss and SAB outcomes in larger studies. Strengths of this study include description of a novel treatment model that incorporates patient family building goals, individualized risk assessment, and personalized weight navigation care plans in tandem with reproductive health. This model also allows for a real-life assessment of treatment strategies as opposed to a single weight loss intervention. Limitations include the retrospective design, overall small sample size, and absence of a control group undergoing standard weight loss therapy. Additionally, there was attrition in patient numbers as patients may not have returned for follow-up or became pregnant which did not allow for follow-up weight loss data capture. Pregnancy data must also be interpreted with caution given that many patients had infertility and pregnancy attempts included a range of fertility treatments. Finally, as multiple weight loss treatments were utilized, it was not possible to determine the effectiveness of any singular treatment modality in this population. The impact of obesity on reproduction and pregnancy outcomes is significant and complicated. While it is important for women to be aware of the reproductive risks related to obesity, providing risk counseling without a viable mitigation strategy can leave patients feeling frustrated, discouraged, stigmatized, and isolated ( 39 , 40 ). This is especially the case in a population that already struggles with a pervasive form of social bias and stigma ( 14 ). Utilizing a compassionate patient-centered and multidisciplinary approach to weight loss and fertility offers tangible and multifaceted options for achieving patients’ goals. Conclusion In conclusion, we report that when provided with personalized weight management treatment plans that consider reproductive goals, women are eager to focus on their health. Among baseline characteristics, medical comorbidities, and reproductive/fertility diagnoses, only decision to defer pregnancy was associated with achieving clinically significant weight loss. As rates of obesity continue to rise it is critical to understand how to best treat and care for this population of women trying to manage family building desires, reproductive risks and individual health. Abbreviations Body Mass Index (BMI), Reproductive Endocrinology and Infertility (REI), Michigan Interdisciplinary Clinic for Obesity and Reproduction (MICOR), Maternal Fetal Medicine (MFM), American Board of Obesity Medicine (ABOM), Anti-Obesity Medications (AOMs), Polycystic Ovary Syndrome (PCOS), Glucagon-Like Peptide (GLP-1), Receptor Agonist (RA), American Society for Reproductive Medicine (ASRM), Spontaneous Abortion (SAB) Declarations Ethics approval and consent to participate: Ethical approval of this study was granted by the University of Michigan Institutional Review Board (HUM00227298). Informed consent was waived as this is a retrospective review of existing data included in the standard care of patients. Consent for publication: Not applicable Availability of data and materials: All data generated or analyzed during this study are included in this published article [and its supplementary information files]. Competing interests: SS is guest editor for the collection “Medical and Surgical Treatment of Obesity to Improve Reproductive Health” Funding: There are no funding sources to declare Author Contribution SS designed the study, wrote the main manuscript text, and prepared all figures. DS and JS extracted all data from the medical records, assisted with analysis and edited all manuscript drafts. MM assisted with study conceptualization and edited all drafts of the manuscript. CJ performed the statistical analysis and prepared the initial drafts of the tables. MC, SP, ARJ, AO all reviewed the manuscript and provided input on design and revisions. All authors have reviewed the manuscript. References Emmerich S, Fryar C, Stierman B, Ogden C. Obesity and Severe Obesity Prevalence in Adults: United States, August 2021–August 2023 [Internet]. National Center for Health Statistics (U.S.); 2024 Sep [cited 2024 Nov 25]. Available from: https://stacks.cdc.gov/view/cdc/159281 Driscoll AK. 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Body size and ethnicity are associated with menstrual cycle alterations in women in the early menopausal transition: The Study of Women’s Health across the Nation (SWAN) Daily Hormone Study. J Clin Endocrinol Metab. 2004;89(6):2622–31. Escobar-Morreale HF, Santacruz E, Luque-Ramírez M, Botella Carretero JI. Prevalence of obesity-associated gonadal dysfunction in severely obese men and women and its resolution after bariatric surgery: a systematic review and meta-analysis. Hum Reprod Update. 2017;23(4):390–408. van der Steeg JW, Steures P, Eijkemans MJC, Habbema JDF, Hompes PGA, Burggraaff JM, et al. Obesity affects spontaneous pregnancy chances in subfertile, ovulatory women. Hum Reprod. 2008;23(2):324–8. Wise LA, Rothman KJ, Mikkelsen EM, Sørensen HT, Riis A, Hatch EE. An internet-based prospective study of body size and time-to-pregnancy. Hum Reprod. 2010;25(1):253–64. Gaskins AJ, Rich-Edwards JW, Missmer SA, Rosner B, Chavarro JE. Association of Fecundity With Changes in Adult Female Weight. Obstet Gynecol. 2015;126(4):850–8. Obesity in Pregnancy. ACOG Practice Bulletin, Number 230. Obstet Gynecol. 2021;137(6):e128–44. Lulla D, Neo JHT, Cheah REL, Soedar ZB, Puvanendran R. Decreasing appointment waiting days for first consultation for patients attending adult weight management clinic in a tertiary hospital. BMJ Open Qual. 2023;12(3):e002254. Rubino F, Puhl RM, Cummings DE, Eckel RH, Ryan DH, Mechanick JI, et al. Joint international consensus statement for ending stigma of obesity. Nat Med. 2020;26(4):485–97. Alberga AS, Pickering BJ, Alix Hayden K, Ball GDC, Edwards A, Jelinski S, et al. Weight bias reduction in health professionals: a systematic review. Clin Obes. 2016;6(3):175–88. Farrell E, Hollmann E, le Roux CW, Bustillo M, Nadglowski J, McGillicuddy D. The lived experience of patients with obesity: A systematic review and qualitative synthesis. Obes Rev. 2021;22(12):e13334. Sutin AR, Stephan Y, Terracciano A. Weight Discrimination and Risk of Mortality. Psychol Sci. 2015;26(11):1803–11. Kelley AS, Badon SE, Lanham MSM, Fisseha S, Moravek MB. Body mass index restrictions in fertility treatment: a national survey of OB/GYN subspecialists. J Assist Reprod Genet. 2019;36(6):1117–25. Boots CE, Gloff M, Lustik SJ, Vitek W. Addressing weight bias in reproductive medicine: a call to revisit body mass index restrictions for in vitro fertilization treatment. Fertil Steril. 2024;122(2):204–10. Griauzde DH, Turner CD, Othman A, Oshman L, Gabison J, Arizaca-Dileo PK, et al. A Primary Care–Based Weight Navigation Program. JAMA Netw Open. 2024;7(5):e2412192. Martinez CE, Hatley KE, Polzien K, Diamond M, Tate DF. Testing a Personalized Behavioral Weight Loss Approach Using Multifactor Prescriptions and Self-Experimentation: 12-Week mHealth Pilot Randomized Controlled Trial Results. Obes Sci Pract. 2025;11(1):e70051. Merrill JD, Soliman D, Kumar N, Lim S, Shariff AI, Yancy WS Jr. Low-Carbohydrate and Very-Low-Carbohydrate Diets in Patients With Diabetes. Diabetes Spectr. 2020;33(2):133–42. Kashyap A, Mackay A, Carter B, Fyfe CL, Johnstone AM, Myint PK. Investigating the Effectiveness of Very Low-Calorie Diets and Low-Fat Vegan Diets on Weight and Glycemic Markers in Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis. Nutrients. 2022;14(22):4870. Ard JD, Lewis KH, Rothberg A, Auriemma A, Coburn SL, Cohen SS, et al. Effectiveness of a Total Meal Replacement Program (OPTIFAST Program) on Weight Loss: Results from the OPTIWIN Study. Obesity. 2019;27(1):22–9. Gadde KM, Atkins KD. The limits and challenges of antiobesity pharmacotherapy. Expert Opin Pharmacother. 