{"paper_id":"2973a4e8-60cf-4e4f-9c27-6ff5baf224c5","body_text":"Profiles of exercise adherence in late pregnancy: A latent profile analysis among Chinese women | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Profiles of exercise adherence in late pregnancy: A latent profile analysis among Chinese women He Ma, Huina Chen, Lifen Ouyang, Shuru Xu, Keqing Li, Zhaomei Xie, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7562252/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The benefit of physical activity and exercise interventions for pregnant women crucially depends on adherence. The study aimed to identify latent categories of exercise adherence among pregnant women in the third trimester and explored the influence of these distinct profiles. Methods Convenience sampling was used to recruit participants from three maternal and child health hospitals in China, between November 2024 and June 2025. Latent profile analysis (LPA) was used to identify potential classes of exercise adherence among pregnant women in the third trimester; multinomial logistic regression was used to explore the factors associated with these profiles. Results A total of 531 participants were included in this study and were classified as high (n = 59), moderate (n = 239), and low adherence (n = 233) to exercise. Compared to the low-adherence group, the influencing factors for the high-adherence group were weekly exercise habit, pelvic floor muscle training (PFMT), exercise self-efficacy, social support, enjoyment of exercise, other commitments, lack of time, and fatigue. Compared to the mid-adherence group, the influencing factors for the high-level group were education level, weekly exercise habit, exercise self-efficacy, social support, lack of time, and fatigue. Conclusion Exercise adherence among pregnant women appeared heterogeneous and presented in three distinct categories. Health workers should develop targeted interventions based on the socio-psychological characteristics of pregnant women in the third trimester to improve their adherence to exercise. pregnant women exercise adherence exercise self-efficacy social support latent profile analysis Figures Figure 1 Background Pregnancy is a physiologically and psychologically unique period that is crucial for the health of pregnant women and their offspring. Regular physical activity and exercise during pregnancy are widely recognized for enhancing maternal well-being and optimizing offspring development [ 1 ]. Although the World Health Organization (WHO) recommends that all women with healthy pregnancies engage in at least 150 minutes of moderate-intensity aerobic exercise per week [ 2 ], adherence remains a primary determinant of the effectiveness of exercise during pregnancy. Evidence shows that exercise adherence to recommended guidelines is often low, thereby limiting the benefits that could be gained [ 3 ]. Previous studies have indicated that physical inactivity during pregnancy increased the risk of excessive gestational weight gain, gestational diabetes mellitus, pre-eclampsia, gestational hypertension, macrosomia, instrumental delivery, urinary incontinence, and depressive disorders [ 4 , 5 ]. Sarno et al. [ 6 ] recruited women with a singleton, uneventful pregnancy during their third trimester; 37% of them undertook sports/exercise activities. A systematic review of 11,323 Chinese women during pregnancy reported that 21.0% of them met the recommended level of exercise [ 7 ]. A cross-sectional study involving 1,636 Chinese pregnant women found that the prevalence of physical inactivity was 47.5%, and that walking was the most common form of physical activity [ 8 ]. The benefits of physical activity and exercise for both mother and their child are dependent on long-term adherence. Walasik et al. [ 9 ] examined physical activity patterns among 9000 pregnant women in Poland. During the first and second trimesters, 90% of participants exercised, whereas in the last pregnancy, almost 13% of respondents discontinued physical activity. Kókai et al. [ 10 ] investigated the effectiveness of two 8-week app-based moderate to vigorous physical activity interventions for pregnant women. This study began in October 2021 with 663 participants. At week 21, 254 women discontinued this intervention. Shang et al. [ 11 ] reported that less than half of the women undertook 150 minutes of exercise every week before pregnancy. 40.5% of participants kept regular exercise according to the guidelines during pregnancy. Adherence, defined by the WHO, is the extent to which a person’s behavior complies with agreed recommendations from health care professionals [ 12 ]. Exercise adherence is a complex and dynamic phenomenon during pregnancy, influenced by demographic, psychological, and environmental factors [ 11 ]. Previous studies employed a variable-centered approach to categorize pregnant women based on whether their physical activity and exercise met the standards recommended for exercise [ 6 ]. Researchers classified participants into “exercisers” and “non-exercisers” based on whether they performed recommended physical activity to assess adherence to physical activity and exercise [ 3 , 6 , 10 , 13 ]. Apparently, these analysis methods appeared inadequate for individualized intervention. Knowledge regarding reasons for adherence to exercise during pregnancy remains limited. Exercise adherence, along with reasons for both adherence and non-adherence, was assessed by adopting the Exercise Adherence Rating Scale (EARS) [ 14 ], a reliable and valid self-reported outcome measure consisting of 6 items assessing adherence to exercise and 10 items evaluating reasons for exercise adherence [ 15 ]. EARS has been translated and used in several countries, including Denmark [ 17 ], Brazil [ 18 ], and Sweden [ 16 ]. In the current study, we evaluated adherence to physical activity among low-risk pregnant women by adapting a Chinese version of the EARS. A firm understanding of person-centered factors that influence physical activity during pregnancy is crucial for developing effective individualized exercise programs. We further applied latent LPA, a method particularly suited for identifying individual latent characteristics from a person-centered perspective. The results could facilitate the development of tailored exercise interventions for pregnant women. To our knowledge, no study has used LPA to examine patterns of exercise adherence among pregnant women. The present study, therefore, applied LPA to delineate adherence profiles in pregnant women from three Guangdong cities—Shenzhen, Dongguan, and Shunde (Foshan)—and to identify related factors of these profiles. Methods Study design and participants An observational study was conducted from November 2024 to June 2025 at three maternal and child health hospitals in Shenzhen, Dongguan, and Shunde, Guangdong Province, China. We used convenience sampling to recruit pregnant women in their third trimester of pregnancy. The inclusion criteria: aged ≥ 18 years and voluntarily participating in the study. Exclusion criteria included: aged < 18 years; significant chronic conditions that could affect Exercise during pregnancy (e.g., pre-eclampsia, cervical insufficiency, unexplained persistent vaginal bleeding); mental disorders; or unwillingness to participate. Six trained researchers collected the data in person. After confirming eligibility, the researchers explained the study’s purpose, risks, and benefits to the participants. Those who met the inclusion criteria completed the questionnaire in real-time, thereby minimizing the likelihood of invalid responses. Sampling method and sample size According to the literature[ 17 ], a minimum sample size of 250 to 500 participants is required for LPA. Hence, this study employed the LPA method and adhered to established guidelines for sample size calculations. We conveniently recruited 531 participants from 558 eligible pregnant women. Measures A generic questionnaire was developed based on a review of relevant literature and the study’s objectives. This questionnaire collected information on various demographic factors, including age, pre-pregnancy body mass index (BMI), residence, education level, personal monthly income, and other relevant variables. Among these, pre-pregnancy BMI was calculated as body weight divided by the square of height. Using the Chinese classification, women with a BMI < 18.5 kg/m 2 are considered underweight, those with a BMI of 18.5 ~ 23.9 kg/m 2 as normal weight, those with a BMI of 24 ~ 27.9 kg/m 2 as overweight, and those with a BMI ≥ 28 kg/ m 2 as obese [ 18 ]. The obstetric parameters included history of gravidity and parity. Exercise adherence The exercise adherence was assessed using the exercise adherence rating scale (EARS) developed by Newman in 2017 [ 14 ]. This scale consists of three parts: the EARS-A scale consists of 6 qualitative questions to provide information about their adherence behaviour for individuals; the EARS-B scale consists of 6 items evaluating adherence to prescribed home exercise, with items 1, 3 and 5 are reverse scored; the EARS-C scale consists of 10 questions regarding the reasons for adherence or non-adherence, with items 3, 7, 8 and 10 are reverse scored [ 14 , 15 ]. Translated and validated across several countries, it has shown good reliability and validity (Cronbach’s α = 0.77 to 0.94) [ 16 , 19 , 20 ]. The Chinese version of the EARS was modified by Wu Yuxuan [ 15 ]. The total score range of the EARS-B scale is between 0 and 16, with higher