Copyright is owned by the Author of the thesis. Permission is given for a copy to be downloaded by an individual for the purpose of research and private study only. The thesis may not be reproduced elsewhere without the permission of the Author. 1 Muscle strength and muscle mass in older adults: A focus on protein intake, distribution, and sources A thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Nutritional Science at Massey University, Albany, New Zealand Anne Nadine Hiol 2023 2 Abstract Background: Ageing and obesity, which impair muscle protein synthesis (MPS), are associated with muscle mass and muscle strength loss in older adults. It is recognised that adequate protein intake, distribution and sources contribute to increased MPS and muscle mass in older adults. However, little is known about protein intake, distribution, and sources in New Zealand (NZ) older adults. Furthermore, it is unclear whether dietary protein influences muscle strength. Objectives: This thesis explored muscle strength, muscle mass and dietary protein intake, distribution and sources in community-dwelling older adults living in NZ. To meet this objective, the role of obesity in the relationship between muscle mass and muscle strength was examined. This was followed by an investigation of protein intake, distribution and sources, and their association with muscle strength. Methods: Data were obtained from the Researching Eating Activity and Cognitive Health (REACH) study, a cross-sectional study aimed at investigating dietary patterns and associations with cognitive function and metabolic syndrome in older adults aged 65 to 74 years. Isometric grip strength was measured using a hand grip strength dynamometer (JAMAR HAND). Body fat percentage and appendicular skeletal muscle mass (ASM) (sum of lean mass in the arms and legs) were assessed using dual-energy X-ray absorptiometry (Hologic, QDR Discovery A). The ASM index was calculated by ASM (kilograms, kg) divided by height (meters, m) squared. Dietary intake was collected using a 4-day food record, and the data was entered into FoodWorks 10. Data on absolute daily protein intake (grams, g) were generated. According to the peaks of protein consumption throughout the day, days were divided into three meals: breakfast, mid-day, and the evening meals. Protein sources were classified as meat and fish; plant; or dairy and egg protein sources based on the primary type of protein found in food. The relative protein intakes (g/kg) per day, meal, and source were calculated by dividing the absolute protein intake (g) by each participant's body weight (kg). 3 Statistical analyses: A linear regression analysis was performed to determine the association between muscle mass and muscle strength. This analysis was conducted on males and females based on obesity classifications using body fat percentage (obesity ≥ 30% males, ≥ 40% females). The relative protein intake was compared against a cut-off value of 1.2 g of protein per kg body weight (g/kg BW) per day. The distribution of protein across the three meals was expressed as the coefficient of variance (CV), the average of total protein intake per main meal and the number of meals exceeding 0.4 g/kg BW of protein across the day. Sources of protein intake were assessed at breakfast, mid-day and the evening meals. Results are presented as a percentage of the total protein intake for each meal. Finally, linear regression analyses were conducted separately in males and females to investigate the relationships between BMI- muscle strength and protein intake, distribution and sources, accounting for relevant confounders. Results: Muscle mass was a significant predictor of muscle strength in non-obese participants. However, in participants with obesity, muscle mass was no longer a significant predictor of muscle strength. More than half of the participants had a protein intake of < 1.2 g/kg BW per day (62% females, 57% males). Protein intake was unevenly distributed throughout the day (CV = 0.48 for males and females) and was inadequate for reaching 0.4 g/kg BW at breakfast (for both males and females) and at the mid-day meal for males. The main sources of protein at breakfast were milk (28%), breakfast cereals (22%), and bread (12%); at the mid-day meal, bread (18%), cheese (10%) and milk (9%); and at the evening meal, meat provided over half the protein (56%). In females, relative protein intake was positively associated with muscle strength adjusted BMI (BMI-muscle strength) (r2 = 0.15, ρ < 0.01). Protein derived from either dairy and egg (ρ = 0.03); and plant sources (ρ < 0.01) was related to BMI-muscle strength but not protein from meat and fish (ρ = 0.55). Greater frequency of protein consumption of at least 0.4 g/kg BW per meal was associated with BMI-muscle strength (ρ = 0.01), but the coefficient of variance for protein intake distribution was not related to BMI-muscle strength (ρ = 0.47). 4 There was no relationship between BMI-muscle strength and total daily protein intake, protein from meat and fish; dairy and egg; and plant-based sources, or distribution defined as frequency of protein consumption of at least 0.4 g/kg BW per meal or CV in male older adults. Conclusions: Obesity should be considered when measuring associations between muscle mass and muscle strength in older adults. A higher BMI-adjusted muscle strength was associated with consuming more protein each day and a higher frequency of consumption of a meal containing at least 0.4 g/kg BW; and from dairy and egg; and plant food sources in female older adults. There was no correlation between protein intake, distribution and sources and muscle strength in males. Protein intake was less than 1.2 g/kg BW per day and 0.4 g/kg BW per meal for a large proportion of older adults. At breakfast and the mid-day meals the main sources of protein were from cereals and dairy products, and from meat sources at the evening meal. Further research is needed to investigate how best to optimise protein intake to increase and maintain muscle mass and muscle strength in older adults from the general population. 