Nutritional Knowledge Among female Pilates and Yoga practitioners

Nutritional Knowledge Among female Pilates and Yoga practitioners | 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Article Nutritional Knowledge Among female Pilates and Yoga practitioners AIYA ALACKAM This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7906466/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 Purpose to assess the nutritional knowledge among female Pilates and yoga practitioners. Additionally, we will explore associated factors such as hormonal phase, education status, and practising other types of training. Methods thirty participants from Mindful movement studio and House of Lyla in Gravesend, Kent completed the validated Abridged Nutrition Knowledge Survey Questionnaire (ANKSQ). Data were analysed using descriptive statistics, knowledge categorisation, one-sample t-tests against adequacy benchmarks, subgroup comparisons (ANOVA, Welch’s ANOVA with Games–Howell tests, and independent-samples t-tests), Pearson’s correlations, and linear regression. Effect sizes were reported for all analyses. Results mean score was 48.9% (SD 9.4), significantly below the “good” knowledge benchmark (p < 0.001). Nearly half of participants had “poor” knowledge, and none had “excellent”. Higher education and perimenopausal/menopausal status were linked to better scores; practice type and training habits had a limited impact. Participants primarily used internet/social media or fitness coaches for nutrition information; evidence-based sources (dietitians, academic journals) were seldom used. Conclusion female Pilates and yoga practitioners demonstrated limited nutrition knowledge, shaped primarily by an educational background rather than training behaviours. The heavy reliance on informal sources highlights the need for accessible, evidence-based nutrition education tailored to this population and across women’s life stages. ANKSQ women athletes sports nutrition fitness nutrition nutrition knowledge Figures Figure 1 Introduction Nutrition is a key determinant of athletic performance, recovery, and long-term health, enabling individuals to optimise energy availability, reduce injury risk, and support overall well-being [ 1 , 19 ]. Higher nutrition knowledge is associated with healthier dietary patterns, including greater intake of fruits and vegetables and lower consumption of energy-dense foods [ 17 , 18 , 19 ]. Conversely, limited knowledge has been linked with inadequate energy intake and potential risk of relative energy deficiency in sport, particularly among women [ 14 ]. While research on athletes’ nutritional knowledge is expanding, most studies focus on traditional team or endurance sports rather than mind–body practices, which are increasingly popular worldwide and predominantly practised by women [ 12 ]. Pilates and yoga combine physical performance with holistic approaches to health, stress reduction, and recovery. Although often perceived as low intensity, it involves sustained muscular engagement, balance, and flexibility, as some styles need moderate to vigorous aerobic effort [ 3 , 4 , 10 , 13 , 11 , 16 ]. Pilates sessions typically expend approximately 1.9–2.6 kcal/min, requiring the activation of core and stabilising muscles that increase recovery demands [ 5 ]. Similarly, dynamic yoga styles can reach moderate-to-vigorous intensities, increasing cardiovascular demand and fluid loss, highlighting the importance of carbohydrate availability and hydration [ 21 ]. Preliminary evidence suggests that yoga practitioners are more likely to report healthier dietary behaviours than non-practitioners [ 7 ], but whether this reflects genuine knowledge or misconceptions remains uncertain. For women, nutrition demands also vary across hormonal phases and life stages. Iron deficiency affects 15–50% of active females due to menstrual blood losses combined with training demands [ 14 ]. During pregnancy and lactation, protein and energy requirements rise substantially, with recent systematic reviews estimating average energy intake in pregnant populations around 2,030 − 2,100 kcal/day, depending on trimester and region [ 9 ]. On the other hand, measured energy requirements for active non-pregnant women remain less well documented. In later life, maintaining bone health during menopause requires adequate calcium and vitamin D intake, alongside attention to overall diet quality, to preserve bone mineral density and reduce fracture risk [ 2 , 14 ]. Despite recognition of these stage-specific demands, little is known about how nutrition knowledge among this population aligns with them. To our knowledge, this is the first study to investigate this in female Pilates or yoga practitioners. This study, therefore, aimed to evaluate the nutrition knowledge of female Pilates and yoga practitioners, with secondary objectives of examining differences by different factors. We hypothesised that mean knowledge scores would fall below the benchmark for good knowledge. Methods Ethics approval This study was approved by the School of Biomedical Sciences Ethics Filter Committee at Ulster University (Project Number: FCBMS-25-075). Permission to recruit participants was granted by Mindful Movement Studio and House of Leyla Yoga Centre. All responses were anonymous, and the survey completion implied an informed consent. Reporting followed the STROBE checklist for cross-sectional studies. Participants and recruitment Eligible participants were women aged 18 years or older who were currently practising Pilates and/or yoga. Exclusion criteria included any health condition that prevented safe participation in these activities. Recruitment took place in July 2025 through Instagram posts, email invitations to studio members, and posters displayed at the two partner studios. A total of 45 individuals accessed the online survey. Of these, 11 only completed the initial demographic items and were excluded, and 4 provided partial responses but did not complete the full questionnaire. Thirty participants completed all survey items in full and were included in the analyses. Sample size calculation Prior to recruitment, an a priori power analysis was conducted using G*Power version 3.1.9.7. Assuming a medium effect size (Cohen’s d = 0.5) for differences in nutrition knowledge between subgroups, an α-level of 0.05, and power (1–β) of 0.80, the minimum required sample size for independent-samples t-tests was 27 participants. We therefore aimed to recruit at least 30 participants to allow for incomplete responses and subgroup comparisons (ANOVA). Ultimately, 30 participants completed all survey items, exceeding the minimum required sample size and ensuring adequate power for the planned analyses. Data collection Data were collected using Redcap, a secure web-based platform. The survey required approximately 15–20 minutes to complete, and responses were stored securely before being exported in Excel format for analysis. Survey design Nutrition knowledge was adapted from the (ANKSQ), a validated tool designed to measure both general and sports-specific nutrition knowledge [ 19 ]. One item referred to the 2017 World Anti-Doping Agency list, in which glycerol was prohibited; responses were scored accordingly, although later revisions of the WADA list replaced this with testosterone. The questionnaire comprised three main sections: Demographics and training age, height, weight, BMI, education level, years of Pilates and yoga practice, other exercise habits, nutrition education, and primary sources of nutrition information. Hormonal phase hormonal stage (reproductive, pregnancy, lactation, perimenopause, or menopause) and any