Post-Pandemic Physical Activity, Sedentary Behavior, and Body Composition Among Mexican Breast Cancer Survivors: Implications for Survivorship Health

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Crespo, Graciela Caire-Juvera This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8099176/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Purpose: Physical activity (PA) and sedentary behavior (SB) are modifiable factors associated with improved body composition (BC) and lower morbidity risk in breast cancer survivors. The COVID-19 pandemic disrupted activity patterns worldwide, but data on post-pandemic habits among Latin American survivors remain scarce. This study examined PA and SB levels and explored whether their relationship with BC varies based on cancer history status. Methods: In this cross-sectional study, 120 Mexican women (60 breast cancer survivors and 60 women without cancer history) reported PA and SB using validated questionnaires. BC indicators were assessed using dual-energy X-ray absorptiometry. Correlation analysis and multivariable linear regression were performed, adjusting for pertinent confounders. Results: The mean age was 52.5 ± 9.3 years. Overall, 57% were physically inactive, and the average sitting time was 4.8 ± 2.8 hours per day. PA levels were negatively correlated with total body fat percentage (TBFP) (rho = − 0.26), fat mass index (rho = − 0.20), waist circumference (rho = − 0.20), and android fat mass (rho = − 0.20) (all p < 0.05). SB was not associated with BC. After adjustment, PA level remained independently inversely associated with TBFP (p < 0.05), and cancer history status did not modify this relationship. Conclusions: Physical inactivity persists post-pandemic among Mexican women, including breast cancer survivors. PA is associated with healthier BC, independent of cancer history status. Implications for Cancer Survivors: Increasing PA through structured, culturally tailored support integrated into survivorship care may improve body composition and mitigate long-term health risks among post-pandemic breast cancer survivors. Adiposity lifestyle behavior Breast cancer survivor health After COVID-19 pandemic Introduction Breast cancer remains one of the most common cancers among women worldwide and is a significant cause of morbidity and death [ 1 ]. Advances in early detection and treatment have greatly improved survival rates, leading to a growing number of breast cancer survivors [ 2 ]. However, survivorship often comes with long-term health issues, including metabolic changes, which can negatively affect prognosis, quality of life, sleep, and overall survival [ 3 , 4 ]. These metabolic changes often result from the combined effects of cancer treatments, along with lifestyle factors, which can lead to diverse health problems [ 5 – 7 ]. These changes not only hinder recovery but may also increase the risk of cancer recurrence and death. Therefore, adopting healthy lifestyle habits, especially those that enhance body composition, has become a vital part of survivorship care. Physical activity (PA) is widely recognized for its role in reducing adiposity, preserving lean mass, and improving metabolic health in breast cancer survivors [ 8 ]. In contrast, sedentary behavior (SB) is independently associated with obesity, metabolic syndrome, and poorer cancer outcomes [ 9 ]. Therefore, survivorship guidelines highlight increasing PA and decreasing SB as essential parts of post-treatment care [ 10 ]. In Mexico, adherence to PA guidelines remains low, especially among women and cancer survivors, due to various structural, cultural, and socioeconomic barriers [ 11 , 12 ]. More studies have shown that the COVID-19 pandemic further worsened these issues by reducing PA levels and increasing SB, especially in vulnerable populations [ 13 , 14 ]. These behavioral changes may have adverse effects on body composition and increase long-term health risks. This is especially important for breast cancer survivors (BCS), a group more vulnerable due to metabolic and inflammatory alterations, as well as greater challenges in adopting and maintaining healthy behaviors [ 15 , 16 ]. Given Mexico’s high rate of overweight and obesity, affecting over 70% of adult women, coupled with the negative impact of the COVID-19 pandemic on lifestyle and the importance of breast cancer, it is essential to examine lifestyle patterns in the post-pandemic period starting in May 2023. This study aims to assess PA levels and SB after the COVID-19 pandemic and their relationship with body composition in Mexican women BCS and WCH. Methods Study Design and Participant Selection This cross-sectional study involved BCS and WCH. A convenience sample of Mexican women residing in Hermosillo, Sonora, was recruited between June and December 2024. Participants included women aged 25 years and older, either without a diagnosis of cancer or with a history of breast cancer treated 6 months to 5 years prior. This study was conducted in accordance with the ethical standards established by the institutional research committee and the principles of the 2013 Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of the Centro de Investigación en Alimentación y Desarrollo (CIAD), under approval number CEI/015 − 2/2022. All participants provided written and signed informed consent before their participation. Measures Sociodemographic and Clinical Characteristics Participants were administered a sociodemographic questionnaire that inquired about age, educational background, marital and menopausal status, occupation, and socioeconomic status. This questionnaire was developed and validated by the Asociación Mexicana de Agencias de Investigación de Mercado y Opinión Pública [ 17 ]. Sleep Quality Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), a 19-item questionnaire that measures sleep quality over the past month. It includes seven components, each scored 0–3, with higher scores indicating greater sleep disturbances. The total score ranges from 0 to 21, with scores above 5 indicating poor sleep quality. The PSQI has a sensitivity of 89.6%, specificity of 86.5%, a kappa of 0.75, and p < 0.01[ 18 ]. Food Energy Intake A structured food frequency questionnaire with 113 items was used to estimate dietary energy intake in both groups. Validated among low-income women in Hermosillo, Sonora, it was later adapted for breast cancer survivors and women without cancer in subsequent studies [ 19 – 21 ] Physical Activity Level and Sedentary Behavior PA level and SB were assessed over a week using the Godin Leisure Time Exercise Questionnaire, which had high internal consistency (Cronbach’s alpha 0.845–0.950) [ 22 , 23 ]. Participants recorded their daily sedentary activities, such as office work and TV viewing, as well as the durations of light, moderate, and vigorous physical activity. Anthropometric Measurements and Body Composition