5 Acknowledgements This research was conducted with the support of several people. First and foremost, I would like to thank my supervisors at Massey University's School of Sport, Exercise and Nutrition: Associate Professor Kathryn Beck, who seeded the vision for this thesis and provided substantial content and professional guidance throughout its development; Associate Professor Cathryn Conlon, who reviewed and advised on the thesis's content; and Professor Pamela von Hurst, who provided guidance and feedback throughout this process. My supervisors' expert advice, scientific ideas, and mentorship have been invaluable throughout this process. Several people contributed to the timely and effective completion of the Researching Eating Activity and Cognitive Health (REACH) study. The entire REACH research team deserves special recognition, especially Owen Mugridge and Cassie Slade for managing participant recruitment and data collection; and Karen Mumme, Cherise Pendergrast, Kimberley Brown, Harriet Guy, Angela Yu, and Nicola Gillies for assisting with data collection and data entry. I would like to recognise all the volunteers who have participated in the REACH study for their dedication and commitment to the research. I would like to thank my friends and family for all their emotional support and inspiration. Finally, and most importantly, I want to thank my parents for encouraging me to believe in my ideas and pursue my dreams. I am truly blessed to have my daughter, Malayka Hiol Bayeck, who never ceases to make me smile; waking up every morning to see your face always brightens my day. I'd like to conclude my acknowledgements by thanking Raoul Bayeck, my life partner, for his encouragement throughout this process. 6 Table of contents Abstract ................................................................................................................. 2 Acknowledgements .............................................................................................. 5 Table of contents .................................................................................................. 6 List of tables ....................................................................................................... 11 List of figures ..................................................................................................... 14 List of abbreviations ........................................................................................... 15 List of manuscripts and conference presentations .............................................. 17 Researchers’ contributions ................................................................................. 18 Chapter One – Introduction ............................................................................ 21 1.1. Introduction ................................................................................................. 21 1.2. Research objectives ..................................................................................... 25 1.3. Thesis outline ............................................................................................... 25 1.4. References ................................................................................................... 27 Chapter Two – Literature review ................................................................... 36 2.1. Search strategies .......................................................................................... 36 2.2. Ageing and falls ........................................................................................... 39 2.3. Muscle strength in older adults .................................................................... 41 2.3.1 Assessment of muscle strength ................................................................................... 42 2.3.2. Prevalence of low muscle strength ............................................................................ 44 2.4. Muscle strength and muscle mass in older adults ....................................... 44 2.4.1. Muscle mass, protein, and ageing .............................................................................. 44 7 2.4.2. Assessment and prevalence of low muscle mass ....................................................... 46 2.4.3. Relationship between muscle mass and muscle strength ........................................... 49 2.5. Protein intake, distribution, sources, and muscle protein synthesis ............ 51 2.5.1. Protein intake, recommendations, and muscle protein synthesis in older adults ....... 51 2.5.2. Protein distribution and muscle protein synthesis in older adults .............................. 53 2.5.3. Protein quality, sources, and muscle protein synthesis in older adults ...................... 54 2.6. Dietary assessment of protein: intake, distribution, and sources ................. 56 2.7. Protein intake, distribution, and sources in community-dwelling older adults ............................................................................................................................ 61 2.8. Protein intake, distribution, and sources; muscle mass; and muscle strength ............................................................................................................................ 65 2.8.1. Association between protein intake, muscle mass and muscle strength .................... 