associated changes in diet or activity. Nutrition knowledge : General knowledge (macronutrients, micronutrients, hydration, alcohol, energy balance). Sports nutrition knowledge (nutrient timing, protein and carbohydrate needs, hydration, supplementation, anti-doping). Items included multiple-choice, true/false, and ranking questions. Scores were calculated as the percentage of correct answers, with classifications of poor (< 49%), average (50–65%), good (66–75%), and excellent (≥ 76%) [ 20 ]. The questionnaire was pilot tested among a small group (n = 3) to ensure clarity and flow prior to wider distribution. Statistical analysis Analyses were conducted in IBM SPSS Statistics version 29 (IBM Corp., Armonk, NY, USA). Descriptive statistics summarised sample characteristics and knowledge scores. Normality testing indicated that knowledge scores were normally distributed, whereas age was not. Parametric tests (t-tests, ANOVA, Pearson’s correlations, and linear regression) were therefore applied to knowledge outcomes, and non-parametric equivalents were used where appropriate, yielding consistent results. One-sample t-tests compared mean scores to adequacy thresholds (50% and 65%). Group differences by practice type, education, formal nutrition education, and hormonal phase were assessed with one-way ANOVA or Welch’s ANOVA, with Games–Howell post hoc comparisons where required. Independent-samples t-tests compared participants with and without strength training. Pearson’s correlations tested associations between continuous predictors (age, BMI, years of practice) and knowledge scores. Separate linear regression models examined education and BMI as predictors; a combined model including years of Pilates and yoga practice was also tested, with multicollinearity assessed using variance inflation factors. Effect sizes were reported as Cohen’s d (t-tests), η² (ANOVAs), and r (correlations). Statistical significance was set at p < 0.05. Result Participant Characteristics Thirty participants completed the survey with a mean age of 35.8 years. The majority practised Pilates (73.3%), with smaller groups practising yoga only or both modalities. Half of the participants reported education beyond secondary school but below university level. Most had not undertaken formal nutrition training. Dietary habits were predominantly carnivorous, and most participants were in the reproductive phase of life. Full participant characteristics are presented in Table 1 . Table 1 Participant characteristics of Pilates and yoga practitioners (n = 30). Values are mean ± standard deviation (SD) for continuous variables and n (%) for categorical variables. Characteristic n (%) Mean ± SD (if applicable) Age (years) – 35.8 ± 12.9 BMI (kg/m²) – 25.0 ± 5.7 Education High school 11 (36.7) Diploma 8 (26.7) Undergraduate 7 (23.3) Master’s 3 (10.0) Doctoral 1 (3.3) Practice type Yoga only 4 (13.3) Pilates only 22 (73.3) Both 4 (13.3) Eating habits Carnivorous 24 (80.0) Vegetarian/Vegan 1 (3.3) Pescatarian 3 (10.0) Other 2 (6.7) Hormonal phase Reproductive 21 (70.0) Perimenopause 3 (10.0) Menopause 6 (20.0) * Frequency (percentage) used for categorical variables. Nutrition Knowledge Scores As displayed in Fig. 1 , participants demonstrated limited nutrition knowledge overall. General nutrition knowledge averaged 57.5% (SD = 10.4), with nearly half classified as poor and another half as average. Only one participant achieved a good score, and none reached excellent. Sports nutrition knowledge was lower (49.4% ± 16.2), with all participants falling in poor or average categories. Total knowledge averaged 48.9% (SD = 9.4; range 31.6–65.8%). Scores did not differ from the 50% adequacy benchmark (t (29) = − 0.62, p = .54) but were significantly below the 65% good knowledge threshold (t (29) = − 9.39, p < .001, d = − 1.71). Table 2 shows that participants most frequently cited internet/social media (65%) and fitness coaches (48%) as primary sources of nutrition information, while dietitians and academic journals were the least reported. Table 2 Primary sources of nutrition information ranked by participants (n and mean ranks). Source Mean Rank (SD) Participants (n) Internet / social media 2.3 (1.5) 19 Fitness Coach 2.6 (1.3) 14 Doctor 3.4 (1.6) 7 Dietitian 3.8 (1.1) 5 * Rankings based on participant self-report. *p < .05; **p < .01; ***p < .001 Differences in Nutrition Knowledge Scores between Groups General knowledge scores differed significantly by practice type (F (2, 65.96) = 13.59, p < .001). Participants who practised yoga scored higher in general nutrition knowledge than those practising both modalities (p = .027). No significant differences were found in sports or total knowledge (Table 3 ). Table 3 Mean knowledge scores (total, general, sports) compared with adequacy benchmarks (50% and 65%), including one-sample t-tests, p-values, and Cohen’s d. Practice type n Total (Mean ± SD) General (Mean ± SD) Sports (Mean ± SD) Yoga only 4 50.0 ± 10.3 61.8 ± 3.4 48.5 ± 20.6 Pilates only 22 48.8 ± 9.0 55.9 ± 11.6 51.1 ± 14.9 Pilates + Yoga 4 48.7 ± 13.0 61.8 ± 5.9 41.2 ± 25.0 * Welch’s correction applied where assumptions were violated. *p < .05; **p < .01; **p < .001 Table 4 Nutrition knowledge scores stratified by education level. Education level n Total knowledge (Mean ± SD) General knowledge (Mean ± SD) Sports knowledge (Mean ± SD) High School 11 46.2 ± 9.4 54.5 ± 10.6 44.3 ± 16.7 Diploma 8 50.3 ± 6.7 61.8 ± 8.9 47.1 ± 11.8 Undergraduate 7 50.0 ± 9.7 55.8 ± 7.5 53.5 ± 23.1 Master’s 3 55.3 ± 17.5 56.9 ± 20.7 56.9 ± 23.6 Doctoral 1 55.3 ± – 64.7 ± – 52.9 ± – Total 30 49.4 ± 9.4 57.5 ± 10.4 49.4 ± 16.2 * Significant differences across education levels (F (4, 175) = 4.67, p = .001, η² = .096) A one-way ANOVA *p < .05; **p < .01; **p < .001. Education: participants holding only primary education score lower than those with higher qualifications. Differences were also evident in sports and total knowledge (p < .05). Nutrition education: Unexpectedly, participants without formal nutrition education scored higher in general knowledge (M = 58.4%, SD = 10.6) than those with such education (M = 51.5%, SD = 5.0), t (62.7) = 5.21, p < .001, d = 0.69. No differences were identified for sports or total knowledge. Hormonal phase: Participants in the reproductive phase scored lower than those in perimenopause (–10.1%, p < .001) and menopause (–9.2%, p < .001) for total knowledge and lower than both groups in sports knowledge (ps < .001). See Table 6 below. Information provided in Table 7 details that the mean total nutrition knowledge score was higher among participants who reported strength training compared with those who did not. Table 5 Nutrition knowledge scores stratified by formal nutrition education. Group n Total (Mean ± SD) General (Mean ± SD) Sports (Mean ± SD) Nutrition education 26 49.1 ± 8.8 58.4 ± 10.8 48.6 ± 14.1 No nutrition education 4 48.0 ± 14.0 51.5 ± 5.6 54.4 ± 29.4 * Values are mean ± SD. Welch’s correction applied where assumptions were violated. *p < .05; **p < .01; **p < .001. Table 6 Nutrition knowledge scores by hormonal phase, n = 30. Hormonal phase n Total (Mean ± SD) General (Mean ± SD) Sports (Mean ± SD) Reproductive 21 47.7 ± 9.1 57.4 ± 11.0 47.1 ± 14.3 Perimenopause 3 57.9 ± 4.6 60.8 ± 12.2 66.7 ± 29.4 Menopause 6 48.7 ± 10.6 55.9 ± 8.9 49.0 ± 21.3 Total 30 49.4 ± 9.4 57.5 ± 10.4 49.4 ± 16.2 *Significant variations in total knowledge (F (2, 57.41) = 37.09, p < .001) and sports knowledge (F (2, 42.67) = 25.64, p < .001) across phases by Welch’s correction, applied where assumptions were violated. ᵃ Perimenopause group (n = 3); interpret with caution *p < .05; **p < .01; **p < .001. Table 7 