Analysis of Obesity Prevalence and Trend Prediction among Professional Women in a Hospital from 2010 to 2024: A Weight Management Perspective

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Methods: We collated physical examination data from 248,147 female participants aged 20-59 years who underwent examinations at the Shanghai Health and Medical Center between 2010 and 2024. Overweight and obesity were determined based on body mass index (BMI), while central obesity was diagnosed using waist circumference (WC), waist-hip ratio (WHR), and waist-height ratio (WHtR) as reference values. The JoinPoint regression model was employed to calculate the average annual percent change (AAPC) and its 95% confidence interval (CI). The Bayesian age-period-cohort (BAPC) model was used to predict the development trends of these indicators from 2025 to 2035. Results: Among the 248,147 female examinees, the prevalence of overweight was 21.26% (56,010 cases), obesity was 5.14% (13,248 cases), and central obesity was 25.23% (67,363 cases). From 2010 to 2024, the prevalence of overweight (AAPC=1.19%; 95%CI: 0.71 to 1.68; P <0.05) and obesity (AAPC=4.63%; 95%CI: 4.05 to 5.36; P <0.05) increased annually; the prevalence of central obesity peaked at 29.94% in 2013 and exhibited a fluctuating trend (AAPC=0.25; 95%CI: -0.83 to 1.29; P =0.605). Comparative analysis among age subgroups revealed a highly significant upward trend in the rates of overweight, obesity, and central obesity with increasing age (all P <0.05). The forecast results indicated that the prevalence of obesity would increase by 2.69% annually, reaching 9.14% by 2035 ( P <0.001); the prevalence of central obesity would increase by 0.52% annually, reaching 25.02% by 2035 ( P =0.040). Conclusion: Professional women should strengthen weight management, with employers facilitating health education, providing preferential medical insurance policies, improving the monitoring system, and implementing targeted interventions to control the obesity trend. Overweight Obesity Central obesity Trend analysis Trend forecast Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Obesity is a global public health challenge. According to the World Health Organization and the 2025 World Obesity Atlas, as of 2022, approximately 2.548 billion adults worldwide were overweight or obese, and this number is projected to reach 2.9 billion by 2030, accounting for 50% of the global population [ 1 ]. In China, the situation is worsening, with a significant increase in prevalence [2–3]. Obesity is closely associated with the occurrence and mortality of various chronic diseases, such as cardiovascular diseases, diabetes, kidney diseases, and certain types of cancers, posing a serious threat to human health and lifespan [4–7]. Therefore, controlling obesity can not only reduce the burden of related diseases but also improve the overall health status of the population and promote sustainable development of the economy and society [8]. Based on the large-scale data of physical examinations among female professionals in a hospital in Shanghai from 2010 to 2024, this study analyzed the prevalence rates of overweight, obesity, and central obesity, and predicted their future trends. This is conducive to gaining an in-depth understanding of the development trend of obesity among local professional women, thereby providing strong support for formulating targeted weight management strategies and public health intervention measures. This study has significant practical implications for improving the health status of female professional groups, reducing the disease burden related to obesity, and optimizing the allocation of public health resources. Materials and methods 1.1 Participants A retrospective analysis was conducted on the physical examination data of professional women who underwent physical examinations at our hospital between January 2010 and December 2024. The inclusion criteria were as follows: (1) aged between 20 and 59 years; (2) having resided in Shanghai for ≥ 6 months; (3) being employed female staff from government agencies, enterprises, or public institutions; (4) non-pregnant women; and (5) having no severe physical disabilities or mental illnesses. The participants were divided into four age groups: 20–29 years, 30–39 years, 40–49 years, and 50–59 years. This study was approved by the Ethics Committee of our hospital (Ethics No.: 2022 Lunyan Pihui No. 16). 1.2 Research Methods Cluster random sampling was employed, with 1–2 units randomly selected from each of the 16 administrative districts in Shanghai, totaling 20 units, covering various types of institutions, including government agencies, state-owned enterprises, foreign-funded enterprises, and private enterprises. All employed women who underwent physical examinations at our hospital during the study period from the selected units were included in the study cohort. Data were collected using epidemiological cross-sectional survey methods, encompassing general information and physical examination results, including age, height, weight, waist circumference (WC), and hip circumference. Body mass index (BMI) was calculated as weight (kg)/height² (m²), waist-hip ratio (WHR) as waist circumference (WC) (cm)/hip circumference (cm), and waist-height ratio (WHtR) as WC (cm)/height (cm). Measurement tools specified by the Chinese Center for Disease Control and Prevention were used. For height and weight measurements, the participants were required to remove their shoes and hats and stand naturally, ensuring that the horizontal headpiece of the stadiometer was placed at a right angle to the scale. For WC measurement, the participants were asked to wear single-layer clothing and to breathe naturally. WC was measured at the midpoint between the anterior superior iliac spine and the lower edge of the 12th rib, and the hip circumference was measured at the level of the symphysis pubis to determine the maximum hip girth. BMI is a universal criterion for assessing generalized obesity. According to the "China Adult Overweight and Obesity Prevention and Control Guide" [9], a BMI of 24-27.9 kg/m² indicates overweight, while a BMI ≥ 28 kg/m² indicates obesity. However, body fat percentage exhibits significant variations with age, and obesity in the Chinese population is characterized by a higher distribution of visceral fat in the abdominal cavity, making individuals more prone to central obesity (i.e., abdominal obesity). Central obesity can be diagnosed when WC ≥ 85 cm, WHR ≥ 0.85, or WHtR ≥ 0.5 [10–11]. 1.3 Statistical Analysis Data were entered using Excel. Statistical analyses were conducted using SPSS 25.0 software (IBM Corporation, USA). Continuous variables were expressed as mean ± standard deviation (x̅ ± s), and differences in means were compared using one-way analysis of variance. Categorical variables were presented as counts and percentages, and differences between groups were compared using the chi-square test. The age-standardized prevalence rates of overweight, obesity, and central obesity were calculated using the age composition from the 2020 national population census data as the standard. The Joinpoint regression model was employed to calculate the average annual percent change (AAPC) and its 95% confidence interval (CI). The Bayesian age-period-cohort (BAPC) model was used to predict the development trends of the above indicators from 2025 to 2035. Statistical significance was set at P < 0.05. Results 2.1 General Overview Among the 248,147 female participants who underwent physical examinations, the age range was 20–59 years, with a mean age of (42.56 ± 9.73) years. The average BMI, WC, hip circumference, WHR, and WHtR in the study population were (22.63 ± 3.04) kg/m², (74.55 ± 8.20) cm, (92.57 ± 6.42) cm, (0.81 ± 0.07), and (0.46 ± 0.05), respectively (Fig. 1). From 2010 to 2024, the prevalence rate of overweight ranged from 18.53–23.12%, with a peak in 2024. The prevalence rate of obesity ranged from 3.71–6.75%, peaking in 2024. The prevalence of abnormal WC ranged from 7.37–11.53%, with the highest rate observed in 2013. The prevalence rate of abnormal WHR ranged from 14.61–22.33%, peaking in 2013. The prevalence rate of abnormal WHtR ranged from 16.85–24.81%, with the highest rate in 2013. The prevalence rate of central obesity ranged from 21.59–29.94%, reaching its peak in 2013 (Table 1). Table 1 Prevalence rates of standardized overweight, obesity, and central obesity among Shanghai's female professionals (2010–2024) (%) year Prevalence rate of overweight Prevalence rate of obesity Prevalence rate of abnormal WC Prevalence rate of abnormal WHR Prevalence rate of abnormal WHtR Prevalence rate of central obesity 2010 18.89 3.71 7.96 14.61 18.43 21.59 2011 18.53 3.73 9.15 17.63 20.61 24.90 2012 20.16 3.82 9.71 19.02 22.12 26.53 2013 20.09 4.12 11.53 22.33 24.81 29.94 2014 20.29 4.25 10.34 21.47 23.19 28.60 2015 20.42 4.35 9.34 18.35 19.97 24.95 2016 20.85 4.45 8.65 20.89 18.95 26.27 2017 21.61 4.69 8.75 20.65 20.41 26.82 2018 19.23 4.17 8.46 19.74 19.23 25.62 2019 20.73 4.59 8.38 19.02 19.15 24.94 2020 20.43 4.94 8.02 19.10 17.35 24.02 2021 21.24 5.09 7.37 17.60 16.85 23.14 2022 22.13 5.77 8.33 15.71 18.50 22.86 2023 22.77 6.57 11.32 18.20 22.24 26.49 2024 23.12 6.75 9.89 15.67 19.18 23.06 2.2 Trends in the Prevalence Rates of Overweight, Obesity, and Central Obesity among Shanghai's Female professionals (2010–2024) From 2010 to 2024, among the 248,147 female physical examination participants, the prevalence rate of overweight increased annually by 1.19% (AAPC = 1.19; 95%CI: 0.71 to 1.68; P < 0.001), the prevalence rate of obesity increased annually by 4.63% (AAPC = 4.63; 95%CI: 4.05 to 5.36; P < 0.001), and the prevalence rate of abnormal WC increased annually by 2.16% (AAPC = 2.16; 95%CI: 0.70 to 3.70; P 0.05) (Table 1, Fig. 2, and Fig. 3). The results of the JoinPoint regression analysis showed that the obesity rate in women increased annually by 3.57% from 2010 to 2016 (APC = 3.57; 95%CI: 1.61 to 8.86; P 0.05); and it increased annually by 9.14% from 2019 to 2024 (APC = 9.14; 95%CI: 6.84 to 14.04; P < 0.001] (Fig. 3). 