scores indicating better adherence. This study utilized the EARS-B scale to evaluate exercise adherence in pregnant women and the EARS-C scale to identify its influencing factors. In this study, Cronbach’s alpha of the scale was 0.817. Pregnancy exercise social support The present study used the Physical Activity Social Support Scale (PASSS) to measure social support for physical activity [ 21 ]. The PASSS has 24 items. Items are scored on a 5-point Likert scale, with one indicating “strongly disagree” and five indicating “strongly agree.” The total scores range from 24 to 120, with higher scores indicating greater social support for physical activity. The reported Cronbach’s α was 0.95 [ 21 ]. The Cronbach’s α of the PASSS was 0.967 in the present study. Pregnancy exercise self-efficacy Prenatal exercise self-efficacy was measured using the Pregnancy Exercise Self-Efficacy Scale (P-ESES). Kroll et al. devised an Exercise Self-Efficacy Scale for spinal cord injury in 2007 [ 22 ]. Bland et al. adapted and validated it among pregnant women in 2013, with a Cronbach’s α of 0.838 [ 23 ]. The Chinese version of the P-SESE was modified by Yang Hongmei et al., Cronbach’s α = 0.804. The P-ESES includes 10 items, which are divided into three domains: overcoming exercise barriers, emotional barriers, and support barriers. Items are scored on a 5-point Likert scale, with one indicating “strongly disagree” and five indicating “strongly agree.” The total P-ESES score ranges from 10 to 50. A total P-ESES score < 20 indicates a low level of exercise self-efficacy, a score 21 to 40 suggests a moderate level, and a score >40 is regarded as indicative of a high level of exercise self-efficacy. In this study, Cronbach’s alpha of the scale was 0.963. Data analysis Descriptive analysis SPSS software version 27.0 was used for statistical analysis. Necessary normality tests were performed with kurtosis and skewness − 3.29 to 3.29 [ 24 ]. In the study, descriptive statistics were made with the SPSS 27.0 package program. Demographic characteristics and scale scores now explicitly include calculated values of N (%), mean (±), and standard deviation (SD) to improve clarity and interpretability. Latent profile analysis Mplus software, version 8.3, was used to analyze the latent profiles of the pregnancy exercise self-efficacy. The best model was selected based on model fit indices and clinical significance. The fit index included the Akaike information criterion (AIC), Bayesian information criterion (BIC), adjusted BIC (aBIC), entropy, Lo-Mendell-Rubin likelihood ratio test (LMR), and Bootstrap-based likelihood ratio test (BLRT). Lower AIC, BIC, and aBIC values indicate a better model fit. Entropy, ranging from 0 to 1, reflects classification accuracy, with values closer to 1 indicating higher accuracy. The LMR and BLRT were used to compare models with k and (k-1) classes; p < 0.05 suggests that the k-class model fits the data significantly better than the (k-1)-class model [ 25 ]. Ethical considerations This study was conducted in accordance with the guidelines of the Declaration of Helsinki. It was approved by the Ethics Committee of the Dongguan Maternal and Child Health Hospital (Approval No. 2024 − 155); Shunde Women and Children's Hospital of Guangdong Medical University (KY-2024-070); and Baoan Central Hospital of Shenzhen (BYL20240628). Before the study, both oral and written consents were obtained from all eligible participants, ensuring that participation or non-participation would not affect their work performance or future employment opportunities. Additionally, all collected information would be anonymous and de-identified. Furthermore, participants were informed that they could withdraw from the study at any time. Results Demographic information A total of 558 questionnaires were distributed in this study. Among them, 27 questionnaires had incomplete responses and were deemed invalid; therefore, they were eliminated. Complete responses were considered valid, resulting in a total of 531 valid questionnaires. The effective response rate of the questionnaire was 95.16%. All participants were in the third trimester. Most resided in urban areas and had a mean age of 31.81 ± 3.99 years. Only 23.4% achieved 150 minutes or more of exercise per week. The participants' average total PASSS score was 34.47 ± 8.10, and that of P-ESES was also 34.47 ± 8.10. Other demographic information was detailed in Table 1. Table 2 presents the average scores for each item of the EARS-C scale (reasons for adherence / non-adherence). Statistical results indicate that most items have high F -values and p < 0.05, demonstrating statistically significant differences among exercise adherence levels. Results of latent profile analysis The study conducted a profile analysis based on the EARS-B scale scores. It used AIC, BIC, aBIC, LMR ( P -value), and BLRT ( P -value) as evaluation indices to select the best model from 1 to 4 potential profile models established in sequence. The results of the model fit metrics for each profile are detailed in Table 3. The number of model categories increased from 1 to 4, and the AIC, BIC, and aBIC continued to decrease, with entropy being the highest among the four profile models. The 4-profile model LMR was excluded（ P > 0.05）. Therefore, the model with three profiles was finally chosen as the optimal potential profile model for this study, as shown in Table 3. Naming of latent profile Fig. 1 presents the mean scores of each item for the three exercise adherence profiles among pregnant women. The categories were named: “low-adherence” group, “moderate-adherence” group, and “high-adherence” group based on the characteristics of the mean scores across different categories. The “moderate-adherence” profile had the highest percentage, at 45.0%, followed by the “low-adherence” profile at 43.9%, and the “high-adherence” profile at 11.1%. Inter-profile characteristic differences The chi-square test and the one-way analysis of variance were used to compare differences in the presence of influencing factors among pregnant women in different potential exercise adherence categories. The results showed that gravidity, parity, education level, Exercise habit, PFMT, exercise self-efficacy, and social support were statistically significant ( P < 0.05). The rest of the categorical differences were not statistically significant ( P > 0.05), as seen in Table 4. Multinomial logistic regression of exercise adherence profiles Demographic information When the low-adherence profile was the reference group, relative to the moderate-adherence profile, the weekly exercise habit < 30 min (OR = 0.218, p < 0.001) for the moderate-adherence profile was significantly harmful; the scores of PASSS (OR = 1.060, p < 0.001) and P-ESES (OR = 1.189, p < 0.001) for the moderate-adherence profile were significantly positive. The results presented in Table 5 suggest that, first, women’s weekly exercise habit < 30 minutes, the less likely they are to be categorized into the moderate-adherence profile. Second, the higher scores of PASSS and P-ESES were more likely they were to be classified as moderate-adherence. Relative to the high-adherence profile: the exercise habit weekly < 30 min (OR = 0.021, p < 0.001) and <150 min (OR = 0.174, p < 0.001), and never PFMT (OR = 0.319, p < 0.05) for the high-adherence profile was significantly negative; the scores of PASSS (OR = 1.091, p < 0.001) and P-ESES (OR = 1.347, p < 0.001) for high-adherence were significantly positive. Suggests that, first, the weekly exercise habit < 30 min and < 150 min, and women who have never engaged in PFMT, are less likely they are to be categorized into the high-adherence profile. Second, the higher scores of PASSS and P-ESES were more likely to be classified as a high adherence profile. When the moderate-adherence profile was the reference group, relative to the high-adherence profile: the college education level (OR = 0.299, p < 0.05), weekly exercise habit < 30 min (OR = 0.097, p < 0.001) and <150min (OR = 0.259, p < 0.001) for high-adherence profile were significantly negative; PASSS (OR = 1.029, p < 0.05) and P-ESES (OR = 1.133, p < 0.001) scores for high-adherence profile were significantly positive. Suggests that, first, college education level and weekly exercise habit (< 30min and < 150min) in pregnant women are less likely to be classified as a high-adherence profile. Second, the higher the PASSS and P-ESES scores, the more likely pregnant women are to be classified as a high-adherence profile. Reasons for adherence / non-adherence When the low-adherence profile was the reference group, relative to the moderate-adherence profile: item 1: “I adjust the way I do my exercises to suit myself” (OR = 0.689, p < 0.05), for moderate-adherence were significantly negative; item 2: “Other commitments prevent me from doing my exercises” (OR = 1.520, p < 0.05), item 3: “I feel confident about doing my exercises” (OR = 3.280, p < 0.001), item 7: “I do my exercises because I enjoy them” (OR = 1.981, p < 0.001), item 8: “My family and friends encourage me to do my exercises” (OR = 1.513, p < 0.05), and item 10: “I do my exercises to improve my health” (OR = 1.412, p < 0.05), for moderate-adherence was significantly positive; This suggests that, first, the higher scores of item 3, item 7, item 8 and item 10 more likely they were to be categorized as moderate-adherence profile; second, the lower scores of item 1 of scores more likely they was to be categorized as moderate-adherence profile. The results