Nutrition knowledge scores by strength training participation (n = 30). Domain Strength training (n = 14) No strength training (n = 15) Mean difference (95% CI) t (df) p Cohen’s d Total knowledge (%) 64.0 ± 50.0 40.0 ± 51.0 –24.0 [–63.0, 14.0] –1.30(27) .204 0.48 General knowledge (%) 58.8 ± 9.8 56.3 ± 11.2 –2.6 [–10.5, 5.3] –0.67(28) .510 0.24 Sports knowledge (%) 52.1 ± 13.0 47.1 ± 18.7 –5.0 [–17.3, 7.2] –0.84(28) .406 0.31 * Independent-samples t tests were used. *p < .05; **p < .01; **p < .001. Correlations As can be concluded from Table 8 , no significant correlations were observed between age, BMI, or years of practice and knowledge scores. Table 9 shows regression analyses indicated that education and BMI predicted knowledge scores when tested separately. Years of yoga and Pilates practice together explained substantial variance (R² = .75). However, it was detected when predictors were combined, limiting interpretation. Table 8 Pearson correlations between participant characteristics (age, BMI, years of practice) and knowledge scores. Predictor General Knowledge (r) Sports Knowledge (r) Total Knowledge (r) Age .20 –.00 .17 BMI –.08 –.28 –.23 Pilates years .06 .08 .04 Yoga years –.65 –.38 –.43 * No significant difference by Pearson’s correlation coefficients (r). ᵃ Positive values indicate higher knowledge with higher predictor levels; negative values indicate inverse associations. *p < .05; **p < .01; **p < .001. Table 9 Regression models predicting nutrition knowledge scores (education, BMI, years of practice). Model / Predictor B SE B β t p R² (Adj. R²) F (df) Model 1: Education .048 (.043) 9.01 (1,28) Constant 45.07 1.46 – 30.91 < .001 Education 1.79 0.60 .22 3.00 .003 Model 2: BMI .053 (.047) 9.54 (1,28) Constant 58.26 3.16 – 18.43 < .001 BMI –0.38 0.12 –.23 –3.09 .002 Model 3: Yoga + Pilates .749 (.725) 31.35 (2,21) Constant 41.10 1.98 – 20.75 < .001 Yoga years 6.87 0.89 2.52 7.70 < .001 Pilates years –6.32 0.80 –2.57 –7.88 < .001 * Values are unstandardized regression coefficients (B) with standard errors (SE B). ᵃ Multicollinearity was detected when all predictors were entered simultaneously; therefore, predictors were tested in separate models. *p < .05; **p < .01; **p < .001. Discussion This study aimed to assess nutrition knowledge among female yoga and Pilates practitioners, with particular attention to differences across education, training habits, and hormonal phases. Addressing this gap makes an important contribution, as no previous research has assessed nutritional knowledge of this population. Overall, participants demonstrated only “average” knowledge (48.9%), well below the benchmark for “good” knowledge, with sports nutrition being a particular weakness. Most participants relied on the internet and social media sources rather than dietitians or academic materials, which may explain the prevalence of misconceptions. Subgroup analyses suggested that education level, practice type, and hormonal status influenced knowledge scores, although unexpectedly, formal nutrition education did not consistently predict higher knowledge. Despite some limitations, such as small sample size and self-reported data limit generalisability and preclude causal inference. findings carry important practical implications. As participants most frequently relied on the internet or social media (65%), while academic journals (10%) were rarely consulted. This reliance on informal sources has also been observed in other active populations and is strongly associated with exposure to misinformation [ 20 , 8 ]. The limited engagement with dietitians (18%) is concerning, as professional guidance is known to support healthier dietary behaviours [ 15 ]. Education was a consistent determinant of nutrition knowledge. Participants with higher academic qualifications scored better, and regression models confirmed education as a significant predictor, in line with evidence linking academic attainment to health and nutrition literacy [ 6 ]. Unexpectedly, participants with formal nutrition education did not outperform those without, echoing earlier reports that prior training does not always predict higher knowledge [ 19 ]. This may reflect differences in the scope or quality of previous education or difficulties with long-term retention, suggesting that nutrition training should be reinforced regularly. Knowledge scores also differed by practice type, with yoga-only participants achieving higher general nutrition scores than those practising both modalities, although no differences were observed for total or sports knowledge. Pilates-only participants performed similarly to both groups. These findings suggest that exercise modality is not a major determinant of knowledge, consistent with reports showing weak associations between training type and nutrition literacy [ 22 ]. Similarly, participants engaging in strength training scored slightly higher on average, but differences were not statistically significant, further supporting the view that exercise engagement alone does not translate into superior knowledge. A novel finding was the variation in knowledge by hormonal phase. Women in perimenopause and menopause scored higher in both total and sports nutrition knowledge compared with those in the reproductive phase. Although based on a very small perimenopausal subgroup (n = 3), this trend is consistent with previous studies reporting modest positive associations between age and nutrition knowledge [ 19 ]. Older women may be more motivated to acquire nutrition information due to heightened concerns about bone health, cardiovascular disease, or recovery during midlife transitions. While these results must be interpreted cautiously, they suggest potential value in tailoring nutrition education to women’s needs across different life stages. Our findings showed no significant correlations between age, BMI, or years of practice and nutrition knowledge; however, regression analyses indicated that education and BMI independently predicted knowledge when tested separately. This partially reflects previous work, where BMI and education were also identified as significant predictors of nutrition knowledge [ 6 ]. Years of Pilates and yoga practice explained a large proportion of variance when modelled together, but multicollinearity limited interpretability. Taken together, these results indicate that while demographic and practice characteristics contribute to knowledge variation, broader social and informational influences are likely to play a more significant role. In summary, this study found that female Pilates and yoga practitioners demonstrated limited nutrition knowledge, with average scores below the threshold for good knowledge and variations observed across education level, practice type, and hormonal phase. Informal sources, such as the internet and fitness coaches, were the most frequently consulted for nutrition information. In conclusion, women practicing Pilates and yoga exhibited insufficient nutrition knowledge, particularly in sports nutrition, with variations evident across education, training habits, and hormonal phases. Addressing these gaps requires targeted, evidence-based nutrition education strategies that improve access to professional guidance, counter misinformation, and support women’s health, performance, and quality of life across the lifespan. Declarations Ethics Approval: This study was approved by the School of Biomedical Sciences Ethics Filter Committee at Ulster University (Approval No. FCBMS-25-075). All participants provided written informed consent. Author Contribution The author (A.A.) conceptualized and designed the study, collected and analyzed the data, wrote the manuscript, and prepared the figures. The author reviewed and approved the final manuscript. References Alaunyte I, Perry JL, Aubrey T (2015) Nutritional knowledge and eating habits of professional rugby league players: does knowledge translate into practice? 