65 2.8.2. Associations between protein distribution, muscle mass, and muscle strength in older adults .................................................................................................................................... 72 2.8.3. Associations between protein sources, muscle mass, and muscle strength in older adults .................................................................................................................................... 74 2.9. Conclusions from the literature ................................................................... 78 2.10. References ................................................................................................. 80 Chapter Three – Body composition associations with muscle strength in older adults living in Auckland, New Zealand ............................................. 112 3.1. Abstract ...................................................................................................... 113 3.2. Introduction ............................................................................................... 114 3.3. Materials and methods ............................................................................... 115 3.3.1. Study design ............................................................................................................. 115 8 3.3.2. Study participants and procedures ........................................................................... 116 3.3.3. Data collection ......................................................................................................... 116 3.3.4. Statistical analysis .................................................................................................... 117 3.4. Results ....................................................................................................... 118 3.5. Discussion .................................................................................................. 123 3.5.1. Prevalence of obesity, low muscle strength and low muscle mass .......................... 123 3.5.2. Association between body composition and muscle strength .................................. 124 3.5.3. The role of obesity classification in the relationship between muscle strength and muscle mass ....................................................................................................................... 125 3.6. Conclusions ............................................................................................... 126 3.7. References ................................................................................................. 128 Chapter Four – Protein intake, distribution, and sources in community- dwelling older adults living in Auckland, New Zealand ............................. 135 4.1. Abstract ...................................................................................................... 136 4.2. Introduction ............................................................................................... 137 4.3. Materials and methods ............................................................................... 138 4.3.1. Study population ...................................................................................................... 139 4.3.2. Data collection ......................................................................................................... 139 4.3.3. Data handling ........................................................................................................... 140 4.3.4. Statistical analysis .................................................................................................... 141 4.4. Results ....................................................................................................... 142 4.5. Discussion .................................................................................................. 151 4.5.1. Prevalence of low protein intake .............................................................................. 151 9 4.5.2. Distribution of protein intake ................................................................................... 152 4.5.3. Relative contribution of protein from different food sources .................................. 153 4.5.4. Sources of protein determining high protein intake ................................................. 153 4.6. Strengths and limitations ........................................................................... 154 4.7. Conclusions ............................................................................................... 155 4.8. References ................................................................................................. 156 Chapter Five – The association between muscle strength and protein intake, sources, and distribution in community-dwelling older adults living in Auckland, New Zealand ................................................................................. 165 5.1. Abstract ...................................................................................................... 166 5.2. Introduction ............................................................................................... 168 5.3. Materials and methods ............................................................................... 170 5.3.1. Study design ............................................................................................................. 170 5.3.2. Data collection ......................................................................................................... 170 5.3.3. Data handling ........................................................................................................... 