The Effect of Culinary Medicine to Enhance Protein Intake on Muscle Quality in Older Adults: A Randomized Controlled Trial

The Effect of Culinary Medicine to Enhance Protein Intake on Muscle Quality in Older Adults: A Randomized Controlled Trial | 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 The Effect of Culinary Medicine to Enhance Protein Intake on Muscle Quality in Older Adults: A Randomized Controlled Trial Shannon Galyean, Michelle Alcorn, Justin Chavez, Surya Raj Niraula, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5868973/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 May, 2025 Read the published version in Aging Clinical and Experimental Research → Version 1 posted 10 You are reading this latest preprint version Abstract Background Age-related muscle loss can be decreased with increased protein intake. Recent evidence suggests that increasing animal-based protein such as lean beef can be the most effective for age-related muscle repair and growth. Culinary medicine (CM) is a science-based field to teach people the art of food and cooking with the science of medicine to improve health. Aim This study aimed to assess the impact of a digital culinary medicine education program emphasizing lean beef on protein intake and muscle quality among community-dwelling senior adults. Methods A 16-week randomized study compared a culinary medicine intervention group (CM) to a control group (CN). Among 47 senior adults assessed for eligibility, 28 participants completed the intervention. The CM invention included weekly cooking demonstration and nutrition education videos. Protein intake, cooking effectiveness, physical activity, and nutrition knowledge were assessed with questionnaires while muscle quality, vitamin B 12 , folate, and creatinine levels were objectively measured. Results Muscle quality measurements showed a significant difference in change in muscle mass between groups ( P = 0.041). Higher protein intake was seen in the CM group compared to a decrease in protein intake seen among the CN group. However, there was no between-group difference in protein intake from the pre-study ( P = 0.454). Similar results were seen with the other measurements from baseline. Conclusion The results suggest that this CM intervention was associated with improved muscle mass. There is also potential for this type of intervention to increase protein intake. Clinical Trials ID: NCT06157385 Animal Protein Beef Culinary Medicine Lifestyle Medicine Muscle Quality Nutrition Figures Figure 1 1. Introduction Aging is associated with a decline in muscle mass, strength, and physical function, which can lead to sarcopenia and frailty[ 1 ]. This deterioration of muscle and physical capabilities impacts an individual's functional independence and quality of life. Dietary protein stimulates muscle protein synthesis (MPS). Evidence suggests that optimal protein intake for an older individual is greater than the Recommended Dietary Allowance (RDA)[ 2 , 3 ]. In addition, recent research demonstrates that increased oxidation and inflammation play a role in muscle protein breakdown that occurs during aging. Therefore, nutritional interventions that reduce oxidation or inflammation along with higher protein intakes may enhance MPS[ 4 ]. Food intake, including protein-rich foods like red meat, has been shown to decline with age[ 5 – 7 ]. Barriers to consuming protein-rich foods include reductions in taste and smell, dentition and dexterity, and changes in living situation[ 8 ]. Nutritional interventions that can improve eating behaviors, diet quality, and stimulate MPS in older adults are necessary to help prevent, manage, and promote recovery of sarcopenia. To reduce potential barriers of red meat consumption in community-dwelling older adults, an additional strategy may be the use of cooking demonstrations, or culinary medicine that imparts knowledge about healthy cooking to improve the dietary habits of individuals at risk of sarcopenia. With this approach, people will be educated about age-appropriate, healthy eating behaviors and equipped with basic cooking skills to incorporate nutritious food into their daily diet [ 9 , 10 ]. A systematic review concluded that culinary interventions such as cooking classes effectively improved attitudes, self-efficacy, and healthy eating in children and adults [ 11 ]. A recent study using cooking videos to encourage the consumption of calcium-rich foods showed that the subjects gained knowledge, were motivated to consume calcium-rich foods, and video demonstrations were accepted as an effective communication channel to impart cooking skills [ 12 ]. Additionally, it is suggested that cooking at home improves adherence to healthy nutrition, thereby reducing chronic illness risks [ 13 ]. Another study showed an association between cooking frequency and improved diet quality with a higher overall Healthy Eating Index (HEI) – 2015 scores [ 14 ]. Older adults may not be aware of their changing nutrient needs and therefore may lack the skills to prepare nutritionally adequate foods appropriately. Thus, cooking demonstrations can be a novel strategy to improve diet quality in older adults and promote and augment at-home cooking. Culinary medicine (CM) is an evidence-based field that combines skills of preparing, cooking, and presenting food with the science of medicine to accomplish potential improvements in eating behaviors and health outcomes [ 15 ]. The goal of CM is to help people improve their diet quality which assists them in their medical regimen to produce an effective treatment [ 10 ]. A tailored CM program for older adults can be an effective strategy that could reduce barriers to protein intake that will enable older adults to age well and productively. Different types of protein may have different effects on sarcopenia risk. To accurately assess protein intake and the impact on muscle strength, function, and mass, a grip strength dynamometer, short physical performance battery tests (SPPB), and body composition are promising outcome measurements. Assessing muscle strength, function, and muscle mass is necessary to identify the intervention needed to address the risk of sarcopenia.[ 16 ]. Therefore, our study aimed to examine how an online CM intervention, emphasizing convenient ways to increase lean beef intake, could improve protein intake to see how this intervention could affect older adults’ muscle strength and mass. 2. Material and Methods 2.1 Study Design and Study Participants A 16-week single-center, parallel-group, randomized study compared a culinary medicine intervention group (CM) to a control group (CN) on their protein intake, cooking effectiveness, muscle quality, vitamin B 12 , folate, creatinine levels, physical activity, and nutrition knowledge. The study was conducted at Texas Tech University Nutrition and Metabolic Health Initiative (NMHI), Lubbock, TX. The study population included independent senior adults who were able to regularly perform physical activity and prepare their meals. Recruitment began July 2023 and concluded in January 2024. Participants were excluded from the study if they were less than 65 years old, had limited mobility, intake of nicotine, excessive alcohol, and/or use of drugs (i.e., amphetamines, cocaine, marijuana, and opiates), cancer, transplant, pacemaker, renal disorders, or Type 1 diabetes or Type 2 diabetes with insulin therapy, did not have access to a computer, smartphone, or tablet, or if they scored 4 or more points on the SARC-F sarcopenia screening tool. This is a screening tool for sarcopenia that has been validated by research to adequately identify this in older adults.[ 17 ] The study was approved by the institutional review board of Texas Tech University (IRB2023-505). All participants provided written informed consent. Participants were randomly allocated to two groups, the CM or CN group. Randomization was implemented with a randomly generated sequence created from an online randomizing tool, randomizer.org. After this sequence was generated, every other number was assigned to the CM group starting with the first number. Participants were assigned these numbers with their subject codes in the order they were admitted into the study. Before the start of the intervention, participants in both groups were provided a handout that offered information on healthful dietary habits for older adults from the Academy of Nutrition and Dietetics (AND) and another one that provided examples of various exercises for different muscle groups and purposes that were designed for seniors from SeniorsMobility.org. Both groups received an activity monitor (Garmin Vivofit 4) to help monitor their activity level. Both groups were instructed to include one meal of lean beef three times per week (lunch or dinner, 400 kcal/30gm protein). An adequate amount of lean beef was provided for participants, allowing three servings a week to circumvent possible obstacles to consuming beef, like its cost. This beef was purchased from a local organization affiliated with the Texas Tech University College of Agricultural Sciences and Natural Resources and stored in a freezer according to proper USDA guidelines. Before receiving beef, participants were provided a physical handout with instructions from the USDA Kitchen Companion handbook on safely storing and thawing frozen beef at home. Both groups were provided two lean beef-based recipes each week. Experienced research team members, including two registered dietitians and a culinary professor, collaborated to design this CM program (recipes, cooking demonstrations, and nutritional education videos) to increase awareness and counter common nutritional issues older adults face. The recipes included at least a serving of lean beef, 400 kcal, and 30 grams of protein and utilized multiple cuts of beef, including lean ground beef, sirloin, roast beef, chuck roast, and bottom round roast. Preparation technique, time, level of difficulty, and the cost of ingredients were considered, as these are potential barriers to consuming and preparing red meat at home. This program focused on preparation methods that are tender and lean as older adults can experience difficulty in chewing and a decline in appetite with high fat and fibrous red meats. All recipes were tested and evaluated based on sensory characteristics such as appearance, odor, texture, and flavor. Members of the CN and CM groups received different forms of culinary instruction to promote protein intake. The CN group only received weekly online recipes and exercise recommendation handouts without the CM intervention. While the CN group received only the recipes and exercises, the members of the CM group were additionally provided weekly (1) cooking demonstration videos that provided further step-by-step visual instruction on how to prepare these meals and (2) nutrition education videos covering nutritional topics that were especially relevant to older adults. 2.2 Questionnaires To measure protein intake, a modified version of the rapid self-administered dietary protein food frequency questionnaire was used. This questionnaire contains 20 items evaluating the weekly intake of different types of meat, dairy, eggs, and beans.[ 18 ] This outcome measure was changed to the primary outcome after the trial commenced due to reviewers’ comments and recommendations of the authors’ preliminary data that was published stating that this intervention had a strong dietary focus. The Physical Activity Scale for the Elderly (PASE) questionnaire assessed physical activity habits and how they might have altered throughout the study. This questionnaire has demonstrated a reliable representation of physical activity rates in free-living older adult populations.[ 19 ] Based on modifications to a previous questionnaire to assess the effectiveness of the CM intervention in education, a multiple-choice nutrition knowledge questionnaire was used to assess knowledge related to the protein and micronutrient composition of various foods, average dietary needs, and physiological processes related to skeletal muscle maintenance. The research team also modified a previous resource, the Cooking Effectiveness Questionnaire, to assess the participants' experience and feelings about cooking. This questionnaire was used to assess the participant’s adherence to the intervention as well as their experience implementing recipes from the intervention. This questionnaire was modified between the groups to include questions related to cooking and nutrition education videos for the CM group. Information from these questionnaires further assessed the ability of this CM intervention to encourage healthful behavioral changes, like cooking at home, performing physical activity, addressing common nutritional concerns for older adults, as well as the comprehension of nutritional concepts. 2.3 Muscle Quality Muscle strength has been determined to be one of the key fields when assessing muscle quality, and handgrip strength has been shown to provide an accurate representation of changes in overall strength.[ 20 ] Muscle strength is measured by grip strength using a digital hand-held dynamometer (Camry EH101), focused on the change in strength over four months between the two groups. A Tanita MC-780U bioelectric impedance analysis (BIA) scale was used to assess changes in multiple fields related to muscle and body composition, including muscle mass in pounds, weight in pounds, and BMI. Previous research has demonstrated that BIA scans accurately assess muscle mass, another key field for determining muscle quality.[ 21 ] This machine automatically calculated BMI after inputting height, which researchers measured using a stadiometer. Muscle mass was assessed by BIA. This outcome focused on the change in muscle mass over the four months between CM- and CN-group. The final major field used to determine muscle quality is muscle function, and changes in this field were assessed with a Short Physical Performance Battery (SPPB) exam. This a resource that has been determined to provide a reliable assessment of muscle function and consists of a series of exercises related to the three categories of balance, gait speed, and chair standing.[ 22 ] A researcher read from a script with descriptive instructions on these exercises for the participants, and they were scored from zero to four points in each of these categories based on their performance for a total score ranging from zero to twelve points. 2.4 Muscle Synthesis Finally, blood samples were collected at baseline and following the completion of the study. Participants were instructed to fast 8 hours before these blood draws were carried out by an experienced phlebotomist. Then, they were analyzed to measure serum vitamin B12, folate, and creatinine values. These micronutrients all act as cofactors in the process of MPS and increases in these values demonstrate improvements in the activity rate of this process. 2.5 Statistical Analysis The study included the final 13 participants in the intervention arm and 15 in the control arm for the analysis. The mean change in protein intake in between the intervention and control groups as reported in a literature.