of the study are presented in Table 6. Relative to the high-adherence profile: item 2: “Other commitments prevent me from doing my exercises” (OR = 2.005, p < 0.05), item 3: “I feel confident about doing my exercises” (OR = 9.089, p < 0.001), item 4: “I don’t have time to do my exercises” (OR = 4.505, p < 0.001), item 6: “I don’t do my exercises when I am tired” (OR = 2.692, p < 0.001), item 7: “I do my exercises because I enjoy them” (OR = 2.141, p < 0.05) and item 8: “My family and friends encourage me to do my exercises” (OR = 3.743, p < 0.05) were significantly positive; This suggests that, the higher scores of item2, 3, 4, 6, 7 and 8 more likely they were to be categorized the high-adherence profile. When the moderate-adherence profile was the reference group, relative to the high-adherence profile: item 3: “I feel confident about doing my exercises” (OR = 2.522, p < 0.05), item 4: “I don’t have time to do my exercises” (OR = 3.916, p < 0.001), item 6: “I don’t do my exercises when I am tired” (OR = 2.211, p < 0.001), item 8: “My family and friends encourage me to do my exercises” (OR = 2.474, p < 0.05) for high-adherence were significantly positive. Suggests that the higher scores of items 3, 4, 6, and 8 are more likely to be categorized as high-adherence. Discussion This study is the first to examine latent profiles of exercise adherence among women in their third trimester and to identify subtypes of exercise adherence using a person-centered approach. Exercise adherence among pregnant women was classified into three distinct profiles: low-adherence (43.9%), moderate-adherence (46%), and high-adherence (11.1%). The average scores for these groups were 9.32, 13.77, and 19.66, respectively. This result was consistent with the finding from Lu [ 26 ]. The mean score on the EARS-B scale among pregnant women was 12.47 ± 4.01, which fell below the established cut-off point [ 27 ]. The current study demonstrated that education level, weekly exercise habit, and PFMT were associated with exercise adherence among pregnant women. Consistent with previous studies, low education level was identified as a negative influence on meeting recommended physical activity and exercise during pregnancy [ 28 , 29 ]. Compared to the high-adherence group, pregnant women who had a lower education level were more likely to be classified into the mid-adherence group. Zhang et al. [ 30 ] found that pre-pregnancy exercise habit was a significant predictor of intent to initiate physical activity. A systematic review also demonstrated that regular physical activity was associated with higher self-efficacy. Pregnant women had a more positive attitude toward physical activity and exercise during pregnancy; ultimately, they adhered to exercise [ 31 ]. In this study, women who performed PFMT tended to have higher exercise adherence. Pelvic floor disorders, such as stress urinary incontinence (SUI) and pelvic floor pain during the last pregnancy, may impair women's motivation and ability to exercise. PFMT is most effective in treating SUI by strengthening the pelvic floor muscles. Physical activity programs that incorporate PFMT may be more motivating for women to engage in general aerobic exercise during pregnancy [ 32 , 33 ]. Additionally, information about the benefits of exercise and the dangers of inactivity during pregnancy should be incorporated into tailored exercise programs for pregnant women with less formal education. Multinomial logistic regression analysis indicated that exercise self-efficacy was a crucial factor influencing exercise adherence among pregnant women; higher scores on the P-ESES significantly increased the odds of membership in the moderate or high adherence profiles. Aligning with social cognitive theory [ 23 ], exercise self-efficacy refers to the confidence in one's ability to overcome more challenging tasks and achieve desired results[ 34 , 35 ]. Similarly, social support has been identified as a predictor of exercise adherence, as confirmed by a systematic review [ 36 ]. Although the present study also observed a comparatively modest effect of social support on exercise adherence, this suggests that the influence of social support on exercise adherence may be moderated by internal and external factors [ 36 ]. Indeed, partners, family members, friends, and health-care professionals have repeatedly been identified as key sources of social support for promoting physical activity during pregnancy [ 37 ]. Moreover, studies by Verloigne and Lu [ 38 , 39 ] indicated that physical activity self-efficacy mediates the relationship between social support and physical activity. Therefore, interventions designed to enhance exercise self-efficacy, leverage multiple sources of social support, and encourage regular physical activity may help pregnant women achieve better adherence outcomes. We used the EARS-C scale to investigate the reasons for adherence in those who exhibited good and poor adherence to exercise. These included items 3 and 8 as two major protective factors in the mid- and high-adherence groups (Table 6 ), indicating that exercise self-efficacy and social support play crucial roles in exercise adherence [ 23 ]. Other facilitating factors included enjoyment of exercise and self-adjustment. In line with self-determination theory, the enjoyment of exercise, as an inherent motivator, was positively associated with exercise behavior [ 40 ]. Empirical evidence further confirmed that intrinsic motivation supports both sustained exercise and psychological well-being[ 40 ]. Accordingly, prenatal exercise programs should emphasize enjoyment, skill mastery, and accomplishment, while enhancing maternal well-being and vitality. Mobile Health exercise programs with attractive course visuals and motivating music enhance the overall workout experience, making it more enjoyable [ 41 ]. Furthermore, healthcare professionals should focus on developing personalized and gamified mobile health (mHealth) exercise programs for pregnant women. Negative influences to exercise adherence included competing commitments, lack of time, and fatigue, which align with findings from Shang and Koleilat [ 11 , 42 ]. Prior research attributes these barriers to the dual responsibilities of caregiving and the workforce that these women faced [ 37 ]. Since the implementation of China’s “three-child policy”, the proportion of multiparous women has increased; over half of the participants who were multiparas in our study faced challenges of balancing competing commitments and physical exercise. For this reason, it is essential to consider time constraints when designing physical activity interventions for pregnant women. In response, we propose a community-based program that will facilitate peer interaction and the sharing of challenges and concerns [ 43 ]. The program will include weekly group classes tailored to varying fitness levels, as well as workshops on time management and strategies for balancing responsibilities [ 44 ]. This study has two strengths. First, it uses a multicenter design, which reduces the bias that single-center studies often have. Second, it takes a person-centered analytical approach to capture varied adherence patterns among individuals. This study has several limitations. First, all measures were self-reported questionnaires, excluding weight and height. Nevertheless, these scales have all shown good reliability and validity in this study, ensuring the accuracy of the results. Its cross-sectional design limits causal inference and does not allow for investigating how exercise adherence changes during the entire pregnancy period. Future studies should follow pregnant women across the three trimesters of pregnancy to facilitate a more comprehensive exploration of the multi-trajectory mechanisms underlying exercise adherence. Conclusion This study showed that exercise adherence among pregnant women appeared heterogeneous and presented in three distinct categories. Exercise self-efficacy, social support, weekly exercise habit, PFMT, enjoyment of exercise, other commitments, lack of time, and fatigue emerged as primary factors influencing sustained exercise. This evidence lays a crucial foundation for future tailored physical activity programs. Abbreviations WHO World Health Organization GDM Gestational Diabetes Mellitus EARS Exercise Adherence Rating Scale LPA Latent Profile Analysis BMI Body Mass Index PASSS Physical Activity Social Support Scale P-ESES Pregnancy Exercise Self-Efficacy Scale SD Standard Deviation AIC Akaike Information Criterion BIC ayesian Information Criterion aBIC adjusted Bayesian Information Criterion LMR Lo-Mendell-Rubin BLRT Bootstrapped Likelihood Ratio Test OR Odds Ratio RMB Renminbi PFMT Pelvic floor muscle training Declarations Author contributions ZCH and MH design and write articles. MH, CHN, XSR, OYLF, LKQ, and XZM completed the data collection. MH and CHN completed the data input and analysis. ZCH completed the revision and check of the article. All the authors read and approved the final version of the manuscript. Funding This work was supported by the Guangdong Province Graduate Education Innovation Program Project (2025JGXM_083). Data availability The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was conducted in accordance with the guidelines of the Declaration of Helsinki. It was approved by the Ethics Committee of the Dongguan Maternal and Child Health Hospital (Approval No. 2024-155); Shunde Women and Children's Hospital of Guangdong Medical University (KY-2024-070); and Baoan Central Hospital of Shenzhen (BYL20240628). Before the study, both oral and written consents were obtained from all eligible participants, ensuring that participation or non-participation would not affect their work performance or future employment opportunities. 