171 5.3.4. Statistical analysis .................................................................................................... 172 5.4. Results ....................................................................................................... 173 5.5. Discussion .................................................................................................. 182 5.5.1. Associations between BMI-muscle strength and protein intake, sources, and distribution in females ........................................................................................................ 182 5.5.2. Associations between muscle strength and protein intake, sources, and evenness distribution in males ........................................................................................................... 184 5.6. Conclusions ............................................................................................... 185 5.7. References ................................................................................................. 186 10 6.1. Discussion of main results and further perspectives ................................. 196 6.2. Strengths and limitations ........................................................................... 199 6.2.1. Study design ............................................................................................................. 199 6.3.2. Study population ...................................................................................................... 199 6.3.3. Measurement of body composition .......................................................................... 200 6.3.4. Measurement of muscle strength ............................................................................. 200 6.3.5. Dietary assessment ................................................................................................... 200 6.3. Further perspectives and conclusions ........................................................ 201 6.4. References ................................................................................................. 203 7. Appendices .................................................................................................. 208 Appendix A – Statement of contribution manuscript (chapter three) ................................ 208 Appendix B – Statement of contribution manuscript (chapter four) ................................. 209 Appendix C – Statement of contribution manuscript (chapter five) .................................. 210 Appendix D – Protocol for all anthropometric measures (adapted from International Society for the Advancement of Kinanthropometry (ISAK) protocol) .......................................... 211 Appendix E – Standard operating procedure for handgrip strength .................................. 213 Appendix F – Standard operating procedure for the 4-day food diary .............................. 215 Appendix G – Food groupings from derived from the 4-day food record ......................... 216 11 List of tables Chapter Two Table 2. 1. Literature review search strategies ................................................... 37 Table 2. 2. Consensus statements on cut-off values for determining low muscle strength in older adults. ...................................................................................... 43 Table 2. 3. Prevalence of low muscle mass in older adults: a comparison of different definitions and cut-off values. ............................................................. 48 Table 2. 4. Cross-sectional studies investigating the relationship between muscle mass and muscle strength in older adults. .......................................................... 50 Table 2. 5. Nutrient Reference Values for protein for adults and older adults in Australia and New Zealand (National Health and Medical Research Council Australian Government Department of Health and Ageing, 2006). ................... 52 Table 2. 6. Digestibility and amino acid concentrations of common animal protein sources. Adapted from van Vliet et al. (2015). ................................................... 55 Table 2. 7. Dietary assessment methods and their advantages and limitations. . 57 Table 2. 8. Summary of different approaches used to define eating occasions (Leech et al., 2015a, 2015b). .............................................................................. 60 Table 2. 9. Prevalence of low protein intake. ..................................................... 61 12 Table 2. 10. Associations between protein intake and handgrip strength in older adults. .................................................................................................................. 69 Table 2. 11. The association between sources of protein and muscle mass ....... 76 Chapter Three Table 3. 1. Characteristics of study participants by sex a,b. .............................. 119 Table 3. 2. Results of multiple linear regression modelling on the relationship between muscle strength, mass, and body fat percentage in older females. .... 121 Table 3. 3. Results of multiple linear regression modelling on the relationship between muscle strength, mass and body fat percentage in older males. ......... 121 Table 3. 4. Results of multiple linear regression modelling on the effect of obesity in the relationship between muscle strength and mass in older females. ......... 122 Table 3. 5. Results of multiple linear regression modelling on the effect of obesity in the relationship between muscle strength and mass in older males. ............ 122 Chapter Four Table 4. 1. Characteristics of participants a,b .................................................... 143 Table 4. 2. Median daily energy, macronutrient, and protein intake in older adults by sex a,b. ........................................................................................................... 