[ 23 ] Enrolling the participants in each group provides 95% power in estimation to detect 23.2g/day mean difference of change in the protein intake between the groups with 17.48g/day pooled standard deviation at 95% Confidence Interval (CI). Data were entered into Microsoft Excel and analyzed with IBM SPSS version 29.0.0.0. Descriptive statistics were used to describe background characteristics of the participants in terms of mean, standard deviation, and percentage in two groups. Cross-tabulation was done to examine the association between gender and the two groups. All the continues outcome variables were tested for normality (p > 0.05) using two-sample Kolmogorov-Smirnov test. Independent sample t-test was used for post values and post scores. Univariate ANOVA was used to examine association of different parameters between the groups after adjusting possible confounders. The probability of significance was set at 5% level of significance. 3. Results A total of 47 participants were assessed for eligibility. Ten (21.2%) were excluded during screening due to failing to meet inclusion criteria or losing contact. Thirty-four participants were randomized: 15 to the CM and 19 to the CN. A total of 13 in the CM, compared with 15 in the CN group, completed the 16-week study. Six (17.6%) participants withdrew or dropped out before the completion of the study due to medical reasons unrelated to the study, family reasons, lost contact, or no longer wanting to participate in the study. See the CONSORT study flow diagram (Fig. 1 ) for the study details. The baseline characteristics of the groups are presented in Table 1 . The study included a greater proportion of females [78.6% (22 of 28)]. The CM group’s mean age, weight, and body mass index (BMI) were 71.54 ± 4.48 years, 183.58 ± 43.80 lbs, and 29.17 ± 5.12 kg/m 2 , respectively. In the CN group, they were slightly older (74.00 ± 5.68 years) but had lower weight (161.01 ± 22.35 lbs) and BMI (27.47 ± 4.31 kg/m 2 ). The CN group has higher PASE and lower knowledge scores than the CM group. Regarding diet, the CN group consumed more protein than the CM group. Meanwhile, the CM group had greater grip strength and muscle mass than the CN group. However, the CN group had slightly higher SPPB scores than the CM group. Finally, the CM group had higher levels of muscle synthesis biomarkers than the CN group. The demographic characteristic, age (t=-1.24, p = 0.220) and gender ( \(\:{\chi\:}_{c}^{2}\) =2.51, p = 0.113) were homogeneously distributed among the groups. Before the intervention, pre-values and pre-scores were insignificant between the groups (P > 0.05). The incomplete numbers in the CM group are the missing cases. Table 1 Baseline characteristics of of different variables between the groups Variables Culinary Medicine b Control b Total b Male/Female [#, ( %)] 5 (38.5)/8 (61.5) 1 (0.06)/14 (93.3) 6 (21.4)/22 (78.6) Mean N SD Mean N SD Mean N SD P c Age 71.54 13 4.48 74.00 15 5.68 72.86 28 5.22 0.220 Knowledge 69.62 11 9.37 65.61 15 12.60 67.31 26 11.32 0.384 PASE 52.75 10 11.93 59.33 15 16.24 56.70 25 14.77 0.284 Protein (g d ) 55.52 11 36.88 60.68 15 24.43 58.50 26 29.75 0.671 MS e dom. f (kg g ) 29.17 13 12.22 22.97 15 6.28 25.85 28 9.84 0.117 Non-Dominated Hand (kg) 26.58 13 11.27 21.41 15 6.54 23.81 28 9.25 0.162 Wt (lbs h ) 183.58 13 43.80 161.01 15 22.35 171.49 28 35.26 0.111 BMI (kg/m 2 ) i 29.17 13 5.12 27.47 15 4.31 28.26 28 4.69 0.350 Muscle Mass (lbs) 116.40 13 29.69 97.93 15 11.31 106.51 28 23.37 0.052 SPPB j 10.23 13 1.64 10.87 15 .99 10.57 28 1.35 0.238 Vitamin B 12 821.85 13 458.76 776.14 14 379.00 798.15 27 411.70 0.779 Creatinine .92 13 .23 .84 15 .16 .88 28 .19 0.327 Folate 17.28 13 3.72 17.19 15 4.78 17.23 28 4.25 0.953 a All the variables were tested for normality (p > 0.05) using two-sample Kolmogorov-Smirnov test. b All values are mean ± standard deviation. c P value refers to between-group differences were calculated using the chi-squared test for categorical variables or t-test for continuous variables. d g: gram e MS: muscle strength f dom.: dominant g kg: kilogram h lbs: pounds i kg/m 2 : kilograms/meter 2 * Statistically significant j Short Physical Performance Battery tests There was a slight increase of protein intake seen in the CM group compared to a slight decrease in protein intake seen among the CN group. However, there was no between-group difference in protein intake from the pre-study ( P = 0.454; Table 2 ). Similar results were seen with PASE and knowledge scores from baseline ( P = 1.00; P = 0.785, respectively). When comparing weight and body composition, there were no significant differences between groups in change from baseline measurements ( P = 0.103; P = 0.300, respectively). Muscle quality measurements showed that there was a significant difference in change in muscle mass between groups ( P = 0.041). However, for measurements of muscle strength in both dominant and non-dominant hands, there was no between-group difference in the muscle strength change from the pre-study (dominant: P = 0.122 and non-dominant: P = 0.207). Additionally, there were no between-group differences in the muscle function change from baseline ( P = 0.360). Lastly, there were no between-group differences in vitamin B 12 , folate, or creatinine change from pre-study measurements ( P = 0.270; P = 0.441; P = 0.430, respectively) Table 2 Mean characteristics of participants at pre- and post-study a CM (n = 13) b CN (n = 15) b Variable Pre-Study Post-Study Pre-Study Post-Study Post-Study Between Group Differences P c Knowledge 69.62 ± 9.37 70.47 ± 9.65 65.61 ± 12.60 69.30 ± 8.22 1.17 0.785 PASE 52.75 ± 11.93 60.00 ± 17.32 59.33 ± 16.24 60.00 ± 11.28 0.00 1.00 Protein Intake (g d ) 55.52 ± 36.88 60.02 ± 21.40 60.68 ± 24.43 52.89 ± 17.85 7.12 0.454 MS e dom. f (kg g ) 29.17 ± 12.22 29.24 ± 10.80 22.97 ± 6.28 23.57 ± 5.98 5.67 0.122 MS non-dom. (kg) 26.58 ± 11.27 26.15 ± 10.22 21.41 ± 6.54 21.89 ± 6.28 4.27 0.207 Weight (lbs h ) 183.58 ± 43.80 184.60 ± 44.94 161.01 ± 22.35 161.01 ± 21.92 23.59 0.103 Body Mass Index (kg/m 2 ) i 29.17 ± 5.12 29.42 ± 5.65 27.47 ± 4.31 27.41 ± 4.36 2.00 0.300 Muscle Mass (lbs) 116.40 ± 29.69 116.97 ± 30.05 97.93 ± 11.31 97.31 ± 10.52 19.66 0.041 * SPPB j 10.23 ± 1.64 10.77 ± 1.36 10.87 ± .99 11.20 ± 10.8 -0.43 0.360 Vitamin B 12 821.85 ± 458.75 657.23 ± 310.99 776.14 ± 379.00 830.27 ± 470.88 -173.04 0.270 Creatinine 0.92 ± 0.23 0.95 ± 0.25 0.84 ± 0.16 0.89 ± 0.15 0.06 0.441 Folate 17.28 ± 3.72 16.39 ± 4.67 17.19 ± 4.78 17.64 ± 3.30 -4.47 0.430 a The independent sample t -test was used to compare between-group differences in the post-study. b All values are mean ± standard deviation. c P value refers to between-group differences by independent sample t- test d g: gram e MS: muscle strength f dom.: dominant g kg: kilogram h lbs: pounds i kg/m 2 : kilograms/meter 2 * Statistically significant j Short Physical Performance Battery tests We used Univariate ANOVA to examine the association of different parameters between the groups after adjusting possible confounders ( Gender and Age ). The Post-Protein Intake was insignificant between the groups, even after adjusting the Gender and Age . The CM group had an average Post-Protein Intake of 60 grams (men: ~78g, women: ~51g), and the CN group had 53 grams (men: 95g, women: 48g). These differences weren’t statistically significant. Table 3 Univariate ANOVA for different parameters between groups adjusting age and gender Parameter B Std. Error t Sig. 95% Confidence Interval Lower Bound Upper Bound Post Protein(gm) Intercept 94.31 55.17 1.709 0.111 -24.876 213.497 Age -0.63 0.741 -0.85 0.411 -2.231 0.972 Group 0.238 8.374 0.028 0.978 -17.853 18.33 Sex(M/F) 46.761 14.918 3.135 0.008 14.534 78.989 Group*Gender -19.135 17.933 -1.067 0.305 -57.877 19.608 Post Dominated Hand (Kg) Intercept 35.642 14.967 2.381 0.026 4.602 66.682 Age -0.179 0.201 -0.89 0.383 -0.596 0.238 Group -0.904 2.499 -0.362 0.721 -6.086 4.279 Sex(M/F) 17.623 5.402 3.262 0.004 6.42 28.825 Group*Gender 0.004 6.235 0.001 1 -12.927 12.934 Post Non-Dominated Hand (Kg) Intercept 36.163 14.825 2.439 0.023 5.496 66.83 Age -0.211 0.199 -1.06 0.3 -0.623 0.201 Group -1.174 2.395 -0.49 0.629 -6.128 3.78 Sex(M/F) 20.252 5.362 3.777 0.001 9.16 31.345 Group*Gender -3.946 6.155 -0.641 0.528 -16.679 8.788 Post Wt(lbs) Intercept 124.234 75.191 1.652 0.112 -31.311 279.779 Age 0.496 1.011 0.491 0.628 -1.595 2.587 Group -1.476 12.146 -0.121 0.904 -26.602 23.651 Sex(M/F) 0.946 27.198 0.035 0.973 -55.317 57.209 Group*Gender 67.556 31.22 2.164 0.041 2.972 132.14 Post BMI Intercept 24.255 14.016 1.731 0.097 -4.739 53.249 Age 0.045 0.188 0.241 0.812 -0.344 0.435 Group -0.102 2.264 -0.045 0.964 -4.786 4.581 Sex(M/F) -3.073 5.07 -0.606 0.55 -13.56 7.415 Group*Gender 8.302 5.82 1.427 0.167 -3.736 20.341 Similarly, Post Dominated Hand and Post Non-Dominated Hand had no association with the groups. However, there was a significant association with gender (P < 0.001). Men had significantly stronger hands compared to women in both groups. Non-Dominated Hand Strength showed similar patterns, with men being significantly stronger than women, but no significant differences between the two groups. The interaction effect of gender and the groups was significant with Post-Weight (P = 0.041). This means that men and women responded differently to the intervention regarding their weight, depending on whether they were in the CM or CN groups. In the CM group, men had a much higher average Post-Weight (~ 227 lbs) than women (~ 158 lbs). In contrast, in the CN group, men had an average Post-Weight of 161 lbs, closer to the women’s average Post-Weight (160 lbs). This difference between men and women across groups was significant. There was no significant difference in Post-BMI between the groups (CM vs. CN). The average Post-BMI in the CM group was about 29.4 compared to the CN group, which was 27.4. These differences were not statistically meaningful. There was no significant association of Post-Muscle Mass between the groups; however, it was significant with gender and its interaction effect(P = 0.019). While the group alone didn't impact muscle mass, being male or female, along with the group they were in, significantly influenced muscle mass after the intervention. Men had higher Post-Muscle Mass (150.8 lbs in the CM group) than women (95.8 lbs). This difference in Post-Muscle Mass between men and women was statistically significant, and the group they were in (CM or CN) further influenced this outcome. Table 4 Univariate ANOVA for different parameters between groups adjusting age and gender Parameter B Std. Error t Sig. 95% Confidence Interval Lower Bound Upper Bound Post Muscle Mass (lbs) Intercept 96.816 29.246 3.31 0.003 36.316 157.316 Age -0.017 0.393 -0.044 0.965 -0.831 0.796 Group 0.212 4.724 0.045 0.965 -9.562 9.985 Sex(M/F) 26.653 10.579 2.519 0.019 4.769 48.537 Group*Gender 28.428 12.143 2.341 0.028 3.308 53.549 Post SPPB Intercept 16.167 3.062 5.28 0 9.833 22.5 Age -0.068 0.041 -1.648 0.113 -0.153 0.017 Group -1.252 0.495 -2.531 0.019 -2.275 -0.229 Sex(M/F) 0.784 1.107 0.708 0.486 -1.506 3.075 Group*Gender 1.052 1.271 0.827 0.417 -1.578 3.681 Post Vit B Intercept 105.797 1165.067 0.091 0.928 -2304.328 2515.921 Age 9.257 15.66 0.591 0.56 -23.139 41.653 Group -38.47 188.203 -0.204 0.84 -427.799 350.858 Sex(M/F) 591.419 421.42 1.403 0.174 -280.356 1463.193 Group*Gender -779.53 483.748 -1.611 0.121 -1780.238 221.179 Post Creatinine Intercept 1.224 0.448 2.733 0.012 0.297 2.151 Age -0.005 0.006 -0.759 0.455 -0.017 0.008 Group -0.101 0.072 -1.402 0.174 -0.251 0.048 Sex(M/F) 0.109 0.162 0.675 0.506 -0.226 0.445 Group*Gender 0.301 0.186 1.62 0.119 -0.083 0.686 Post Folate Intercept 26.826 11.117 2.413 0.024 3.829 49.823 Age -0.126 0.149 -0.845 0.407 -0.435 0.183 Group 0.043 1.796 0.024 0.981 -3.672 3.758 Sex(M/F) 2.393 4.021 0.595 0.558 -5.925 10.711 Group*Gender -6.143 4.616 -1.331 0.196 -15.692 3.405 There was a significant difference in Post-SPPB between the groups (P = 0.019). The CM group had an average Post-SPPB score of 10.77, while the CN group had a higher average score of 11.20. There was no significant difference in Post-Vitamin B Levels, Post-Creatinine Levels , or Post-Folate Levels between the CM and CN groups. When examining cooking effectiveness before the study, the majority of both groups felt fairly to completely confident, the CM group (64.3%) and CN group (73.3%). Additionally, when asked about cooking attitudes, CM and CN groups had a majority (72.7%, 66.7%, respectively) that enjoyed cooking, thought it was important, and it brought happiness; didn’t think it took too much time, cost too much, or was a burden or stressful. Furthermore, five CM participants (50%) and three CN participants (20%) felt confident and knew what to eat. Lastly, when asked about the time it took to cook, seven CM participants (77.7%) and three CN participants (20%) felt cooking did not take too much time. When examining cooking effectiveness after the study, four participants did not complete the questionnaire in the CM group and three did not complete the questionnaire in the CN group. The results from those who completed the questionnaire showed that the CM group (100%) felt fairly to completely confident, and the CN group (33.3). Additionally, when asked about cooking attitudes, four CM participants and five CN participants didn’t answer the questionnaire. Of those that answered the questionnaire, seven CM participants and seven CN participants (77.8%, and 70%, respectively) enjoyed cooking, thought it was important, and it brought happiness; didn’t think it took too much time, cost too much, or was a burden or stressful. Furthermore, three CM participants (33.3%) and three CN participants (30%) felt confident and knew what to eat. Lastly, when asked about the time it took to cook, three CM participants (70%) and three CN participants (30%) felt cooking did not take too much time. At the end of the study, both groups were asked about the main challenges or barriers to managing protein intake and answers included “eating enough protein”; “loving carbs”; “not wanting to cook”; and “knowing the right amount”. Meanwhile, the CM group was asked how the CM videos specifically helped clarify managing their protein intake and answers included “they demonstrated how easy it was to cook the protein to produce a tasty meal”; “they helped with knowing the right portion size”; and “it helped with knowing how to cook in different ways”. Finally, the CM participants were asked what the most memorable or favorite part of the CM videos was, and answers included “impressed with how easy the videos made it seem to cook”; “short and sweet”; “they were not time-consuming”; and “having new recipes”. All CM participants reported having no technical difficulties accessing and watching the videos. 