2020;21(11):1319–28. Office USGA. Obesity Drugs: Few Adults Used Prescription Drugs for Weight Loss and Insurance Coverage Varied | U.S. GAO [Internet]. [cited 2025 Jan 1]. Available from: https://www.gao.gov/products/gao-19-577 Nuako A, Tu L, Campoverde Reyes KJ, Chhabria SM, Stanford FC. Pharmacologic Treatment of Obesity in Reproductive Aged Women. Curr Obstet Gynecol Rep. 2023;12(2):138–46. Goldberg AS, Boots CE. Treating obesity and fertility in the era of glucagon-like peptide 1 receptor agonists. Fertil Steril. 2024;122(2):211–8. Goldman RH, Farland LV, Thomas AM, Zera CA, Ginsburg ES. The combined impact of maternal age and body mass index on cumulative live birth following in vitro fertilization. American Journal of Obstetrics and Gynecology. 2019;221(6):617.e1-617.e13. Vitek WS, Hoeger KM. Worth the wait? Preconception weight reduction in women and men with obesity and infertility: a narrative review. Fertil Steril. 2022;118(3):447–55. Legro RS, Hansen KR, Diamond MP, Steiner AZ, Coutifaris C, Cedars MI, et al. Effects of preconception lifestyle intervention in infertile women with obesity: The FIT-PLESE randomized controlled trial. PLoS Med. 2022;19(1):e1003883. Mutsaerts MAQ, van Oers AM, Groen H, Burggraaff JM, Kuchenbecker WKH, Perquin DAM, et al. Randomized Trial of a Lifestyle Program in Obese Infertile Women. N Engl J Med. 2016;374(20):1942–53. Moran L, Tsagareli V, Norman R, Noakes M. Diet and IVF pilot study: short-term weight loss improves pregnancy rates in overweight/obese women undertaking IVF. Aust N Z J Obstet Gynaecol. 2011;51(5):455–9. Einarsson S, Bergh C, Friberg B, Pinborg A, Klajnbard A, Karlström PO, et al. Weight reduction intervention for obese infertile women prior to IVF: a randomized controlled trial. Hum Reprod. 2017;32(8):1621–30. Wang Z, Zhao J, Ma X, Sun Y, Hao G, Yang A, et al. Effect of Orlistat on Live Birth Rate in Overweight or Obese Women Undergoing IVF-ET: A Randomized Clinical Trial. J Clin Endocrinol Metab. 2021;106(9):e3533–45. Sim KA, Dezarnaulds GM, Denyer GS, Skilton MR, Caterson ID. Weight loss improves reproductive outcomes in obese women undergoing fertility treatment: a randomized controlled trial. Clin Obes. 2014;4(2):61–8. Espinós JJ, Polo A, Sánchez-Hernández J, Bordas R, Pares P, Martínez O, et al. Weight decrease improves live birth rates in obese women undergoing IVF: a pilot study. Reprod Biomed Online. 2017;35(4):417–24. Caldwell AE, Gorczyca AM, Bradford AP, Nicklas JM, Montgomery RN, Smyth H, et al. Effectiveness of preconception weight loss interventions on fertility in women: a systematic review and meta-analysis. Fertil Steril. 2024;122(2):326–40. Ogden K, Barr J, Rossetto G, Mercer J. A messy ball of wool: a qualitative study of the dimensions of the lived experience of obesity. BMC Psychol. 2020;8(1):67. Riggan KA, Rousseau AC, DSouza KN, Woodward KT, Lue J, Phelan SM, et al. Patient perceptions of body mass index restrictions limiting fertility care for women with high body mass index. Reprod Biomed Online. 2023;47(2):103210. Additional Declarations No competing interests reported. Supplementary Files SupplementalTables.docx Cite Share Download PDF Status: Published Journal Publication published 10 Jun, 2025 Read the published version in Reproductive Biology and Endocrinology → Version 1 posted Editorial decision: Revision requested 23 Apr, 2025 Reviews received at journal 23 Apr, 2025 Reviews received at journal 21 Apr, 2025 Reviewers agreed at journal 13 Apr, 2025 Reviewers agreed at journal 11 Apr, 2025 Reviewers invited by journal 08 Apr, 2025 Submission checks completed at journal 08 Apr, 2025 First submitted to journal 02 Apr, 2025 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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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-6017583","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":440310853,"identity":"c8e450dc-7fe0-4cea-8f94-d20936b08908","order_by":0,"name":"Samantha Schon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYHACNiC2AeIEIDaAkkRoSSNdy2GoFgYitMj3H3724OOO89H87AlsUjcK7PIY2Ju3SeDTYnAjzdxw5pnbuTN7HrBJ5xgkFzPwHCvDr0WCh02at+127oYbCSAtBxIbJHLM8GqR7z8D0nIudz9ci/wb/FoYDuSAtBzI3SABt4UHvxagX8wkZ7Yl584487DZGuiXxDaetGIL/A47/EziY5tdbn978sHbOX/sEvvZD2+8gddhCMDYAKbYiFQ+CkbBKBgFowAPAACyI0ZbnNXtqQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":true,"prefix":"","firstName":"Samantha","middleName":"","lastName":"Schon","suffix":""},{"id":440310854,"identity":"a7b03235-5175-4cad-8838-315f250982be","order_by":1,"name":"Jocelyn Spizman","email":"","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Jocelyn","middleName":"","lastName":"Spizman","suffix":""},{"id":440310855,"identity":"8669721b-49b6-41ec-91f4-73620e527c06","order_by":2,"name":"Daria Stelmak","email":"","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Daria","middleName":"","lastName":"Stelmak","suffix":""},{"id":440310856,"identity":"667a289e-d2fb-49a2-bfb7-23aa70456ddb","order_by":3,"name":"Mark Chames","email":"","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Chames","suffix":""},{"id":440310857,"identity":"98d2b5c5-d842-4ce7-956f-d2bd1dd40450","order_by":4,"name":"Stacey Pilarz","email":"","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Stacey","middleName":"","lastName":"Pilarz","suffix":""},{"id":440310858,"identity":"fc83e578-826c-4016-a460-ec17144d3d6e","order_by":5,"name":"Jamila Abdur-Rahman","email":"","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Jamila","middleName":"","lastName":"Abdur-Rahman","suffix":""},{"id":440310859,"identity":"e992f455-c05f-4c48-8a43-df3f09b29909","order_by":6,"name":"Charley Jiang","email":"","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Charley","middleName":"","lastName":"Jiang","suffix":""},{"id":440310860,"identity":"56b127ac-d0d8-4281-9072-b51de8a41f46","order_by":7,"name":"Amal Othman","email":"","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Amal","middleName":"","lastName":"Othman","suffix":""},{"id":440310861,"identity":"f74abd5e-158b-4f22-9461-a9849785d976","order_by":8,"name":"Marie Menke","email":"","orcid":"","institution":"University of Michigan–Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"","lastName":"Menke","suffix":""}],"badges":[],"createdAt":"2025-02-12 19:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6017583/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6017583/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12958-025-01415-x","type":"published","date":"2025-06-10T15:58:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80579554,"identity":"48511583-2456-441b-939b-9d24e22225e7","added_by":"auto","created_at":"2025-04-14 23:08:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25439,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWeight management treatment selected at time of initial MICOR visit.\u003c/strong\u003e Bar graph demonstrating percentage of patients selecting a particular weight management treatment.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6017583/v1/05f4b33aace0e2ef53f3780b.png"},{"id":80580796,"identity":"c2d044eb-987c-4ac6-947a-38c8afbdfa68","added_by":"auto","created_at":"2025-04-14 23:16:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":97718,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferences in weight loss at 3 and 6 months between those willing vs not willing to delay pregnancy attempts. \u003c/strong\u003eA) Dot plot demonstrating mean weight loss at 3 months, lines represent 95% confidence intervals. B) Bar graph demonstrating the percentage of individuals achieving \u0026gt;5% and \u0026gt;10% weight loss at 3 months. C) Dot plot demonstrating mean weight loss at 6 months, lines represent 95% confidence intervals. D) Bar graph demonstrating the percentage of individuals achieving \u0026gt;5% and \u0026gt;10% weight loss at 6 months.