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J Int Soc Sports Nutr 14:26. https://doi.org/10.1186/s12970-017-0182-y Trakman GL, Forsyth A, Hoye R, Belski R (2018) Development and validation of a brief general and sports nutrition knowledge questionnaire and assessment of athletes' nutrition knowledge. J Int Soc Sports Nutr 15:17. https://doi.org/10.1186/s12970-018-0223-1 Tran MD, Holly RG, Lashbrook J, Amsterdam EA (2001) Effects of Hatha yoga practice on the health-related aspects of physical fitness. Prev Cardiol 4(4):165–170. https://doi.org/10.1111/j.1520-037x.2001.00542.x Zinn C, Schofield G, Wall C (2006) Evaluation of sports nutrition knowledge of New Zealand premier club rugby coaches. Int J Sport Nutr Exerc Metab 16(2):214–225. https://doi.org/10.1123/ijsnem.16.2.214 Additional Declarations No competing interests reported. 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Error bars represent 95% confidence intervals.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7906466/v1/9c3fbf2c92bd746b6c46a213.png"},{"id":94489866,"identity":"e4c90049-7143-40e8-b9fc-e910c2bf3eac","added_by":"auto","created_at":"2025-10-27 17:06:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":917900,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7906466/v1/c40d89fe-5a55-49ee-9ad0-5585564535b4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Nutritional Knowledge Among female Pilates and Yoga practitioners","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNutrition is a key determinant of athletic performance, recovery, and long-term health, enabling individuals to optimise energy availability, reduce injury risk, and support overall well-being [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Higher nutrition knowledge is associated with healthier dietary patterns, including greater intake of fruits and vegetables and lower consumption of energy-dense foods [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Conversely, limited knowledge has been linked with inadequate energy intake and potential risk of relative energy deficiency in sport, particularly among women [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. While research on athletes\u0026rsquo; nutritional knowledge is expanding, most studies focus on traditional team or endurance sports rather than mind\u0026ndash;body practices, which are increasingly popular worldwide and predominantly practised by women [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePilates and yoga combine physical performance with holistic approaches to health, stress reduction, and recovery. Although often perceived as low intensity, it involves sustained muscular engagement, balance, and flexibility, as some styles need moderate to vigorous aerobic effort [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Pilates sessions typically expend approximately 1.9\u0026ndash;2.6 kcal/min, requiring the activation of core and stabilising muscles that increase recovery demands [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Similarly, dynamic yoga styles can reach moderate-to-vigorous intensities, increasing cardiovascular demand and fluid loss, highlighting the importance of carbohydrate availability and hydration [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Preliminary evidence suggests that yoga practitioners are more likely to report healthier dietary behaviours than non-practitioners [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], but whether this reflects genuine knowledge or misconceptions remains uncertain.\u003c/p\u003e\u003cp\u003eFor women, nutrition demands also vary across hormonal phases and life stages. Iron deficiency affects 15\u0026ndash;50% of active females due to menstrual blood losses combined with training demands [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. During pregnancy and lactation, protein and energy requirements rise substantially, with recent systematic reviews estimating average energy intake in pregnant populations around 2,030\u0026thinsp;\u0026minus;\u0026thinsp;2,100 kcal/day, depending on trimester and region [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. On the other hand, measured energy requirements for active non-pregnant women remain less well documented. In later life, maintaining bone health during menopause requires adequate calcium and vitamin D intake, alongside attention to overall diet quality, to preserve bone mineral density and reduce fracture risk [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Despite recognition of these stage-specific demands, little is known about how nutrition knowledge among this population aligns with them. To our knowledge, this is the first study to investigate this in female Pilates or yoga practitioners. This study, therefore, aimed to evaluate the nutrition knowledge of female Pilates and yoga practitioners, with secondary objectives of examining differences by different factors. We hypothesised that mean knowledge scores would fall below the benchmark for good knowledge.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEthics approval\u003c/h2\u003e\u003cp\u003e This study was approved by the School of Biomedical Sciences Ethics Filter Committee at Ulster University (Project Number: FCBMS-25-075). Permission to recruit participants was granted by Mindful Movement Studio and House of Leyla Yoga Centre. All responses were anonymous, and the survey completion implied an informed consent. Reporting followed the STROBE checklist for cross-sectional studies.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants and recruitment\u003c/h3\u003e\n\u003cp\u003eEligible participants were women aged 18 years or older who were currently practising Pilates and/or yoga. Exclusion criteria included any health condition that prevented safe participation in these activities. Recruitment took place in July 2025 through Instagram posts, email invitations to studio members, and posters displayed at the two partner studios. A total of 45 individuals accessed the online survey. Of these, 11 only completed the initial demographic items and were excluded, and 4 provided partial responses but did not complete the full questionnaire. Thirty participants completed all survey items in full and were included in the analyses.\u003c/p\u003e\n\u003ch3\u003eSample size calculation\u003c/h3\u003e\n\u003cp\u003ePrior to recruitment, an a priori power analysis was conducted using G*Power version 3.1.9.7. Assuming a medium effect size (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.5) for differences in nutrition knowledge between subgroups, an α-level of 0.05, and power (1\u0026ndash;β) of 0.80, the minimum required sample size for independent-samples t-tests was 27 participants. We therefore aimed to recruit at least 30 participants to allow for incomplete responses and subgroup comparisons (ANOVA). Ultimately, 30 participants completed all survey items, exceeding the minimum required sample size and ensuring adequate power for the planned analyses.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eData were collected using Redcap, a secure web-based platform. The survey required approximately 15\u0026ndash;20 minutes to complete, and responses were stored securely before being exported in Excel format for analysis.