4. Discussion To the authors’ knowledge research utilizing a CM in a senior adult population is lacking sufficient evidence to demonstrate its impact on improving protein intake and potentially muscle quality. In this study, the CM participants had a significantly higher change in muscle mass after 4 months compared to those in the CN group ((116.97 ± 30.05 vs. 97.31 ± 10.52; P = 0.041). Furthermore, although not significant, there was a higher protein intake seen among CM participants and a lower protein intake seen among the CN group after four months (60.02 ± 21.40 vs. 52.89 ± 17.85; P = 0.454). These results indicate that CM emphasizing lean beef improved muscle mass and protein intake among senior adults. However, there was no additional impact of the CM emphasizing lean beef intervention over the CN group when analyzing the other outcomes. Insufficient consistent protein intake, lack of combining physical activity with nutrition intervention, adherence to the intervention, not recording medications that could influence outcomes, and missing/accuracy of the questionnaires could explain these results. Additionally, there was also a lack of representation of men in this study, which limits generalizability to men. Ethnicity information was also lacking. The accuracy of each group’s protein questionnaire could play a factor since they were self-administered. Self-administered questionnaires are more susceptible to item non-response[ 24 ]. CM participants had up to 30.74% (4 of 11), and CN participants had up to 33.3% (5 of 15) of questionnaires with blank answers, so intake could have been higher and explained better how some outcomes were affected. Additionally, the participants were not asked to change their diet outside their protein intake. Some evidence suggests that 25–30 g serving of animal protein per meal (e.g., lean beef) can increase MPS by ~ 50%.[ 25 , 26 ] Another study recommended 1.0 to 1.2 g of protein per kilogram of body weight per day to help senior adults maintain and regain lean body mass and function.[ 27 ] Similarly, in the current study, participants were instructed to consume 25–30 gm protein for each meal specifically lean red meat three times per week (lunch or dinner, 400 kcal/30 protein). Although the participants did not achieve the 25–30 gm protein for each meal consistently, the results showed that CM participants increased protein intake after the invention and the CN group decreased protein intake. Further results showed a significant difference between the groups in change in muscle mass after four months. This is similar to Sammarco et al. who showed improvements in body composition and grip strength in the participants who consumed high-protein diets.[ 28 ] However, because the participants did not achieve the recommended increased protein intake this could be the reason for nonsignificant increased protein consumption in the CM group. Nevertheless, the current study saw a trend of increased protein intake among those who received the CM intervention compared to a slight decrease in protein intake among the CN group. Reinders et al. also found that participants provided with personalized dietary advice and appropriate high-protein foods increased their protein intake.[ 23 ] The current study strengthens previous findings that increased quality protein intake among senior adults can improve muscle quality. Grip strength and SPPB tests have been used to examine muscle strength and function as components of muscle quality.[ 20 ] However, the current study did not find significant differences between groups in muscle strength and function change. Kim et al. found that the amount of change in dietary protein (increase or decrease) was not associated with muscle strength.[ 29 ] There are also mixed findings of Samaneh et al. that showed an even distribution of daily protein intake across meals was independently associated with greater muscle strength, but not with the mobility score (i.e., SPPB tests) in older adults.[ 30 ] Our current study also did not find that muscle function improved. Once more, because the CM participants did not achieve the recommended protein consumption this could be the reason for no between-group differences in change in muscle strength and function. Recent evidence suggests that certain biomarkers such as serum vitamin B 12 , folate, and creatinine are closely associated with muscle health.[ 31 – 33 ] The current study measured these biomarkers to determine the impact of CM on increasing lean beef consumption and found no significant between-group differences in change in these muscle synthesis biomarkers. Both groups consumed animal protein and did not have sarcopenia, which may have played a role. A review by Tosato et al. suggested that creatinine levels are maintained in the presence of stable renal function and animal protein intake, which provides reasoning for the results of nonsignificant between-group differences in the change of creatinine levels in the current study.[ 34 ] Moreover, no between-group differences in the change in folate could be a result of nonsignificant differences in change in protein intake. There was a nonsignificant decrease in serum vitamin B 12 in the CM group but not in the CN group. This study did not assess multiple factors that could influence serum vitamin B 12 levels such as pathophysiological changes (i.e. decreased intrinsic factor and malabsorption) along with medication intake (i.e. gastric acid inhibitors). 4.1 Strengths This study is one of the first to evaluate CM’s effect on enhancing lean beef intake and muscle quality in older adults. This study provided more insight into a CM intervention program to improve knowledge, awareness, and attitude toward animal protein intake within four months. In addition, the feedback from the participants can be applied to future interventions and practices. Registered dietitians (RDNs), fully trained and qualified with years of experience, developed the whole program with assistance from those with expertise in Hospitality. In addition, a RDN implemented the intervention and provided advice if participants needed clarification about their intervention. This study objectively determined the impact of a CM education strategy to increase protein intake by measuring the actual achieved change in protein intake by questionnaires, as well as subjectively assessed the appreciation of the CM education strategy by questionnaire. Lastly, providing dietary advice strategies that include whole diet are likely to be more sustainable. 4.2 Limitations Although exercise recommendation handouts were given in this study, this was a diet and nutrition education-focused intervention. An intervention including an exercise component along with digital CM education and nutrition would have given more opportunity for significant differences in muscle strength and function outcomes. Additionally, this study may not be representative of the general population with most participants being female (78.6%) and similar age. The inability to measure potential vitamin B 12 absorption issues and the participants’ medications not being recorded were also limitations of this study. Additional research is needed to further investigate with a larger sample size to provide more power which increase the likelihood of detecting effects of the intervention to prevent and treatment senior adults who are at risk for age-related muscle loss. There may be a recall bias due to the questionnaires being self-reported. Furthermore, the questionnaire results may not be accurate because of the blank questions. Interview-administered questionnaires could improve these limitations. Finally, the CM intervention being delivered by email is not as effective as a digital tool provided by a smartphone application. 5. Conclusion The current study is one of the few to examine the outcomes of a digital CM education program with cooking demonstration and nutrition education videos to enhance lean beef intake and muscle quality in older adults. The results revealed evidence that this intervention improved muscle mass and could potentially increase protein intake. Many of the intervention group reported that the cooking demonstrations helped with meal preparation of lean beef in the appropriate portions in easy and tasty ways, which can increase confidence in the kitchen and prepare more meals at home. It would be important to further investigate other factors that could have affected this study. Future studies could include exercise training sessions and a CM app that develops personalized meal plans to determine if it would improve results. It would be ideal to include a diverse age range and ethnicity with an equal gender to better represent the general senior adult population. Once again, interview-administered questionaries would improve protein intake and cooking effectiveness accuracy. This type of intervention can further knowledge advancement towards CM emphasizing lean beef, sarcopenia, and older adults. Such evidence could significantly link adequate protein intake (i.e., lean beef), physical activity, and sarcopenia. Once a link has been identified, the evidence can confirm that qualified health professionals providing CM emphasizing lean beef to older adults can provide a beneficial strategy for sarcopenia prevention. This link can be vital because research surrounding CM is in its infancy. If CM emphasizing lean beef can influence behavioral change in dietary patterns leading to muscle quality maintenance and improvement, this will be the most significant factor in the intervention’s success and effectiveness. We expect these findings to encourage practitioners to become more educated on CM to ensure that their services can continue to advance as this research becomes more prevalent, in line with the potential advances in CM. Ultimately, this proposal could show how CM emphasizing lean beef could positively benefit public health. Declarations Competing Interests Drs. Galyean, Childress, and Alcorn are owners of 3 CulinaryMed Docs, LLC. The electronic platform was used as part of the nutrition education to help participants know how to prepare vegetables. Author Contribution Author ContributionsConceptualization, S.G., A.C., M.A.; methodology, S.G., A.C., M.A., and S.N.; software, S.G., A.C., M.A., and J.C.; validation, J.C., S.G., and S.N.; formal analysis, S.N.; investigation, J.C. and S.G.; resources, J.C. and S.G.; data curation, J.C. and S.G.; writing—original draft preparation, S.G., J.C., and M.A.; writing—review and editing, S.G., A.C., M.A., S.N.; supervision, S.G.; project administration, J.C., S.G.. All authors have read and agreed to the published version of the manuscript Data Availability Data supporting reported results can be found by contacting the corresponding author. Data will be made available upon request. References S. Genaro Pde and L. A. Martini, "Effect of protein intake on bone and muscle mass in the elderly," (in eng), Nutr Rev, vol. 68, no. 10, pp. 616-23, Oct 2010, doi: 10.1111/j.1753-4887.2010.00321.x. B. Franzke, O. Neubauer, D. Cameron-Smith, and K. H. Wagner, "Dietary Protein, Muscle and Physical Function in the Very Old," (in eng), Nutrients, vol. 10, no. 7, Jul 20 2018, doi: 10.3390/nu10070935. M. Ni Lochlainn, R. C. E. Bowyer, and C. J. Steves, "Dietary Protein and Muscle in Aging People: The Potential Role of the Gut Microbiome," (in eng), Nutrients, vol. 10, no. 7, Jul 20 2018, doi: 10.3390/nu10070929. J. M. Cholewa et al. , "Dietary proteins and amino acids in the control of the muscle mass during immobilization and aging: role of the MPS response," (in eng), Amino Acids, vol. 49, no. 5, pp. 811-820, May 2017, doi: 10.1007/s00726-017-2390-9. S. K. Jyväkorpi et al. , "Low protein and micronutrient intakes in heterogeneous older population samples," (in eng), Arch Gerontol Geriatr, vol. 61, no. 3, pp. 464-71, Nov-Dec 2015, doi: 10.1016/j.archger.2015.06.022. L. A. Berner, G. Becker, M. Wise, and J. Doi, "Characterization of dietary protein among older adults in the United States: amount, animal sources, and meal patterns," (in eng), J Acad Nutr Diet, vol. 113, no. 6, pp. 809-15, Jun 2013, doi: 10.1016/j.jand.2013.01.014. V. L. Fulgoni, 3rd, "Current protein intake in America: analysis of the National Health and Nutrition Examination Survey, 2003-2004," (in eng), Am J Clin Nutr, vol. 87, no. 5, pp. 1554s-1557s, May 2008, doi: 10.1093/ajcn/87.5.1554S. K. M. Appleton, "Barriers to and Facilitators of the Consumption of Animal-Based Protein-Rich Foods in Older Adults," (in eng), Nutrients, vol. 8, no. 4, pp. 187-187, 2016, doi: 10.3390/nu8040187. N. LeBlanc-Morales, "Culinary Medicine: Patient Education for Therapeutic Lifestyle Changes," Critical Care Nursing Clinics of North America, vol. 31, no. 1, pp. 109-123, 2019/03/01/ 2019, doi: https://doi.org/10.1016/j.cnc.2018.11.009. J. La Puma, "What Is Culinary Medicine and What Does It Do?," Population health management, vol. 19, 06/02 2015, doi: 10.1089/pop.2015.0003. B. Hasan et al. , "The effect of culinary interventions (cooking classes) on dietary intake and behavioral change: a systematic review and evidence map," (in eng), BMC Nutr, vol. 5, p. 29, 2019, doi: 10.1186/s40795-019-0293-8. V. Bramston, A. Rouf, and M. Allman-Farinelli, "The Development of Cooking Videos to Encourage Calcium Intake in Young Adults," Nutrients, vol. 12, no. 5, 2020, doi: 10.3390/nu12051236. R. Polak et al. , "Preventing Type 2 Diabetes with Home Cooking: Current Evidence and Future Potential," Current Diabetes Reports, vol. 18, no. 10, p. 99, 2018/09/14 2018, doi: 10.1007/s11892-018-1061-x. J. A. Wolfson, C. W. Leung, and C. R. Richardson, "More frequent cooking at home is associated with higher Healthy Eating Index-2015 score," (in eng), Public Health Nutr, vol. 23, no. 13, pp. 2384-2394, Sep 2020, doi: 10.1017/s1368980019003549. H. Irl B et al. , "Culinary Medicine: Advancing a Framework for Healthier Eating to Improve Chronic Disease Management and Prevention," Clinical Therapeutics, vol. 41, no. 10, pp. 2184-2198, 2019/10/01/ 2019, doi: https://doi.org/10.1016/j.clinthera.2019.08.009. A. M. Zivkovic and J. B. German, "Metabolomics for assessment of nutritional status," (in eng), Current opinion in clinical nutrition and metabolic care, vol. 12, no. 5, pp. 501-507, 2009, doi: 10.1097/MCO.0b013e32832f1916. T. K. Malmstrom, D. K. Miller, E. M. Simonsick, L. Ferrucci, and J. E. Morley, "SARC-F: a symptom score to predict persons with sarcopenia at risk for poor functional outcomes," (in eng), J Cachexia Sarcopenia Muscle, vol. 7, no. 1, pp. 28-36, Mar 2016, doi: 10.1002/jcsm.12048. P. Morin, F. Herrmann, P. Ammann, B. Uebelhart, and R. Rizzoli, "A rapid self-administered food frequency questionnaire for the evaluation of dietary protein intake," (in eng), Clin Nutr, vol. 24, no. 5, pp. 768-74, Oct 2005, doi: 10.1016/j.clnu.2005.03.002. R. A. Washburn, K. W. Smith, A. M. Jette, and C. A. Janney, "The Physical Activity Scale for the Elderly (PASE): development and evaluation," (in eng), J Clin Epidemiol, vol. 46, no. 2, pp. 153-62, Feb 1993, doi: 10.1016/0895-4356(93)90053-4. M. Cesari et al. , "Biomarkers of sarcopenia in clinical trials-recommendations from the International Working Group on Sarcopenia," (in eng), J Cachexia Sarcopenia Muscle, vol. 3, no. 3, pp. 181-90, Sep 2012, doi: 10.1007/s13539-012-0078-2. A. J. Cruz-Jentoft et al. , "Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People," (in eng), Age Ageing, vol. 39, no. 4, pp. 412-23, Jul 2010, doi: 10.1093/ageing/afq034. C. de Fátima Ribeiro Silva, D. G. Ohara, A. P. Matos, A. Pinto, and M. S. Pegorari, "Short Physical Performance Battery as a Measure of Physical Performance and Mortality Predictor in Older Adults: A Comprehensive Literature Review," (in eng), Int J Environ Res Public Health, vol. 18, no. 20, Oct 10 2021, doi: 10.3390/ijerph182010612. I. Reinders, M. Visser, and H. A. H. Wijnhoven, "Two dietary advice strategies to increase protein intake among community-dwelling older adults: A feasibility study," (in eng), Clin Nutr ESPEN, vol. 37, pp. 157-167, Jun 2020, doi: 10.1016/j.clnesp.2020.02.020. P. Edwards, "Questionnaires in clinical trials: guidelines for optimal design and administration," (in eng), Trials, vol. 11, p. 2, Jan 11 2010, doi: 10.1186/1745-6215-11-2. C. Nowson and S. O'Connell, "Protein Requirements and Recommendations for Older People: A Review," (in eng), Nutrients, vol. 7, no. 8, pp. 6874-99, Aug 14 2015, doi: 10.3390/nu7085311. T. B. Symons, M. Sheffield-Moore, R. R. Wolfe, and D. Paddon-Jones, "A moderate serving of high-quality protein maximally stimulates skeletal muscle protein synthesis in young and elderly subjects," (in eng), J Am Diet Assoc, vol. 109, no. 9, pp. 1582-6, Sep 2009, doi: 10.1016/j.jada.2009.06.369. J. Bauer et al. , "Evidence-based recommendations for optimal dietary protein intake in older people: a position paper from the PROT-AGE Study Group," (in eng), J Am Med Dir Assoc, vol. 14, no. 8, pp. 542-59, Aug 2013, doi: 10.1016/j.jamda.2013.05.021. R. Sammarco et al. , "Evaluation of Hypocaloric Diet With Protein Supplementation in Middle-Aged Sarcopenic Obese Women: A Pilot Study," Obesity Facts, vol. 10, no. 3, pp. 160-167, 2017, doi: 10.1159/000468153. H.