144 13 Table 4. 3. Mean intake and relative contribution of protein from different food sources at each meal. ........................................................................................ 147 Table 4. 4. Final model for prediction of protein intake ≥ 0.4 g/kg BW at each meal. ................................................................................................................. 150 Chapter Five Table 5. 1. Participants’ characteristics a,b ........................................................ 174 Table 5. 2. Median protein intake, distribution, and sources a,b ....................... 176 Table 5. 3. Association between protein intake and muscle strength in females and males. ......................................................................................................... 177 Table 5. 4. Associations between sources of protein and muscle strength in females and males. ............................................................................................ 179 Table 5. 5. Associations between protein distribution and muscle strength and in males and females. ............................................................................................ 180 14 List of figures Chapter Two Figure 2. 1. Declining quadriceps muscle strength in adults. Data from Al- Abdulwahab (1999). ........................................................................................... 41 Figure 2. 2. Adequate protein distribution (A) and inadequate protein distribution (B). Adapted from Paddon-Jones and Rasmussen (2009). ................................. 54 Chapter Three Figure 3. 1. Association between muscle strength and mass in females and males (n = 369). .......................................................................................................... 120 Chapter Four Figure 4. 1. Distribution of dietary protein intake across the day in community- dwelling older adults. ....................................................................................... 145 Figure 4. 2. Relative protein intakes for breakfast, the mid-day meal, and the evening meal, by sex. ....................................................................................... 146 15 List of abbreviations ACC Accident Compensation Corporation ANZSSFR Australian and New Zealand Society for Sarcopenia and Frailty Research AA Amino acid ASM Appendicular skeletal muscle mass ALM Appendicular lean mass BW Body weight BMI Body mass index BIA Bioelectrical impedance analysis CSA Cross-sectional area CT Computed tomography DXA Dual-energy X-ray absorptiometry EAR Estimated average requirement EFSA European Food Safety Authority EWGSOP European Working Group on Sarcopenia in Older People FFM Fat-free mass FFQ Food frequency questionnaire HGS Handgrip strength IAAO Indicator amino acid oxidation IDAA Indispensable dietary amino acid IQS Isokinetic quadriceps strength LM Lean mass LBM Lean body mass MAMA MeSH Midarm muscle area Medical subject headings MPS Muscle protein synthesis MPB Muscle protein breakdown MRI Magnetic resonance imaging NHANES National Health and Nutrition Examination Survey 16 NZ New Zealand RDI Recommended daily intake RDA Recommended daily allowance REACH RNI Researching Eating Activity and Cognitive Health Recommended Nutrient Intake SMM UK US Skeletal muscle mass United Kingdom United States USDA United States Department of Agriculture WHO World Health Organisation 17 List of manuscripts and conference presentations This is a thesis with publications. Three publications were written as well as oral and poster conference presentations. Published manuscript Paper I Incorporated as chapter 3 Hiol, A. N., von Hurst, P. R., Conlon, C. A., Mugridge, O., & Beck, K. L. (2021). Body composition associations with muscle strength in older adults living in Auckland, New Zealand. PloS ONE 16(5): e0250439. https://doi.org/10.1371/journal.pone.0250439. Manuscript under review Paper II Incorporated as chapter 4 Hiol, A. N., von Hurst, P. R., Conlon, C. A., Mumme, K. D., & Beck, K. L. (2023). Protein intake, distribution, and sources in community-dwelling older adults living in Auckland, New Zealand. Nutrition and Healthy Aging. Manuscript under review Paper III Incorporated as chapter 5 Hiol, A. N., von Hurst, P. R., Conlon, C. A., & Beck, K. L. (2023). The association between muscle strength and protein intake, sources, and distribution in older adults living in Auckland, New Zealand. Submitted to Journal of Nutritional Science. Published oral presentations Abstract I Hiol, A. N., von Hurst, P. R., Conlon, C. A., & Beck, K. L. (2019). Body composition and associations with muscle strength in older adults living in Auckland, New Zealand. Proceedings, 37(1), 51. https://doi.org/10.3390/proceedings2019037051. Abstract II Hiol, A. N., von Hurst, P. R., Conlon, C. A., de Seymour, J. V., & Beck, K. L. (2020). Prevalence of low muscle mass, muscle strength and upper-body muscle quality in community-living older adults living in Auckland, New Zealand. Symposia. The Journal of Frailty & Aging 9 (Suppl 1), 1–45. https://doi.org/10.14283/jfa.2020.8. Published poster presentation Abstract III Hiol, A. N., von Hurst, P. R., Conlon, C. A., & Beck, K. L. (2022). Protein sources across the day in community-dwelling older adults living in Auckland, New Zealand. Medical Sciences Forum, 9, 40. https://doi.org/10.3390/msf2022009040. 