\u003c/p\u003e\n\u003ch3\u003eSurvey design\u003c/h3\u003e\n\u003cp\u003eNutrition knowledge was adapted from the (ANKSQ), a validated tool designed to measure both general and sports-specific nutrition knowledge [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. One item referred to the 2017 World Anti-Doping Agency list, in which glycerol was prohibited; responses were scored accordingly, although later revisions of the WADA list replaced this with testosterone.\u003c/p\u003e\u003cp\u003eThe questionnaire comprised three main sections:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDemographics and training\u003c/strong\u003e\u003cp\u003eage, height, weight, BMI, education level, years of Pilates and yoga practice, other exercise habits, nutrition education, and primary sources of nutrition information.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHormonal phase\u003c/strong\u003e\u003cp\u003ehormonal stage (reproductive, pregnancy, lactation, perimenopause, or menopause) and any associated changes in diet or activity.\u003c/p\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003eNutrition knowledge\u003c/b\u003e:\u003c/h2\u003e\u003cp\u003eGeneral knowledge (macronutrients, micronutrients, hydration, alcohol, energy balance).\u003c/p\u003e\u003cp\u003eSports nutrition knowledge (nutrient timing, protein and carbohydrate needs, hydration, supplementation, anti-doping).\u003c/p\u003e\u003cp\u003eItems included multiple-choice, true/false, and ranking questions. Scores were calculated as the percentage of correct answers, with classifications of poor (\u0026lt;\u0026thinsp;49%), average (50\u0026ndash;65%), good (66\u0026ndash;75%), and excellent (\u0026ge;\u0026thinsp;76%) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe questionnaire was pilot tested among a small group (n\u0026thinsp;=\u0026thinsp;3) to ensure clarity and flow prior to wider distribution.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAnalyses were conducted in IBM SPSS Statistics version 29 (IBM Corp., Armonk, NY, USA). Descriptive statistics summarised sample characteristics and knowledge scores. Normality testing indicated that knowledge scores were normally distributed, whereas age was not. Parametric tests (t-tests, ANOVA, Pearson\u0026rsquo;s correlations, and linear regression) were therefore applied to knowledge outcomes, and non-parametric equivalents were used where appropriate, yielding consistent results.\u003c/p\u003e\u003cp\u003eOne-sample t-tests compared mean scores to adequacy thresholds (50% and 65%). Group differences by practice type, education, formal nutrition education, and hormonal phase were assessed with one-way ANOVA or Welch\u0026rsquo;s ANOVA, with Games\u0026ndash;Howell post hoc comparisons where required. Independent-samples t-tests compared participants with and without strength training. Pearson\u0026rsquo;s correlations tested associations between continuous predictors (age, BMI, years of practice) and knowledge scores. Separate linear regression models examined education and BMI as predictors; a combined model including years of Pilates and yoga practice was also tested, with multicollinearity assessed using variance inflation factors. Effect sizes were reported as Cohen\u0026rsquo;s d (t-tests), η\u0026sup2; (ANOVAs), and r (correlations). Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eParticipant Characteristics\u003c/h2\u003e\u003cp\u003eThirty participants completed the survey with a mean age of 35.8 years. The majority practised Pilates (73.3%), with smaller groups practising yoga only or both modalities. Half of the participants reported education beyond secondary school but below university level. Most had not undertaken formal nutrition training. Dietary habits were predominantly carnivorous, and most participants were in the reproductive phase of life. Full participant characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipant characteristics of Pilates and yoga practitioners (n\u0026thinsp;=\u0026thinsp;30). Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for continuous variables and n (%) for categorical variables.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (if applicable)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e25.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (36.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiploma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (26.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndergraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (23.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaster\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDoctoral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePractice type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYoga only\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePilates only\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (73.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEating habits\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarnivorous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (80.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVegetarian/Vegan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePescatarian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHormonal phase\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReproductive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (70.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerimenopause\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMenopause\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*\u003c/em\u003e Frequency (percentage) used for categorical variables.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eNutrition Knowledge Scores\u003c/h2\u003e\u003cp\u003eAs displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, participants demonstrated limited nutrition knowledge overall. General nutrition knowledge averaged 57.5% (SD\u0026thinsp;=\u0026thinsp;10.4), with nearly half classified as poor and another half as average. Only one participant achieved a good score, and none reached excellent. Sports nutrition knowledge was lower (49.4% \u0026plusmn; 16.2), with all participants falling in poor or average categories. Total knowledge averaged 48.9% (SD\u0026thinsp;=\u0026thinsp;9.4; range 31.6\u0026ndash;65.8%). Scores did not differ from the 50% adequacy benchmark (t (29) = \u0026minus;\u0026thinsp;0.62, p\u0026thinsp;=\u0026thinsp;.54) but were significantly below the 65% good knowledge threshold (t (29) = \u0026minus;\u0026thinsp;9.39, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, d = \u0026minus;\u0026thinsp;1.71). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that participants most frequently cited internet/social media (65%) and fitness coaches (48%) as primary sources of nutrition information, while dietitians and academic journals were the least reported.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrimary sources of nutrition information ranked by participants (n and mean ranks).