-N. Kim, S.-H. Kim, Y.-M. Eun, and S.-W. Song, "Impact of dietary protein intake on the incidence of low muscle strength in middle-aged and older adults," Clinical Nutrition, vol. 40, no. 4, pp. 1467-1474, 2021/04/01/ 2021, doi: https://doi.org/10.1016/j.clnu.2021.02.034. S. Farsijani, H. Payette, J. A. Morais, B. Shatenstein, P. Gaudreau, and S. Chevalier, "Even mealtime distribution of protein intake is associated with greater muscle strength, but not with 3-y physical function decline, in free-living older adults: the Quebec longitudinal study on Nutrition as a Determinant of Successful Aging (NuAge study)," The American Journal of Clinical Nutrition, vol. 106, no. 1, pp. 113-124, 2017/07/01/ 2017, doi: https://doi.org/10.3945/ajcn.116.146555. J. Zhao, Q. Lu, and X. Zhang, "Associations of serum vitamin B12 and its biomarkers with musculoskeletal health in middle-aged and older adults," (in eng), Front Endocrinol (Lausanne), vol. 15, p. 1387035, 2024, doi: 10.3389/fendo.2024.1387035. S. Y. Hwang, B. Sung, and N. D. Kim, "Roles of folate in skeletal muscle cell development and functions," (in eng), Arch Pharm Res, vol. 42, no. 4, pp. 319-325, Apr 2019, doi: 10.1007/s12272-018-1100-9. D. Groothof et al. , "Creatinine, cystatin C, muscle mass, and mortality: Findings from a primary and replication population-based cohort," (in eng), J Cachexia Sarcopenia Muscle, vol. 15, no. 4, pp. 1528-1538, Aug 2024, doi: 10.1002/jcsm.13511. M. Tosato et al. , "Measurement of muscle mass in sarcopenia: from imaging to biochemical markers," (in English), Aging Clinical and Experimental Research, suppl. 1, vol. 29, pp. 19-27, Feb 2017 2023-11-18 2017, doi: https://doi.org/10.1007/s40520-016-0717-0. Additional Declarations Competing interest reported. Drs. Galyean, Childress, and Alcorn are owners of 3 CulinaryMed Docs, LLC. The electronic platform was used as part of the nutrition education to help participants know how to prepare vegetables. Supplementary Files GraphicalAbstract.tif Cite Share Download PDF Status: Published Journal Publication published 27 May, 2025 Read the published version in Aging Clinical and Experimental Research → Version 1 posted Editorial decision: Revision requested 14 Feb, 2025 Reviews received at journal 07 Feb, 2025 Reviews received at journal 04 Feb, 2025 Reviews received at journal 02 Feb, 2025 Reviewers agreed at journal 26 Jan, 2025 Reviewers agreed at journal 26 Jan, 2025 Reviewers invited by journal 26 Jan, 2025 Editor assigned by journal 25 Jan, 2025 Submission checks completed at journal 21 Jan, 2025 First submitted to journal 20 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5868973","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":405067383,"identity":"027196d2-3dd2-4602-81b8-a03568deb1d0","order_by":0,"name":"Shannon Galyean","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYDACCTiLuQFEykE4bERpYQRrMeZhI1VLYg8hLfKzm589Lqi4wyDvfrBN4kPNnfT98j0GDB/KDuPUYnDnmLnxjDPPGAzPJLZJzjj2LLeHjceAccY5PFokEsykedsOMxg2JLZJ87AdBmthBongdNiM9G8QLf0P26T//DuczgPS8hePFoYbORBb5CWAtjC2HU4Aa2HEo8XgRk6ZNM+ZwzwGEg+bLXv7Dhv2HEsrONhzLh2fw7ZJ81QclpPvTz5448e3w/LszYc3PvhRZo3bYVDAY3CAgQUeRwcIqgdb18DA/IEolaNgFIyCUTDiAABDQlPCvv9x0QAAAABJRU5ErkJggg==","orcid":"","institution":"Texas Tech University","correspondingAuthor":true,"prefix":"","firstName":"Shannon","middleName":"","lastName":"Galyean","suffix":""},{"id":405067384,"identity":"ea2f4520-8b1e-484b-b876-8189defd2c47","order_by":1,"name":"Michelle Alcorn","email":"","orcid":"","institution":"Texas Tech University","correspondingAuthor":false,"prefix":"","firstName":"Michelle","middleName":"","lastName":"Alcorn","suffix":""},{"id":405067385,"identity":"00c04a18-45ef-42e3-8529-eb7af27101e6","order_by":2,"name":"Justin Chavez","email":"","orcid":"","institution":"Texas Tech University","correspondingAuthor":false,"prefix":"","firstName":"Justin","middleName":"","lastName":"Chavez","suffix":""},{"id":405067386,"identity":"a154fe84-9274-49db-9588-0b1f8e0b98ca","order_by":3,"name":"Surya Raj Niraula","email":"","orcid":"","institution":"Texas Tech University","correspondingAuthor":false,"prefix":"","firstName":"Surya","middleName":"Raj","lastName":"Niraula","suffix":""},{"id":405067387,"identity":"b42b3dfd-deb8-4128-94b6-70607393235a","order_by":4,"name":"Allison Childress","email":"","orcid":"","institution":"Texas Tech University","correspondingAuthor":false,"prefix":"","firstName":"Allison","middleName":"","lastName":"Childress","suffix":""}],"badges":[],"createdAt":"2025-01-20 23:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5868973/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5868973/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40520-025-03075-8","type":"published","date":"2025-05-27T15:57:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":75308420,"identity":"74954ccb-48c8-4b4a-83df-8ea628032ca8","added_by":"auto","created_at":"2025-02-03 08:47:28","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":183520,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the study participants\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5868973/v1/ee40f1ca3c91e5315f7adfb0.jpeg"},{"id":83783105,"identity":"8f1b8f84-0662-4d54-9625-e415bc2335b4","added_by":"auto","created_at":"2025-06-02 16:10:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1382734,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5868973/v1/15ef7217-568c-475e-a9e9-c9e797c25a23.pdf"},{"id":75308428,"identity":"4b6ee554-d16d-48b8-b5c5-cf351c8a1ded","added_by":"auto","created_at":"2025-02-03 08:47:29","extension":"tif","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":12699558,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.tif","url":"https://assets-eu.researchsquare.com/files/rs-5868973/v1/06beb3d74eb03674e0855a9a.tif"}],"financialInterests":"Competing interest reported. Drs. Galyean, Childress, and Alcorn are owners of 3 CulinaryMed Docs, LLC. The electronic platform was used as part of the nutrition education to help participants know how to prepare vegetables.","formattedTitle":"The Effect of Culinary Medicine to Enhance Protein Intake on Muscle Quality in Older Adults: A Randomized Controlled Trial","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAging is associated with a decline in muscle mass, strength, and physical function, which can lead to sarcopenia and frailty[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This deterioration of muscle and physical capabilities impacts an individual's functional independence and quality of life. Dietary protein stimulates muscle protein synthesis (MPS). Evidence suggests that optimal protein intake for an older individual is greater than the Recommended Dietary Allowance (RDA)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition, recent research demonstrates that increased oxidation and inflammation play a role in muscle protein breakdown that occurs during aging. Therefore, nutritional interventions that reduce oxidation or inflammation along with higher protein intakes may enhance MPS[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFood intake, including protein-rich foods like red meat, has been shown to decline with age[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Barriers to consuming protein-rich foods include reductions in taste and smell, dentition and dexterity, and changes in living situation[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Nutritional interventions that can improve eating behaviors, diet quality, and stimulate MPS in older adults are necessary to help prevent, manage, and promote recovery of sarcopenia. To reduce potential barriers of red meat consumption in community-dwelling older adults, an additional strategy may be the use of cooking demonstrations, or culinary medicine that imparts knowledge about healthy cooking to improve the dietary habits of individuals at risk of sarcopenia. With this approach, people will be educated about age-appropriate, healthy eating behaviors and equipped with basic cooking skills to incorporate nutritious food into their daily diet [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A systematic review concluded that culinary interventions such as cooking classes effectively improved attitudes, self-efficacy, and healthy eating in children and adults [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A recent study using cooking videos to encourage the consumption of calcium-rich foods showed that the subjects gained knowledge, were motivated to consume calcium-rich foods, and video demonstrations were accepted as an effective communication channel to impart cooking skills [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, it is suggested that cooking at home improves adherence to healthy nutrition, thereby reducing chronic illness risks [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Another study showed an association between cooking frequency and improved diet quality with a higher overall Healthy Eating Index (HEI) \u0026ndash; 2015 scores [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Older adults may not be aware of their changing nutrient needs and therefore may lack the skills to prepare nutritionally adequate foods appropriately. Thus, cooking demonstrations can be a novel strategy to improve diet quality in older adults and promote and augment at-home cooking.\u003c/p\u003e \u003cp\u003eCulinary medicine (CM) is an evidence-based field that combines skills of preparing, cooking, and presenting food with the science of medicine to accomplish potential improvements in eating behaviors and health outcomes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The goal of CM is to help people improve their diet quality which assists them in their medical regimen to produce an effective treatment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A tailored CM program for older adults can be an effective strategy that could reduce barriers to protein intake that will enable older adults to age well and productively.\u003c/p\u003e \u003cp\u003eDifferent types of protein may have different effects on sarcopenia risk. To accurately assess protein intake and the impact on muscle strength, function, and mass, a grip strength dynamometer, short physical performance battery tests (SPPB), and body composition are promising outcome measurements. Assessing muscle strength, function, and muscle mass is necessary to identify the intervention needed to address the risk of sarcopenia.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Therefore, our study aimed to examine how an online CM intervention, emphasizing convenient ways to increase lean beef intake, could improve protein intake to see how this intervention could affect older adults\u0026rsquo; muscle strength and mass.\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design and Study Participants\u003c/h2\u003e \u003cp\u003eA 16-week single-center, parallel-group, randomized study compared a culinary medicine intervention group (CM) to a control group (CN) on their protein intake, cooking effectiveness, muscle quality, vitamin B\u003csub\u003e12\u003c/sub\u003e, folate, creatinine levels, physical activity, and nutrition knowledge. The study was conducted at Texas Tech University Nutrition and Metabolic Health Initiative (NMHI), Lubbock, TX.\u003c/p\u003e \u003cp\u003eThe study population included independent senior adults who were able to regularly perform physical activity and prepare their meals. Recruitment began July 2023 and concluded in January 2024. Participants were excluded from the study if they were less than 65 years old, had limited mobility, intake of nicotine, excessive alcohol, and/or use of drugs (i.e., amphetamines, cocaine, marijuana, and opiates), cancer, transplant, pacemaker, renal disorders, or Type 1 diabetes or Type 2 diabetes with insulin therapy, did not have access to a computer, smartphone, or tablet, or if they scored 4 or more points on the SARC-F sarcopenia screening tool. This is a screening tool for sarcopenia that has been validated by research to adequately identify this in older adults.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] The study was approved by the institutional review board of Texas Tech University (IRB2023-505). All participants provided written informed consent.\u003c/p\u003e \u003cp\u003eParticipants were randomly allocated to two groups, the CM or CN group. Randomization was implemented with a randomly generated sequence created from an online randomizing tool, randomizer.org. After this sequence was generated, every other number was assigned to the CM group starting with the first number. Participants were assigned these numbers with their subject codes in the order they were admitted into the study.\u003c/p\u003e \u003cp\u003eBefore the start of the intervention, participants in both groups were provided a handout that offered information on healthful dietary habits for older adults from the Academy of Nutrition and Dietetics (AND) and another one that provided examples of various exercises for different muscle groups and purposes that were designed for seniors from SeniorsMobility.org. Both groups received an activity monitor (Garmin Vivofit 4) to help monitor their activity level.\u003c/p\u003e \u003cp\u003eBoth groups were instructed to include one meal of lean beef three times per week (lunch or dinner, 400 kcal/30gm protein). An adequate amount of lean beef was provided for participants, allowing three servings a week to circumvent possible obstacles to consuming beef, like its cost. This beef was purchased from a local organization affiliated with the Texas Tech University College of Agricultural Sciences and Natural Resources and stored in a freezer according to proper USDA guidelines. Before receiving beef, participants were provided a physical handout with instructions from the USDA Kitchen Companion handbook on safely storing and thawing frozen beef at home.