Weight and height were measured in accordance with the guidelines of Jelliffe (1966) [ 24 ]. Waist circumference conformed to ISAK guidelines [ 25 ]. Body composition was evaluated using DXA with a Hologic scanner, adhering to established procedures to ensure precision [ 26 ]. Measurements encompassed total body fat, lean mass, and regional fat. Scans were conducted by trained technicians, with daily calibration performed as recommended. Statistical Analysis Descriptive statistics characterized the study sample and subgroups, specifically BCS and WCH. Means and standard deviations were used to summarize continuous variables, while frequencies and percentages were used to describe categorical variables. Comparisons between BCS and WCH were conducted using t-tests and chi-square tests. Bivariate and multivariable linear regression analyses were employed to investigate the relationships between dependent and independent variables. Ten models included physical activity (PA) level as the independent variable, with body composition metrics as dependent variables. Another ten models analyzed sitting time similarly. Covariates included socioeconomic status, civil and menopausal status, sleep duration, energy intake, sitting time (excluding instances where it was used as a predictor), and cancer history. An interaction term tested whether cancer history affected the relationship between PA and body composition. Model assumptions were checked, and standardized beta coefficients (β) were reported. Statistical significance was set at P < 0.05. Data analysis was performed using IBM SPSS version 30. Results Overall Sample Characteristics and Groups Comparison Table 1 shows the characteristics of 120 Mexican women, evenly distributed between the BCS and WCH groups. The average age was 52.5 years (SD = 9.3), with no significant difference in age. Notable differences were observed in sleep quality, daily energy intake, and waist circumference (p < 0.05), all of which were lower in the BCS group. No significant differences were observed in other body composition measures. Most participants (57.5%) were inactive, while only 25.8% were active, with no significant differences between the groups. The entire sample spent approximately 4.8 ± 2.8 hours daily sitting, with no significant differences in sitting time between groups. Table 1 Descriptive Characteristics of Participants Characteristic Total Sample (n = 120) BCS (n = 60) WCH (n = 60) p-value Age (years), mean ± SD 52.5 ± 9.3 52.9 ± 9.4 52.13 ± 9.2 0.65 Sleep Quality Score, mean ± SD 8.14 ± 4.1 8.9 ± 4.2 7.4 ± 3.9 0.04 Daily energy intake (kcal), mean ± SD 1922.3 ± 915.9 1683.3 ± 762.6 2161.2 ± 997.1 0.01 Sitting time (hours/day) 4.8 ± 2.8 5 ± 2.8 4.5 ± 2.8 0.33 Total body fat (%) 44.04 ± 4.3 43.8 ± 4.4 44.3 ± 4.3 0.49 Fat mass index (kg/m²) 13.23 ± 3.5 12.78 ± 3.4 13. 7 ± 3.6 0.11 Waist circumference (cm) 97.8 ± 11.9 95.3 ± 11.4 100.5 ± 11.9 0.02 Android fat mass (kg) 3.1 ± 0.9 3 ± 0.9 3.2 ± 0.9 0.12 Gynoid fat mass (kg) 5.8 ± 1.5 5.7 ± 1.6 5.8 ± 1.4 0.63 Android-to-gynoid fat ratio 0.5 ± 0.1 0.53 ± 0.12 0.55 ± 0.11 0.30 Total fat mass (kg) 33.1 ± 8.2 32.4 ± 8.4 33.9 ± 8.1 0.21 Total Fat-free mass (kg) 40.05 ± 12 41.3 ± 6.3 38.8 ± 15.7 0.98 Fat-free mass index (kg/m²) 16.03 ± 4.6 16.37 ± 2.3 15.68 ± 6.1 0.53 Body Mass Index (kg/m²) 30.4 ± 5.8 29.6 ± 5.5 31.25 ± 6.1 0.11 Menopausal status, n (%) -Pre 33 (27.5) 9 (15) 24 (40) 0.01 -Post 87 (72.5) 51 (85) 36 (60) Marital status n (%) -Single 45 (37.5) 27 (45) 18 (30) 0.9 -Live with partner 75 (62.5) 33 (55) 42 (70) Economic status n(%) -Low 48 (40) 21 (36.8) 27 (46.6) 0.44 -Medium 42 (35) 24 (42.1) 18 (31) -High 25 (20.8) 12 (21.1) 13 (22.4) Missing value 5 (4.2) Physical activity level n (%) -Inactive 69 (57.5) 34 (56.7) 35 (58.3) 0.88 -Moderate active 20 (16.7) 11 (18.3) 9 (15) -Active 31 (25.8) 15 (25) 16 (26.7) BCS : Breast Cancer survivors; WCH : Women without cancer history Associations Between Physical Activity, Sitting Time, and Body Composition Table 2 shows the Spearman correlations between physical activity, sitting time, and body composition. PA level was inversely associated with total body fat, fat mass index, waist, and android fat (p < 0.05). No statistically significant association was found between PA level and gynoid fat, android-to-gynoid ratio, fat-free mass, or BMI. Sitting time also showed no significant correlations with any body composition parameters. Table 2 Correlations Between Physical Activity, Sitting Time, and Body Composition Outcomes (n = 120) Outcome Physical Activity level (rho, p value) Sitting Time per day (rho, p value) Total body fat Percentage -0.26 ; p = 0.01 -0.10 ; p = 0.26 Fat mass index (kg/m²) -0.20 ; p = 0.03 -0.12 ; p = 0.19 Waist circumference (cm) -0.20 ; p = 0.02 -0.09 ; p = 0.33 Android fat mass (kg) -0.20 ; p = 0.02 -0.01 ; p = 0.94 Gynoid fat mass (kg) -0.05 ; p = 0.61 -0.05 ; p = 0.57 Android-to-gynoid fat ratio -0.13 ; p = 0.15 0.02 ; p = 0.84 Total fat mass (kg) -0.13 ; p = 0.15 -0.07 ; p = 0.41 Total Fat-free mass (kg) 0.03 ; p = 0.73 0.00 ; p = 0.99 Fat-free mass index (kg/m²) -0.07 ; p = 0.43 -0.06 ; p = 0.49 Body Mass Index (kg/m²) -0.16 ; p = 0.81 -0.09 ; p = 0.31 Multivariable Regression Analyses Table 3 presents the results of multivariable regression analysis, indicating that PA levels are significantly associated with total body fat (p < 0.05) after adjusting for covariates. A history of cancer did not modify these associations. No other outcomes demonstrated significant associations with PA following adjustment. Additionally, sitting time was not significantly correlated with any of the body composition parameters. Table 3 Multivariable Linear Regression Models Predicting Body Composition Outcomes Outcome Physical Activity level (β ; p value) 1 Sitting Time per day (β, p value) 2 Total body fat Percentage -0.19; p = 0.04 -0.02; p = 0.81 Fat mass index (kg/m²) -0.14; p = 0.15 -0.09; p = 0.31 Waist circumference (cm) -0.13; p = 0.12 -0.06; p = 0.51 Android fat mass (kg) -0.15; p = 0.11 0.01; p = 0.97 Gynoid fat mass (kg) -0.04; p = 0.66 -0.07; p = 0.49 Android-to-gynoid fat ratio -0.14; p = 0.13 0.05; p = 0.59 Total fat mass (kg) -0.11; p = 0.25 -0.08; p = 0.38 Total Fat-free mass (kg) -0.01; p = 0.91 -0.05; p = 0.61 Fat-free mass index (kg/m²) -0.06; p = 0.57 -0.07; p = 0.49 Body Mass Index (kg/m²) -0.12; p = 0.20 -0.08; p = 0.39 1 Model adjusted for economic status, civil status, menopausal status, sleep quality, energy intake, sitting time, and cancer history 2 Model adjusted for economic status, civil status, menopausal status, sleep quality, energy intake, physical activity level, and cancer history Discussion This study examined post-COVID-19 physical activity, sedentary behavior, and their relationship with body composition among Mexican women breast cancer survivors and women without a cancer history. Results showed that 57. 