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Lu J, Wang J, You Z, Wang Q, Sun G: A study on the influencing factors of exercise adherence in patients with chronic heart failure: from a configuration perspective . Frontiers in psychology 2025, 16 :1536349. de Lira MR, de Oliveira AS, França RA, Pereira AC, Godfrey EL, Chaves TC: The Brazilian Portuguese version of the Exercise Adherence Rating Scale (EARS-Br) showed acceptable reliability, validity and responsiveness in chronic low back pain . BMC musculoskeletal disorders 2020, 21 (1):294. Ceprnja D, Chipchase L, Liamputtong P, Gupta A: Physical activity and associated factors in Australian women during pregnancy: A cross-sectional study . Health promotion journal of Australia : official journal of Australian Association of Health Promotion Professionals 2024, 35 (4):1217-1223. Chen X, Xiang Z, Chen L, Sun K, Deng Y, Gao L: Physical activity among Chinese pregnant women in the first trimester: A cross-sectional study . International journal of nursing sciences 2025, 12 (3):261-267. Chen X, Xiang Z, Chen L, Sun K, Deng Y, Gao L: Predicting Physical Activity in Chinese Pregnant Women Using Multi-Theory Model: A Cross-Sectional Study. Int J Environ Res Public Health , 2022. 19 (20). Yang C, Wu Q, Lv Q, Hou X, Ye X, Yang Y: Efficacy of physical exercise on the physical ability, cardiac function and cardiopulmonary fitness of patients with atrial fibrillation: a systematic review and meta-analysis . Frontiers in cardiovascular medicine 2024, 11 :1352643. Zhang DF，Kari B, Roc M, Migue SP, Cristina SJ, Montse P: Influence of pelvic floor muscle training alone or as part of a general physical activity program during pregnancy on urinary incontinence, episiotomy and third- or fourth-degree perineal tear: Systematic review and meta-analysis of randomized clinical trials. Acta Obstet Gynecol Scand , 2024. 103 (6): p. 1015-1027. Stephanie JW, Peter L, Rhianon B, June DC, Siv M, Ashleigh K: Pelvic floor muscle training for preventing and treating urinary and faecal incontinence in antenatal and postnatal women. Cochrane Database Syst Rev , 2020. 5 (5): p. Cd007471. Xiang Z, Han R, Chen L, Gao L: Predictors of physical activity among Chinese pregnant women during the first trimester: A cross-sectional study . Journal of sports sciences 2023, 41 (20):1883-1891. Yang X, Han R, Song Y, Zhang J, Huang H, Zhang J: The Mediating Role of Physical Activity Self-Efficacy in Predicting Moderate-Intensity Physical Activity in Pregnant People at High Risk for Gestational Diabetes . Journal of midwifery & women's health 2024, 69 (3):403-413. Thompson EL, Vamos CA, Daley EM: Physical activity during pregnancy and the role of theory in promoting positive behavior change: A systematic review . Journal of sport and health science 2017, 6 (2):198-206. Shum KW, Ang MQ, Shorey S: Perceptions of physical activity during pregnancy among women: A descriptive qualitative study . Midwifery 2022, 107 :103264. Chen L, Han RR, Chen X, Fu BL, Nogueira B, Gao LL: Evaluation of the mediating role of physical activity self-efficacy in the relationship between knowledge, social support, and physical activity in pregnant women with a high risk for gestational diabetes . BMC pregnancy and childbirth 2024, 24 (1):857. Verloigne M, Cardon G, De Craemer M, D' Haese S, De Bourdeaudhuij I: Mediating Effects of Self-Efficacy, Benefits and Barriers on the Association between Peer and Parental Factors and Physical Activity among Adolescent Girls with a Lower Educational Level . PLoS One 2016, 11 (6):e0157216. Teixeira PJ, Carraca EV, Markland D, Silva MN, Ryan RM: Exercise, physical activity, and self-determination theory: a systematic review. Int J Behav Nutr Phys Act, 2012, 9 : 78. Verloigne M, Cardon G, De Craemer M, D' Haese S, De Bourdeaudhuij I: Effectiveness of a Smartphone App to Promote Healthy Weight Gain, Diet, and Physical Activity During Pregnancy (HealthyMoms): Randomized Controlled Trial. JMIR Mhealth Uhealth , 2021. 9 (3): p. e26091. Koleilat M, Vargas N, vanTwist V, Kodjebacheva GD: Perceived barriers to and suggested interventions for physical activity during pregnancy among participants of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in Southern California . BMC pregnancy and childbirth 2021, 21 (1):69. Chen YP, Hou LY, Li Y, Lou Y, Li W, Yang H: Barriers and motivators to promotion of physical activity participation for older adults with mild cognitive impairment or dementia: An umbrella review. Int J Nurs Stud , 2023. 143 : p. 104493. Modolo VB, Antunes HK, Gimenez PR, Santiago ML, Tufik S, Mello MT: Negative addiction to exercise: are there differences between genders? Clinics (Sao Paulo, Brazil) 2011, 66 (2):255-260. Tables Tables 1 to 6 are available in the Supplementary Files section Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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13:56:53\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":51095,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSchematic diagram of the 3-category model of adherence to exercise in pregnant women.\\u003c/p\\u003e\\n\\u003cp\\u003eDescription \\u0026nbsp;\\u0026nbsp;of the selected LPA profiles of exercise adherence in pregnant women. \\u0026nbsp;\\u0026nbsp;Depiction: Class 1, Low-adherence profile; Class 2, Moderate-adherence \\u0026nbsp;\\u0026nbsp;profile; Class 3, High-adherence profile\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eNote. \\u003c/em\\u003eQ1 \\u0026nbsp;\\u0026nbsp;= I do my exercises as often as recommended; Q2 = I don't get around to doing \\u0026nbsp;\\u0026nbsp;my exercises; Q3 = I do most, or all, of my exercises; Q4 = I do less \\u0026nbsp;\\u0026nbsp;exercise than recommended by my healthcare professional; Q5 = I fit my \\u0026nbsp;\\u0026nbsp;exercises into my regular routine; Q6 = I forget to do my exercises in the \\u0026nbsp;\\u0026nbsp;horizontal coordinate.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7562252/v1/24648dd2c3158a889a4883dd.png\"},{\"id\":105366657,\"identity\":\"0f8cd3e2-1fd4-4830-825c-9509caf5ef7a\",\"added_by\":\"auto\",\"created_at\":\"2026-03-25 08:43:15\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2977896,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7562252/v1/fdb1a015-a2e3-4bb7-af30-6304606c8485.pdf\"},{\"id\":94399173,\"identity\":\"9a887555-8237-42ba-bc4e-0594e16159c4\",\"added_by\":\"auto\",\"created_at\":\"2025-10-27 13:57:22\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":41326,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Tables.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7562252/v1/9cd5165f9ff9871785277378.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Profiles of exercise adherence in late pregnancy: A latent profile analysis among Chinese women\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003ePregnancy is a physiologically and psychologically unique period that is crucial for the health of pregnant women and their offspring. Regular physical activity and exercise during pregnancy are widely recognized for enhancing maternal well-being and optimizing offspring development [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. Although the World Health Organization (WHO) recommends that all women with healthy pregnancies engage in at least 150 minutes of moderate-intensity aerobic exercise per week [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e], adherence remains a primary determinant of the effectiveness of exercise during pregnancy. Evidence shows that exercise adherence to recommended guidelines is often low, thereby limiting the benefits that could be gained [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003ePrevious studies have indicated that physical inactivity during pregnancy increased the risk of excessive gestational weight gain, gestational diabetes mellitus, pre-eclampsia, gestational hypertension, macrosomia, instrumental delivery, urinary incontinence, and depressive disorders [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Sarno et al. [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e] recruited women with a singleton, uneventful pregnancy during their third trimester; 37% of them undertook sports/exercise activities. A systematic review of 11,323 Chinese women during pregnancy reported that 21.0% of them met the recommended level of exercise [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. A cross-sectional study involving 1,636 Chinese pregnant women found that the prevalence of physical inactivity was 47.5%, and that walking was the most common form of physical activity [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eThe benefits of physical activity and exercise for both mother and their child are dependent on long-term adherence. Walasik et al. [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e] examined physical activity patterns among 9000 pregnant women in Poland. During the first and second trimesters, 90% of participants exercised, whereas in the last pregnancy, almost 13% of respondents discontinued physical activity. K\\u0026oacute;kai et al. [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e] investigated the effectiveness of two 8-week app-based moderate to vigorous physical activity interventions for pregnant women. This study began in October 2021 with 663 participants. At week 21, 254 women discontinued this intervention. Shang et al. [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e] reported that less than half of the women undertook 150 minutes of exercise every week before pregnancy. 