\u003c/p\u003e \u003cp\u003eBoth groups were provided two lean beef-based recipes each week. Experienced research team members, including two registered dietitians and a culinary professor, collaborated to design this CM program (recipes, cooking demonstrations, and nutritional education videos) to increase awareness and counter common nutritional issues older adults face. The recipes included at least a serving of lean beef, 400 kcal, and 30 grams of protein and utilized multiple cuts of beef, including lean ground beef, sirloin, roast beef, chuck roast, and bottom round roast. Preparation technique, time, level of difficulty, and the cost of ingredients were considered, as these are potential barriers to consuming and preparing red meat at home. This program focused on preparation methods that are tender and lean as older adults can experience difficulty in chewing and a decline in appetite with high fat and fibrous red meats. All recipes were tested and evaluated based on sensory characteristics such as appearance, odor, texture, and flavor.\u003c/p\u003e \u003cp\u003eMembers of the CN and CM groups received different forms of culinary instruction to promote protein intake. The CN group only received weekly online recipes and exercise recommendation handouts without the CM intervention. While the CN group received only the recipes and exercises, the members of the CM group were additionally provided weekly (1) cooking demonstration videos that provided further step-by-step visual instruction on how to prepare these meals and (2) nutrition education videos covering nutritional topics that were especially relevant to older adults.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Questionnaires\u003c/h2\u003e \u003cp\u003eTo measure protein intake, a modified version of the rapid self-administered dietary protein food frequency questionnaire was used. This questionnaire contains 20 items evaluating the weekly intake of different types of meat, dairy, eggs, and beans.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] This outcome measure was changed to the primary outcome after the trial commenced due to reviewers\u0026rsquo; comments and recommendations of the authors\u0026rsquo; preliminary data that was published stating that this intervention had a strong dietary focus.\u003c/p\u003e \u003cp\u003eThe Physical Activity Scale for the Elderly (PASE) questionnaire assessed physical activity habits and how they might have altered throughout the study. This questionnaire has demonstrated a reliable representation of physical activity rates in free-living older adult populations.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eBased on modifications to a previous questionnaire to assess the effectiveness of the CM intervention in education, a multiple-choice nutrition knowledge questionnaire was used to assess knowledge related to the protein and micronutrient composition of various foods, average dietary needs, and physiological processes related to skeletal muscle maintenance.\u003c/p\u003e \u003cp\u003eThe research team also modified a previous resource, the Cooking Effectiveness Questionnaire, to assess the participants' experience and feelings about cooking. This questionnaire was used to assess the participant\u0026rsquo;s adherence to the intervention as well as their experience implementing recipes from the intervention. This questionnaire was modified between the groups to include questions related to cooking and nutrition education videos for the CM group.\u003c/p\u003e \u003cp\u003eInformation from these questionnaires further assessed the ability of this CM intervention to encourage healthful behavioral changes, like cooking at home, performing physical activity, addressing common nutritional concerns for older adults, as well as the comprehension of nutritional concepts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Muscle Quality\u003c/h2\u003e \u003cp\u003eMuscle strength has been determined to be one of the key fields when assessing muscle quality, and handgrip strength has been shown to provide an accurate representation of changes in overall strength.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] Muscle strength is measured by grip strength using a digital hand-held dynamometer (Camry EH101), focused on the change in strength over four months between the two groups.\u003c/p\u003e \u003cp\u003eA Tanita MC-780U bioelectric impedance analysis (BIA) scale was used to assess changes in multiple fields related to muscle and body composition, including muscle mass in pounds, weight in pounds, and BMI. Previous research has demonstrated that BIA scans accurately assess muscle mass, another key field for determining muscle quality.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] This machine automatically calculated BMI after inputting height, which researchers measured using a stadiometer. Muscle mass was assessed by BIA. This outcome focused on the change in muscle mass over the four months between CM- and CN-group.\u003c/p\u003e \u003cp\u003eThe final major field used to determine muscle quality is muscle function, and changes in this field were assessed with a Short Physical Performance Battery (SPPB) exam. This a resource that has been determined to provide a reliable assessment of muscle function and consists of a series of exercises related to the three categories of balance, gait speed, and chair standing.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] A researcher read from a script with descriptive instructions on these exercises for the participants, and they were scored from zero to four points in each of these categories based on their performance for a total score ranging from zero to twelve points.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Muscle Synthesis\u003c/h2\u003e \u003cp\u003eFinally, blood samples were collected at baseline and following the completion of the study. Participants were instructed to fast 8 hours before these blood draws were carried out by an experienced phlebotomist. Then, they were analyzed to measure serum vitamin B12, folate, and creatinine values. These micronutrients all act as cofactors in the process of MPS and increases in these values demonstrate improvements in the activity rate of this process.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe study included the final 13 participants in the intervention arm and 15 in the control arm for the analysis. The mean change in protein intake in between the intervention and control groups as reported in a literature.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Enrolling the participants in each group provides 95% power in estimation to detect 23.2g/day mean difference of change in the protein intake between the groups with 17.48g/day pooled standard deviation at 95% Confidence Interval (CI).\u003c/p\u003e \u003cp\u003eData were entered into Microsoft Excel and analyzed with IBM SPSS version 29.0.0.0. Descriptive statistics were used to describe background characteristics of the participants in terms of mean, standard deviation, and percentage in two groups. Cross-tabulation was done to examine the association between gender and the two groups. All the continues outcome variables were tested for normality (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) using two-sample Kolmogorov-Smirnov test. Independent sample t-test was used for post values and post scores. Univariate ANOVA was used to examine association of different parameters between the groups after adjusting possible confounders. The probability of significance was set at 5% level of significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA total of 47 participants were assessed for eligibility. Ten (21.2%) were excluded during screening due to failing to meet inclusion criteria or losing contact. Thirty-four participants were randomized: 15 to the CM and 19 to the CN. A total of 13 in the CM, compared with 15 in the CN group, completed the 16-week study. Six (17.6%) participants withdrew or dropped out before the completion of the study due to medical reasons unrelated to the study, family reasons, lost contact, or no longer wanting to participate in the study. See the CONSORT study flow diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) for the study details.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe baseline characteristics of the groups are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The study included a greater proportion of females [78.6% (22 of 28)]. The CM group\u0026rsquo;s mean age, weight, and body mass index (BMI) were 71.54\u0026thinsp;\u0026plusmn;\u0026thinsp;4.48 years, 183.58\u0026thinsp;\u0026plusmn;\u0026thinsp;43.80 lbs, and 29.17\u0026thinsp;\u0026plusmn;\u0026thinsp;5.12 kg/m\u003csup\u003e2\u003c/sup\u003e, respectively. In the CN group, they were slightly older (74.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.68 years) but had lower weight (161.01\u0026thinsp;\u0026plusmn;\u0026thinsp;22.35 lbs) and BMI (27.47\u0026thinsp;\u0026plusmn;\u0026thinsp;4.31 kg/m\u003csup\u003e2\u003c/sup\u003e). The CN group has higher PASE and lower knowledge scores than the CM group. Regarding diet, the CN group consumed more protein than the CM group. Meanwhile, the CM group had greater grip strength and muscle mass than the CN group. However, the CN group had slightly higher SPPB scores than the CM group. Finally, the CM group had higher levels of muscle synthesis biomarkers than the CN group.\u003c/p\u003e \u003cp\u003eThe demographic characteristic, age (t=-1.24, p\u0026thinsp;=\u0026thinsp;0.220) and gender (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}_{c}^{2}\\)\u003c/span\u003e\u003c/span\u003e=2.51, p\u0026thinsp;=\u0026thinsp;0.113) were homogeneously distributed among the groups. Before the intervention, pre-values and pre-scores were insignificant between the groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The incomplete numbers in the CM group are the missing cases.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of of different variables between the groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \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=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCulinary Medicine\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eControl\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eTotal\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale/Female [#, \u003csup\u003e(\u003c/sup\u003e%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e5 (38.5)/8 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e1 (0.06)/14 (93.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e6 (21.4)/22 (78.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e72.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e67.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePASE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein (g\u003csup\u003ed\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMS\u003csup\u003ee\u003c/sup\u003e dom.\u003csup\u003ef\u003c/sup\u003e (kg\u003csup\u003eg\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Dominated Hand (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWt (lbs\u003csup\u003eh\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e161.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e171.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e35.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuscle Mass (lbs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e106.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPPB\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin B\u003csub\u003e12\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e821.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e458.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e776.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e379.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e798.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e411.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFolate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.953\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 \u003csup\u003ea\u003c/sup\u003eAll the variables were tested for normality (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) using two-sample Kolmogorov-Smirnov test.\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003eAll values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e value refers to between-group differences were calculated using the chi-squared test for categorical variables or t-test for continuous variables.\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003eg: gram\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003eMS: muscle strength\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003edom.: dominant\u003c/p\u003e \u003cp\u003e \u003csup\u003eg\u003c/sup\u003ekg: kilogram\u003c/p\u003e \u003cp\u003e \u003csup\u003eh\u003c/sup\u003elbs: pounds\u003c/p\u003e \u003cp\u003e \u003csup\u003ei\u003c/sup\u003ekg/m\u003csup\u003e2\u003c/sup\u003e: kilograms/meter\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003eStatistically significant\u003c/p\u003e \u003cp\u003e \u003csup\u003ej\u003c/sup\u003eShort Physical Performance Battery tests\u003c/p\u003e \u003cp\u003eThere was a slight increase of protein intake seen in the CM group compared to a slight decrease in protein intake seen among the CN group. However, there was no between-group difference in protein intake from the pre-study (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.454; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Similar results were seen with PASE and knowledge scores from baseline (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.00; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.785, respectively). When comparing weight and body composition, there were no significant differences between groups in change from baseline measurements (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.103; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.300, respectively).\u003c/p\u003e \u003cp\u003eMuscle quality measurements showed that there was a significant difference in change in muscle mass between groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041). However, for measurements of muscle strength in both dominant and non-dominant hands, there was no between-group difference in the muscle strength change from the pre-study (dominant: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.122 and non-dominant: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.207). Additionally, there were no between-group differences in the muscle function change from baseline (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.360). Lastly, there were no between-group differences in vitamin B\u003csub\u003e12\u003c/sub\u003e, folate, or creatinine change from pre-study measurements (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.270; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.441; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.430, respectively)\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\u003e\u003cb\u003eMean characteristics of participants at pre- and post-study\u003c/b\u003e\u003csup\u003ea\u003c/sup\u003e\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCM (n\u0026thinsp;=\u0026thinsp;13)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCN (n\u0026thinsp;=\u0026thinsp;15)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-Study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost-Study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePre-Study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost-Study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePost-Study Between Group Differences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.62\u0026thinsp;\u0026plusmn;\u0026thinsp;9.