2.3 Trend Analysis of Overweight and Obesity Rates among Women in Different Age Groups Among the 248,147 female participants who underwent physical examinations from 2010 to 2024, the prevalence rates of overweight increased annually in the 20–29, 30–39, and 40–49 age groups (all P < 0.05). Moreover, the prevalence rates of obesity among women in each of the ten-year age groups spanning from 20 to 59 years also demonstrated a steady annual increase (all with P < 0.05) (Fig. 4). Furthermore, the prevalence rates of abnormal WC increased annually in the 30–39 and 40–49 age groups (all P < 0.05), and the prevalence rate of abnormal WHtR increased annually in the 30–39 age group ( P < 0.05) (Fig. 5). 2.4 Trend Prediction of Obesity Prevalence among Professional Women in a Shanghai Hospital The obesity detection rate among professional women in Shanghai is predicted to increase from 2025 to 2035.The estimated AAPC was 2.69% (95% CI: 2.12 to 3.18; P < 0.001). Based on this trend, it is projected to reach 9.14% (95% CI: 7.12 to 11.16) by 2035(Fig. 6). Discussion High BMI has been defined by the World Health Organization as "one of the most crucial controllable risk factors for diseases in the 21st century." The latest data from the Global Burden of Disease Study (GBD 2021) revealed that a high BMI resulted in a loss of 62 million to 90.7 million disability-adjusted life years (DALYs) globally. Its health hazards are primarily manifested as an increased burden of ischemic heart disease, type 2 diabetes, and hypertensive heart disease. These diseases account for a dominant proportion of the overall disease burden attributable to high BMI, and with the ongoing rise in both the aging population and obesity rates, their impact is expected to intensify further [ 12 ]. In China, along with economic transformation and the Westernization of dietary patterns, the average BMI of adult men and women has shown a steady upward trend. The male BMI increased from 21.06 in 1982 to 24.25 in 2015, while the women’s BMI rose from 21.32 in 1982 to 23.89 in 2015. Despite the fact that the growth rate of BMI in women is lower than that in men [ 13 ], women face a higher risk of central obesity due to physiological factors, social roles, and occupational stress [14]. Compared with men, a high BMI in women is more closely associated with diseases such as breast cancer (especially postmenopausal breast cancer), endometrial cancer, polycystic ovary syndrome, gestational diabetes mellitus, and depressive disorders [ 15 – 17 ]. For professional women, the imbalance between excessive energy intake and insufficient physical activity is particularly prominent due to prolonged sitting, psychological stress, and dual "work-family" responsibilities. Based on a large-scale physical examination cohort of 248,000 individuals over a 15-year span, this study systematically delineated, for the first time, the dynamic trajectories of overweight, obesity, and central obesity among professional women in Shanghai. It also extended projections to 2035 using the BAPC model, providing verifiable baselines and evaluation metrics for the "Weight Management Year" action plan. Currently, there is a lack of nationwide obesity monitoring data for professional female workers in China. This study indicates an obesity prevalence rate of 6.75% in 2024, which, although lower than that in American and European countries [ 18 – 19 ], is higher than that in Japan (4.3%) [ 20 ]. This suggests that China is experiencing a rapid increase in obesity. A high BMI contributes to 6.50% of the total disability-adjusted life years (DALYs) [8] and is closely linked to strategies for preventing and controlling hypertension, diabetes, and cancer. Therefore, this study not only provides evidence-based guidance for weight management among professional women but also aligns with the comprehensive chronic disease prevention and control strategy outlined in China's "Healthy China 2030" plan. The results of this study indicate that from 2010 to 2024, the annual average increase in the prevalence of overweight among professional women in Shanghai was 1.19%, and the annual average increase in the prevalence of obesity was 4.63%. According to the BAPC model projections, the obesity rate will reach 9.14% by 2035, showing a continuous upward trend. The prevalence of central obesity peaked in 2013 and then fluctuated and stabilized, suggesting that the growth rate of generalized obesity was faster than that of central obesity. In contrast, the growth rate of obesity prevalence among women in high-income countries in Europe and the United States has slowed [ 21 ]. Although the obesity rate among professional women in Shanghai remains low, its growth rate is significantly faster than the average in high-income countries, and the window for prevention and control is rapidly narrowing. Therefore, there is an urgent need to develop more targeted prevention and control strategies to curb the further increase in the prevalence of obesity. Currently, global weight management is undergoing a transformation from individualized interventions to systemic governance and from medical settings to the workplace environment. The reasons for the rising prevalence of high BMI in Shanghai can be summarized as follows: (1)Westernization of dietary patterns and intake of takeaway food, sugary drinks, and ultra-processed foods; (2) long average weekly working hours, prolonged sedentary time, and insufficient physical activity; (3)accumulated mental stress leading to elevated cortisol levels, which promotes fat deposition; and (4) shorter intervals between two pregnancies after the adjustment of fertility policies, resulting in the weight retention effect. Drawing on international experience, Shanghai can start with "workplace microenvironment optimization" and implement the following measures: First, the government should incorporate the annual increase in BMI among female employees into the assessment criteria for civilized units and provide rewards to those who meet the standards. Second, “10-minute workplace exercises,” stair culture, and a star rating system for healthy canteens should be promoted. Third, AI and wearable devices should be utilized to establish a closed-loop management system involving "individuals-enterprises-medical insurance," and rewards should be provided to employees who effectively control their BMI by adding credits to their medical insurance accounts. Fourth, psychological support should be strengthened and health promotion programs should be launched. Studies have confirmed that such programs can effectively reduce the prevalence of overweight and obesity among employees [ 22 – 23 ] and improve work efficiency and quality of life. This study did not directly incorporate gender difference analysis; however, comparisons can be made using data from Shanghai and global studies. The age-standardized obesity rate among women in Shanghai (9.26%) is still lower than that among men of the same age (10.40%) [ 24 ]. In high-income countries in Europe and the United States, obesity rates have shown a trend of being "higher in women than in men" and have plateaued, such as in the United States (41.3% vs. 39.2%) [ 18 ] and the United Kingdom (26.9% vs. 26.2%) [ 19 ]. This suggests that women in Shanghai are currently in a "low-level potential acceleration" stage, and factors such as postmenopausal fat redistribution and insufficient physical activity may significantly increase obesity rates within the next 10–15 years, necessitating early intervention. Targeted measures should focus on the "female full life cycle": strengthening school nutrition education during adolescence, incorporating weight management into premarital and pre-pregnancy healthcare during the childbearing period, and emphasizing resistance training and bone density protection after