5% of the participants were inactive and spent over four hours daily engaged in sedentary activities, aligning with 2023 national data indicating that 60.2% of the adult Mexican population was inactive, with a higher prevalence among women (66%) than men (53.3%), representing a 5.6% increase in inactivity over the past decade [ 27 ]. The COVID-19 pandemic further worsened these trends globally, leading to widespread decreases in PA and increased SB [ 13 ]. Our findings indicate that during-pandemic behaviors marked by low PA and prolonged sitting persist after the pandemic and are significantly increasing among Mexican population women. Such patterns are concerning, given their well-known association with adverse health outcomes [ 28 , 29 ]. No statistically significant differences were observed in PA level and SB between the groups, contrary to some studies suggesting that cancer survivors adopt healthier habits following diagnosis [ 30 ]. Other studies indicate that factors such as fatigue, treatment side effects, and psychosocial challenges may explain the reduced PA levels [ 31 , 32 ]. Bivariate analyses demonstrated associations between PA level and variables including total body fat percentage, waist circumference, and fat mass, supporting the hypothesis that moderate to vigorous PA reduces adiposity [ 33 ]. After adjusting for confounding factors, most associations lost statistical significance, except for total body fat percentage, suggesting that some health benefits of physical activity on body composition may be partly influenced or confounded by other lifestyle and demographic factors [ 34 ]. Daily sitting time was not significantly associated with any body composition parameters, while some previous research associated sedentary behavior with central obesity [ 35 ]. Other research suggests that this relationship may be multifaceted and influenced by contextual factors [ 36 ]. Self-reported sitting duration may limit the accuracy of the measurement. Women with breast cancer exhibited lower waist circumference and energy intake, potentially reflecting intentional lifestyle changes made after diagnosis, recommended by survivorship guidelines [ 37 ]. No significant interaction was observed between cancer history and the effects of physical activity on body composition, suggesting that the benefits of physical activity are similar regardless of cancer status. The high prevalence of sedentary behavior and low activity levels observed in both groups after the pandemic underscores the need for targeted interventions and highlights the importance of community strategies in promoting physical activity among women as a public health priority. Strengths and Limitations This study has several strengths, including its focus on an underexplored group of Mexican women, covering both BCS and WCH, while considering relevant covariates. It utilizes Dual-Energy X-ray Absorptiometry (DXA), recognized as the gold standard for accurate body composition assessment, thereby enhancing the validity of the results. However, some limitations should also be acknowledged. The cross-sectional design restricts the ability to determine causality, and reliance on self-reported data for PA and SB may introduce recall and social desirability biases. To minimize these biases, we employed validated questionnaires, trained data collectors, emphasized confidentiality to encourage honest responses, and adhered to standardized data collection procedures. These efforts helped minimize misreporting and improve data reliability. Additionally, some confounding factors from unmeasured variables, such as psychological stress or environmental barriers, may still be present. Conclusions Mexican women, including breast cancer survivors, continue to exhibit low physical activity levels and considerable sedentary time in the post-pandemic period. A higher physical activity level was associated with healthier body composition, specifically a lower total body fat percentage, while sedentary behavior showed no significant relationship with adiposity. These findings underscore the urgent need to incorporate culturally relevant and feasible physical activity strategies into survivorship care plans. Promoting and supporting increased physical activity may contribute to improved long-term health outcomes and reduce chronic disease risk among breast cancer survivors. Declarations Author Contribution PMN, NCC, and GCJ contributed to the conception and design of the study. PMN handled material preparation and data collection, while PMN and NCC performed data analysis. PMN drafted the initial version of the manuscript, NCC and GCJ provided feedback on previous versions, and all the authors read and approved the final manuscript. Acknowledgement We thank all the women who participated in this study for generously sharing their time and experiences. We also thank the clinical and administrative staff at the CEO and ISSSTE for their support in participant recruitment, as well as María del Socorro Saucedo, Kathia Susset Enrique Mada, María José Mendívil Armenta, Brenda Rosario Valle Valdez, and María Fernanda Armenta Corral for their assistance with data collection. Finally, we are grateful to Centro de Investigación en Alimentación y Desarrollo (CIAD) for making this research possible. Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. References Sung, H., Ferlay, J., Siegel, R. L., et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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The Journal of Nutrition Health & Aging . 2019; 24 (1), 63–70. https://doi.org/10.1007/s12603-019-1298-3 Ekelund, U., Tarp, J., Steene-Johannessen, J., Hansen, B. H., Jefferis, B., Fagerland, M. W., Whincup, P., Diaz, K. M., Hooker, S. P., Chernofsky, A., Larson, M. G., Spartano, N., Vasan, R. S., Dohrn, I., Hagströmer, M., Edwardson, C., Yates, T., Shiroma, E., Anderssen, S. A., & Lee, I. Dose-response associations between accelerometry measured physical activity and sedentary time and all-cause mortality: systematic review and harmonised meta-analysis. BMJ . 2019; l4570. https://doi.org/10.1136/bmj.l4570 Rock, C. L., Thomson, C. A., Sullivan, K. R., Howe, C. L., Kushi, L. H., Caan, B. J., Neuhouser, M. L., Bandera, E. V., Wang, Y., Robien, K., Basen-Engquist, K. M., Brown, J. C., Courneya, K. S., Crane, T. E., Garcia, D. O., Grant, B. L., Hamilton, K. K., Hartman, S. J., Kenfield, S. A.,.. . McCullough, M. L. American Cancer Society nutrition and physical activity guidelines for cancer survivors. CA: A Cancer Journal for Clinicians . 2022; 72 (3), 230–262. https://doi.org/10.3322/caac.21719 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 05 May, 2026 Reviewers invited by journal 09 Dec, 2025 Editor assigned by journal 09 Dec, 2025 Submission checks completed at journal 19 Nov, 2025 First submitted to journal 12 Nov, 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. We do this by developing innovative software and high quality services for the global research community. 