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean Rank (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eParticipants (n)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInternet / social media\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.3 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFitness Coach\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.6 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDoctor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.4 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDietitian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.8 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003e*\u003c/em\u003eRankings based on participant self-report. *p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eDifferences in Nutrition Knowledge Scores between Groups\u003c/h2\u003e\u003cp\u003eGeneral knowledge scores differed significantly by practice type (F (2, 65.96)\u0026thinsp;=\u0026thinsp;13.59, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Participants who practised yoga scored higher in general nutrition knowledge than those practising both modalities (p\u0026thinsp;=\u0026thinsp;.027). No significant differences were found in sports or total knowledge (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMean knowledge scores (total, general, sports) compared with adequacy benchmarks (50% and 65%), including one-sample t-tests, p-values, and Cohen\u0026rsquo;s d.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePractice type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGeneral (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSports (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYoga only\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e50.0\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e61.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e48.5\u0026thinsp;\u0026plusmn;\u0026thinsp;20.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePilates only\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e55.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e51.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePilates\u0026thinsp;+\u0026thinsp;Yoga\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e61.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e41.2\u0026thinsp;\u0026plusmn;\u0026thinsp;25.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*\u003c/em\u003eWelch\u0026rsquo;s correction applied where assumptions were violated.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; **p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNutrition knowledge scores stratified by education level.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal knowledge (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGeneral knowledge (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSports knowledge (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e46.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e54.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e44.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiploma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e50.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e61.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e47.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndergraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e50.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e55.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e53.5\u0026thinsp;\u0026plusmn;\u0026thinsp;23.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaster\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e55.3\u0026thinsp;\u0026plusmn;\u0026thinsp;17.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e56.9\u0026thinsp;\u0026plusmn;\u0026thinsp;20.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e56.9\u0026thinsp;\u0026plusmn;\u0026thinsp;23.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDoctoral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e55.3 \u0026plusmn; \u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e64.7 \u0026plusmn; \u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e52.9 \u0026plusmn; \u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e57.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e49.4\u0026thinsp;\u0026plusmn;\u0026thinsp;16.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003e*\u003c/em\u003e Significant differences across education levels \u003cem\u003e(F (4, 175)\u0026thinsp;=\u0026thinsp;4.67, p\u0026thinsp;=\u0026thinsp;.001, η\u0026sup2; = .096)\u003c/em\u003e A one-way ANOVA\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; **p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eEducation: participants holding only primary education score lower than those with higher qualifications. Differences were also evident in sports and total knowledge (p\u0026thinsp;\u0026lt;\u0026thinsp;.05).\u003c/p\u003e\u003cp\u003eNutrition education: Unexpectedly, participants without formal nutrition education scored higher in general knowledge (M\u0026thinsp;=\u0026thinsp;58.4%, SD\u0026thinsp;=\u0026thinsp;10.6) than those with such education (M\u0026thinsp;=\u0026thinsp;51.5%, SD\u0026thinsp;=\u0026thinsp;5.0), t (62.7)\u0026thinsp;=\u0026thinsp;5.21, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, d\u0026thinsp;=\u0026thinsp;0.69. No differences were identified for sports or total knowledge.\u003c/p\u003e\u003cp\u003eHormonal phase: Participants in the reproductive phase scored lower than those in perimenopause (\u0026ndash;10.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and menopause (\u0026ndash;9.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) for total knowledge and lower than both groups in sports knowledge (ps\u0026thinsp;\u0026lt;\u0026thinsp;.001). See Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e below. Information provided in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e details that the mean total nutrition knowledge score was higher among participants who reported strength training compared with those who did not.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNutrition knowledge scores stratified by formal nutrition education.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGeneral (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSports (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNutrition education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e58.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e48.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo nutrition education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.0\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e51.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54.4 \u0026plusmn;\u0026thinsp;29.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*\u003c/em\u003eValues are mean\u0026thinsp;\u003cem\u003e\u0026plusmn;\u0026thinsp;SD.\u003c/em\u003e Welch\u0026rsquo;s correction applied where assumptions were violated.\u003c/p\u003e\u003cp\u003e\u003cem\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; **p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNutrition knowledge scores by hormonal phase, n\u0026thinsp;=\u0026thinsp;30.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHormonal phase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGeneral (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSports (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReproductive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e47.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e57.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e47.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerimenopause\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e57.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e60.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e66.7\u0026thinsp;\u0026plusmn;\u0026thinsp;29.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMenopause\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e55.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e49.0\u0026thinsp;\u0026plusmn;\u0026thinsp;21.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e57.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e49.4\u0026thinsp;\u0026plusmn;\u0026thinsp;16.