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6017583/v1/80cbe5a38de015989c28759a.png"},{"id":84726740,"identity":"bbca86c6-b8e2-49f4-ad31-5122ffe6ba16","added_by":"auto","created_at":"2025-06-16 16:08:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":960420,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6017583/v1/badf073f-ced4-413c-a375-b3e29f20796a.pdf"},{"id":80580798,"identity":"8dd2592e-e402-48bd-8ac3-9c67949610de","added_by":"auto","created_at":"2025-04-14 23:16:35","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27444,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6017583/v1/f722fe7cc9441a6ce1e26bb1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA Multidisciplinary Approach to Weight Management and Reproductive Care: A Retrospective Cohort Study on Weight Loss through Personalized and Patient-Centered Care\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eObesity is a highly prevalent chronic disease, affecting over 40% of US adults (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). While men and women experience similar overall rates of obesity (defined as a BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;), the rate of severe obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;40 kg/m\u0026sup2;) is nearly double in women compared with men (12.1% vs. 6.7%) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Obesity affects nearly one-third of reproductive-aged women before pregnancy (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe impact of obesity on reproduction is both significant and complex. Clinically, women with obesity often experience menstrual irregularities, anovulation, and longer time to pregnancy (\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Infertility rates are higher in women with obesity, and fertility treatments are less successful (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). During pregnancy, obesity is also associated with an increased risk of miscarriage, hypertensive disorders of pregnancy, gestational diabetes, cesarean section, and stillbirth (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Given the impact of obesity on fertility as well as associated maternal and fetal risks, national societies recommend weight loss for women with obesity prior to pregnancy (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Despite broad recommendations for weight loss, interventions to achieve this goal are usually limited to encouragement of general behavioral modification and/or referral to comprehensive weight management programs (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), rather than treatments designed specifically for this unique and underrepresented population. Furthermore, long wait times for specialty clinics may pose challenges for women of advanced reproductive age who wish to conceive (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition to a lack of personalized interventions, women with obesity and reproductive disorders may face significant barriers to receiving comprehensive and sensitive care. Individuals with obesity face pervasive society-wide stigma which adversely affects the quality of healthcare provided (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Fear of judgment along with internalized weight bias may also result in delay of care with studies demonstrating a direct correlation between an increase in body weight and subsequent delay or avoidance of healthcare (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Thus, many women with obesity may struggle to even present for care and upon presentation they may face additional barriers such as BMI restrictions for fertility treatment (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). These obstacles create a major gap in clinical care where women are instructed to lose weight or are denied reproductive care entirely until a specific BMI is achieved, yet they are often not provided with concrete guidance and support to achieve the recommended weight loss.\u003c/p\u003e \u003cp\u003eTo fill this gap, we report the development of a multidisciplinary weight management program aimed at providing comprehensive weight loss counselling and obesity treatment that also considers reproductive and gynecologic history, reproductive age, family building goals, and obstetrical risks. The overall objectives of this study are to 1) describe the design and implementation of a multidisciplinary program for women with reproductive disorders and obesity 2) report baseline characteristics, treatment selection, and weight loss outcomes of participants and 3) understand differences in baseline characteristics and weight loss outcomes between women who were willing vs not willing to defer pregnancy attempts to focus on weight loss.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eProgram Design\u003c/h2\u003e \u003cp\u003eThe Michigan Interdisciplinary Clinic for Obesity and Reproduction (MICOR) is designed specifically for women interested in current or future pregnancy who also have a reproductive disorder such as infertility, Polycystic Ovary Syndrome (PCOS), endometriosis, or abnormal uterine bleeding. The program provides weight management counseling and individualized weight loss plans as well as comprehensive counselling regarding current obstetrical and reproductive risks while also considering ideal family size, age and fertility status. MICOR patients work with a multidisciplinary team including a nutritionist, social worker, and physicians specializing in Maternal Fetal Medicine (MFM), Obesity Medicine (American Board of Obesity Medicine (ABOM) diplomate) and REI (also ABOM diplomate). Personalized weight loss plans are developed utilizing all university weight loss resources and modelled after the Weight Navigation Program (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The Weight Navigation Program utilizes American Board of Obesity Medicine-certified primary care physicians to provide weight-focused visits and guide weight management treatments based off patient preference. Weight navigation includes a discussion of available weight management options throughout the university including individualized nutrition plans and registered dietician support, a supervised very low-calorie meal-replacement program, bariatric surgery, endoscopic bariatric therapy, and incorporation of anti-obesity medications (AOMs). MICOR expands on this model by also incorporating reproductive and obstetrical assessment and risk counseling. Specifically, weight loss plans consider family building, age, ovarian reserve, and current/future plans for fertility treatments. MFM preconception counseling includes evaluation of current medical co-morbidities and medications, risks during pregnancy, the need for additional testing and evaluation prior to pregnancy, counseling on physical activity recommendations (prior to and during pregnancy), and weight gain recommendations during pregnancy. During their encounter with REI, participants discuss planned fertility treatments and/or pregnancy attempts as well as the risk/benefits of delaying conception for more focused weight management. As most weight loss options (except for a more general pregnancy-safe nutrition plan) require avoidance of pregnancy, contraception is also discussed as appropriate for selected treatment option. Social work visits assess current mental health, provide resources and support, and consider how prior experiences with external and internalized stigma/bias may influence motivation and weight management. Following initial consultation with the entire team and selection of a weight management plan, individuals follow longitudinally with REI, social work, and nutrition (unless directly referred into a meal replacement program or bariatric surgery). Future visits assess weight loss, pharmacotherapy adjustment, and pregnancy planning.