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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-8099176","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":558187228,"identity":"f7e3b5f6-8e6b-4adc-8ab7-319624ec6b4c","order_by":0,"name":"Paul Marcel Nindenshuti","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYFACHiA2ALMYD3wAkmzsxGg5ANHCcHAGSAszUVqgzMMgGxkIaTHnP3tM+kPBNnnz9sMHDtv82ibPx8zA+OFjDm4tljPy0iQOGNw2nHMmLeFwbt9twzZmBmbJmdtwazG4wWMG0sI4Q4LH4HBuz21GoBY2Zl58Ws6fAWuxnyHB/+GwZc9te8JaDuSAtSQCbWE4zPDjdiJhLTdyjC3OGNxOnsGTZnCwt+F2chszYzN+v5w/Y3ij4s9t2xnshx8++AFkzG9vPvjhIx4tqICxDUw2EKseBP6QongUjIJRMApGCgAAKM5USV2TulwAAAAASUVORK5CYII=","orcid":"","institution":"Centro de Investigación en Alimentación y Desarrollo","correspondingAuthor":true,"prefix":"","firstName":"Paul","middleName":"Marcel","lastName":"Nindenshuti","suffix":""},{"id":558187231,"identity":"24821a98-e63e-428f-8553-44ba8ec13345","order_by":1,"name":"Noe C. Crespo","email":"","orcid":"","institution":"San Diego State University","correspondingAuthor":false,"prefix":"","firstName":"Noe","middleName":"C.","lastName":"Crespo","suffix":""},{"id":558187233,"identity":"faace049-ef6a-42d9-8747-d248ec02790c","order_by":2,"name":"Graciela Caire-Juvera","email":"","orcid":"","institution":"Centro de Investigación en Alimentación y Desarrollo","correspondingAuthor":false,"prefix":"","firstName":"Graciela","middleName":"","lastName":"Caire-Juvera","suffix":""}],"badges":[],"createdAt":"2025-11-12 18:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8099176/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8099176/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98209366,"identity":"1a44a869-5b45-476b-94e0-36b27115ab5d","added_by":"auto","created_at":"2025-12-15 09:17:08","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":53498,"visible":true,"origin":"","legend":"","description":"","filename":"MainManuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-8099176/v1/c1f1635801443052b97e75f3.docx"},{"id":98433122,"identity":"a4747736-9e7d-413e-b583-09086fa2e356","added_by":"auto","created_at":"2025-12-17 16:50:18","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6058,"visible":true,"origin":"","legend":"","description":"","filename":"ee61c2d7fcf54a9388e7e6809100f9b9.json","url":"https://assets-eu.researchsquare.com/files/rs-8099176/v1/5a9048172f74cbc1a790256f.json"},{"id":98209370,"identity":"02960077-3067-44c4-bb3a-257f01cdda14","added_by":"auto","created_at":"2025-12-15 09:17:08","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":111981,"visible":true,"origin":"","legend":"","description":"","filename":"ee61c2d7fcf54a9388e7e6809100f9b91enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8099176/v1/eb2b62a2848496318f1f05c2.xml"},{"id":98209367,"identity":"6c06480a-9ff4-4f57-bf53-b3fd0c93a656","added_by":"auto","created_at":"2025-12-15 09:17:08","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":110856,"visible":true,"origin":"","legend":"","description":"","filename":"ee61c2d7fcf54a9388e7e6809100f9b91structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8099176/v1/cb0bfbbbcaf49f4532ab6887.xml"},{"id":98209369,"identity":"402fc16b-f112-4d47-9be5-a0151cfa5e23","added_by":"auto","created_at":"2025-12-15 09:17:08","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":121040,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8099176/v1/b8be2f8dd54dd0205fca48b5.html"},{"id":98445008,"identity":"76189067-1a91-4e8c-b0cd-539fc21348e6","added_by":"auto","created_at":"2025-12-17 17:18:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":928881,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8099176/v1/5f956e76-3904-4af8-b9f4-cdb7578214b0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Post-Pandemic Physical Activity, Sedentary Behavior, and Body Composition Among Mexican Breast Cancer Survivors: Implications for Survivorship Health","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer remains one of the most common cancers among women worldwide and is a significant cause of morbidity and death [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Advances in early detection and treatment have greatly improved survival rates, leading to a growing number of breast cancer survivors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, survivorship often comes with long-term health issues, including metabolic changes, which can negatively affect prognosis, quality of life, sleep, and overall survival [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese metabolic changes often result from the combined effects of cancer treatments, along with lifestyle factors, which can lead to diverse health problems [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These changes not only hinder recovery but may also increase the risk of cancer recurrence and death. Therefore, adopting healthy lifestyle habits, especially those that enhance body composition, has become a vital part of survivorship care.\u003c/p\u003e\u003cp\u003ePhysical activity (PA) is widely recognized for its role in reducing adiposity, preserving lean mass, and improving metabolic health in breast cancer survivors [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In contrast, sedentary behavior (SB) is independently associated with obesity, metabolic syndrome, and poorer cancer outcomes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, survivorship guidelines highlight increasing PA and decreasing SB as essential parts of post-treatment care [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn Mexico, adherence to PA guidelines remains low, especially among women and cancer survivors, due to various structural, cultural, and socioeconomic barriers [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. More studies have shown that the COVID-19 pandemic further worsened these issues by reducing PA levels and increasing SB, especially in vulnerable populations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These behavioral changes may have adverse effects on body composition and increase long-term health risks. This is especially important for breast cancer survivors (BCS), a group more vulnerable due to metabolic and inflammatory alterations, as well as greater challenges in adopting and maintaining healthy behaviors [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven Mexico\u0026rsquo;s high rate of overweight and obesity, affecting over 70% of adult women, coupled with the negative impact of the COVID-19 pandemic on lifestyle and the importance of breast cancer, it is essential to examine lifestyle patterns in the post-pandemic period starting in May 2023. This study aims to assess PA levels and SB after the COVID-19 pandemic and their relationship with body composition in Mexican women BCS and WCH.