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.47\u0026thinsp;\u0026plusmn;\u0026thinsp;9.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.61\u0026thinsp;\u0026plusmn;\u0026thinsp;12.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.30\u0026thinsp;\u0026plusmn;\u0026thinsp;8.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePASE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.75\u0026thinsp;\u0026plusmn;\u0026thinsp;11.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.00\u0026thinsp;\u0026plusmn;\u0026thinsp;17.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.33\u0026thinsp;\u0026plusmn;\u0026thinsp;16.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.00\u0026thinsp;\u0026plusmn;\u0026thinsp;11.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein Intake (g\u003csup\u003ed\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.52\u0026thinsp;\u0026plusmn;\u0026thinsp;36.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.02\u0026thinsp;\u0026plusmn;\u0026thinsp;21.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.68\u0026thinsp;\u0026plusmn;\u0026thinsp;24.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.89\u0026thinsp;\u0026plusmn;\u0026thinsp;17.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMS\u003csup\u003ee\u003c/sup\u003e dom.\u003csup\u003ef\u003c/sup\u003e (kg\u003csup\u003eg\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.17\u0026thinsp;\u0026plusmn;\u0026thinsp;12.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.24\u0026thinsp;\u0026plusmn;\u0026thinsp;10.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.97\u0026thinsp;\u0026plusmn;\u0026thinsp;6.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.57\u0026thinsp;\u0026plusmn;\u0026thinsp;5.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMS non-dom. (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.58\u0026thinsp;\u0026plusmn;\u0026thinsp;11.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.15\u0026thinsp;\u0026plusmn;\u0026thinsp;10.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.41\u0026thinsp;\u0026plusmn;\u0026thinsp;6.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.89\u0026thinsp;\u0026plusmn;\u0026thinsp;6.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (lbs\u003csup\u003eh\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183.58\u0026thinsp;\u0026plusmn;\u0026thinsp;43.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184.60\u0026thinsp;\u0026plusmn;\u0026thinsp;44.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e161.01\u0026thinsp;\u0026plusmn;\u0026thinsp;22.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e161.01\u0026thinsp;\u0026plusmn;\u0026thinsp;21.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody Mass Index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.17\u0026thinsp;\u0026plusmn;\u0026thinsp;5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.42\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.47\u0026thinsp;\u0026plusmn;\u0026thinsp;4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.41\u0026thinsp;\u0026plusmn;\u0026thinsp;4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuscle Mass (lbs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116.40\u0026thinsp;\u0026plusmn;\u0026thinsp;29.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116.97\u0026thinsp;\u0026plusmn;\u0026thinsp;30.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.93\u0026thinsp;\u0026plusmn;\u0026thinsp;11.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.31\u0026thinsp;\u0026plusmn;\u0026thinsp;10.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.041\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPPB\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.87\u0026thinsp;\u0026plusmn;\u0026thinsp;.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.20\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin B\u003csub\u003e12\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e821.85\u0026thinsp;\u0026plusmn;\u0026thinsp;458.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e657.23\u0026thinsp;\u0026plusmn;\u0026thinsp;310.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e776.14\u0026thinsp;\u0026plusmn;\u0026thinsp;379.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e830.27\u0026thinsp;\u0026plusmn;\u0026thinsp;470.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-173.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFolate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.39\u0026thinsp;\u0026plusmn;\u0026thinsp;4.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.19\u0026thinsp;\u0026plusmn;\u0026thinsp;4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.64\u0026thinsp;\u0026plusmn;\u0026thinsp;3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.430\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 \u003csup\u003ea\u003c/sup\u003eThe independent sample \u003cem\u003et\u003c/em\u003e-test was used to compare between-group differences in the post-study.\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003eAll values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e value refers to between-group differences by independent sample \u003cem\u003et-\u003c/em\u003etest\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003eg: gram\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003eMS: muscle strength\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003edom.: dominant\u003c/p\u003e \u003cp\u003e \u003csup\u003eg\u003c/sup\u003ekg: kilogram\u003c/p\u003e \u003cp\u003e \u003csup\u003eh\u003c/sup\u003elbs: pounds\u003c/p\u003e \u003cp\u003e \u003csup\u003ei\u003c/sup\u003ekg/m\u003csup\u003e2\u003c/sup\u003e: kilograms/meter\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003eStatistically significant\u003c/p\u003e \u003cp\u003e \u003csup\u003ej\u003c/sup\u003eShort Physical Performance Battery tests\u003c/p\u003e \u003cp\u003eWe used Univariate ANOVA to examine the association of different parameters between the groups after adjusting possible confounders (\u003cem\u003eGender\u003c/em\u003e and \u003cem\u003eAge\u003c/em\u003e). The \u003cem\u003ePost-Protein Intake\u003c/em\u003e was insignificant between the groups, even after adjusting the \u003cem\u003eGender\u003c/em\u003e and \u003cem\u003eAge\u003c/em\u003e. The CM group had an average \u003cem\u003ePost-Protein Intake\u003c/em\u003e of 60 grams (men: ~78g, women: ~51g), and the CN group had 53 grams (men: 95g, women: 48g). These differences weren\u0026rsquo;t statistically significant.\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\u003eUnivariate ANOVA for different parameters between groups adjusting age and gender\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eParameter\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStd. Error\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSig.\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003e95% Confidence Interval\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eLower Bound\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eUpper Bound\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost Protein(gm)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-24.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e213.497\u003c/p\u003e \u003c/td\u003e \u003c/tr\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-0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-17.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.989\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-19.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-57.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.608\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost Dominated Hand (Kg)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\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-0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-6.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-12.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.934\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePost Non-Dominated Hand (Kg)\u003c/b\u003e\u003c/p\u003e \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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\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-0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-6.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-16.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.788\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost Wt(lbs)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-31.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e279.779\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.595\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.587\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-26.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-55.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e132.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost BMI\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.249\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.581\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-13.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.415\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.341\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\u003eSimilarly, \u003cem\u003ePost Dominated Hand\u003c/em\u003e and \u003cem\u003ePost Non-Dominated Hand\u003c/em\u003e had no association with the groups. However, there was a significant association with gender (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Men had significantly stronger hands compared to women in both groups. \u003cem\u003eNon-Dominated Hand Strength\u003c/em\u003e showed similar patterns, with men being significantly stronger than women, but no significant differences between the two groups.\u003c/p\u003e \u003cp\u003eThe interaction effect of gender and the groups was significant with \u003cem\u003ePost-Weight\u003c/em\u003e (P\u0026thinsp;=\u0026thinsp;0.041). This means that men and women responded differently to the intervention regarding their weight, depending on whether they were in the CM or CN groups. In the CM group, men had a much higher average \u003cem\u003ePost-Weight\u003c/em\u003e (~\u0026thinsp;227 lbs) than women (~\u0026thinsp;158 lbs). In contrast, in the CN group, men had an average \u003cem\u003ePost-Weight\u003c/em\u003e of 161 lbs, closer to the women\u0026rsquo;s average \u003cem\u003ePost-Weight\u003c/em\u003e (160 lbs). This difference between men and women across groups was significant.\u003c/p\u003e \u003cp\u003eThere was no significant difference in \u003cem\u003ePost-BMI\u003c/em\u003e between the groups (CM vs. CN). The average \u003cem\u003ePost-BMI\u003c/em\u003e in the CM group was about 29.4 compared to the CN group, which was 27.4. These differences were not statistically meaningful.\u003c/p\u003e \u003cp\u003eThere was no significant association of \u003cem\u003ePost-Muscle Mass\u003c/em\u003e between the groups; however, it was significant with gender and its interaction effect(P\u0026thinsp;=\u0026thinsp;0.019). While the group alone didn't impact muscle mass, being male or female, along with the group they were in, significantly influenced muscle mass after the intervention. Men had higher \u003cem\u003ePost-Muscle Mass\u003c/em\u003e (150.8 lbs in the CM group) than women (95.8 lbs). This difference in \u003cem\u003ePost-Muscle Mass\u003c/em\u003e between men and women was statistically significant, and the group they were in (CM or CN) further influenced this outcome.\u003c/p\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\u003eUnivariate ANOVA for different parameters between groups adjusting age and gender\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=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eParameter\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStd. Error\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSig.\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003e95% Confidence Interval\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eLower Bound\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eUpper Bound\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost Muscle Mass (lbs)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e36.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e157.316\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-9.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.537\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost SPPB\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-2.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost Vit B\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1165.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-2304.328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2515.921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-23.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.653\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-38.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e188.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-427.799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e350.858\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e591.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e421.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-280.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1463.193\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-779.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e483.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1780.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e221.179\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost Creatinine\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost Folate\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49.823\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-3.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.595\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-5.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup*Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-15.692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.405\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\u003eThere was a significant difference in \u003cem\u003ePost-SPPB\u003c/em\u003e between the groups (P\u0026thinsp;=\u0026thinsp;0.019). The CM group had an average \u003cem\u003ePost-SPPB\u003c/em\u003e score of 10.77, while the CN group had a higher average score of 11.20. There was no significant difference in \u003cem\u003ePost-Vitamin B Levels, Post-Creatinine Levels\u003c/em\u003e, or \u003cem\u003ePost-Folate Levels\u003c/em\u003e between the CM and CN groups.