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design\u003c/h3\u003e\n\u003cp\u003eThis was a retrospective cohort study of all patients who presented to the Michigan Interdisciplinary Clinic for Obesity and Reproduction between November 2021 (clinic establishment) and July 2023. Data was abstracted from the electronic medical record. Demographic and clinical data, including past medical history, weight management selection, weight loss, and pregnancy outcomes, was abstracted. Information on utilization of anti-obesity medications (AOMs) was also collected including use of any of the following FDA approved medications: Liraglutide, Semaglutide, Tirzepatide, Phentermine with or without Topiramate ER, and Naltrexone/Bupropion. Individuals were further characterized based on their willingness to delay pregnancy and/or fertility treatments to focus on weight management. The primary outcome of the study was percent body weight loss at 3 months. Secondary outcomes included weight loss at 6 months and achievement of \u0026gt;\u0026thinsp;5% and \u0026gt;\u0026thinsp;10% weight loss at each time point.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e of this study was granted by the University of Michigan Institutional Review Board (HUM00227298). Informed consent was waived as this is a retrospective review of existing data included in the standard care of patients.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eBaseline descriptive statistics were assessed via calculation of means, medians and proportions as appropriate. Comparisons between continuous variables were analyzed using a Kruskal-Wallis test as normality assumptions were not met; categorical variables were compared with chi-squared tests; ordinal categorical variables were compared with a Mantel-Haenszel chi-squared test. Bonferonni correction was performed in subgroup analyses as appropriate. Power calculations for comparison of baseline characteristics and medical history between those individuals desiring pregnancy who were not willing vs willing to defer pregnancy attempts demonstrated power values between 65\u0026ndash;89%. For comparison of individuals who did vs did not achieve\u0026thinsp;\u0026gt;\u0026thinsp;5% total body weight loss at 6 months, power values were between 63\u0026ndash;98%. Linear and logistic regression were also performed to assess for predictors of overall weight loss and \u0026gt;\u0026thinsp;5% weight loss respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 237 patients were seen in MICOR between November 2021 and July 2023 and included in the analysis. Follow-up data was available on 167 individuals at 3 months and 80 individuals at 6 months. Baseline characteristics and medical history of all individuals who participated in MICOR are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age was 32.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5 years and mean BMI was 43.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3 kg/m2. Upon presentation to the clinic, 64.6% of patients had at least one metabolic co-morbidity, such as hypertension (16.9%), hyperlipidemia (31.6%), pre-diabetes (Hemoglobin A1C between 5.7\u0026ndash;6.4%) (29.5%), or diabetes mellitus (14.8%). In terms of obstetrical and gynecologic history, 51.9% of individuals reported a prior pregnancy, while about half of those individuals (26.6%) reported a prior live birth (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). 61.6% had a diagnosis of infertility, and 51.9% had a diagnosis of PCOS at time of presentation. The majority of participants (88.2%) desired pregnancy at time of their first MICOR visit. Differences in baseline characteristics and medical history between those not interested vs interested in pregnancy are shown in Supplemental Table\u0026nbsp;1. Those who presented to MICOR and were not interested in pregnancy had a lower starting BMI (40.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.69 vs 43.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.23, p\u0026thinsp;=\u0026thinsp;0.030), were more likely to identify as Black or African American (50.0% vs 23.4%, p\u0026thinsp;=\u0026thinsp;0.040), were more likely to have a history of fibroids (28.6% vs 9.6%, p\u0026thinsp;=\u0026thinsp;0.003) and were less likely to have a history of infertility (0% vs 69.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics and medical history of all individuals participating in MICOR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll participants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;237\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years) - mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, [CI]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.54, [32.2\u0026ndash;33.6]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e) - mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, [CI]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.34, [42.5\u0026ndash;44.4]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian American (Chinese, Indian, Japanese, Korean, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (26.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite/Caucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149 (62.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic/Latino/Latina/Latinx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (8.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic/Non-Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214 (90.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical History\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-Diabetes Mellitus n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (29.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least 1 metabolic co-morbidity n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e153 (64.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least 2 metabolic co-morbidities n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (24.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObstetric and Gynecologic History\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Pregnancy n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Live Birth n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (26.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently Desires Pregnancy n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209 (88.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Infertility n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146 (61.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of PCOS n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Fibroids n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH (ng/mL) - mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, \u003cb\u003e[CI]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.708, [3.63\u0026ndash;4.73]\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\u003eFollowing initial counselling with the multidisciplinary team and discussion of available weight management options, participants selected a treatment plan based on shared decision making. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e demonstrates initial treatment selection. The majority of participants (86.4%) elected to work with the MICOR dietician, while 45.6% were also started on an anti-obesity medication (AOM) in conjunction with nutritional support. Selection of a specific pharmacotherapy was based on anticipated break from pregnancy attempts, medical contraindications, and insurance coverage. 7.2% of participants elected to enroll in a supervised very low-calorie meal replacement program run through the Michigan Metabolism, Endocrinology \u0026amp; Diabetes division. A small percentage of individuals (3.4%) elected for a referral to bariatric surgery.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo understand patient motivation and decision making, participants were next analyzed by their willingness to defer pregnancy for at least 3 months to focus on weight loss. Differences in baseline characteristic and medical history are demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A total of 209 participants desired pregnancy at time of presentation. 