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Participant Selection\u003c/h2\u003e\u003cp\u003eThis cross-sectional study involved BCS and WCH. A convenience sample of Mexican women residing in Hermosillo, Sonora, was recruited between June and December 2024. Participants included women aged 25 years and older, either without a diagnosis of cancer or with a history of breast cancer treated 6 months to 5 years prior. This study was conducted in accordance with the ethical standards established by the institutional research committee and the principles of the 2013 Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of the Centro de Investigaci\u0026oacute;n en Alimentaci\u0026oacute;n y Desarrollo (CIAD), under approval number CEI/015\u0026thinsp;\u0026minus;\u0026thinsp;2/2022. All participants provided written and signed informed consent before their participation.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eSociodemographic and Clinical Characteristics\u003c/h2\u003e\u003cp\u003eParticipants were administered a sociodemographic questionnaire that inquired about age, educational background, marital and menopausal status, occupation, and socioeconomic status. This questionnaire was developed and validated by the Asociaci\u0026oacute;n Mexicana de Agencias de Investigaci\u0026oacute;n de Mercado y Opini\u0026oacute;n P\u0026uacute;blica [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSleep Quality\u003c/h3\u003e\n\u003cp\u003eSleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), a 19-item questionnaire that measures sleep quality over the past month. It includes seven components, each scored 0\u0026ndash;3, with higher scores indicating greater sleep disturbances. The total score ranges from 0 to 21, with scores above 5 indicating poor sleep quality. The PSQI has a sensitivity of 89.6%, specificity of 86.5%, a kappa of 0.75, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.01[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eFood Energy Intake\u003c/h3\u003e\n\u003cp\u003eA structured food frequency questionnaire with 113 items was used to estimate dietary energy intake in both groups. Validated among low-income women in Hermosillo, Sonora, it was later adapted for breast cancer survivors and women without cancer in subsequent studies [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePhysical Activity Level and Sedentary Behavior\u003c/h2\u003e\u003cp\u003ePA level and SB were assessed over a week using the Godin Leisure Time Exercise Questionnaire, which had high internal consistency (Cronbach\u0026rsquo;s alpha 0.845\u0026ndash;0.950) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Participants recorded their daily sedentary activities, such as office work and TV viewing, as well as the durations of light, moderate, and vigorous physical activity.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAnthropometric Measurements and Body Composition\u003c/h3\u003e\n\u003cp\u003eWeight and height were measured in accordance with the guidelines of Jelliffe (1966) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Waist circumference conformed to ISAK guidelines [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Body composition was evaluated using DXA with a Hologic scanner, adhering to established procedures to ensure precision [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Measurements encompassed total body fat, lean mass, and regional fat. Scans were conducted by trained technicians, with daily calibration performed as recommended.\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics characterized the study sample and subgroups, specifically BCS and WCH. Means and standard deviations were used to summarize continuous variables, while frequencies and percentages were used to describe categorical variables. Comparisons between BCS and WCH were conducted using t-tests and chi-square tests. Bivariate and multivariable linear regression analyses were employed to investigate the relationships between dependent and independent variables. Ten models included physical activity (PA) level as the independent variable, with body composition metrics as dependent variables. Another ten models analyzed sitting time similarly. Covariates included socioeconomic status, civil and menopausal status, sleep duration, energy intake, sitting time (excluding instances where it was used as a predictor), and cancer history. An interaction term tested whether cancer history affected the relationship between PA and body composition. Model assumptions were checked, and standardized beta coefficients (β) were reported. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Data analysis was performed using IBM SPSS version 30.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eOverall Sample Characteristics and Groups Comparison\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the characteristics of 120 Mexican women, evenly distributed between the BCS and WCH groups. The average age was 52.5 years (SD\u0026thinsp;=\u0026thinsp;9.3), with no significant difference in age. Notable differences were observed in sleep quality, daily energy intake, and waist circumference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), all of which were lower in the BCS group. No significant differences were observed in other body composition measures. Most participants (57.5%) were inactive, while only 25.8% were active, with no significant differences between the groups. The entire sample spent approximately 4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 hours daily sitting, with no significant differences in sitting time between groups.\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\u003eDescriptive Characteristics of Participants\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\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Sample\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBCS\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWCH\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52.13\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep Quality Score, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.14\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDaily energy intake (kcal), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1922.3\u0026thinsp;\u0026plusmn;\u0026thinsp;915.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1683.3\u0026thinsp;\u0026plusmn;\u0026thinsp;762.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2161.2\u0026thinsp;\u0026plusmn;\u0026thinsp;997.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSitting time (hours/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal body fat (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44.04\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFat mass index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.23\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13. 