menopause. At the family level, the concept of "shared health" should be promoted, encouraging spouses and children to participate in dietary and exercise plans to sustain weight management. At the societal level, the media should promote diverse concepts of healthy body image. Age-stratified analysis showed that the prevalence of overweight, obesity, and central obesity all increased with age, with the obesity rate in the 50–59 age group (8.87%) being approximately 3.2 times that in the 20–29 age group (2.74%). The reasons include: (1) a 2–3% decrease in basal metabolic rate every decade, leading to reduced energy expenditure; (2) a decline in estrogen levels triggering fat redistribution; and (3) a decrease in work intensity in the later stages of one's career but the continuation of dietary patterns. The prevalence of abnormal WHtR in the 30–39 age group increased by 2.1% annually, which may be related to the combination of a peak in childbirth, sedentary office work, and parenting stress in this age group. Fortunately, weight control in middle-aged and elderly individuals is not "irreversible." Studies have shown that effective knowledge translation tools (KT tools) can help middle-aged women make weight management decisions [ 25 ], the development of assessment tools based on behavioral classification (such as OxFAB-MAW) can evaluate weight management behaviors [ 26 ], and weight loss treatment programs for elderly obese women can significantly reduce weight and improve health status. Shanghai can rely on platforms such as community health stations, senior sports and health centers [ 27 ], and retired faculty associations to promote low-threshold exercises such as "midday brisk walking and square dancing" and combine them with family doctor contract services to assess BMI, blood pressure, and blood sugar every quarter for "early prevention and early control." This study had two limitations. First, the data were sourced from the physical examination center of a single tertiary hospital in Shanghai, which may have introduced selection bias (primarily consisting of government agencies, public institutions, and state-owned enterprises). This study standardized the data according to the age structure of the 2020 population census and supplemented it with data from five private technology companies in 2024 to improve representativeness. Second, the physical examination data lack key behavioral information, such as diet, physical activity, and psychology. A "professional women's health follow-up cohort" has been launched in collaboration with the Shanghai Municipal Center for Disease Control and Prevention, using mobile apps and wearable devices to collect lifestyle data in real time, with the first round of follow-up expected to be completed in 2025. Based on 248,147 person-times of continuous physical examination data over 15 years, this study systematically described the dynamic changes in overweight, obesity, and central obesity among professional women in Shanghai using JoinPoint and BAPC models and projected the results until 2035. The research results provide key evidence-based support for the government, enterprises, and medical insurance departments to collaboratively implement precise weight management and curb the increase in chronic diseases. Declarations Author agreement The corresponding author hereby declares that all authors have seen and approved the final version of the manuscript submitted. This article is the authors’ original work, has not been previously published, and is not under consideration for publication elsewhere. CRediT authorship contribution statement Mei Liu: Writing—review & editing, Supervision, Methodology, Investigation, Data curation. Yanfeng Shi: Writing—review & editing, Investigation, Data curation. Chunyun Shao: Writing—review & editing, Investigation, Data curation. Wenchang Jia: Writing—review & editing, Writing—original draft, Visualization, Validation, Supervision, Software, Resources, Project administration. Xiaopan Li: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Funding acquisition, Writing—original draft, Writing—review & editing, Visualization. Jianguang Tian: Writing—review & editing, Supervision. Xiaohui Zhou: Conceptualization, Methodology, Investigation, Data curation, Funding acquisition, Writing—original draft, Writing—review & editing, Visualization, Validation, Supervision, Software, Project administration. Consent to participate and permission to publish the data We affirm that all participants were informed about the possible risks and benefits related to participation in the study and provided informed consent for participation in the study and publication of the data before participating in the study. Ethical approval This study involving humans was approved by the Ethics Committee of Shanghai Health and Medical Center (Ethics No.: 2022 Lunyan Pihui No. 16) and was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Declaration of Competing Interest On behalf of all authors, the corresponding author states that there are no conflicts of interest. Acknowledgements We thank Chenyu Wu and Kefang Wang for their practical assistance. Funding Declaration The study was supported by the Key Disciplines of the Three-Year Action Plan for Strengthening the Construction of the Public Health System in Shanghai (2023-2025 GWVI-11.1-28). The supporters had no role in the study design, data collection, data analysis, data interpretation, or writing of the article. References World Obesity Federation. World Obesity Atlas 2025 [EB/0L](2025-03-04)2025-03-13.https://data.worldobesity.org/publications/? cat=23. Zhao ZP, Zhang M, Li C, Yu MT, Zhang X, Wang LM, et al. Growth rate of adult obesity prevalence in china and target population for prevention and control from 2013 to 2018 [J]. Zhonghua Xin Xue Guan Bing Za Zhi, 2024, 52(1): 34-41. DOI: 10.3760/cma.j.cn112148-20231023-00369. Hao LX, Zhang B, Wang HJ, Wang LS, Jiang HR,Wang SSZ, et al. Trends and epidemic characteristics of overweight and obesity among adults aged 18-35 in 15 provinces(autonomous regions/municipalities) of china from 1989 to 2018 [J]. 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Front Psychol. 2023,13:1069775. DOI: 10.3389/fpsyg.2022.1069775. FENG L. Shanghai launches “Seniors’ Fitness Homes” – elders get their own gyms right at the doorstep [EB/OL].(2024-03-21)[2025-08-08]. https://www.sport.gov.cn/n20001280/n20001265/n20067708/c27581742/content.html Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2025 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 08 Sep, 2025 Editor assigned by journal 05 Sep, 2025 Submission checks completed at journal 05 Sep, 2025 First submitted to journal 01 Sep, 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. 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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-7508365","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510227760,"identity":"dbda3382-0756-49df-9a0a-ded9d2811934","order_by":0,"name":"Mei Liu","email":"","orcid":"","institution":"Shanghai Health and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Liu","suffix":""},{"id":510227762,"identity":"96de384c-3404-437b-ac50-b0bf8cfb85eb","order_by":1,"name":"Yanfeng Shi","email":"","orcid":"","institution":"Shanghai Health and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yanfeng","middleName":"","lastName":"Shi","suffix":""},{"id":510227764,"identity":"0f859fe4-b753-42f7-aeda-0612534421cc","order_by":2,"name":"Chunyun Shao","email":"","orcid":"","institution":"Shanghai Health and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Chunyun","middleName":"","lastName":"Shao","suffix":""},{"id":510227766,"identity":"bad460a3-98a5-4778-91e6-7ecd9dde1a05","order_by":3,"name":"Wenchang Jia","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Wenchang","middleName":"","lastName":"Jia","suffix":""},{"id":510227767,"identity":"daf66169-8ae2-4d97-9fcf-3499ef766062","order_by":4,"name":"Xiaopan Li","email":"","orcid":"","institution":"Zhongshan Hospital Affiliated to Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Xiaopan","middleName":"","lastName":"Li","suffix":""},{"id":510227769,"identity":"a469bb0a-958f-42d0-ab87-5528f3a5d90e","order_by":5,"name":"Jianguang Tian","email":"","orcid":"","institution":"Shanghai Health and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jianguang","middleName":"","lastName":"Tian","suffix":""},{"id":510227770,"identity":"2e9d111a-bc68-4f45-ab73-8826d50d11d2","order_by":6,"name":"Xiaohui Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApElEQVRIiWNgGAWjYDCCA0DM2GDDw8/eQJqWNBnJngOkaTlsY3DDgUgdfMebH3/m3XGeh+EGA+OHjzlEaJE8c8zAcOaZ2zyMsxuYJWduI0KLwY0choSPbbd5mGUOsDHzEqvlQGLbOR42iQTitTA2fGw7wMNDtBagX4wZZ7Yl80jwHGwmzi+QEGuzs7c/3nzww0ditCABxgbS1I+CUTAKRsEowA0Aga04JIa/AUEAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai Health and Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Xiaohui","middleName":"","lastName":"Zhou","suffix":""}],"badges":[],"createdAt":"2025-09-01 12:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7508365/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7508365/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-025-25276-6","type":"published","date":"2025-11-28T15:58:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90892049,"identity":"860cc16a-2703-4112-a4d3-b53c53ac15db","added_by":"auto","created_at":"2025-09-09 11:14:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":93502,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eObesity-related basic characteristics among Shanghai's female professionals (2010-2024)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7508365/v1/1f0bc50deedc9a337e48ea56.png"},{"id":90892051,"identity":"e1063d58-cfd3-45fd-965a-29d3bca05c78","added_by":"auto","created_at":"2025-09-09 11:14:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":406805,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend of prevalence rates of abnormal WC, WHR, and WHtR among Shanghai's female professionals (2010-2024)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7508365/v1/bba1dd6d3473af225618cf47.png"},{"id":90892054,"identity":"946ce8a8-8149-4825-919b-a043515a764f","added_by":"auto","created_at":"2025-09-09 11:14:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":231618,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend of overweight, obesity, and central obesity among Shanghai's female professionals (2010-2024)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7508365/v1/a2a50941bce8a80e276ca41e.png"},{"id":90892537,"identity":"c3c87306-5e7c-4a75-91bf-83b932bc16fc","added_by":"auto","created_at":"2025-09-09 11:22:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":313992,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend of prevalence rates of overweight and obesity among Shanghai's female professionals (2010-2024)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7508365/v1/38887a6978cbda244b0ad64a.png"},{"id":90892060,"identity":"ae5eb527-a290-4430-b617-b1e56d2c280b","added_by":"auto","created_at":"2025-09-09 11:14:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":415832,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend of prevalence rates of abnormal WC, WHR, and WHtR among Shanghai's female professionals (2010-2024)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7508365/v1/c8695e5575a58f9612eec0c8.png"},{"id":90894464,"identity":"b00dc6e9-a0d4-4477-88ff-a45e539c7b2c","added_by":"auto","created_at":"2025-09-09 11:30:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":313138,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProjecting overweight and obesity rates among Shanghai's female professionals (2025-2035)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7508365/v1/05699dc773ec844c628fa7a0.png"},{"id":97178596,"identity":"1018f2a1-8790-48ee-a049-7fb3266d92a8","added_by":"auto","created_at":"2025-12-01 16:11:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2599739,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7508365/v1/60fe5036-2578-4262-8bf0-c84c81c4fedc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of Obesity Prevalence and Trend Prediction among Professional Women in a Hospital from 2010 to 2024: A Weight Management Perspective","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity is a global public health challenge. According to the World Health Organization and the 2025 World Obesity Atlas, as of 2022, approximately 2.548 billion adults worldwide were overweight or obese, and this number is projected to reach 2.9 billion by 2030, accounting for 50% of the global population [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e]. In China, the situation is worsening, with a significant increase in prevalence [2\u0026ndash;3]. Obesity is closely associated with the occurrence and mortality of various chronic diseases, such as cardiovascular diseases, diabetes, kidney diseases, and certain types of cancers, posing a serious threat to human health and lifespan [4\u0026ndash;7]. Therefore, controlling obesity can not only reduce the burden of related diseases but also improve the overall health status of the population and promote sustainable development of the economy and society [8].\u003c/p\u003e\n\u003cp\u003eBased on the large-scale data of physical examinations among female professionals in a hospital in Shanghai from 2010 to 2024, this study analyzed the prevalence rates of overweight, obesity, and central obesity, and predicted their future trends. This is conducive to gaining an in-depth understanding of the development trend of obesity among local professional women, thereby providing strong support for formulating targeted weight management strategies and public health intervention measures. This study has significant practical implications for improving the health status of female professional groups, reducing the disease burden related to obesity, and optimizing the allocation of public health resources.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003cp\u003e1.1 Participants\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003cp\u003eA retrospective analysis was conducted on the physical examination data of professional women who underwent physical examinations at our hospital between January 2010 and December 2024. The inclusion criteria were as follows: (1) aged between 20 and 59 years; (2) having resided in Shanghai for \u0026ge;\u0026thinsp;6 months; (3) being employed female staff from government agencies, enterprises, or public institutions; (4) non-pregnant women; and (5) having no severe physical disabilities or mental illnesses. The participants were divided into four age groups: 20\u0026ndash;29 years, 30\u0026ndash;39 years, 40\u0026ndash;49 years, and 50\u0026ndash;59 years. This study was approved by the Ethics Committee of our hospital (Ethics No.: 2022 Lunyan Pihui No. 16).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003cp\u003e1.2 Research Methods\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003cp\u003eCluster random sampling was employed, with 1\u0026ndash;2 units randomly selected from each of the 16 administrative districts in Shanghai, totaling 20 units, covering various types of institutions, including government agencies, state-owned enterprises, foreign-funded enterprises, and private enterprises. All employed women who underwent physical examinations at our hospital during the study period from the selected units were included in the study cohort. Data were collected using epidemiological cross-sectional survey methods, encompassing general information and physical examination results, including age, height, weight, waist circumference (WC), and hip circumference. Body mass index (BMI) was calculated as weight (kg)/height\u0026sup2; (m\u0026sup2;), waist-hip ratio (WHR) as waist circumference (WC) (cm)/hip circumference (cm), and waist-height ratio (WHtR) as WC (cm)/height (cm). Measurement tools specified by the Chinese Center for Disease Control and Prevention were used. For height and weight measurements, the participants were required to remove their shoes and hats and stand naturally, ensuring that the horizontal headpiece of the stadiometer was placed at a right angle to the scale. For WC measurement, the participants were asked to wear single-layer clothing and to breathe naturally. WC was measured at the midpoint between the anterior superior iliac spine and the lower edge of the 12th rib, and the hip circumference was measured at the level of the symphysis pubis to determine the maximum hip girth.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003cp\u003eBMI is a universal criterion for assessing generalized obesity. According to the \u0026quot;China Adult Overweight and Obesity Prevention and Control Guide\u0026quot; [9], a BMI of 24-27.9 kg/m\u0026sup2; indicates overweight, while a BMI\u0026thinsp;\u0026ge;\u0026thinsp;28 kg/m\u0026sup2; indicates obesity. However, body fat percentage exhibits significant variations with age, and obesity in the Chinese population is characterized by a higher distribution of visceral fat in the abdominal cavity, making individuals more prone to central obesity (i.e., abdominal obesity). Central obesity can be diagnosed when WC\u0026thinsp;\u0026ge;\u0026thinsp;85 cm, WHR\u0026thinsp;\u0026ge;\u0026thinsp;0.85, or WHtR\u0026thinsp;\u0026ge;\u0026thinsp;0.5 [10\u0026ndash;11].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003cp\u003e1.3 Statistical Analysis\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003cp\u003eData were entered using Excel. Statistical analyses were conducted using SPSS 25.0 software (IBM Corporation, USA). Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (x̅ \u0026plusmn; s), and differences in means were compared using one-way analysis of variance. Categorical variables were presented as counts and percentages, and differences between groups were compared using the chi-square test. The age-standardized prevalence rates of overweight, obesity, and central obesity were calculated using the age composition from the 2020 national population census data as the standard. The Joinpoint regression model was employed to calculate the average annual percent change (AAPC) and its 95% confidence interval (CI). The Bayesian age-period-cohort (BAPC) model was used to predict the development trends of the above indicators from 2025 to 2035. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\"\u003e\n \u003cp\u003e2.1 General Overview\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003cp\u003eAmong the 248,147 female participants who underwent physical examinations, the age range was 20–59 years, with a mean age of (42.56 ± 9.73) years. The average BMI, WC, hip circumference, WHR, and WHtR in the study population were (22.63 ± 3.04) kg/m², (74.55 ± 8.20) cm, (92.57 ± 6.42) cm, (0.81 ± 0.07), and (0.46 ± 0.05), respectively (Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003cp\u003eFrom 2010 to 2024, the prevalence rate of overweight ranged from 18.53–23.12%, with a peak in 2024. The prevalence rate of obesity ranged from 3.71–6.75%, peaking in 2024. The prevalence of abnormal WC ranged from 7.37–11.53%, with the highest rate observed in 2013. The prevalence rate of abnormal WHR ranged from 14.61–22.33%, peaking in 2013. The prevalence rate of abnormal WHtR ranged from 16.85–24.81%, with the highest rate in 2013. The prevalence rate of central obesity ranged from 21.59–29.94%, reaching its peak in 2013 (Table 1).\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cp\u003eTable 1\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003ePrevalence rates of standardized overweight, obesity, and central obesity among Shanghai's female professionals (2010–2024) (%)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eyear\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePrevalence rate of overweight\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePrevalence rate of obesity\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePrevalence rate of abnormal WC\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePrevalence rate of abnormal WHR\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePrevalence rate of abnormal WHtR\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePrevalence rate of central obesity\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2010\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e18.89\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3.71\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e7.96\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e18.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e21.59\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2011\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e18.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3.73\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e9.15\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e17.63\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e24.90\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2012\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3.82\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e9.71\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e26.53\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2013\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e11.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e24.81\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e29.94\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2014\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e10.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e21.47\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e23.19\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e28.60\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2015\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e9.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e18.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.97\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e24.95\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2016\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.85\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.45\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e8.65\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.89\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e18.95\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e26.27\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2017\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e21.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.69\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e8.75\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.65\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e26.82\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2018\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.17\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e8.46\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.74\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e25.62\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2019\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.73\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.59\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e8.38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.15\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e24.94\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2020\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.94\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e8.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e17.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e24.02\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2021\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e21.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e7.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e17.60\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e16.85\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e23.14\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2022\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22.13\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5.77\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e8.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15.71\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e18.50\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22.86\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2023\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22.77\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e6.57\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e11.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e18.20\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e26.49\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2024\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e23.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e6.75\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e9.89\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15.67\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e19.18\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e23.06\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.2 Trends in the Prevalence Rates of Overweight, Obesity, and Central Obesity among Shanghai's Female professionals (2010–2024)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFrom 2010 to 2024, among the 248,147 female physical examination participants, the prevalence rate of overweight increased annually by 1.19% (AAPC = 1.19; 95%CI: 0.71 to 1.68; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), the prevalence rate of obesity increased annually by 4.63% (AAPC = 4.63; 95%CI: 4.05 to 5.36; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and the prevalence rate of abnormal WC increased annually by 2.16% (AAPC = 2.16; 95%CI: 0.70 to 3.70; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). No significant trends were observed in the prevalence rates of abnormal WHR, abnormal WHtR, or central obesity (all \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05) (Table\u0026nbsp;1, Fig.\u0026nbsp;2, and Fig.\u0026nbsp;3).\u003c/p\u003e\n \u003cp\u003eThe results of the JoinPoint regression analysis showed that the obesity rate in women increased annually by 3.57% from 2010 to 2016 (APC = 3.57; 95%CI: 1.61 to 8.86; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001); there was no significant trend from 2016 to 2019 (APC=-0.45; 95%CI: -2.94 to 6.13; \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05); and it increased annually by 9.14% from 2019 to 2024 (APC = 9.14; 95%CI: 6.84 to 14.04; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001] (Fig.\u0026nbsp;3).