132 of those individuals (63.2%) were willing to postpone pregnancy attempts/fertility treatments to focus on weight loss. Participants willing to defer pregnancy attempts were less likely to have a diagnosis of Diabetes Mellitus (10.6% willing to defer pregnancy vs 22.1% not willing to defer pregnancy, p\u0026thinsp;=\u0026thinsp;0.024) and anxiety (20.5% willing to defer pregnancy vs 36.4% not willing to defer pregnancy, p\u0026thinsp;=\u0026thinsp;0.012). There were no statistically significant differences in age, BMI, race, or presence of other medical co-morbidities. In terms of obstetric and gynecologic history, Anti-Mullerian Hormone (AMH) was higher in the group willing to defer pregnancy (mean 4.80ng/mL willing to defer pregnancy vs mean 3.24ng/mL not willing to defer pregnancy, p\u0026thinsp;=\u0026thinsp;0.004). There were no other differences noted between groups, including prior pregnancy history or current diagnosis of infertility or PCOS.\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\u003eDifferences in baseline characteristics and medical history between those individuals desiring pregnancy who are not willing vs willing to defer pregnancy attempts\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\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll participants\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;209)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;77)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years) - mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.85, [31.9\u0026ndash;34.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92, [32.0-33.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e) - mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.64, [41.8\u0026ndash;45.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.01, [42.8\u0026ndash;45.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian American (Chinese, Indian, Japanese, Korean, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (23.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (24.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite/Caucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (65.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (61.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (68.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity n (%)\u003c/b\u003e\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 \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic/Latino/Latina/Latinx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic/Non-Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189 (90.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (90.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119 (90.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical History\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (22.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (10.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-Diabetes Mellitus n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (29.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (23.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (19.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (26.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least 1 metabolic co-morbidity n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134 (64.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (62.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86 (65.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least 2 metabolic co-morbidities n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (22.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (33.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (24.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (20.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObstetric and Gynecologic History\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Pregnancy n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (54.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (62.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 (49.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Live Birth n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (33.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (24.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Infertility n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146 (69.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (67.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (71.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.576\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of PCOS n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (51.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (46.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72 (54.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Fibroids n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH (ng/mL) - mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.056, [2.46\u0026ndash;4.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.80\u0026thinsp;\u0026plusmn;\u0026thinsp;3.999, [3.98\u0026ndash;5.61]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e1\u003c/sup\u003eContinuous variables use a Kruskal-Wallis test for comparison; categorical variables use a chi-squared test for comparison; ordinal categorical variables use a Mantel-Haenszel chi-squared test for comparison\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eParticipants willing to defer pregnancy attempts achieved a significantly greater weight loss at 3 months compared to those who continued pregnancy attempts (mean \u0026minus;\u0026thinsp;4.8% vs -2.5%, p\u0026thinsp;=\u0026thinsp;0.004) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Individuals willing to defer pregnancy were also more likely to achieve\u0026thinsp;\u0026gt;\u0026thinsp;10% body weight loss at 3 months (14.0% vs 2.20%, p\u0026thinsp;=\u0026thinsp;0.031) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). At 6 months those willing to defer pregnancy similarly demonstrated a greater mean weight loss (-6.5% vs -2.6%, p\u0026thinsp;=\u0026thinsp;0.02) and were significantly more likely to have achieved\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss (61.4 vs 28.6%, p\u0026thinsp;=\u0026thinsp;0.024) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC \u0026amp;D).\u003c/p\u003e \u003cp\u003eTo evaluate for participant characteristics associated with successful weight loss, we next evaluated MICOR participants at 3 months and 6 months who achieved\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss, and assessed for differences in baseline characteristics, medical, and gynecologic history (Supplemental Tables\u0026nbsp;2 \u0026amp;3). There were no differences found between those who did vs did not achieve\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss at 3 months (Supplemental Table\u0026nbsp;2). At 6 months we found that those who identified as White/Caucasian were more likely to achieve\u0026thinsp;\u0026gt;\u0026thinsp;5% loss (p\u0026thinsp;=\u0026thinsp;0.028) as were those patients who had hyperlipidemia at baseline (p\u0026thinsp;=\u0026thinsp;0.022). Patients with Diabetes Mellitus were less likely to achieve\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss at 6 months (p\u0026thinsp;=\u0026thinsp;0.024). Logistic and linear regression were also performed to try and identify predictors of weight loss success, with willingness to delay pregnancy identified as the only predictor of achieving\u0026thinsp;\u0026gt;\u0026thinsp;5% body weight loss at 6 months (OR 18.44 95%CI [1.3\u0026ndash;256.0]).