7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaist circumference (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e97.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndroid fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGynoid fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndroid-to-gynoid fat ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Fat-free mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40.05\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38.8\u0026thinsp;\u0026plusmn;\u0026thinsp;15.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFat-free mass index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.37\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.68\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody Mass Index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.25\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMenopausal status, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33 (27.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24 (40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e87 (72.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51 (85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (60)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Single\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45 (37.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Live with partner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75 (62.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (70)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEconomic status n(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Low\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48 (40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (36.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (46.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Medium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (42.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (31)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-High\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (20.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (22.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (4.2)\u003c/p\u003e\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\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePhysical activity level n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Inactive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69 (57.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (56.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35 (58.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Moderate active\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (18.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (15)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e-Active\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31 (25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (26.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eBCS\u003c/b\u003e: Breast Cancer survivors; \u003cb\u003eWCH\u003c/b\u003e: Women without cancer history\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eAssociations Between Physical Activity, Sitting Time, and Body Composition\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the Spearman correlations between physical activity, sitting time, and body composition. PA level was inversely associated with total body fat, fat mass index, waist, and android fat (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No statistically significant association was found between PA level and gynoid fat, android-to-gynoid ratio, fat-free mass, or BMI. Sitting time also showed no significant correlations with any body composition parameters.\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\u003eCorrelations Between Physical Activity, Sitting Time, and Body Composition Outcomes (n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Activity level (rho, p value)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSitting Time per day\u003c/p\u003e\u003cp\u003e(rho, p value)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal body fat Percentage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.26 ; p\u0026thinsp;=\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.10 ; p\u0026thinsp;=\u0026thinsp;0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFat mass index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.20 ; p\u0026thinsp;=\u0026thinsp;0.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.12 ; p\u0026thinsp;=\u0026thinsp;0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaist circumference (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.20 ; p\u0026thinsp;=\u0026thinsp;0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.09 ; p\u0026thinsp;=\u0026thinsp;0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndroid fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.20 ; p\u0026thinsp;=\u0026thinsp;0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.01 ; p\u0026thinsp;=\u0026thinsp;0.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGynoid fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.05 ; p\u0026thinsp;=\u0026thinsp;0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.05 ; p\u0026thinsp;=\u0026thinsp;0.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndroid-to-gynoid fat ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.13 ; p\u0026thinsp;=\u0026thinsp;0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02 ; p\u0026thinsp;=\u0026thinsp;0.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.13 ; p\u0026thinsp;=\u0026thinsp;0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.07 ; p\u0026thinsp;=\u0026thinsp;0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Fat-free mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.03 ; p\u0026thinsp;=\u0026thinsp;0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00 ; p\u0026thinsp;=\u0026thinsp;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFat-free mass index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.07 ; p\u0026thinsp;=\u0026thinsp;0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.06 ; p\u0026thinsp;=\u0026thinsp;0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody Mass Index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.16 ; p\u0026thinsp;=\u0026thinsp;0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.09 ; p\u0026thinsp;=\u0026thinsp;0.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eMultivariable Regression Analyses\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of multivariable regression analysis, indicating that PA levels are significantly associated with total body fat (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) after adjusting for covariates. A history of cancer did not modify these associations. No other outcomes demonstrated significant associations with PA following adjustment. Additionally, sitting time was not significantly correlated with any of the body composition parameters.