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003cp\u003e2.3 Trend Analysis of Overweight and Obesity Rates among Women in Different Age Groups\u003c/p\u003e\n \u003cp\u003eAmong the 248,147 female participants who underwent physical examinations from 2010 to 2024, the prevalence rates of overweight increased annually in the 20–29, 30–39, and 40–49 age groups (all \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Moreover, the prevalence rates of obesity among women in each of the ten-year age groups spanning from 20 to 59 years also demonstrated a steady annual increase (all with \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (Fig.\u0026nbsp;4).\u003c/p\u003e\n \u003cp\u003eFurthermore, the prevalence rates of abnormal WC increased annually in the 30–39 and 40–49 age groups (all \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), and the prevalence rate of abnormal WHtR increased annually in the 30–39 age group (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (Fig.\u0026nbsp;5).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003cp\u003e2.4 Trend Prediction of Obesity Prevalence among Professional Women in a Shanghai Hospital\u003c/p\u003e\n \u003cp\u003eThe obesity detection rate among professional women in Shanghai is predicted to increase from 2025 to 2035.The estimated AAPC was 2.69% (95% CI: 2.12 to 3.18; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Based on this trend, it is projected to reach 9.14% (95% CI: 7.12 to 11.16) by 2035(Fig.\u0026nbsp;6).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHigh BMI has been defined by the World Health Organization as \"one of the most crucial controllable risk factors for diseases in the 21st century.\" The latest data from the Global Burden of Disease Study (GBD 2021) revealed that a high BMI resulted in a loss of 62\u0026nbsp;million to 90.7\u0026nbsp;million disability-adjusted life years (DALYs) globally. Its health hazards are primarily manifested as an increased burden of ischemic heart disease, type 2 diabetes, and hypertensive heart disease. These diseases account for a dominant proportion of the overall disease burden attributable to high BMI, and with the ongoing rise in both the aging population and obesity rates, their impact is expected to intensify further [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn China, along with economic transformation and the Westernization of dietary patterns, the average BMI of adult men and women has shown a steady upward trend. The male BMI increased from 21.06 in 1982 to 24.25 in 2015, while the women\u0026rsquo;s BMI rose from 21.32 in 1982 to 23.89 in 2015. Despite the fact that the growth rate of BMI in women is lower than that in men [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e13\u003c/span\u003e], women face a higher risk of central obesity due to physiological factors, social roles, and occupational stress [14]. Compared with men, a high BMI in women is more closely associated with diseases such as breast cancer (especially postmenopausal breast cancer), endometrial cancer, polycystic ovary syndrome, gestational diabetes mellitus, and depressive disorders [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR5\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. For professional women, the imbalance between excessive energy intake and insufficient physical activity is particularly prominent due to prolonged sitting, psychological stress, and dual \"work-family\" responsibilities.\u003c/p\u003e\u003cp\u003eBased on a large-scale physical examination cohort of 248,000 individuals over a 15-year span, this study systematically delineated, for the first time, the dynamic trajectories of overweight, obesity, and central obesity among professional women in Shanghai. It also extended projections to 2035 using the BAPC model, providing verifiable baselines and evaluation metrics for the \"Weight Management Year\" action plan. Currently, there is a lack of nationwide obesity monitoring data for professional female workers in China. This study indicates an obesity prevalence rate of 6.75% in 2024, which, although lower than that in American and European countries [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e19\u003c/span\u003e], is higher than that in Japan (4.3%) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This suggests that China is experiencing a rapid increase in obesity. A high BMI contributes to 6.50% of the total disability-adjusted life years (DALYs) [8] and is closely linked to strategies for preventing and controlling hypertension, diabetes, and cancer. Therefore, this study not only provides evidence-based guidance for weight management among professional women but also aligns with the comprehensive chronic disease prevention and control strategy outlined in China's \"Healthy China 2030\" plan.\u003c/p\u003e\u003cp\u003eThe results of this study indicate that from 2010 to 2024, the annual average increase in the prevalence of overweight among professional women in Shanghai was 1.19%, and the annual average increase in the prevalence of obesity was 4.63%. According to the BAPC model projections, the obesity rate will reach 9.14% by 2035, showing a continuous upward trend. The prevalence of central obesity peaked in 2013 and then fluctuated and stabilized, suggesting that the growth rate of generalized obesity was faster than that of central obesity. In contrast, the growth rate of obesity prevalence among women in high-income countries in Europe and the United States has slowed [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Although the obesity rate among professional women in Shanghai remains low, its growth rate is significantly faster than the average in high-income countries, and the window for prevention and control is rapidly narrowing. Therefore, there is an urgent need to develop more targeted prevention and control strategies to curb the further increase in the prevalence of obesity.\u003c/p\u003e\u003cp\u003eCurrently, global weight management is undergoing a transformation from individualized interventions to systemic governance and from medical settings to the workplace environment. The reasons for the rising prevalence of high BMI in Shanghai can be summarized as follows: (1)Westernization of dietary patterns and intake of takeaway food, sugary drinks, and ultra-processed foods; (2) long average weekly working hours, prolonged sedentary time, and insufficient physical activity; (3)accumulated mental stress leading to elevated cortisol levels, which promotes fat deposition; and (4) shorter intervals between two pregnancies after the adjustment of fertility policies, resulting in the weight retention effect.\u003c/p\u003e\u003cp\u003eDrawing on international experience, Shanghai can start with \"workplace microenvironment optimization\" and implement the following measures: First, the government should incorporate the annual increase in BMI among female employees into the assessment criteria for civilized units and provide rewards to those who meet the standards. Second, \u0026ldquo;10-minute workplace exercises,\u0026rdquo; stair culture, and a star rating system for healthy canteens should be promoted. Third, AI and wearable devices should be utilized to establish a closed-loop management system involving \"individuals-enterprises-medical insurance,\" and rewards should be provided to employees who effectively control their BMI by adding credits to their medical insurance accounts. Fourth, psychological support should be strengthened and health promotion programs should be launched. Studies have confirmed that such programs can effectively reduce the prevalence of overweight and obesity among employees [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and improve work efficiency and quality of life.\u003c/p\u003e\u003cp\u003eThis study did not directly incorporate gender difference analysis; however, comparisons can be made using data from Shanghai and global studies. The age-standardized obesity rate among women in Shanghai (9.26%) is still lower than that among men of the same age (10.40%) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In high-income countries in Europe and the United States, obesity rates have shown a trend of being \"higher in women than in men\" and have plateaued, such as in the United States (41.3% vs. 39.2%) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and the United Kingdom (26.9% vs. 26.2%) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This suggests that women in Shanghai are currently in a \"low-level potential acceleration\" stage, and factors such as postmenopausal fat redistribution and insufficient physical activity may significantly increase obesity rates within the next 10\u0026ndash;15 years, necessitating early intervention.\u003c/p\u003e\u003cp\u003eTargeted measures should focus on the \"female full life cycle\": strengthening school nutrition education during adolescence, incorporating weight management into premarital and pre-pregnancy healthcare during the childbearing period, and emphasizing resistance training and bone density protection after menopause. At the family level, the concept of \"shared health\" should be promoted, encouraging spouses and children to participate in dietary and exercise plans to sustain weight management. At the societal level, the media should promote diverse concepts of healthy body image.