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant variations in total knowledge (F (2, 57.41)\u0026thinsp;=\u0026thinsp;37.09, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and sports knowledge (F (2, 42.67)\u0026thinsp;=\u0026thinsp;25.64, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) across phases by \u003cem\u003eWelch\u0026rsquo;s\u003c/em\u003e correction, applied where assumptions were violated. \u003cem\u003eᵃ\u003c/em\u003e Perimenopause group \u003cem\u003e(n\u0026thinsp;=\u0026thinsp;3);\u003c/em\u003e interpret with caution\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; **p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNutrition knowledge scores by strength training participation (n\u0026thinsp;=\u0026thinsp;30).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrength training (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo strength training (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean difference (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e(df)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal knowledge (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e64.0\u0026thinsp;\u0026plusmn;\u0026thinsp;50.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e40.0\u0026thinsp;\u0026plusmn;\u0026thinsp;51.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;24.0 [\u0026ndash;63.0, 14.0]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;1.30(27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral knowledge (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e58.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e56.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;2.6 [\u0026ndash;10.5, 5.3]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;0.67(28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.510\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSports knowledge (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e52.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e47.1\u0026thinsp;\u0026plusmn;\u0026thinsp;18.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;5.0 [\u0026ndash;17.3, 7.2]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;0.84(28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.406\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*\u003c/em\u003e Independent-samples t tests were used.\u003c/p\u003e\u003cp\u003e\u003cem\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; **p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eCorrelations\u003c/h2\u003e\u003cp\u003eAs can be concluded from Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, no significant correlations were observed between age, BMI, or years of practice and knowledge scores. Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e shows regression analyses indicated that education and BMI predicted knowledge scores when tested separately. Years of yoga and Pilates practice together explained substantial variance (R\u0026sup2; = .75). However, it was detected when predictors were combined, limiting interpretation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePearson correlations between participant characteristics (age, BMI, years of practice) and knowledge scores.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGeneral Knowledge (r)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSports Knowledge (r)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal Knowledge (r)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePilates years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYoga years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*\u003c/em\u003eNo significant difference by Pearson\u0026rsquo;s correlation coefficients \u003cem\u003e(r). ᵃ\u003c/em\u003e Positive values indicate higher knowledge with higher predictor levels; negative values indicate inverse associations.\u003c/p\u003e\u003cp\u003e\u003cem\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; **p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRegression models predicting nutrition knowledge scores (education, BMI, years of practice).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel / Predictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE B\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eR\u0026sup2; (Adj. R\u0026sup2;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e(df)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel 1: Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.048 (.043)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e9.01 (1,28)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e30.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel 2: BMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.053 (.047)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e9.54 (1,28)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;3.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel 3: Yoga\u0026thinsp;+\u0026thinsp;Pilates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.749 (.725)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e31.35 (2,21)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYoga years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePilates years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;6.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;2.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;7.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*\u003c/em\u003e Values are unstandardized regression coefficients \u003cem\u003e(B)\u003c/em\u003e with standard errors \u003cem\u003e(SE B). ᵃ\u003c/em\u003e Multicollinearity was detected when all predictors were entered simultaneously; therefore, predictors were tested in separate models.\u003c/p\u003e\u003cp\u003e\u003cem\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; **p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to assess nutrition knowledge among female yoga and Pilates practitioners, with particular attention to differences across education, training habits, and hormonal phases. Addressing this gap makes an important contribution, as no previous research has assessed nutritional knowledge of this population. Overall, participants demonstrated only \u0026ldquo;average\u0026rdquo; knowledge (48.9%), well below the benchmark for \u0026ldquo;good\u0026rdquo; knowledge, with sports nutrition being a particular weakness. Most participants relied on the internet and social media sources rather than dietitians or academic materials, which may explain the prevalence of misconceptions. Subgroup analyses suggested that education level, practice type, and hormonal status influenced knowledge scores, although unexpectedly, formal nutrition education did not consistently predict higher knowledge. Despite some limitations, such as small sample size and self-reported data limit generalisability and preclude causal inference. findings carry important practical implications.\u003c/p\u003e\u003cp\u003eAs participants most frequently relied on the internet or social media (65%), while academic journals (10%) were rarely consulted. This reliance on informal sources has also been observed in other active populations and is strongly associated with exposure to misinformation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The limited engagement with dietitians (18%) is concerning, as professional guidance is known to support healthier dietary behaviours [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEducation was a consistent determinant of nutrition knowledge. Participants with higher academic qualifications scored better, and regression models confirmed education as a significant predictor, in line with evidence linking academic attainment to health and nutrition literacy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Unexpectedly, participants with formal nutrition education did not outperform those without, echoing earlier reports that prior training does not always predict higher knowledge [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This may reflect differences in the scope or quality of previous education or difficulties with long-term retention, suggesting that nutrition training should be reinforced regularly.