40.5% of participants kept regular exercise according to the guidelines during pregnancy.\\u003c/p\\u003e\\u003cp\\u003eAdherence, defined by the WHO, is the extent to which a person\\u0026rsquo;s behavior complies with agreed recommendations from health care professionals [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]. Exercise adherence is a complex and dynamic phenomenon during pregnancy, influenced by demographic, psychological, and environmental factors [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Previous studies employed a variable-centered approach to categorize pregnant women based on whether their physical activity and exercise met the standards recommended for exercise [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. Researchers classified participants into \\u0026ldquo;exercisers\\u0026rdquo; and \\u0026ldquo;non-exercisers\\u0026rdquo; based on whether they performed recommended physical activity to assess adherence to physical activity and exercise [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Apparently, these analysis methods appeared inadequate for individualized intervention. Knowledge regarding reasons for adherence to exercise during pregnancy remains limited.\\u003c/p\\u003e\\u003cp\\u003eExercise adherence, along with reasons for both adherence and non-adherence, was assessed by adopting the Exercise Adherence Rating Scale (EARS) [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e], a reliable and valid self-reported outcome measure consisting of 6 items assessing adherence to exercise and 10 items evaluating reasons for exercise adherence [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. EARS has been translated and used in several countries, including Denmark [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e], Brazil [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e], and Sweden [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. In the current study, we evaluated adherence to physical activity among low-risk pregnant women by adapting a Chinese version of the EARS.\\u003c/p\\u003e\\u003cp\\u003eA firm understanding of person-centered factors that influence physical activity during pregnancy is crucial for developing effective individualized exercise programs. We further applied latent LPA, a method particularly suited for identifying individual latent characteristics from a person-centered perspective. The results could facilitate the development of tailored exercise interventions for pregnant women.\\u003c/p\\u003e\\u003cp\\u003eTo our knowledge, no study has used LPA to examine patterns of exercise adherence among pregnant women. The present study, therefore, applied LPA to delineate adherence profiles in pregnant women from three Guangdong cities\\u0026mdash;Shenzhen, Dongguan, and Shunde (Foshan)\\u0026mdash;and to identify related factors of these profiles.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eStudy design and participants\\u003c/h2\\u003e\\u003cp\\u003eAn observational study was conducted from November 2024 to June 2025 at three maternal and child health hospitals in Shenzhen, Dongguan, and Shunde, Guangdong Province, China. We used convenience sampling to recruit pregnant women in their third trimester of pregnancy. The inclusion criteria: aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;18 years and voluntarily participating in the study. Exclusion criteria included: aged\\u0026thinsp;\\u0026lt;\\u0026thinsp;18 years; significant chronic conditions that could affect Exercise during pregnancy (e.g., pre-eclampsia, cervical insufficiency, unexplained persistent vaginal bleeding); mental disorders; or unwillingness to participate.\\u003c/p\\u003e\\u003cp\\u003eSix trained researchers collected the data in person. After confirming eligibility, the researchers explained the study\\u0026rsquo;s purpose, risks, and benefits to the participants. Those who met the inclusion criteria completed the questionnaire in real-time, thereby minimizing the likelihood of invalid responses.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eSampling method and sample size\\u003c/h3\\u003e\\n\\u003cp\\u003eAccording to the literature[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e], a minimum sample size of 250 to 500 participants is required for LPA. Hence, this study employed the LPA method and adhered to established guidelines for sample size calculations. We conveniently recruited 531 participants from 558 eligible pregnant women.\\u003c/p\\u003e\\n\\u003ch3\\u003eMeasures\\u003c/h3\\u003e\\n\\u003cp\\u003eA generic questionnaire was developed based on a review of relevant literature and the study\\u0026rsquo;s objectives. This questionnaire collected information on various demographic factors, including age, pre-pregnancy body mass index (BMI), residence, education level, personal monthly income, and other relevant variables. Among these, pre-pregnancy BMI was calculated as body weight divided by the square of height. Using the Chinese classification, women with a BMI\\u0026thinsp;\\u0026lt;\\u0026thinsp;18.5 kg/m\\u003csup\\u003e2\\u003c/sup\\u003e are considered underweight, those with a BMI of 18.5\\u0026thinsp;~\\u0026thinsp;23.9 kg/m\\u003csup\\u003e2\\u003c/sup\\u003e as normal weight, those with a BMI of 24\\u0026thinsp;~\\u0026thinsp;27.9 kg/m\\u003csup\\u003e2\\u003c/sup\\u003e as overweight, and those with a BMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;28 kg/ m\\u003csup\\u003e2\\u003c/sup\\u003e as obese [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. The obstetric parameters included history of gravidity and parity.\\u003c/p\\u003e\\n\\u003ch3\\u003eExercise adherence\\u003c/h3\\u003e\\n\\u003cp\\u003eThe exercise adherence was assessed using the exercise adherence rating scale (EARS) developed by Newman in 2017 [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. This scale consists of three parts: the EARS-A scale consists of 6 qualitative questions to provide information about their adherence behaviour for individuals; the EARS-B scale consists of 6 items evaluating adherence to prescribed home exercise, with items 1, 3 and 5 are reverse scored; the EARS-C scale consists of 10 questions regarding the reasons for adherence or non-adherence, with items 3, 7, 8 and 10 are reverse scored [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Translated and validated across several countries, it has shown good reliability and validity (Cronbach\\u0026rsquo;s α\\u0026thinsp;=\\u0026thinsp;0.77 to 0.94) [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. The Chinese version of the EARS was modified by Wu Yuxuan [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. The total score range of the EARS-B scale is between 0 and 16, with higher scores indicating better adherence. This study utilized the EARS-B scale to evaluate exercise adherence in pregnant women and the EARS-C scale to identify its influencing factors. In this study, Cronbach\\u0026rsquo;s alpha of the scale was 0.817.\\u003c/p\\u003e\\n\\u003ch3\\u003ePregnancy exercise social support\\u003c/h3\\u003e\\n\\u003cp\\u003eThe present study used the Physical Activity Social Support Scale (PASSS) to measure social support for physical activity [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. The PASSS has 24 items. Items are scored on a 5-point Likert scale, with one indicating \\u0026ldquo;strongly disagree\\u0026rdquo; and five indicating \\u0026ldquo;strongly agree.\\u0026rdquo; The total scores range from 24 to 120, with higher scores indicating greater social support for physical activity. The reported Cronbach\\u0026rsquo;s α was 0.95 [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. The Cronbach\\u0026rsquo;s α of the PASSS was 0.967 in the present study.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003ePregnancy exercise self-efficacy\\u003c/h2\\u003e\\u003cp\\u003ePrenatal exercise self-efficacy was measured using the Pregnancy Exercise Self-Efficacy Scale (P-ESES). Kroll et al. devised an Exercise Self-Efficacy Scale for spinal cord injury in 2007 [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]. Bland et al. adapted and validated it among pregnant women in 2013, with a Cronbach\\u0026rsquo;s α of 0.838 [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. The Chinese version of the P-SESE was modified by Yang Hongmei et al., Cronbach\\u0026rsquo;s α\\u0026thinsp;=\\u0026thinsp;0.804. The P-ESES includes 10 items, which are divided into three domains: overcoming exercise barriers, emotional barriers, and support barriers. Items are scored on a 5-point Likert scale, with one indicating \\u0026ldquo;strongly disagree\\u0026rdquo; and five indicating \\u0026ldquo;strongly agree.\\u0026rdquo; The total P-ESES score ranges from 10 to 50. A total P-ESES score\\u0026thinsp;\\u0026lt;\\u0026thinsp;20 indicates a low level of exercise self-efficacy, a score 21 to 40 suggests a moderate level, and a score \\u0026gt;40 is regarded as indicative of a high level of exercise self-efficacy. In this study, Cronbach\\u0026rsquo;s alpha of the scale was 0.963.