\u003c/p\u003e \u003cp\u003eTo try to understand how weight loss may impact fertility/pregnancy outcomes in this population, pregnancy (within the first 6 months of attempted conception) and miscarriage rates were also evaluated. Pregnancy rates were calculated for all individuals attempting conception, regardless of type of fertility treatment. Those individuals who elected to defer pregnancy to focus on weight loss were less likely to conceive within the first 6 months (23.5% vs 37.7%, p\u0026thinsp;=\u0026thinsp;0.029), however, there was no difference in miscarriage rate between the 2 groups (24.1% vs 32.3%, p\u0026thinsp;=\u0026thinsp;0.485). To further assess how successful weight may impact conception, pregnancy rates were then compared between individuals who achieved\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss vs those who did not achieve 5% weight loss (Supplemental Tables\u0026nbsp;2 \u0026amp;3). There were no differences seen in pregnancy rates or miscarriage rates among those who achieved\u0026thinsp;\u0026gt;\u0026thinsp;5% vs those who did not achieve\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss at 3 months (Supplemental Table\u0026nbsp;2). However, those participants who achieved\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss at 6 months were more likely to achieve pregnancy within the first 6 months of trying to conceive (34.1% vs 7.7%, p\u0026thinsp;=\u0026thinsp;0.004), and achieve any conception (including beyond initial 6 months of attempted conception) (56.1% vs 15.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) when compared to those who did not achieve\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss (Supplemental Table\u0026nbsp;2). There was no difference in miscarriage rates (7.7% vs 14.6%, p\u0026thinsp;=\u0026thinsp;0.326).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHere we report the successful establishment of a multidisciplinary weight management program for women with reproductive disorders and obesity. We found that when offered personalized weight management strategies, many women (63.2%) elected to postpone pregnancy/fertility treatments for at least 3 months to focus on weight management and ultimately achieved greater weight loss than those women not deferring pregnancy attempts.\u003c/p\u003e \u003cp\u003eWeight loss strategies were diverse and tailored per patient preference. This is important as recent data suggests that personalized diet and activity treatments may be more effective in achieving weight loss compared to standard recommendations (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Among all patients seen in MICOR (including those not desiring pregnancy), we found that most women elected to proceed with nutritional interventions (86.4%). Nutritional plans were created by a registered dietician with macronutrient and calorie recommendations based on whether a patient was actively trying to conceive. Among those women trying to conceive, a gentle low carbohydrate plan was usually suggested (approximately 100-130gm of carbohydrates per day with a focus on weight-based protein intake) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). For individuals who were not actively attempting pregnancy, nutritional plans included low carbohydrate (50-130gm carbohydrate per day), very low carbohydrate interventions (\u0026lt;\u0026thinsp;50gm of carbohydrate per day), and low-calorie interventions (generally 1200-1500kcal per day) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Individuals interested in very low-calorie options were directly referred into a supervised meal-replacement program managed by the department of endocrinology which incorporates meal replacements and targets 800kcal per day (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnti-obesity medications (AOMs) were utilized in 45.6% of individuals. It is notable that in the general US population, AOMs are severely underutilized with only 1\u0026ndash;3% of eligible patients with obesity receiving prescriptions (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). There are several short and long-term medications currently FDA approved for weight loss. Short-term sympathomimetics (phentermine, benzphetamine, diethylpropion, and phendimetrazine) are approved for 3 months of use, with phentermine being the most widely prescribed (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). AOMs approved for long-term use include the oral medications Orlistat (Xenical and Alli), Phentermine/Topiramate extended release (Qsymia), and Naltrexone/Bupropion extended release (Contrave). Injectable Glucagon-like peptide agonist (GLP-1) receptor agonists (RA) include Liraglutide (Saxenda) and Semaglutide (Wegovy) and the combination GLP-1/GIP agonist Tirzepatide (Zepbound).\u003c/p\u003e \u003cp\u003eIt should be noted that all anti-obesity medications are contraindicated in women attempting pregnancy. Thus, in our population, AOMs were only utilized among women electing to defer pregnancy attempts and utilize contraception. The recommendations for cessation of AOMs prior to pregnancy attempts varies based on the half-life of the medication. In the setting of longer-acting GLP1 RAs, the recommended wash-out period may require several months. For example, the manufacturer for Semaglutide advises waiting at least 2 months after stopping the medication to attempt pregnancy and it is suggested to wait at least 1 month following Tirzepatide (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Given that Semaglutide and Tirzepatide are titrated once monthly (maximum dose achieved after 5\u0026ndash;6 months) and there is a 1-2-month waiting period following cessation of the medication prior to pregnancy attempts, these medications were generally only utilized in individuals willing to defer pregnancy for at least 6\u0026ndash;12 months. MICOR uniquely offers medication counseling, management, and monitoring for women in the program on AOMs with goals of future fertility and childbearing.\u003c/p\u003e \u003cp\u003eAs mentioned above, after taking the time to discuss the complex interaction between fertility, obesity and pregnancy outcomes, many women elected to defer pregnancy/fertility treatments to focus on weight loss. When we assessed for differences between those women who were willing vs not willing to focus on weight loss, we found women willing to defer pregnancy attempts were less likely to have a diagnosis of diabetes or anxiety. They also had a higher AMH. It is logical that baseline ovarian reserve status would factor into the decision to postpone pregnancy attempts. Surprisingly, there was no difference in other medical or gynecologic factors such as presence of other metabolic conditions such as hypertension, hyperlipidemia, prior pregnancy, history of infertility, or other gynecologic diagnoses such as PCOS. While the authors originally hypothesized that metabolic co-morbidities may provide an impetus for focused weight loss prior to pregnancy, women who did not defer pregnancy attempts still elected to engage in tailored nutrition and physical activity plans aimed at gentle weight loss and weight maintenance. Indeed, the average weight loss at 3 months among those women who did not desire to postpone pregnancy attempts was \u0026minus;\u0026thinsp;2.5% and almost one third of women (28.2%) still achieved a\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss.\u003c/p\u003e \u003cp\u003eThe MICOR program was designed to provide personalized weight management plans for the treatment of obesity and incorporate family building goals, treatment of reproductive disorders and mitigation of obstetrical risks; for some MICOR patient this meant electing to continue pregnancy attempts. Similarly, while national guidelines suggest that weight loss should be encouraged in all women with obesity prior to pregnancy (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), this may not be an appropriate strategy in certain populations especially those with advanced reproductive age. For example, a study examining cumulative live birth rates following 51, 959 cycles of IVF found that the age-related decline in fertility had a greater impact on cumulative live birth rates at older reproductive ages as opposed to BMI (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In this case, the time it takes to achieve clinically significant weight loss may be more detrimental to chance of a future live birth than proceeding immediately with fertility treatments (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Furthermore, the data regarding the impact of weight loss on fertility treatment success is mixed