\u003c/p\u003e\u003cp\u003eKnowledge scores also differed by practice type, with yoga-only participants achieving higher general nutrition scores than those practising both modalities, although no differences were observed for total or sports knowledge. Pilates-only participants performed similarly to both groups. These findings suggest that exercise modality is not a major determinant of knowledge, consistent with reports showing weak associations between training type and nutrition literacy [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Similarly, participants engaging in strength training scored slightly higher on average, but differences were not statistically significant, further supporting the view that exercise engagement alone does not translate into superior knowledge.\u003c/p\u003e\u003cp\u003eA novel finding was the variation in knowledge by hormonal phase. Women in perimenopause and menopause scored higher in both total and sports nutrition knowledge compared with those in the reproductive phase. Although based on a very small perimenopausal subgroup (n\u0026thinsp;=\u0026thinsp;3), this trend is consistent with previous studies reporting modest positive associations between age and nutrition knowledge [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Older women may be more motivated to acquire nutrition information due to heightened concerns about bone health, cardiovascular disease, or recovery during midlife transitions. While these results must be interpreted cautiously, they suggest potential value in tailoring nutrition education to women\u0026rsquo;s needs across different life stages.\u003c/p\u003e\u003cp\u003eOur findings showed no significant correlations between age, BMI, or years of practice and nutrition knowledge; however, regression analyses indicated that education and BMI independently predicted knowledge when tested separately. This partially reflects previous work, where BMI and education were also identified as significant predictors of nutrition knowledge [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Years of Pilates and yoga practice explained a large proportion of variance when modelled together, but multicollinearity limited interpretability. Taken together, these results indicate that while demographic and practice characteristics contribute to knowledge variation, broader social and informational influences are likely to play a more significant role.\u003c/p\u003e\u003cp\u003eIn summary, this study found that female Pilates and yoga practitioners demonstrated limited nutrition\u003c/p\u003e\u003cp\u003eknowledge, with average scores below the threshold for good knowledge and variations observed across\u003c/p\u003e\u003cp\u003eeducation level, practice type, and hormonal phase. Informal sources, such as the internet and fitness coaches,\u003c/p\u003e\u003cp\u003ewere the most frequently consulted for nutrition information. In conclusion, women practicing Pilates and yoga exhibited insufficient nutrition knowledge, particularly in sports nutrition, with variations evident across education, training habits, and hormonal phases. Addressing these gaps requires targeted, evidence-based nutrition education strategies that improve access to professional guidance, counter misinformation, and support women\u0026rsquo;s health, performance, and quality of life across the lifespan.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics Approval:\u003c/h2\u003e\u003cp\u003e This study was approved by the School of Biomedical Sciences Ethics Filter Committee at Ulster University (Approval No. FCBMS-25-075). All participants provided written informed consent.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe author (A.A.) conceptualized and designed the study, collected and analyzed the data, wrote the manuscript, and prepared the figures. The author reviewed and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlaunyte I, Perry JL, Aubrey T (2015) Nutritional knowledge and eating habits of professional rugby league players: does knowledge translate into practice? 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Int J Sport Nutr Exerc Metab 16(2):214\u0026ndash;225. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1123/ijsnem.16.2.214\u003c/span\u003e\u003cspan address=\"10.1123/ijsnem.16.2.214\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"[email protected]","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":"ANKSQ, women athletes, sports nutrition, fitness nutrition, nutrition knowledge","lastPublishedDoi":"10.21203/rs.3.rs-7906466/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7906466/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eto assess the nutritional knowledge among female Pilates and yoga practitioners. Additionally, we will explore associated factors such as hormonal phase, education status, and practising other types of training.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e thirty participants from Mindful movement studio and House of Lyla in Gravesend, Kent completed the validated Abridged Nutrition Knowledge Survey Questionnaire (ANKSQ). Data were analysed using descriptive statistics, knowledge categorisation, one-sample t-tests against adequacy benchmarks, subgroup comparisons (ANOVA, Welch\u0026rsquo;s ANOVA with Games\u0026ndash;Howell tests, and independent-samples t-tests), Pearson\u0026rsquo;s correlations, and linear regression. Effect sizes were reported for all analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003emean score was 48.9% (SD 9.4), significantly below the \u0026ldquo;good\u0026rdquo; knowledge benchmark (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Nearly half of participants had \u0026ldquo;poor\u0026rdquo; knowledge, and none had \u0026ldquo;excellent\u0026rdquo;. Higher education and perimenopausal/menopausal status were linked to better scores; practice type and training habits had a limited impact. Participants primarily used internet/social media or fitness coaches for nutrition information; evidence-based sources (dietitians, academic journals) were seldom used.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003efemale Pilates and yoga practitioners demonstrated limited nutrition knowledge, shaped primarily by an educational background rather than training behaviours. The heavy reliance on informal sources highlights the need for accessible, evidence-based nutrition education tailored to this population and across women\u0026rsquo;s life stages.\u003c/p\u003e","manuscriptTitle":"Nutritional Knowledge Among female Pilates and Yoga practitioners","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 23:56:55","doi":"10.21203/rs.3.rs-7906466/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","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":"a63a242d-c090-43b8-9b3b-6e1ab3d98284","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T15:00:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-21 23:56:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7906466","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7906466","identity":"rs-7906466","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}