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eData analysis\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eDescriptive analysis\\u003c/h2\\u003e\\u003cp\\u003eSPSS software version 27.0 was used for statistical analysis. Necessary normality tests were performed with kurtosis and skewness \\u0026minus;\\u0026thinsp;3.29 to 3.29 [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. In the study, descriptive statistics were made with the SPSS 27.0 package program. Demographic characteristics and scale scores now explicitly include calculated values of \\u003cem\\u003eN\\u003c/em\\u003e (%), mean (\\u0026plusmn;), and standard deviation (SD) to improve clarity and interpretability.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eLatent profile analysis\\u003c/h2\\u003e\\u003cp\\u003eMplus software, version 8.3, was used to analyze the latent profiles of the pregnancy exercise self-efficacy. The best model was selected based on model fit indices and clinical significance. The fit index included the Akaike information criterion (AIC), Bayesian information criterion (BIC), adjusted BIC (aBIC), entropy, Lo-Mendell-Rubin likelihood ratio test (LMR), and Bootstrap-based likelihood ratio test (BLRT). Lower AIC, BIC, and aBIC values indicate a better model fit. Entropy, ranging from 0 to 1, reflects classification accuracy, with values closer to 1 indicating higher accuracy. The LMR and BLRT were used to compare models with k and (k-1) classes; \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 suggests that the k-class model fits the data significantly better than the (k-1)-class model [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e].\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eEthical considerations\\u003c/h2\\u003e\\u003cp\\u003e This study was conducted in accordance with the guidelines of the Declaration of Helsinki. It was approved by the Ethics Committee of the Dongguan Maternal and Child Health Hospital (Approval No. 2024\\u0026thinsp;\\u0026minus;\\u0026thinsp;155); Shunde Women and Children's Hospital of Guangdong Medical University (KY-2024-070); and Baoan Central Hospital of Shenzhen (BYL20240628). Before the study, both oral and written consents were obtained from all eligible participants, ensuring that participation or non-participation would not affect their work performance or future employment opportunities. Additionally, all collected information would be anonymous and de-identified. Furthermore, participants were informed that they could withdraw from the study at any time.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eDemographic information\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eA total of 558 questionnaires were distributed in this study. Among them, 27 questionnaires had incomplete responses and were deemed invalid; therefore, they were eliminated. Complete responses were considered valid, resulting in a total of 531 valid questionnaires. The effective response rate of the questionnaire was 95.16%. All participants were in the third trimester. Most resided in urban areas and had a mean age of 31.81 \\u0026plusmn; 3.99 years. Only 23.4% achieved 150 minutes or more of exercise per week. The participants\\u0026apos; average total PASSS score was 34.47 \\u0026plusmn; 8.10, and that of P-ESES was also 34.47 \\u0026plusmn; 8.10. Other demographic information was detailed in Table 1.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eTable 2 presents the average scores for each item of the EARS-C scale (reasons for adherence / non-adherence). Statistical results indicate that most items have high \\u003cem\\u003eF\\u003c/em\\u003e-values and \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05, demonstrating statistically significant differences among exercise adherence levels.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults of latent profile analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study conducted a profile analysis based on the EARS-B scale scores. It used AIC, BIC, aBIC, LMR (\\u003cem\\u003eP\\u003c/em\\u003e-value), and BLRT (\\u003cem\\u003eP\\u003c/em\\u003e-value) as evaluation indices to select the best model from 1 to 4 potential profile models established in sequence. The results of the model fit metrics for each profile are detailed in Table 3. The number of model categories increased from 1 to 4, and the AIC, BIC, and aBIC continued to decrease, with entropy being the highest among the four profile models. The 4-profile model LMR was excluded（\\u003cem\\u003eP\\u003c/em\\u003e \\u0026gt; 0.05）. Therefore, the model with three profiles was finally chosen as the optimal potential profile model for this study, as shown in Table 3.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eNaming of latent profile\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eFig. 1 presents the mean scores of each item for the three exercise adherence profiles among pregnant women. The categories were named: \\u0026ldquo;low-adherence\\u0026rdquo; group, \\u0026ldquo;moderate-adherence\\u0026rdquo; group, and \\u0026ldquo;high-adherence\\u0026rdquo; group based on the characteristics of the mean scores across different categories. The \\u0026ldquo;moderate-adherence\\u0026rdquo; profile had the highest percentage, at 45.0%, followed by the \\u0026ldquo;low-adherence\\u0026rdquo; profile at 43.9%, and the \\u0026ldquo;high-adherence\\u0026rdquo; profile at 11.1%.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eInter-profile characteristic differences\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe chi-square test and the one-way analysis of variance were used to compare differences in the presence of influencing factors among pregnant women in different potential exercise adherence categories. The results showed that gravidity, parity, education level, Exercise habit, PFMT, exercise self-efficacy, and social support were statistically significant (\\u003cem\\u003eP\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05). The rest of the categorical differences were not statistically significant (\\u003cem\\u003eP\\u0026nbsp;\\u003c/em\\u003e\\u0026gt; 0.05), as seen in Table 4.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMultinomial logistic regression of exercise adherence profiles\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDemographic information\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWhen the low-adherence profile was the reference group, relative to the\\u0026nbsp;moderate-adherence\\u0026nbsp;profile,\\u0026nbsp;the weekly exercise habit \\u0026lt; 30 min (OR = 0.218, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001) for the moderate-adherence profile was significantly harmful; the scores of PASSS (OR = 1.060, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001) and P-ESES (OR = 1.189, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001)\\u0026nbsp;for the moderate-adherence profile were significantly positive. The results presented in Table 5 suggest that, first, women\\u0026rsquo;s weekly exercise habit \\u0026lt; 30 minutes, the less likely they are to be categorized into the moderate-adherence profile. Second, the higher scores of PASSS and P-ESES were more likely they were to be classified as moderate-adherence.\\u003c/p\\u003e\\n\\u003cp\\u003eRelative to the high-adherence profile: the exercise habit weekly \\u0026lt; 30 min (OR = 0.021, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001) and \\u0026lt;150 min (OR = 0.174, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001), and never PFMT\\u0026nbsp;(OR = 0.319, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.05)\\u0026nbsp;for the high-adherence profile was significantly negative; the scores of PASSS (OR = 1.091, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001) and P-ESES (OR = 1.347, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001) for high-adherence were significantly positive. Suggests that, first, the weekly exercise habit \\u0026lt; 30 min and \\u0026lt; 150 min, and women who have never engaged in PFMT, are less likely they are to be categorized into the high-adherence profile. Second, the higher scores of PASSS and P-ESES were more likely to be classified as a high adherence profile.\\u003c/p\\u003e\\n\\u003cp\\u003eWhen the moderate-adherence profile was the reference group, relative to the high-adherence profile: the college education level (OR = 0.299, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05), weekly exercise habit \\u0026lt; 30 min (OR = 0.097, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001) and \\u0026lt;150min (OR = 0.259, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001) for high-adherence profile were significantly negative; PASSS (OR = 1.029, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05) and P-ESES (OR = 1.133, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001) scores for high-adherence profile were significantly positive. Suggests that, first, college education level and weekly exercise habit (\\u0026lt; 30min and \\u0026lt; 150min) in pregnant women are less likely to be classified as a high-adherence profile. Second, the higher the PASSS and P-ESES scores, the more likely pregnant women are to be classified as a high-adherence profile.