with most randomized-controlled trials failing to demonstrate improved live birth rates following pre-conception weight loss (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). While weight loss is consistently associated with improved rates of ovulation, the impact of weight loss on pregnancy and live birth rates among norm-ovulatory women with infertility is less clear (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). For example in the FIT-PLEASE study 379 women with unexplained infertility and obesity were randomized to either a 16-week pre-conception intensive intervention including meal replacements and pharmacotherapy (Orlistat) or a standard group with increased physical activity without targeted weight loss (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). While the intervention group achieved an average of 7% weight loss, there was no difference in the primary outcome of a healthy live birth. Most randomized controlled trials (RCTs) that have assessed weight loss prior to IVF similarly do not demonstrate improvements in live birth (\u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), although there are some small studies that have documented significant improvements (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). A recent systematic review and meta-analysis that included 16 studies (total n\u0026thinsp;=\u0026thinsp;3,588 participants) found that while women randomized to a weight loss intervention prior to pregnancy attempts were more likely to become pregnant, they were not more likely to achieve a live birth (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Thus, while pre-conception weight loss is important to promote healthier pregnancies, it is not clear that all women will experience an improved chance of a live birth. This complicated relationship between obesity, reproductive age, and infertility, is why more recent guidelines from national reproductive societies such as the American Society of Reproductive Medicine (ASRM), recommend against BMI cutoffs for reproductive treatment (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eTo try to understand pregnancy outcomes within the MICOR population we examined pregnancy and miscarriage rates within the first 6 months of attempted conception. While those individuals who initially elected to defer pregnancy to focus on weight management were less likely to become pregnant, women who ultimately achieved clinically significant weight loss (\u0026gt;\u0026thinsp;5%) by 6 months demonstrated higher pregnancy rates when compared to those who did not achieve\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss. There was no difference in miscarriage rates. As discussed above, the data regarding improved fertility among normo-ovulatory women with obesity is conflicting. It is worth noting that some studies raise concerns about an increased risk of miscarriage in the setting of weight loss immediately prior to conception (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). For example in the FIT-PLEASE study discussed above a trend towards increased risk of first trimester spontaneous abortion (SAB) (33.3% versus 23.7%), although this did not meet statistical significance (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). When the authors pooled their results with other small studies, they did see a statistically significant increased risk of SAB, which they hypothesized may be related to vitamin or micronutrient deficiencies (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In our study we specifically looked at women who achieved pre-pregnancy weight loss and we did not see a difference in risk of miscarriage among women with \u0026gt;\u0026thinsp;5% weight loss. However, it will be important to assess the correlation between weight loss and SAB outcomes in larger studies.\u003c/p\u003e \u003cp\u003eStrengths of this study include description of a novel treatment model that incorporates patient family building goals, individualized risk assessment, and personalized weight navigation care plans in tandem with reproductive health. This model also allows for a real-life assessment of treatment strategies as opposed to a single weight loss intervention. Limitations include the retrospective design, overall small sample size, and absence of a control group undergoing standard weight loss therapy. Additionally, there was attrition in patient numbers as patients may not have returned for follow-up or became pregnant which did not allow for follow-up weight loss data capture. Pregnancy data must also be interpreted with caution given that many patients had infertility and pregnancy attempts included a range of fertility treatments. Finally, as multiple weight loss treatments were utilized, it was not possible to determine the effectiveness of any singular treatment modality in this population.\u003c/p\u003e \u003cp\u003eThe impact of obesity on reproduction and pregnancy outcomes is significant and complicated. While it is important for women to be aware of the reproductive risks related to obesity, providing risk counseling without a viable mitigation strategy can leave patients feeling frustrated, discouraged, stigmatized, and isolated (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). This is especially the case in a population that already struggles with a pervasive form of social bias and stigma (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Utilizing a compassionate patient-centered and multidisciplinary approach to weight loss and fertility offers tangible and multifaceted options for achieving patients\u0026rsquo; goals.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, we report that when provided with personalized weight management treatment plans that consider reproductive goals, women are eager to focus on their health. Among baseline characteristics, medical comorbidities, and reproductive/fertility diagnoses, only decision to defer pregnancy was associated with achieving clinically significant weight loss. As rates of obesity continue to rise it is critical to understand how to best treat and care for this population of women trying to manage family building desires, reproductive risks and individual health.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBody Mass Index (BMI), Reproductive Endocrinology and Infertility (REI), Michigan Interdisciplinary Clinic for Obesity and Reproduction (MICOR), Maternal Fetal Medicine (MFM), American Board of Obesity Medicine (ABOM), Anti-Obesity Medications (AOMs), Polycystic Ovary Syndrome (PCOS), Glucagon-Like Peptide (GLP-1), Receptor Agonist (RA), American Society for Reproductive Medicine (ASRM), Spontaneous Abortion (SAB)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: Ethical approval of this study was granted by the University of Michigan Institutional Review Board (HUM00227298). Informed consent was waived as this is a retrospective review of existing data included in the standard care of patients.\u003c/p\u003e\n\u003cp\u003eConsent for publication: Not applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: All data generated or analyzed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e\n\u003cp\u003eCompeting interests: SS is guest editor for the collection \u0026ldquo;Medical and Surgical Treatment of Obesity to Improve Reproductive Health\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding: There are no funding sources to declare\u003c/p\u003e\n\u003cp\u003eAuthor Contribution\u003c/p\u003e\u003cp\u003eSS designed the study, wrote the main manuscript text, and prepared all figures. DS and JS extracted all data from the medical records, assisted with analysis and edited all manuscript drafts. MM assisted with study conceptualization and edited all drafts of the manuscript. CJ performed the statistical analysis and prepared the initial drafts of the tables. MC, SP, ARJ, AO all reviewed the manuscript and provided input on design and revisions. All authors have reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEmmerich S, Fryar C, Stierman B, Ogden C. Obesity and Severe Obesity Prevalence in Adults: United States, August 2021\u0026ndash;August 2023 [Internet]. National Center for Health Statistics (U.S.); 2024 Sep [cited 2024 Nov 25]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://stacks.cdc.gov/view/cdc/159281\u003c/span\u003e\u003cspan address=\"https://stacks.cdc.gov/view/cdc/159281\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDriscoll AK. 