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariable Linear Regression Models Predicting Body Composition Outcomes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Activity level\u003c/p\u003e\u003cp\u003e(β ; p value)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSitting Time per day\u003c/p\u003e\u003cp\u003e(β, p value)\u003csup\u003e2\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\u003eTotal body fat Percentage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.19; p\u0026thinsp;=\u0026thinsp;0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.02; p\u0026thinsp;=\u0026thinsp;0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFat mass index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.14; p\u0026thinsp;=\u0026thinsp;0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.09; p\u0026thinsp;=\u0026thinsp;0.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaist circumference (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.13; p\u0026thinsp;=\u0026thinsp;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.06; p\u0026thinsp;=\u0026thinsp;0.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndroid fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.15; p\u0026thinsp;=\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01; p\u0026thinsp;=\u0026thinsp;0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGynoid fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.04; p\u0026thinsp;=\u0026thinsp;0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.07; p\u0026thinsp;=\u0026thinsp;0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndroid-to-gynoid fat ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.14; p\u0026thinsp;=\u0026thinsp;0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05; p\u0026thinsp;=\u0026thinsp;0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal fat mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.11; p\u0026thinsp;=\u0026thinsp;0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.08; p\u0026thinsp;=\u0026thinsp;0.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Fat-free mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.01; p\u0026thinsp;=\u0026thinsp;0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.05; p\u0026thinsp;=\u0026thinsp;0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFat-free mass index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.06; p\u0026thinsp;=\u0026thinsp;0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.07; p\u0026thinsp;=\u0026thinsp;0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody Mass Index (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.12; p\u0026thinsp;=\u0026thinsp;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.08; p\u0026thinsp;=\u0026thinsp;0.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e1\u003c/sup\u003eModel adjusted for economic status, civil status, menopausal status, sleep quality, energy intake, sitting time, and cancer history\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e2\u003c/sup\u003eModel adjusted for economic status, civil status, menopausal status, sleep quality, energy intake, physical activity level, and cancer history\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined post-COVID-19 physical activity, sedentary behavior, and their relationship with body composition among Mexican women breast cancer survivors and women without a cancer history. Results showed that 57. 5% of the participants were inactive and spent over four hours daily engaged in sedentary activities, aligning with 2023 national data indicating that 60.2% of the adult Mexican population was inactive, with a higher prevalence among women (66%) than men (53.3%), representing a 5.6% increase in inactivity over the past decade [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The COVID-19 pandemic further worsened these trends globally, leading to widespread decreases in PA and increased SB [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Our findings indicate that during-pandemic behaviors marked by low PA and prolonged sitting persist after the pandemic and are significantly increasing among Mexican population women. Such patterns are concerning, given their well-known association with adverse health outcomes [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. No statistically significant differences were observed in PA level and SB between the groups, contrary to some studies suggesting that cancer survivors adopt healthier habits following diagnosis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Other studies indicate that factors such as fatigue, treatment side effects, and psychosocial challenges may explain the reduced PA levels [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Bivariate analyses demonstrated associations between PA level and variables including total body fat percentage, waist circumference, and fat mass, supporting the hypothesis that moderate to vigorous PA reduces adiposity [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. After adjusting for confounding factors, most associations lost statistical significance, except for total body fat percentage, suggesting that some health benefits of physical activity on body composition may be partly influenced or confounded by other lifestyle and demographic factors [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Daily sitting time was not significantly associated with any body composition parameters, while some previous research associated sedentary behavior with central obesity [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Other research suggests that this relationship may be multifaceted and influenced by contextual factors [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Self-reported sitting duration may limit the accuracy of the measurement. Women with breast cancer exhibited lower waist circumference and energy intake, potentially reflecting intentional lifestyle changes made after diagnosis, recommended by survivorship guidelines [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. No significant interaction was observed between cancer history and the effects of physical activity on body composition, suggesting that the benefits of physical activity are similar regardless of cancer status. The high prevalence of sedentary behavior and low activity levels observed in both groups after the pandemic underscores the need for targeted interventions and highlights the importance of community strategies in promoting physical activity among women as a public health priority.