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eReasons for adherence / non-adherence\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWhen the low-adherence profile was the reference group, relative to the moderate-adherence profile: item 1: \\u0026ldquo;I adjust the way I do my exercises to suit myself\\u0026rdquo; (OR = 0.689, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.05), for moderate-adherence were significantly negative; item 2: \\u0026ldquo;Other commitments prevent me from doing my exercises\\u0026rdquo; (OR = 1.520, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.05), item 3: \\u0026ldquo;I feel confident about doing my exercises\\u0026rdquo; (OR = 3.280, \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001), item 7: \\u0026ldquo;I do my exercises because I enjoy them\\u0026rdquo; (OR = 1.981, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001), item 8: \\u0026ldquo;My family and friends encourage me to do my exercises\\u0026rdquo; (OR = 1.513, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05), and item 10: \\u0026ldquo;I do my exercises to improve my health\\u0026rdquo; (OR = 1.412, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05), for moderate-adherence was significantly positive; This suggests that, first, the higher scores of item 3, item 7, item 8 and item 10 more likely they were to be categorized as moderate-adherence profile; second, the lower scores of item 1 of scores more likely they was to be categorized as moderate-adherence profile. The results of the study are presented in Table 6. Relative to the high-adherence profile: item 2: \\u0026ldquo;Other commitments prevent me from doing my exercises\\u0026rdquo; (OR = 2.005, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05), item 3: \\u0026ldquo;I feel confident about doing my exercises\\u0026rdquo; (OR = 9.089, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001), item 4: \\u0026ldquo;I don\\u0026rsquo;t have time to do my exercises\\u0026rdquo; (OR = 4.505, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001), item 6: \\u0026ldquo;I don\\u0026rsquo;t do my exercises when I am tired\\u0026rdquo; (OR = 2.692, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001), item 7: \\u0026ldquo;I do my exercises because I enjoy them\\u0026rdquo; (OR = 2.141, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05) and item 8: \\u0026ldquo;My family and friends encourage me to do my exercises\\u0026rdquo; (OR = 3.743, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05)\\u0026nbsp;were significantly positive; This suggests that, the higher scores of item2, 3, 4, 6, 7 and 8\\u0026nbsp;more likely they were to be categorized the high-adherence profile.\\u003c/p\\u003e\\n\\u003cp\\u003eWhen the moderate-adherence profile was the reference group, relative to the high-adherence profile: item 3: \\u0026ldquo;I feel confident about doing my exercises\\u0026rdquo; (OR = 2.522, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05), item 4: \\u0026ldquo;I don\\u0026rsquo;t have time to do my exercises\\u0026rdquo; (OR = 3.916, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001), item 6: \\u0026ldquo;I don\\u0026rsquo;t do my exercises when I am tired\\u0026rdquo; (OR = 2.211, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.001), item 8: \\u0026ldquo;My family and friends encourage me to do my exercises\\u0026rdquo; (OR = 2.474, \\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05) for high-adherence were significantly positive. Suggests that the higher scores of items 3, 4, 6, and 8 are more likely to be categorized as high-adherence.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study is the first to examine latent profiles of exercise adherence among women in their third trimester and to identify subtypes of exercise adherence using a person-centered approach. Exercise adherence among pregnant women was classified into three distinct profiles: low-adherence (43.9%), moderate-adherence (46%), and high-adherence (11.1%). The average scores for these groups were 9.32, 13.77, and 19.66, respectively. This result was consistent with the finding from Lu [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. The mean score on the EARS-B scale among pregnant women was 12.47\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.01, which fell below the established cut-off point [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eThe current study demonstrated that education level, weekly exercise habit, and PFMT were associated with exercise adherence among pregnant women. Consistent with previous studies, low education level was identified as a negative influence on meeting recommended physical activity and exercise during pregnancy [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]. Compared to the high-adherence group, pregnant women who had a lower education level were more likely to be classified into the mid-adherence group. Zhang et al. [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e] found that pre-pregnancy exercise habit was a significant predictor of intent to initiate physical activity. A systematic review also demonstrated that regular physical activity was associated with higher self-efficacy. Pregnant women had a more positive attitude toward physical activity and exercise during pregnancy; ultimately, they adhered to exercise [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. In this study, women who performed PFMT tended to have higher exercise adherence. Pelvic floor disorders, such as stress urinary incontinence (SUI) and pelvic floor pain during the last pregnancy, may impair women's motivation and ability to exercise. PFMT is most effective in treating SUI by strengthening the pelvic floor muscles. Physical activity programs that incorporate PFMT may be more motivating for women to engage in general aerobic exercise during pregnancy [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. Additionally, information about the benefits of exercise and the dangers of inactivity during pregnancy should be incorporated into tailored exercise programs for pregnant women with less formal education.\\u003c/p\\u003e\\u003cp\\u003eMultinomial logistic regression analysis indicated that exercise self-efficacy was a crucial factor influencing exercise adherence among pregnant women; higher scores on the P-ESES significantly increased the odds of membership in the moderate or high adherence profiles. Aligning with social cognitive theory [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e], exercise self-efficacy refers to the confidence in one's ability to overcome more challenging tasks and achieve desired results[\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. Similarly, social support has been identified as a predictor of exercise adherence, as confirmed by a systematic review [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e]. Although the present study also observed a comparatively modest effect of social support on exercise adherence, this suggests that the influence of social support on exercise adherence may be moderated by internal and external factors [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e]. Indeed, partners, family members, friends, and health-care professionals have repeatedly been identified as key sources of social support for promoting physical activity during pregnancy [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. Moreover, studies by Verloigne and Lu [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e] indicated that physical activity self-efficacy mediates the relationship between social support and physical activity. Therefore, interventions designed to enhance exercise self-efficacy, leverage multiple sources of social support, and encourage regular physical activity may help pregnant women achieve better adherence outcomes.\\u003c/p\\u003e\\u003cp\\u003eWe used the EARS-C scale to investigate the reasons for adherence in those who exhibited good and poor adherence to exercise. These included items 3 and 8 as two major protective factors in the mid- and high-adherence groups (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e), indicating that exercise self-efficacy and social support play crucial roles in exercise adherence [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. Other facilitating factors included enjoyment of exercise and self-adjustment. In line with self-determination theory, the enjoyment of exercise, as an inherent motivator, was positively associated with exercise behavior [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. Empirical evidence further confirmed that intrinsic motivation supports both sustained exercise and psychological well-being[\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. Accordingly, prenatal exercise programs should emphasize enjoyment, skill mastery, and accomplishment, while enhancing maternal well-being and vitality. Mobile Health exercise programs with attractive course visuals and motivating music enhance the overall workout experience, making it more enjoyable [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. Furthermore, healthcare professionals should focus on developing personalized and gamified mobile health (mHealth) exercise programs for pregnant women.