\u003c/p\u003e \u003cp\u003eWhen examining cooking effectiveness before the study, the majority of both groups felt fairly to completely confident, the CM group (64.3%) and CN group (73.3%). Additionally, when asked about cooking attitudes, CM and CN groups had a majority (72.7%, 66.7%, respectively) that enjoyed cooking, thought it was important, and it brought happiness; didn\u0026rsquo;t think it took too much time, cost too much, or was a burden or stressful. Furthermore, five CM participants (50%) and three CN participants (20%) felt confident and knew what to eat. Lastly, when asked about the time it took to cook, seven CM participants (77.7%) and three CN participants (20%) felt cooking did not take too much time.\u003c/p\u003e \u003cp\u003eWhen examining cooking effectiveness after the study, four participants did not complete the questionnaire in the CM group and three did not complete the questionnaire in the CN group. The results from those who completed the questionnaire showed that the CM group (100%) felt fairly to completely confident, and the CN group (33.3). Additionally, when asked about cooking attitudes, four CM participants and five CN participants didn\u0026rsquo;t answer the questionnaire. Of those that answered the questionnaire, seven CM participants and seven CN participants (77.8%, and 70%, respectively) enjoyed cooking, thought it was important, and it brought happiness; didn\u0026rsquo;t think it took too much time, cost too much, or was a burden or stressful. Furthermore, three CM participants (33.3%) and three CN participants (30%) felt confident and knew what to eat. Lastly, when asked about the time it took to cook, three CM participants (70%) and three CN participants (30%) felt cooking did not take too much time.\u003c/p\u003e \u003cp\u003eAt the end of the study, both groups were asked about the main challenges or barriers to managing protein intake and answers included \u0026ldquo;eating enough protein\u0026rdquo;; \u0026ldquo;loving carbs\u0026rdquo;; \u0026ldquo;not wanting to cook\u0026rdquo;; and \u0026ldquo;knowing the right amount\u0026rdquo;. Meanwhile, the CM group was asked how the CM videos specifically helped clarify managing their protein intake and answers included \u0026ldquo;they demonstrated how easy it was to cook the protein to produce a tasty meal\u0026rdquo;; \u0026ldquo;they helped with knowing the right portion size\u0026rdquo;; and \u0026ldquo;it helped with knowing how to cook in different ways\u0026rdquo;. Finally, the CM participants were asked what the most memorable or favorite part of the CM videos was, and answers included \u0026ldquo;impressed with how easy the videos made it seem to cook\u0026rdquo;; \u0026ldquo;short and sweet\u0026rdquo;; \u0026ldquo;they were not time-consuming\u0026rdquo;; and \u0026ldquo;having new recipes\u0026rdquo;. All CM participants reported having no technical difficulties accessing and watching the videos.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTo the authors\u0026rsquo; knowledge research utilizing a CM in a senior adult population is lacking sufficient evidence to demonstrate its impact on improving protein intake and potentially muscle quality. In this study, the CM participants had a significantly higher change in muscle mass after 4 months compared to those in the CN group ((116.97\u0026thinsp;\u0026plusmn;\u0026thinsp;30.05 vs. 97.31\u0026thinsp;\u0026plusmn;\u0026thinsp;10.52; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041). Furthermore, although not significant, there was a higher protein intake seen among CM participants and a lower protein intake seen among the CN group after four months (60.02\u0026thinsp;\u0026plusmn;\u0026thinsp;21.40 vs. 52.89\u0026thinsp;\u0026plusmn;\u0026thinsp;17.85; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.454). These results indicate that CM emphasizing lean beef improved muscle mass and protein intake among senior adults.\u003c/p\u003e \u003cp\u003eHowever, there was no additional impact of the CM emphasizing lean beef intervention over the CN group when analyzing the other outcomes. Insufficient consistent protein intake, lack of combining physical activity with nutrition intervention, adherence to the intervention, not recording medications that could influence outcomes, and missing/accuracy of the questionnaires could explain these results. Additionally, there was also a lack of representation of men in this study, which limits generalizability to men. Ethnicity information was also lacking.\u003c/p\u003e \u003cp\u003eThe accuracy of each group\u0026rsquo;s protein questionnaire could play a factor since they were self-administered. Self-administered questionnaires are more susceptible to item non-response[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. CM participants had up to 30.74% (4 of 11), and CN participants had up to 33.3% (5 of 15) of questionnaires with blank answers, so intake could have been higher and explained better how some outcomes were affected. Additionally, the participants were not asked to change their diet outside their protein intake.\u003c/p\u003e \u003cp\u003eSome evidence suggests that 25\u0026ndash;30 g serving of animal protein per meal (e.g., lean beef) can increase MPS by ~\u0026thinsp;50%.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] Another study recommended 1.0 to 1.2 g of protein per kilogram of body weight per day to help senior adults maintain and regain lean body mass and function.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] Similarly, in the current study, participants were instructed to consume 25\u0026ndash;30 gm protein for each meal specifically lean red meat three times per week (lunch or dinner, 400 kcal/30 protein). Although the participants did not achieve the 25\u0026ndash;30 gm protein for each meal consistently, the results showed that CM participants increased protein intake after the invention and the CN group decreased protein intake. Further results showed a significant difference between the groups in change in muscle mass after four months. This is similar to Sammarco et al. who showed improvements in body composition and grip strength in the participants who consumed high-protein diets.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] However, because the participants did not achieve the recommended increased protein intake this could be the reason for nonsignificant increased protein consumption in the CM group. Nevertheless, the current study saw a trend of increased protein intake among those who received the CM intervention compared to a slight decrease in protein intake among the CN group. Reinders et al. also found that participants provided with personalized dietary advice and appropriate high-protein foods increased their protein intake.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] The current study strengthens previous findings that increased quality protein intake among senior adults can improve muscle quality.\u003c/p\u003e \u003cp\u003eGrip strength and SPPB tests have been used to examine muscle strength and function as components of muscle quality.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] However, the current study did not find significant differences between groups in muscle strength and function change. Kim et al. found that the amount of change in dietary protein (increase or decrease) was not associated with muscle strength.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] There are also mixed findings of Samaneh et al. that showed an even distribution of daily protein intake across meals was independently associated with greater muscle strength, but not with the mobility score (i.e., SPPB tests) in older adults.[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] Our current study also did not find that muscle function improved. Once more, because the CM participants did not achieve the recommended protein consumption this could be the reason for no between-group differences in change in muscle strength and function.\u003c/p\u003e \u003cp\u003eRecent evidence suggests that certain biomarkers such as serum vitamin B\u003csub\u003e12\u003c/sub\u003e, folate, and creatinine are closely associated with muscle health.[\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] The current study measured these biomarkers to determine the impact of CM on increasing lean beef consumption and found no significant between-group differences in change in these muscle synthesis biomarkers. Both groups consumed animal protein and did not have sarcopenia, which may have played a role. A review by Tosato et al. suggested that creatinine levels are maintained in the presence of stable renal function and animal protein intake, which provides reasoning for the results of nonsignificant between-group differences in the change of creatinine levels in the current study.[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] Moreover, no between-group differences in the change in folate could be a result of nonsignificant differences in change in protein intake. There was a nonsignificant decrease in serum vitamin B\u003csub\u003e12\u003c/sub\u003e in the CM group but not in the CN group. This study did not assess multiple factors that could influence serum vitamin B\u003csub\u003e12\u003c/sub\u003e levels such as pathophysiological changes (i.e. decreased intrinsic factor and malabsorption) along with medication intake (i.e. gastric acid inhibitors).\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Strengths\u003c/h2\u003e \u003cp\u003eThis study is one of the first to evaluate CM\u0026rsquo;s effect on enhancing lean beef intake and muscle quality in older adults. This study provided more insight into a CM intervention program to improve knowledge, awareness, and attitude toward animal protein intake within four months. In addition, the feedback from the participants can be applied to future interventions and practices.\u003c/p\u003e \u003cp\u003eRegistered dietitians (RDNs), fully trained and qualified with years of experience, developed the whole program with assistance from those with expertise in Hospitality. In addition, a RDN implemented the intervention and provided advice if participants needed clarification about their intervention.\u003c/p\u003e \u003cp\u003eThis study objectively determined the impact of a CM education strategy to increase protein intake by measuring the actual achieved change in protein intake by questionnaires, as well as subjectively assessed the appreciation of the CM education strategy by questionnaire. Lastly, providing dietary advice strategies that include whole diet are likely to be more sustainable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Limitations\u003c/h2\u003e \u003cp\u003eAlthough exercise recommendation handouts were given in this study, this was a diet and nutrition education-focused intervention. An intervention including an exercise component along with digital CM education and nutrition would have given more opportunity for significant differences in muscle strength and function outcomes. Additionally, this study may not be representative of the general population with most participants being female (78.6%) and similar age. The inability to measure potential vitamin B\u003csub\u003e12\u003c/sub\u003e absorption issues and the participants\u0026rsquo; medications not being recorded were also limitations of this study. Additional research is needed to further investigate with a larger sample size to provide more power which increase the likelihood of detecting effects of the intervention to prevent and treatment senior adults who are at risk for age-related muscle loss. There may be a recall bias due to the questionnaires being self-reported. Furthermore, the questionnaire results may not be accurate because of the blank questions. Interview-administered questionnaires could improve these limitations. Finally, the CM intervention being delivered by email is not as effective as a digital tool provided by a smartphone application.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe current study is one of the few to examine the outcomes of a digital CM education program with cooking demonstration and nutrition education videos to enhance lean beef intake and muscle quality in older adults. The results revealed evidence that this intervention improved muscle mass and could potentially increase protein intake. Many of the intervention group reported that the cooking demonstrations helped with meal preparation of lean beef in the appropriate portions in easy and tasty ways, which can increase confidence in the kitchen and prepare more meals at home.\u003c/p\u003e \u003cp\u003eIt would be important to further investigate other factors that could have affected this study. Future studies could include exercise training sessions and a CM app that develops personalized meal plans to determine if it would improve results. It would be ideal to include a diverse age range and ethnicity with an equal gender to better represent the general senior adult population. Once again, interview-administered questionaries would improve protein intake and cooking effectiveness accuracy.\u003c/p\u003e \u003cp\u003eThis type of intervention can further knowledge advancement towards CM emphasizing lean beef, sarcopenia, and older adults. Such evidence could significantly link adequate protein intake (i.e., lean beef), physical activity, and sarcopenia. Once a link has been identified, the evidence can confirm that qualified health professionals providing CM emphasizing lean beef to older adults can provide a beneficial strategy for sarcopenia prevention. This link can be vital because research surrounding CM is in its infancy. If CM emphasizing lean beef can influence behavioral change in dietary patterns leading to muscle quality maintenance and improvement, this will be the most significant factor in the intervention\u0026rsquo;s success and effectiveness. We expect these findings to encourage practitioners to become more educated on CM to ensure that their services can continue to advance as this research becomes more prevalent, in line with the potential advances in CM. Ultimately, this proposal could show how CM emphasizing lean beef could positively benefit public health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eDrs. Galyean, Childress, and Alcorn are owners of 3 CulinaryMed Docs, LLC. The electronic platform was used as part of the nutrition education to help participants know how to prepare vegetables.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor ContributionsConceptualization, S.G., A.C., M.A.; methodology, S.G., A.C., M.A., and S.N.; software, S.G., A.C., M.A., and J.C.; validation, J.C., S.G., and S.N.; formal analysis, S.N.; investigation, J.C. and S.G.; resources, J.C. and S.G.; data curation, J.C. and S.G.; writing\u0026mdash;original draft preparation, S.G., J.C., and M.A.; writing\u0026mdash;review and editing, S.G., A.C., M.A., S.N.; supervision, S.G.; project administration, J.C., S.G.. All authors have read and agreed to the published version of the manuscript\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData supporting reported results can be found by contacting the corresponding author. Data will be made available upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eS. Genaro Pde and L. A. Martini, \u0026quot;Effect of protein intake on bone and muscle mass in the elderly,\u0026quot; (in eng), \u003cem\u003eNutr Rev, \u003c/em\u003evol. 68, no. 10, pp. 616-23, Oct 2010, doi: 10.1111/j.1753-4887.2010.00321.x.