18 Researchers’ contributions This research was completed as part of the Researching Eating Activity and Cognitive Health (REACH) study – a cross-sectional study in 371 community-dwelling older adults aged 65 to 74 years living independently. The primary outcome of the REACH study was to investigate dietary patterns and associations with cognitive function and metabolic health in community- dwelling older adults. Participants completed a health and demographics questionnaire, a food frequency questionnaire, a food record over 4 days and an International Physical Activity Questionnaire. Anthropometric measurements including weight, height, waist and hip circumference were performed. Blood pressure was measured, and a fasting blood sample taken for lipid profile, glucose, Haemoglobin A1c, metabolomics and genotyping. Muscle strength was measured using handgrip strength. Dual-energy X-ray absorptiometry (DXA) was used to determine body composition. The Montreal Cognitive Assessment (MoCA) and the Computerised Mental Performance Assessment System were used to assess cognitive function. The American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement criteria were used to determine the incidence of metabolic syndrome (Grundy et al., 2005). The REACH study was funded by a Health Research Council of New Zealand Emerging Researcher Grant 17/566 - Beck: Optimising cognitive function: the role of dietary and lifestyle patterns. Associate Professor Kathryn Beck, Associate Professor Cathryn Conlon, and Professor Pamela von Hurst conceptualised, designed and conducted the REACH study, alongside the wider REACH study team. Several people assisted with the REACH study, including Owen Mugridge and Cassie Slade who managed the recruitment of participants and data collection; Cherise Pendergrast, Kimberley Brown, Harriet Guy, Angela Yu, and Nicola Gillies who assisted with data collection and data entry; and Karen Mumme who was responsible for data management. The PhD candidate undertook an internship at Massey University from January to June 2018. During that time and during her PhD candidature, she worked full time on REACH study preparation and data collection in relation to the research objectives. The PhD candidate’s key responsibilities and roles are outlined below. 19 Task Task details Specific activities undertaken by the PhD candidate Massey University doctoral scholarship application Defined the research topic Reviewed the literature on muscle strength, muscle mass and dietary protein to design the research proposal Stated the problem Literature review Methodology and research design Study preparation Procedures for measuring muscle strength, height, and weight Developed a standard operating procedure for measurement of handgrip strength Generated a standard operating procedure for measurement of height and weight Food diary instructions Involved in the development of a food diary instructions for participants to complete food diaries Data collection Muscle strength measurements Undertook handgrip strength and anthropometric measurements on participants Anthropometric measurements Health and demographic questionnaire Assisted participants with completing health and demographic questionnaire Blood processing Processed blood as part of REACH study wider objectives 20 Data handling and analysis Food diary data processing Entered food record data using FoodWorks 10 – this included creating and adding new recipes of dishes and food to the database Sorted database by timing of intake and sources of protein consumed: each participant provided a detailed description of all food and beverages consumed (food, beverage, name, brand, variety, and preparation methods), portion sizes, and the timing of intake over 4 days-period. There were over 50,000 lines of food and beverages lines in the database Handgrip strength, anthropometric, health and demographic data processing Developed a data cleaning procedure to ensure the removal of duplicate, incorrect, or incomplete data from the dataset. Formatted, organised, and/or combined data sets into single Excel spreadsheets for statistical analysis. Developed a data transformation procedure that included coding, definitions, and assumptions made regarding the data Statistical analysis Undertook all statistical analysis to complete the thesis with guidance from supervisors Writing of thesis Introduction, literature review, manuscripts 1, 2, and 3; discussion and conclusions Interpreted results and wrote all of the thesis components. See appendix A, B and C for contribution forms 21 Chapter One – Introduction This chapter outlines the scope and justification for this thesis by introducing the significance of muscle strength, muscle mass and dietary protein in the context of an aging population with a high risk of falls and injuries. Following this, the aims and objectives are provided along with the thesis outline. 1.1. Introduction Both globally and in New Zealand (NZ) the proportion of older adults is increasing (Wan He et al., 2016). In 2020, 16% of NZ’s population was aged 65 or older (Statistics New Zealand, 2020). This percentage is expected to increase to more than 21% by the year 2048 (Crothers, 2021). With an increasing older population, there is a high proportion of people experiencing falls and fall-related injuries (Health Quality & Safety Commission, 2016; Peel, 2011; Rubenstein & Josephson, 2002). Low muscle strength is an emerging global health concern because it is the leading causes of falls in older adults (American Geriatrics Society et al., 2001; Moreland et al., 2020; Rubenstein, 2006). However, little is known about predictors of muscle strength among NZ’s older adults. Cross-sectional studies have demonstrated that muscle mass is correlated with muscle strength (Barbat-Artigas, Plouffe, et al., 2013; Beliaeff et al., 2008; Chen et al., 2013; Hayashida et al., 2014; Reed et al., 1991). Furthermore, longitudinal studies investigating changes in muscle strength and muscle mass in older adults have shown that loss of muscle mass is a major factor in the decline in muscle strength with age (Frontera et al., 2000; Newman et al., 2003). However, there is also evidence that changes in muscle mass explain only a small proportion of the changes in muscle strength in older adults (Goodpaster et al., 2006; Hughes et al., 2001). Obesity may interact with the relationship between muscle mass and muscle strength, leading to different degrees of association. 