\\u003c/p\\u003e\\u003cp\\u003eNegative influences to exercise adherence included competing commitments, lack of time, and fatigue, which align with findings from Shang and Koleilat [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. Prior research attributes these barriers to the dual responsibilities of caregiving and the workforce that these women faced [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. Since the implementation of China\\u0026rsquo;s \\u0026ldquo;three-child policy\\u0026rdquo;, the proportion of multiparous women has increased; over half of the participants who were multiparas in our study faced challenges of balancing competing commitments and physical exercise. For this reason, it is essential to consider time constraints when designing physical activity interventions for pregnant women. In response, we propose a community-based program that will facilitate peer interaction and the sharing of challenges and concerns [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. The program will include weekly group classes tailored to varying fitness levels, as well as workshops on time management and strategies for balancing responsibilities [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eThis study has two strengths. First, it uses a multicenter design, which reduces the bias that single-center studies often have. Second, it takes a person-centered analytical approach to capture varied adherence patterns among individuals. This study has several limitations. First, all measures were self-reported questionnaires, excluding weight and height. Nevertheless, these scales have all shown good reliability and validity in this study, ensuring the accuracy of the results. Its cross-sectional design limits causal inference and does not allow for investigating how exercise adherence changes during the entire pregnancy period. Future studies should follow pregnant women across the three trimesters of pregnancy to facilitate a more comprehensive exploration of the multi-trajectory mechanisms underlying exercise adherence.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThis study showed that exercise adherence among pregnant women appeared heterogeneous and presented in three distinct categories. Exercise self-efficacy, social support, weekly exercise habit, PFMT, enjoyment of exercise, other commitments, lack of time, and fatigue emerged as primary factors influencing sustained exercise. This evidence lays a crucial foundation for future tailored physical activity programs.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eWHO \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eWorld Health Organization\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eGDM \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eGestational Diabetes Mellitus\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eEARS \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eExercise Adherence Rating Scale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eLPA \\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eLatent Profile Analysis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eBMI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eBody Mass Index\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003ePASSS \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003ePhysical Activity Social Support Scale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eP-ESES\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003ePregnancy Exercise Self-Efficacy Scale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eSD \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eStandard Deviation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAIC \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAkaike Information Criterion\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eBIC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eayesian Information Criterion\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eaBIC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eadjusted Bayesian Information Criterion\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eLMR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eLo-Mendell-Rubin\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eBLRT\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eBootstrapped Likelihood Ratio Test\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eOR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eOdds Ratio\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eRMB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eRenminbi\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003ePFMT\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003ePelvic floor muscle training\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eZCH and MH design and write articles. MH, CHN, XSR, OYLF, LKQ, and XZM completed the data collection. MH and CHN completed the data input and analysis. ZCH completed the revision and check of the article. All the authors read and approved the final version of the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was supported by the Guangdong Province Graduate Education Innovation Program Project (2025JGXM_083).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData availability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was conducted in accordance with the guidelines of the Declaration of Helsinki. It was approved by the Ethics Committee of the Dongguan Maternal and Child Health Hospital (Approval No. 2024-155); Shunde Women and Children\\u0026apos;s Hospital of Guangdong Medical University (KY-2024-070); and Baoan Central Hospital of Shenzhen (BYL20240628). Before the study, both oral and written consents were obtained from all eligible participants, ensuring that participation or non-participation would not affect their work performance or future employment opportunities. Additionally, all collected information would be anonymous and de-identified. Furthermore, participants were informed that they could withdraw from the study at any time.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003cstrong\\u003e\\u003cbr\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eGascoigne EL, Webster CM, Honart AW, Wang P, Smith-Ryan A, Manuck TA: \\u003cstrong\\u003ePhysical activity and pregnancy outcomes: an expert review\\u003c/strong\\u003e. 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BMC pregnancy and childbirth 2021, \\u003cstrong\\u003e21\\u003c/strong\\u003e(1):69.\\u003c/li\\u003e\\n\\u003cli\\u003eChen YP, Hou LY, Li Y, Lou Y, Li W, Yang H: \\u003cstrong\\u003eBarriers and motivators to promotion of physical activity participation for older adults with mild cognitive impairment or dementia: An umbrella review.\\u003c/strong\\u003e\\u003cem\\u003e Int J Nurs Stud\\u003c/em\\u003e, 2023. \\u003cstrong\\u003e143\\u003c/strong\\u003e: p. 104493.\\u003c/li\\u003e\\n\\u003cli\\u003eModolo VB, Antunes HK, Gimenez PR, Santiago ML, Tufik S, Mello MT: \\u003cstrong\\u003eNegative addiction to exercise: are there differences between genders?\\u003c/strong\\u003e Clinics (Sao Paulo, Brazil) 2011, \\u003cstrong\\u003e66\\u003c/strong\\u003e(2):255-260.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003eTables 1 to 6 are available in the Supplementary Files section\\u003c/p\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"pregnant women, exercise adherence, exercise self-efficacy, social support, latent profile analysis\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7562252/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7562252/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e\\u003cp\\u003eThe benefit of physical activity and exercise interventions for pregnant women crucially depends on adherence. The study aimed to identify latent categories of exercise adherence among pregnant women in the third trimester and explored the influence of these distinct profiles.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e\\u003cp\\u003eConvenience sampling was used to recruit participants from three maternal and child health hospitals in China, between November 2024 and June 2025. Latent profile analysis (LPA) was used to identify potential classes of exercise adherence among pregnant women in the third trimester; multinomial logistic regression was used to explore the factors associated with these profiles.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e\\u003cp\\u003eA total of 531 participants were included in this study and were classified as high (n\\u0026thinsp;=\\u0026thinsp;59), moderate (n\\u0026thinsp;=\\u0026thinsp;239), and low adherence (n\\u0026thinsp;=\\u0026thinsp;233) to exercise. Compared to the low-adherence group, the influencing factors for the high-adherence group were weekly exercise habit, pelvic floor muscle training (PFMT), exercise self-efficacy, social support, enjoyment of exercise, other commitments, lack of time, and fatigue. Compared to the mid-adherence group, the influencing factors for the high-level group were education level, weekly exercise habit, exercise self-efficacy, social support, lack of time, and fatigue.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e\\u003cp\\u003eExercise adherence among pregnant women appeared heterogeneous and presented in three distinct categories. Health workers should develop targeted interventions based on the socio-psychological characteristics of pregnant women in the third trimester to improve their adherence to exercise.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Profiles of exercise adherence in late pregnancy: A latent profile analysis among Chinese women\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-10-26 00:34:19\",\"doi\":\"10.21203/rs.3.rs-7562252/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"c1f2723a-478d-442b-8cfe-9eca43f0a7bf\",\"owner\":[],\"postedDate\":\"October 26th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-03-25T08:42:35+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-10-26 00:34:19\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7562252\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7562252\",\"identity\":\"rs-7562252\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}