\u003c/li\u003e\n\u003cli\u003eB. Franzke, O. Neubauer, D. Cameron-Smith, and K. H. Wagner, \u0026quot;Dietary Protein, Muscle and Physical Function in the Very Old,\u0026quot; (in eng), \u003cem\u003eNutrients, \u003c/em\u003evol. 10, no. 7, Jul 20 2018, doi: 10.3390/nu10070935.\u003c/li\u003e\n\u003cli\u003eM. Ni Lochlainn, R. C. E. Bowyer, and C. J. Steves, \u0026quot;Dietary Protein and Muscle in Aging People: The Potential Role of the Gut Microbiome,\u0026quot; (in eng), \u003cem\u003eNutrients, \u003c/em\u003evol. 10, no. 7, Jul 20 2018, doi: 10.3390/nu10070929.\u003c/li\u003e\n\u003cli\u003eJ. M. Cholewa\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Dietary proteins and amino acids in the control of the muscle mass during immobilization and aging: role of the MPS response,\u0026quot; (in eng), \u003cem\u003eAmino Acids, \u003c/em\u003evol. 49, no. 5, pp. 811-820, May 2017, doi: 10.1007/s00726-017-2390-9.\u003c/li\u003e\n\u003cli\u003eS. K. Jyv\u0026auml;korpi\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Low protein and micronutrient intakes in heterogeneous older population samples,\u0026quot; (in eng), \u003cem\u003eArch Gerontol Geriatr, \u003c/em\u003evol. 61, no. 3, pp. 464-71, Nov-Dec 2015, doi: 10.1016/j.archger.2015.06.022.\u003c/li\u003e\n\u003cli\u003eL. A. Berner, G. Becker, M. Wise, and J. Doi, \u0026quot;Characterization of dietary protein among older adults in the United States: amount, animal sources, and meal patterns,\u0026quot; (in eng), \u003cem\u003eJ Acad Nutr Diet, \u003c/em\u003evol. 113, no. 6, pp. 809-15, Jun 2013, doi: 10.1016/j.jand.2013.01.014.\u003c/li\u003e\n\u003cli\u003eV. L. Fulgoni, 3rd, \u0026quot;Current protein intake in America: analysis of the National Health and Nutrition Examination Survey, 2003-2004,\u0026quot; (in eng), \u003cem\u003eAm J Clin Nutr, \u003c/em\u003evol. 87, no. 5, pp. 1554s-1557s, May 2008, doi: 10.1093/ajcn/87.5.1554S.\u003c/li\u003e\n\u003cli\u003eK. M. Appleton, \u0026quot;Barriers to and Facilitators of the Consumption of Animal-Based Protein-Rich Foods in Older Adults,\u0026quot; (in eng), \u003cem\u003eNutrients, \u003c/em\u003evol. 8, no. 4, pp. 187-187, 2016, doi: 10.3390/nu8040187.\u003c/li\u003e\n\u003cli\u003eN. LeBlanc-Morales, \u0026quot;Culinary Medicine: Patient Education for Therapeutic Lifestyle Changes,\u0026quot; \u003cem\u003eCritical Care Nursing Clinics of North America, \u003c/em\u003evol. 31, no. 1, pp. 109-123, 2019/03/01/ 2019, doi: https://doi.org/10.1016/j.cnc.2018.11.009.\u003c/li\u003e\n\u003cli\u003eJ. La Puma, \u0026quot;What Is Culinary Medicine and What Does It Do?,\u0026quot; \u003cem\u003ePopulation health management, \u003c/em\u003evol. 19, 06/02 2015, doi: 10.1089/pop.2015.0003.\u003c/li\u003e\n\u003cli\u003eB. Hasan\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;The effect of culinary interventions (cooking classes) on dietary intake and behavioral change: a systematic review and evidence map,\u0026quot; (in eng), \u003cem\u003eBMC Nutr, \u003c/em\u003evol. 5, p. 29, 2019, doi: 10.1186/s40795-019-0293-8.\u003c/li\u003e\n\u003cli\u003eV. Bramston, A. Rouf, and M. Allman-Farinelli, \u0026quot;The Development of Cooking Videos to Encourage Calcium Intake in Young Adults,\u0026quot; \u003cem\u003eNutrients, \u003c/em\u003evol. 12, no. 5, 2020, doi: 10.3390/nu12051236.\u003c/li\u003e\n\u003cli\u003eR. Polak\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Preventing Type 2 Diabetes with Home Cooking: Current Evidence and Future Potential,\u0026quot; \u003cem\u003eCurrent Diabetes Reports, \u003c/em\u003evol. 18, no. 10, p. 99, 2018/09/14 2018, doi: 10.1007/s11892-018-1061-x.\u003c/li\u003e\n\u003cli\u003eJ. A. Wolfson, C. W. Leung, and C. R. Richardson, \u0026quot;More frequent cooking at home is associated with higher Healthy Eating Index-2015 score,\u0026quot; (in eng), \u003cem\u003ePublic Health Nutr, \u003c/em\u003evol. 23, no. 13, pp. 2384-2394, Sep 2020, doi: 10.1017/s1368980019003549.\u003c/li\u003e\n\u003cli\u003eH. Irl B\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Culinary Medicine: Advancing a Framework for Healthier Eating to Improve Chronic Disease Management and Prevention,\u0026quot; \u003cem\u003eClinical Therapeutics, \u003c/em\u003evol. 41, no. 10, pp. 2184-2198, 2019/10/01/ 2019, doi: https://doi.org/10.1016/j.clinthera.2019.08.009.\u003c/li\u003e\n\u003cli\u003eA. M. Zivkovic and J. B. German, \u0026quot;Metabolomics for assessment of nutritional status,\u0026quot; (in eng), \u003cem\u003eCurrent opinion in clinical nutrition and metabolic care, \u003c/em\u003evol. 12, no. 5, pp. 501-507, 2009, doi: 10.1097/MCO.0b013e32832f1916.\u003c/li\u003e\n\u003cli\u003eT. K. Malmstrom, D. K. Miller, E. M. Simonsick, L. Ferrucci, and J. E. Morley, \u0026quot;SARC-F: a symptom score to predict persons with sarcopenia at risk for poor functional outcomes,\u0026quot; (in eng), \u003cem\u003eJ Cachexia Sarcopenia Muscle, \u003c/em\u003evol. 7, no. 1, pp. 28-36, Mar 2016, doi: 10.1002/jcsm.12048.\u003c/li\u003e\n\u003cli\u003eP. Morin, F. Herrmann, P. Ammann, B. Uebelhart, and R. Rizzoli, \u0026quot;A rapid self-administered food frequency questionnaire for the evaluation of dietary protein intake,\u0026quot; (in eng), \u003cem\u003eClin Nutr, \u003c/em\u003evol. 24, no. 5, pp. 768-74, Oct 2005, doi: 10.1016/j.clnu.2005.03.002.\u003c/li\u003e\n\u003cli\u003eR. A. Washburn, K. W. Smith, A. M. Jette, and C. A. Janney, \u0026quot;The Physical Activity Scale for the Elderly (PASE): development and evaluation,\u0026quot; (in eng), \u003cem\u003eJ Clin Epidemiol, \u003c/em\u003evol. 46, no. 2, pp. 153-62, Feb 1993, doi: 10.1016/0895-4356(93)90053-4.\u003c/li\u003e\n\u003cli\u003eM. Cesari\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Biomarkers of sarcopenia in clinical trials-recommendations from the International Working Group on Sarcopenia,\u0026quot; (in eng), \u003cem\u003eJ Cachexia Sarcopenia Muscle, \u003c/em\u003evol. 3, no. 3, pp. 181-90, Sep 2012, doi: 10.1007/s13539-012-0078-2.\u003c/li\u003e\n\u003cli\u003eA. J. Cruz-Jentoft\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People,\u0026quot; (in eng), \u003cem\u003eAge Ageing, \u003c/em\u003evol. 39, no. 4, pp. 412-23, Jul 2010, doi: 10.1093/ageing/afq034.\u003c/li\u003e\n\u003cli\u003eC. de F\u0026aacute;tima Ribeiro Silva, D. G. Ohara, A. P. Matos, A. Pinto, and M. S. Pegorari, \u0026quot;Short Physical Performance Battery as a Measure of Physical Performance and Mortality Predictor in Older Adults: A Comprehensive Literature Review,\u0026quot; (in eng), \u003cem\u003eInt J Environ Res Public Health, \u003c/em\u003evol. 18, no. 20, Oct 10 2021, doi: 10.3390/ijerph182010612.\u003c/li\u003e\n\u003cli\u003eI. Reinders, M. Visser, and H. A. H. Wijnhoven, \u0026quot;Two dietary advice strategies to increase protein intake among community-dwelling older adults: A feasibility study,\u0026quot; (in eng), \u003cem\u003eClin Nutr ESPEN, \u003c/em\u003evol. 37, pp. 157-167, Jun 2020, doi: 10.1016/j.clnesp.2020.02.020.\u003c/li\u003e\n\u003cli\u003eP. Edwards, \u0026quot;Questionnaires in clinical trials: guidelines for optimal design and administration,\u0026quot; (in eng), \u003cem\u003eTrials, \u003c/em\u003evol. 11, p. 2, Jan 11 2010, doi: 10.1186/1745-6215-11-2.\u003c/li\u003e\n\u003cli\u003eC. Nowson and S. O\u0026apos;Connell, \u0026quot;Protein Requirements and Recommendations for Older People: A Review,\u0026quot; (in eng), \u003cem\u003eNutrients, \u003c/em\u003evol. 7, no. 8, pp. 6874-99, Aug 14 2015, doi: 10.3390/nu7085311.\u003c/li\u003e\n\u003cli\u003eT. B. Symons, M. Sheffield-Moore, R. R. Wolfe, and D. Paddon-Jones, \u0026quot;A moderate serving of high-quality protein maximally stimulates skeletal muscle protein synthesis in young and elderly subjects,\u0026quot; (in eng), \u003cem\u003eJ Am Diet Assoc, \u003c/em\u003evol. 109, no. 9, pp. 1582-6, Sep 2009, doi: 10.1016/j.jada.2009.06.369.\u003c/li\u003e\n\u003cli\u003eJ. Bauer\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Evidence-based recommendations for optimal dietary protein intake in older people: a position paper from the PROT-AGE Study Group,\u0026quot; (in eng), \u003cem\u003eJ Am Med Dir Assoc, \u003c/em\u003evol. 14, no. 8, pp. 542-59, Aug 2013, doi: 10.1016/j.jamda.2013.05.021.\u003c/li\u003e\n\u003cli\u003eR. Sammarco\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Evaluation of Hypocaloric Diet With Protein Supplementation in Middle-Aged Sarcopenic Obese Women: A Pilot Study,\u0026quot; \u003cem\u003eObesity Facts, \u003c/em\u003evol. 10, no. 3, pp. 160-167, 2017, doi: 10.1159/000468153.\u003c/li\u003e\n\u003cli\u003eH.-N. Kim, S.-H. Kim, Y.-M. Eun, and S.-W. Song, \u0026quot;Impact of dietary protein intake on the incidence of low muscle strength in middle-aged and older adults,\u0026quot; \u003cem\u003eClinical Nutrition, \u003c/em\u003evol. 40, no. 4, pp. 1467-1474, 2021/04/01/ 2021, doi: https://doi.org/10.1016/j.clnu.2021.02.034.\u003c/li\u003e\n\u003cli\u003eS. Farsijani, H. Payette, J. A. Morais, B. Shatenstein, P. Gaudreau, and S. Chevalier, \u0026quot;Even mealtime distribution of protein intake is associated with greater muscle strength, but not with 3-y physical function decline, in free-living older adults: the Quebec longitudinal study on Nutrition as a Determinant of Successful Aging (NuAge study),\u0026quot; \u003cem\u003eThe American Journal of Clinical Nutrition, \u003c/em\u003evol. 106, no. 1, pp. 113-124, 2017/07/01/ 2017, doi: https://doi.org/10.3945/ajcn.116.146555.\u003c/li\u003e\n\u003cli\u003eJ. Zhao, Q. Lu, and X. Zhang, \u0026quot;Associations of serum vitamin B12 and its biomarkers with musculoskeletal health in middle-aged and older adults,\u0026quot; (in eng), \u003cem\u003eFront Endocrinol (Lausanne), \u003c/em\u003evol. 15, p. 1387035, 2024, doi: 10.3389/fendo.2024.1387035.\u003c/li\u003e\n\u003cli\u003eS. Y. Hwang, B. Sung, and N. D. Kim, \u0026quot;Roles of folate in skeletal muscle cell development and functions,\u0026quot; (in eng), \u003cem\u003eArch Pharm Res, \u003c/em\u003evol. 42, no. 4, pp. 319-325, Apr 2019, doi: 10.1007/s12272-018-1100-9.\u003c/li\u003e\n\u003cli\u003eD. Groothof\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Creatinine, cystatin C, muscle mass, and mortality: Findings from a primary and replication population-based cohort,\u0026quot; (in eng), \u003cem\u003eJ Cachexia Sarcopenia Muscle, \u003c/em\u003evol. 15, no. 4, pp. 1528-1538, Aug 2024, doi: 10.1002/jcsm.13511.\u003c/li\u003e\n\u003cli\u003eM. Tosato\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Measurement of muscle mass in sarcopenia: from imaging to biochemical markers,\u0026quot; (in English), \u003cem\u003eAging Clinical and Experimental Research, suppl. 1, \u003c/em\u003evol. 29, pp. 19-27, Feb 2017 2023-11-18 2017, doi: https://doi.org/10.1007/s40520-016-0717-0.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Animal Protein, Beef, Culinary Medicine, Lifestyle Medicine, Muscle Quality, Nutrition","lastPublishedDoi":"10.21203/rs.3.rs-5868973/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5868973/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAge-related muscle loss can be decreased with increased protein intake. Recent evidence suggests that increasing animal-based protein such as lean beef can be the most effective for age-related muscle repair and growth. Culinary medicine (CM) is a science-based field to teach people the art of food and cooking with the science of medicine to improve health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to assess the impact of a digital culinary medicine education program emphasizing lean beef on protein intake and muscle quality among community-dwelling senior adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 16-week randomized study compared a culinary medicine intervention group (CM) to a control group (CN). Among 47 senior adults assessed for eligibility, 28 participants completed the intervention. The CM invention included weekly cooking demonstration and nutrition education videos. Protein intake, cooking effectiveness, physical activity, and nutrition knowledge were assessed with questionnaires while muscle quality, vitamin B\u003csub\u003e12\u003c/sub\u003e, folate, and creatinine levels were objectively measured.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMuscle quality measurements showed a significant difference in change in muscle mass between groups (\u003cem\u003eP\u003c/em\u003e = 0.041). Higher protein intake was seen in the CM group compared to a decrease in protein intake seen among the CN group. However, there was no between-group difference in protein intake from the pre-study (\u003cem\u003eP\u003c/em\u003e = 0.454). Similar results were seen with the other measurements from baseline.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results suggest that this CM intervention was associated with improved muscle mass. There is also potential for this type of intervention to increase protein intake.\u003c/p\u003e\n\u003cp\u003eClinical Trials ID: NCT06157385\u003c/p\u003e","manuscriptTitle":"The Effect of Culinary Medicine to Enhance Protein Intake on Muscle Quality in Older Adults: A Randomized Controlled Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-03 08:47:24","doi":"10.21203/rs.3.rs-5868973/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-14T10:53:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-08T04:02:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-04T14:37:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-03T03:00:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"182555991665428231892714667573546252489","date":"2025-01-26T22:40:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78568552815747516812768170161734412921","date":"2025-01-26T15:52:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-26T07:07:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-25T16:53:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-21T11:16:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aging Clinical and Experimental Research","date":"2025-01-20T23:29:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c322bd37-25bd-4a14-bc6a-7a77cd37882c","owner":[],"postedDate":"February 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-02T16:06:49+00:00","versionOfRecord":{"articleIdentity":"rs-5868973","link":"https://doi.org/10.1007/s40520-025-03075-8","journal":{"identity":"aging-clinical-and-experimental-research","isVorOnly":false,"title":"Aging Clinical and Experimental Research"},"publishedOn":"2025-05-27 15:57:58","publishedOnDateReadable":"May 27th, 2025"},"versionCreatedAt":"2025-02-03 08:47:24","video":"","vorDoi":"10.1007/s40520-025-03075-8","vorDoiUrl":"https://doi.org/10.1007/s40520-025-03075-8","workflowStages":[]},"version":"v1","identity":"rs-5868973","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5868973","identity":"rs-5868973","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}