\u003c/p\u003e\u003cp\u003eAge-stratified analysis showed that the prevalence of overweight, obesity, and central obesity all increased with age, with the obesity rate in the 50\u0026ndash;59 age group (8.87%) being approximately 3.2 times that in the 20\u0026ndash;29 age group (2.74%). The reasons include: (1) a 2\u0026ndash;3% decrease in basal metabolic rate every decade, leading to reduced energy expenditure; (2) a decline in estrogen levels triggering fat redistribution; and (3) a decrease in work intensity in the later stages of one's career but the continuation of dietary patterns. The prevalence of abnormal WHtR in the 30\u0026ndash;39 age group increased by 2.1% annually, which may be related to the combination of a peak in childbirth, sedentary office work, and parenting stress in this age group.\u003c/p\u003e\u003cp\u003eFortunately, weight control in middle-aged and elderly individuals is not \"irreversible.\" Studies have shown that effective knowledge translation tools (KT tools) can help middle-aged women make weight management decisions [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e25\u003c/span\u003e], the development of assessment tools based on behavioral classification (such as OxFAB-MAW) can evaluate weight management behaviors [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e26\u003c/span\u003e], and weight loss treatment programs for elderly obese women can significantly reduce weight and improve health status. Shanghai can rely on platforms such as community health stations, senior sports and health centers [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and retired faculty associations to promote low-threshold exercises such as \"midday brisk walking and square dancing\" and combine them with family doctor contract services to assess BMI, blood pressure, and blood sugar every quarter for \"early prevention and early control.\"\u003c/p\u003e\u003cp\u003eThis study had two limitations. First, the data were sourced from the physical examination center of a single tertiary hospital in Shanghai, which may have introduced selection bias (primarily consisting of government agencies, public institutions, and state-owned enterprises). This study standardized the data according to the age structure of the 2020 population census and supplemented it with data from five private technology companies in 2024 to improve representativeness. Second, the physical examination data lack key behavioral information, such as diet, physical activity, and psychology. A \"professional women's health follow-up cohort\" has been launched in collaboration with the Shanghai Municipal Center for Disease Control and Prevention, using mobile apps and wearable devices to collect lifestyle data in real time, with the first round of follow-up expected to be completed in 2025.\u003c/p\u003e\u003cp\u003eBased on 248,147 person-times of continuous physical examination data over 15 years, this study systematically described the dynamic changes in overweight, obesity, and central obesity among professional women in Shanghai using JoinPoint and BAPC models and projected the results until 2035. The research results provide key evidence-based support for the government, enterprises, and medical insurance departments to collaboratively implement precise weight management and curb the increase in chronic diseases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor agreement\u003c/p\u003e\n\u003cp\u003eThe corresponding author hereby declares that all authors have seen and approved the final version of the manuscript submitted. This article is the authors\u0026rsquo; original work, has not been previously published, and is not under consideration for publication elsewhere.\u003c/p\u003e\n\u003cp\u003eCRediT authorship contribution statement\u003c/p\u003e\n\u003cp\u003eMei Liu: Writing\u0026mdash;review \u0026amp; editing, Supervision, Methodology, Investigation, Data curation.\u003c/p\u003e\n\u003cp\u003eYanfeng Shi: Writing\u0026mdash;review \u0026amp; editing, Investigation, Data curation.\u003c/p\u003e\n\u003cp\u003eChunyun Shao: Writing\u0026mdash;review \u0026amp; editing, Investigation, Data curation.\u003c/p\u003e\n\u003cp\u003eWenchang Jia: Writing\u0026mdash;review \u0026amp; editing, Writing\u0026mdash;original draft, Visualization, Validation, Supervision, Software, Resources, Project administration.\u003c/p\u003e\n\u003cp\u003eXiaopan Li: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Funding acquisition, Writing\u0026mdash;original draft, Writing\u0026mdash;review \u0026amp; editing, Visualization.\u003c/p\u003e\n\u003cp\u003eJianguang Tian: Writing\u0026mdash;review \u0026amp; editing, Supervision.\u003c/p\u003e\n\u003cp\u003eXiaohui Zhou: Conceptualization, Methodology, Investigation, Data curation, Funding acquisition, Writing\u0026mdash;original draft, Writing\u0026mdash;review \u0026amp; editing, Visualization, Validation, Supervision, Software, Project administration.\u003c/p\u003e\n\u003cp\u003eConsent to participate and permission to publish the data\u003c/p\u003e\n\u003cp\u003eWe affirm that all participants were informed about the\u0026nbsp;possible risks and benefits related to participation in the study and provided informed consent for participation in the study and publication of the data before participating in the study.\u003c/p\u003e\n\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003eThis study involving humans was approved by the Ethics Committee of Shanghai Health and Medical Center (Ethics No.: 2022 Lunyan Pihui No. 16) and was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDeclaration of Competing Interest\u003c/p\u003e\n\u003cp\u003eOn behalf of all authors, the corresponding author states that there are no conflicts of interest.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe thank \u0026nbsp;Chenyu\u0026nbsp;Wu and\u0026nbsp; Kefang Wang for their\u0026nbsp;practical assistance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding Declaration\u003c/p\u003e\n\u003cp\u003eThe study was supported by the Key Disciplines of the Three-Year Action Plan for Strengthening the Construction of the Public Health System in Shanghai (2023-2025 GWVI-11.1-28). The supporters had no role in the study design, data collection, data analysis, data interpretation, or writing of the article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Obesity Federation. World Obesity Atlas 2025 [EB/0L](2025-03-04)2025-03-13.https://data.worldobesity.org/publications/? cat=23. \u003c/li\u003e\n\u003cli\u003eZhao ZP, Zhang M, Li C, Yu MT, Zhang X, Wang LM, et al. Growth rate of adult obesity prevalence in china and target population for prevention and control from 2013 to 2018 [J]. Zhonghua Xin Xue Guan Bing Za Zhi, 2024, 52(1): 34-41. DOI: 10.3760/cma.j.cn112148-20231023-00369.\u003c/li\u003e\n\u003cli\u003eHao LX, Zhang B, Wang HJ, Wang LS, Jiang HR,Wang SSZ, et al. Trends and epidemic characteristics of overweight and obesity among adults aged 18-35 in 15 provinces(autonomous regions/municipalities) of china from 1989 to 2018 [J]. Journal of Environmental and Occupational Medicine, 2022, 39(5): 471-477. DOI: 10.11836/JEOM21386.\u003c/li\u003e\n\u003cli\u003eHarborg S, Kj\u0026aelig;rgaard KA, Thomsen RW, Borgquist S, Cronin-Fenton D, Hjorth CF. New Horizons: Epidemiology of Obesity, Diabetes Mellitus, and Cancer Prognosis. J Clin Endocrinol Metab. 2024 Mar 15;109(4):924-935. doi: 10.1210/clinem/dgad450\u003c/li\u003e\n\u003cli\u003eDing J, Chen X, Shi Z, Bai K, Shi S. Association of metabolically healthy obesity and risk of cardiovascular disease among adults in china: a retrospective cohort study[J]. Diabetes Metab Syndr Obes. 2023 Jan 19;16:151-159. DOI: 10.2147/DMSO.S397243. \u003c/li\u003e\n\u003cli\u003eJiang WC, Zhang M. Research advances of type 1 diabetes mellitus with overweight and obesity [J]. Chinese Journal of Diabetes Mellitus, 2025, 17(05): 638-642. DOI: 10.3760/cma.j.cn115791-20240908-00541.\u003c/li\u003e\n\u003cli\u003eZeng ZQ, Ma Y, Yang C, Yu CQ, Sun DJY, Pei P, et al. Associations of body mass index and waist circumference with risk of chronic kidney disease in adults in China [J]. Zhonghua Liu Xing Bing Xue Za Zhi., 2024, 45(7): 903-913. DOI: 10.3760/cma.j.cn112338-20240227-00085.\u003c/li\u003e\n\u003cli\u003eYan DH, Gan TZ, Yuan KJ, Zhou GQ. Analysis and prediction of disease burden due to high bmi in china from 1990 to 2019[J]. Chinese General Practice, 2025, 28(10): 1200-1206. DOI: 10.12114/j.issn.1007-9572.2023.0903.\u003c/li\u003e\n\u003cli\u003eNational Health and Family Planning Commission of the People\u0026apos;s Republic of China. Determination of Adult Body Weight: WS/T 428-2013[S]. Beijing: China Standards Press, 2013.