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Diet and IVF pilot study: short-term weight loss improves pregnancy rates in overweight/obese women undertaking IVF. Aust N Z J Obstet Gynaecol. 2011;51(5):455\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEinarsson S, Bergh C, Friberg B, Pinborg A, Klajnbard A, Karlstr\u0026ouml;m PO, et al. Weight reduction intervention for obese infertile women prior to IVF: a randomized controlled trial. Hum Reprod. 2017;32(8):1621\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Zhao J, Ma X, Sun Y, Hao G, Yang A, et al. Effect of Orlistat on Live Birth Rate in Overweight or Obese Women Undergoing IVF-ET: A Randomized Clinical Trial. J Clin Endocrinol Metab. 2021;106(9):e3533\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSim KA, Dezarnaulds GM, Denyer GS, Skilton MR, Caterson ID. Weight loss improves reproductive outcomes in obese women undergoing fertility treatment: a randomized controlled trial. Clin Obes. 2014;4(2):61\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEspin\u0026oacute;s JJ, Polo A, S\u0026aacute;nchez-Hern\u0026aacute;ndez J, Bordas R, Pares P, Mart\u0026iacute;nez O, et al. Weight decrease improves live birth rates in obese women undergoing IVF: a pilot study. Reprod Biomed Online. 2017;35(4):417\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaldwell AE, Gorczyca AM, Bradford AP, Nicklas JM, Montgomery RN, Smyth H, et al. Effectiveness of preconception weight loss interventions on fertility in women: a systematic review and meta-analysis. Fertil Steril. 2024;122(2):326\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOgden K, Barr J, Rossetto G, Mercer J. A messy ball of wool: a qualitative study of the dimensions of the lived experience of obesity. BMC Psychol. 2020;8(1):67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiggan KA, Rousseau AC, DSouza KN, Woodward KT, Lue J, Phelan SM, et al. Patient perceptions of body mass index restrictions limiting fertility care for women with high body mass index. Reprod Biomed Online. 2023;47(2):103210.\u003c/span\u003e\u003c/li\u003e\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":"reproductive-biology-and-endocrinology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rbej","sideBox":"Learn more about [Reproductive Biology and Endocrinology](http://rbej.biomedcentral.com)","snPcode":"12958","submissionUrl":"https://submission.nature.com/new-submission/12958/3","title":"Reproductive Biology and Endocrinology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Weight loss, obesity, infertility, PCOS, anti-obesity medication, weight navigation, reproduction","lastPublishedDoi":"10.21203/rs.3.rs-6017583/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6017583/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eObesity is a highly prevalent chronic disease with a significant and complex impact on reproduction. National guidelines recommend weight loss prior to pregnancy for patients with obesity to mitigate complications and increase fertility; however, targeted, personalized interventions are limited. The objectives of this study are to describe the implementation of a multidisciplinary program designed specifically for women with reproductive disorders and obesity and to report differences in baseline characteristics and weight loss outcomes between women willing vs not willing to defer pregnancy attempts to focus on weight loss.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eRetrospective cohort study at a university multidisciplinary program for women with reproductive disorders and obesity. All participants from program initiation (November 2021) through July 2023 were included in the analysis. Primary outcome was percent body weight loss at 3 months. Secondary outcomes included weight loss at 6 months and achievement of \u0026gt;\u0026thinsp;5% and \u0026gt;\u0026thinsp;10% weight loss at each time point.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 237 participants were included in the analysis. The majority of participants (88.2%) desired pregnancy. 63.2% of participants who desired pregnancy were willing to postpone pregnancy attempts/fertility treatments so that they could focus on weight loss for at least 3 months. Participants willing to defer pregnancy attempts achieved a significantly greater weight loss at 3 months compared to those who continued pregnancy attempts (mean \u0026minus;\u0026thinsp;4.8% vs -2.5%, p\u0026thinsp;=\u0026thinsp;0.004) and were more likely to achieve\u0026thinsp;\u0026gt;\u0026thinsp;10% body weight loss at 3 months (14.0% vs 2.20%, p\u0026thinsp;=\u0026thinsp;0.031). Those who achieved\u0026thinsp;\u0026gt;\u0026thinsp;5% weight loss by 6 months were more likely to achieve pregnancy within the first 6 months of trying to conceive (34.1% vs 7.7%, p\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe describe the development and implementation of a multidisciplinary program for women with reproductive disorders and obesity seeking weight management. An individualized approach to weight management and reproductive care results in clinically significant weight loss especially among women willing to defer pregnancy attempts and focus on weight loss for at least 3 months.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTrial Registration:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e","manuscriptTitle":"A Multidisciplinary Approach to Weight Management and Reproductive Care: A Retrospective Cohort Study on Weight Loss through Personalized and Patient-Centered Care","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-14 23:08:30","doi":"10.21203/rs.3.rs-6017583/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-23T14:21:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-23T13:18:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-21T23:09:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26409281563029948996516883595237471037","date":"2025-04-13T05:58:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100736666498173616364523025433491244881","date":"2025-04-11T18:22:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-08T23:03:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-08T08:30:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Reproductive Biology and Endocrinology","date":"2025-04-02T13:52:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-biology-and-endocrinology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rbej","sideBox":"Learn more about [Reproductive Biology and Endocrinology](http://rbej.biomedcentral.com)","snPcode":"12958","submissionUrl":"https://submission.nature.com/new-submission/12958/3","title":"Reproductive Biology and Endocrinology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"87f4ab10-3bc4-4b0d-960a-f48fd26560f7","owner":[],"postedDate":"April 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-16T16:04:52+00:00","versionOfRecord":{"articleIdentity":"rs-6017583","link":"https://doi.org/10.1186/s12958-025-01415-x","journal":{"identity":"reproductive-biology-and-endocrinology","isVorOnly":false,"title":"Reproductive Biology and Endocrinology"},"publishedOn":"2025-06-10 15:58:02","publishedOnDateReadable":"June 10th, 2025"},"versionCreatedAt":"2025-04-14 23:08:30","video":"","vorDoi":"10.1186/s12958-025-01415-x","vorDoiUrl":"https://doi.org/10.1186/s12958-025-01415-x","workflowStages":[]},"version":"v1","identity":"rs-6017583","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6017583","identity":"rs-6017583","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}