\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and Limitations\u003c/h2\u003e\u003cp\u003eThis study has several strengths, including its focus on an underexplored group of Mexican women, covering both BCS and WCH, while considering relevant covariates. It utilizes Dual-Energy X-ray Absorptiometry (DXA), recognized as the gold standard for accurate body composition assessment, thereby enhancing the validity of the results. However, some limitations should also be acknowledged. The cross-sectional design restricts the ability to determine causality, and reliance on self-reported data for PA and SB may introduce recall and social desirability biases. To minimize these biases, we employed validated questionnaires, trained data collectors, emphasized confidentiality to encourage honest responses, and adhered to standardized data collection procedures. These efforts helped minimize misreporting and improve data reliability. Additionally, some confounding factors from unmeasured variables, such as psychological stress or environmental barriers, may still be present.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMexican women, including breast cancer survivors, continue to exhibit low physical activity levels and considerable sedentary time in the post-pandemic period. A higher physical activity level was associated with healthier body composition, specifically a lower total body fat percentage, while sedentary behavior showed no significant relationship with adiposity. These findings underscore the urgent need to incorporate culturally relevant and feasible physical activity strategies into survivorship care plans. Promoting and supporting increased physical activity may contribute to improved long-term health outcomes and reduce chronic disease risk among breast cancer survivors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePMN, NCC, and GCJ contributed to the conception and design of the study. PMN handled material preparation and data collection, while PMN and NCC performed data analysis. PMN drafted the initial version of the manuscript, NCC and GCJ provided feedback on previous versions, and all the authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank all the women who participated in this study for generously sharing their time and experiences. We also thank the clinical and administrative staff at the CEO and ISSSTE for their support in participant recruitment, as well as Mar\u0026iacute;a del Socorro Saucedo, Kathia Susset Enrique Mada, Mar\u0026iacute;a Jos\u0026eacute; Mend\u0026iacute;vil Armenta, Brenda Rosario Valle Valdez, and Mar\u0026iacute;a Fernanda Armenta Corral for their assistance with data collection. Finally, we are grateful to Centro de Investigaci\u0026oacute;n en Alimentaci\u0026oacute;n y Desarrollo (CIAD) for making this research possible.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung, H., Ferlay, J., Siegel, R. L., et al. 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American Cancer Society nutrition and physical activity guidelines for cancer survivors. \u003cem\u003eCA: A Cancer Journal for Clinicians\u003c/em\u003e. 2022; \u003cem\u003e72\u003c/em\u003e(3), 230\u0026ndash;262. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3322/caac.21719\u003c/span\u003e\u003cspan address=\"10.3322/caac.21719\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Adiposity, lifestyle behavior, Breast cancer survivor health, After COVID-19 pandemic","lastPublishedDoi":"10.21203/rs.3.rs-8099176/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8099176/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose:\u003c/h2\u003e\u003cp\u003ePhysical activity (PA) and sedentary behavior (SB) are modifiable factors associated with improved body composition (BC) and lower morbidity risk in breast cancer survivors. The COVID-19 pandemic disrupted activity patterns worldwide, but data on post-pandemic habits among Latin American survivors remain scarce. This study examined PA and SB levels and explored whether their relationship with BC varies based on cancer history status.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eIn this cross-sectional study, 120 Mexican women (60 breast cancer survivors and 60 women without cancer history) reported PA and SB using validated questionnaires. BC indicators were assessed using dual-energy X-ray absorptiometry. Correlation analysis and multivariable linear regression were performed, adjusting for pertinent confounders.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eThe mean age was 52.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3 years. Overall, 57% were physically inactive, and the average sitting time was 4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 hours per day. PA levels were negatively correlated with total body fat percentage (TBFP) (rho = \u0026minus;\u0026thinsp;0.26), fat mass index (rho = \u0026minus;\u0026thinsp;0.20), waist circumference (rho = \u0026minus;\u0026thinsp;0.20), and android fat mass (rho = \u0026minus;\u0026thinsp;0.20) (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). SB was not associated with BC. After adjustment, PA level remained independently inversely associated with TBFP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and cancer history status did not modify this relationship.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e\u003cp\u003ePhysical inactivity persists post-pandemic among Mexican women, including breast cancer survivors. PA is associated with healthier BC, independent of cancer history status.\u003c/p\u003e\u003ch2\u003eImplications for Cancer Survivors:\u003c/h2\u003e\u003cp\u003eIncreasing PA through structured, culturally tailored support integrated into survivorship care may improve body composition and mitigate long-term health risks among post-pandemic breast cancer survivors.\u003c/p\u003e","manuscriptTitle":"Post-Pandemic Physical Activity, Sedentary Behavior, and Body Composition Among Mexican Breast Cancer Survivors: Implications for Survivorship Health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 09:17:04","doi":"10.21203/rs.3.rs-8099176/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"26805714009557117916613382024325680875","date":"2026-05-06T01:05:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-10T02:16:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-10T02:14:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-19T07:15:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Supportive Care in Cancer","date":"2025-11-12T18:44:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"248a4301-a7a9-4df5-a484-93fa6e3514d7","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"26805714009557117916613382024325680875","date":"2026-05-06T01:05:02+00:00","index":24,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T09:17:04+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-15 09:17:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8099176","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8099176","identity":"rs-8099176","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}