\u003c/li\u003e\n\u003cli\u003eExpert Consensus on Obesity Prevention and Control among Chinese Residents[J]. Chinese Journal of Preventive Medicine, 2022, 23(05): 321-339. DOI: 10.16506/j.1009-6639.2022.05.001.\u003c/li\u003e\n\u003cli\u003eNational Institute for Health and Care Excellence (NICE). Obesity: identification, assessment and management. [EB/OL].(2023-07-26) [2024-05-10]. https://www.nice.org.uk/guidance/cg189. \u003c/li\u003e\n\u003cli\u003eGBD 2021 Risk Factors Collaborators. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021 [J]. Lancet. 2024,403(10440):2162-2203.DOI: 10.1016/S0140-6736(24)00933-4. Erratum in: Lancet. 2024,404(10449):244. DOI: 10.1016/S0140-6736(24)01458-2.\u003c/li\u003e\n\u003cli\u003eFang HY, Wei XQ, Ju LH, Du WW, Yu DM, Zhang JG, et al. Current status and changing trends of Body Mass Index among Chinese adult residents from 1982 to 2015[J]. Journal of Hygiene Research,2025,54(01):18-22.DOI:10.19813/j.cnki.weishengyanjiu.2025.01.005.\u003c/li\u003e\n\u003cli\u003eRatuayudewi S , Yunita J .Waist circumference for central obesity detection from the pre-elderly stage to the elderly stage in indonesia: a longitudinal study[J].Pakistan Journal of Nutrition, 2019,18(4):379-386.DOI:10.3923/PJN.2019.379.386.\u003c/li\u003e\n\u003cli\u003ePark JW, Han K, Shin DW, Yeo Y, Chang JW, Yoo JE, et al. Obesity and breast cancer risk for pre- and postmenopausal women among over 6 million Korean women[J]. Breast Cancer Res Treat. 2021,185(2):495-506.DOI: 10.1007/s10549-020-05952-4.\u003c/li\u003e\n\u003cli\u003eMahabady M, Zolfaghari H, Samimi M, Gilasi H, Sharifi N, Aminianfar A. The association between dietary obesity-prevention score (DOS) and polycystic ovary syndrome: a case-control study[J]. Sci Rep. 2024,14(1):28618. DOI: 10.1038/s41598-024-80238-z.\u003c/li\u003e\n\u003cli\u003eCui H, Xiong Y, Wang C, Ye J, Zhao W. The relationship between BMI and depression: a cross-sectional study[J]. Front Psychiatry. 2024,15:1410782. DOI: 10.3389/fpsyt.2024.1410782. \u003c/li\u003e\n\u003cli\u003eEmmerich SD, Fryar CD, Stierman B, Ogden CL. Obesity and severe obesity prevalence in adults: United States, August 2021\u0026ndash;August 2023[J]. NCHS Data Brief. 2024,(508):10.15620/cdc/159281. DOI: 10.15620/cdc/159281. \u003c/li\u003e\n\u003cli\u003eOffice for Health Improvement and Disparities. (2025, May). Obesity profile: short statistical commentary, May 2025. UK Government. https://www.gov.uk/government/statistics/obesity-profile-may-2025-update/obesity-profile-short-statistical-commentary-may-2025\u003c/li\u003e\n\u003cli\u003eGlobal Nutrition Report. (2022). Japan nutrition profile. https://globalnutritionreport.org/resources/nutrition-profiles/asia/eastern-asia/japan/\u003c/li\u003e\n\u003cli\u003eGBD 2021 Adult BMI Collaborators. Global, regional, and national prevalence of adult overweight and obesity, 1990-2021, with forecasts to 2050: a forecasting study for the Global Burden of Disease Study 2021[J]. Lancet. 2025,405(10481):813-838. DOI: 10.1016/S0140-6736(25)00355-1.\u003c/li\u003e\n\u003cli\u003eReinoso-Barbero L, Mu\u0026ntilde;oz-Due\u0026ntilde;as P, Cano I, Araujo S, G\u0026oacute;mez-Paredes L, Mu\u0026ntilde;oz-Guti\u0026eacute;rrez J, et al. Effectiveness of a workplace health promotion program in reducing obesity: A retrospective study[J]. J Occup Environ Med. 2025,67(8):e549-e554. DOI: 10.1097/JOM.0000000000003408.\u003c/li\u003e\n\u003cli\u003eJim\u0026eacute;nez-M\u0026eacute;rida MR, Vaquero-Abell\u0026aacute;n M, Alcaide-Leyva JM, Cant\u0026oacute;n-Habas V, Raya-Cano E, Romero-Salda\u0026ntilde;a M. Effectiveness of multicomponent interventions and physical activity in the workplace to reduce obesity: a systematic review and meta-analysis[J]. Healthcare (Basel). 2023,11(8):1160. DOI: 10.3390/healthcare11081160. \u003c/li\u003e\n\u003cli\u003eGuo FX,Yang QP,Wu F, Qian XL, Pu ZM, Zhang XH, et al. Overweight/obesity and diet as impact factors among residents aged 18 and over in Shanghai[J].Shanghai Journal of Prevenive Medicine,2019,31(02):111-117.DOI:10.19428/j.cnki.sjpm.2019.19155.\u003c/li\u003e\n\u003cli\u003eStacey D, Jull J, Beach S, Dumas A, Strychar I, Adamo K, et al. Middle-aged women\u0026apos;s decisions about body weight management: needs assessment and testing of a knowledge translation tool. Menopause. 2015,22(4):414-22. DOI: 10.1097/GME.0000000000000326.\u003c/li\u003e\n\u003cli\u003eLeit\u0026atilde;o M, Hartmann-Boyce J, P\u0026eacute;rez-L\u0026oacute;pez FR, Mar\u0026ocirc;co J, Pimenta F. Weight management strategies in Middle-Aged Women (MAW): Development and validation of a questionnaire based on the Oxford Food and Activity Behaviors Taxonomy (OxFAB-MAW) in a Portuguese sample[J]. Front Psychol. 2023,13:1069775. DOI: 10.3389/fpsyg.2022.1069775. \u003c/li\u003e\n\u003cli\u003eFENG L. Shanghai launches \u0026ldquo;Seniors\u0026rsquo; Fitness Homes\u0026rdquo; \u0026ndash; elders get their own gyms right at the doorstep [EB/OL].(2024-03-21)[2025-08-08]. https://www.sport.gov.cn/n20001280/n20001265/n20067708/c27581742/content.html\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Overweight, Obesity, Central obesity, Trend analysis, Trend forecast","lastPublishedDoi":"10.21203/rs.3.rs-7508365/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7508365/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground: \u003c/strong\u003e\u003c/em\u003eTo analyze the prevalence of overweight, obesity, and central obesity among 248,147 professional women in Shanghai from 2010 to 2024 and predict their trends up to 2035, providing a data support for the local implementation of the Weight Management Annual Plan.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e\u003c/em\u003eWe collated physical examination data from 248,147 female participants aged 20-59 years who underwent examinations at the Shanghai Health and Medical Center between 2010 and 2024. Overweight and obesity were determined based on body mass index (BMI), while central obesity was diagnosed using waist circumference (WC), waist-hip ratio (WHR), and waist-height ratio (WHtR) as reference values. The JoinPoint regression model was employed to calculate the average annual percent change (AAPC) and its 95% confidence interval (CI). The Bayesian age-period-cohort (BAPC) model was used to predict the development trends of these indicators from 2025 to 2035.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eAmong the 248,147 female examinees, the prevalence of overweight was 21.26% (56,010 cases), obesity was 5.14% (13,248 cases), and central obesity was 25.23% (67,363 cases). From 2010 to 2024, the prevalence of overweight (AAPC=1.19%; 95%CI: 0.71 to 1.68; \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) and obesity (AAPC=4.63%; 95%CI: 4.05 to 5.36; \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) increased annually; the prevalence of central obesity peaked at 29.94% in 2013 and exhibited a fluctuating trend (AAPC=0.25; 95%CI: -0.83 to 1.29; \u003cem\u003eP\u003c/em\u003e=0.605). Comparative analysis among age subgroups revealed a highly significant upward trend in the rates of overweight, obesity, and central obesity with increasing age (all\u003cem\u003e P\u003c/em\u003e\u0026lt;0.05). The forecast results indicated that the prevalence of obesity would increase by 2.69% annually, reaching 9.14% by 2035 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001); the prevalence of central obesity would increase by 0.52% annually, reaching 25.02% by 2035 (\u003cem\u003eP\u003c/em\u003e=0.040).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eProfessional women should strengthen weight management, with employers facilitating health education, providing preferential medical insurance policies, improving the monitoring system, and implementing targeted interventions to control the obesity trend.\u003c/p\u003e","manuscriptTitle":"Analysis of Obesity Prevalence and Trend Prediction among Professional Women in a Hospital from 2010 to 2024: A Weight Management Perspective","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 11:13:57","doi":"10.21203/rs.3.rs-7508365/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-08T08:33:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-05T11:02:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-05T11:01:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-09-01T12:09:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"869ed730-8697-4743-b8e2-4771d3e4c58b","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:04:16+00:00","versionOfRecord":{"articleIdentity":"rs-7508365","link":"https://doi.org/10.1186/s12889-025-25276-6","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-11-28 15:58:22","publishedOnDateReadable":"November 28th, 2025"},"versionCreatedAt":"2025-09-09 11:13:57","video":"","vorDoi":"10.1186/s12889-025-25276-6","vorDoiUrl":"https://doi.org/10.1186/s12889-025-25276-6","workflowStages":[]},"version":"v1","identity":"rs-7508365","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7508365","identity":"rs-7508365","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}