22 The homeostasis of muscle mass is regulated by a dynamic turnover between muscle protein synthesis (MPS) (anabolic) and muscle protein breakdown (MPB) (catabolic). Studies have suggested that anabolic impairment to ingested protein is an important factor influencing age- related muscle mass loss (Fujita, 2007; Moore, 2014; Volpi et al., 2001). In addition, it is recognised that obesity in older adults can impair the responsiveness of MPS to protein ingestion (Beals et al., 2018; Guillet et al., 2009; Murton et al., 2015). This impaired MPS is likely to affect the intramuscular lipid content (or muscle quality), which is also associated with muscle strength (Goodpaster et al., 2001). However, there is limited evidence on the role of obesity on the relationship between muscle strength and muscle mass in older adults. With increasing rates of obesity in New Zealand and globally (Wan He et al., 2016), a greater understanding of obesity’s role when investigating associations between muscle mass and muscle strength is warranted. Dietary protein impacts on muscle mass and muscle strength in older adults. Per day and per meal stimulation of MPS have a saturable dose relationship with the quantity and quality (i.e., source) of protein consumed (Churchward-Venne et al., 2016; Gorissen et al., 2015). To maximise MPS stimulation, it has been suggested that older adults should consume ≥ 1.2 g of protein per kg body weight (g/kg BW) per day (Rafii et al., 2015), which has been shown to slow muscle mass loss in older adults aged 70 to 79 years (Houston et al., 2008; Scott et al., 2010). However, findings on the association between protein intake and muscle strength in cross-sectional and longitudinal studies have been contradictory. Handgrip strength (HGS) is commonly used to predict overall strength in older adults (Ekstrand et al., 2015; Takahashi et al., 2017). There is evidence of an association between relative protein intake (protein intake based on body weight) and HGS adjusted by body weight (BW) or body mass index (BMI) (Celis-Morales et al., 2018; Fanelli Kuczmarski et al., 2018; Isanejad et al., 2016). Other studies have found no association between relative protein intake and absolute HGS (Granic et al., 2018; Mishra et al., 2018; Ten Haaf et al., 2018). The inconsistent findings could be attributed to the use of different HGS indexes such as absolute HGS versus relative HGS with adjustment for BW or BMI. 23 A maximum stimulation of MPS rate in older adults has been observed at a protein intake of 30 g or 0.4 g/kg BW per meal (Moore et al., 2015; Paddon-Jones & Rasmussen, 2009). Studies have demonstrated that an evenly distributed intake of protein across the day of 30 g or 0.4 g/kg BW per meal resulted in higher MPS than did an uneven protein distribution (Mamerow et al., 2014; Paddon-Jones & Rasmussen, 2009). Furthermore, cross-sectional evidence from large numbers of participants has demonstrated that a more even distribution of protein is associated with greater muscle mass in older adults (Farsijani et al., 2016; Farsijani et al., 2017; Loenneke et al., 2016). Because protein distribution is a new concept, there is no consistent definition (Aoyama et al., 2021; Hudson et al., 2020). Protein distribution is commonly estimated as the coefficient of variance (CV) of the protein intake, or the number of meals exceeding 30 g or 0.4 g/kg BW. However, the use of different methods to estimate protein distribution makes it difficult to make conclusions regarding the relationship between protein distribution and muscle strength in older adults (Bollwein et al., 2013; Gingrich et al., 2017; Kim et al., 2018; Mishra et al., 2018; Ten Haaf et al., 2018). Investigating associations between muscle strength and protein distribution using different estimates of protein distribution commonly used in the literature may assist in clarifying the relationship. High-quality animal proteins such as meat, dairy and eggs have a greater ability to enhance MPS than plant-based proteins (Gorissen et al., 2016; van Vliet et al., 2015; Yang et al., 2012). However, not all animal-based protein sources are comparable in terms of protein quality properties, which determine the amplitude and duration of the muscle protein synthetic response (Schaafsma, 2000; Smith & Gray, 2016; van Vliet et al., 2015). Studies have demonstrated that higher intake of animal-based protein (but not plant-based protein) was associated with higher muscle strength in older adults (Isanejad et al., 2015; McLean et al., 2016). However, these studies did not address whether either animal-based protein sources, (i.e., meat, fish, dairy, or eggs), which differ in quality, is associated with muscle strength. In international cohorts, a high proportion of older adults’ intake of protein has been shown to be < 1.2 g/kg BW (Houston et al., 2017; Isanejad et al., 2016; Mendonça et al., 2018). However, there is no data on the prevalence of protein intakes of < 1.2 g/kg BW in older adults in NZ. 24 Furthermore, few studies have investigated whether older adults are meeting protein intake recommendations of 30 g or 0.4 g/kg BW per meal. Two international cohort studies indicated that a high proportion of older adults were not consuming two or more meals containing at least 30 g or 0.4 g/kg BW of protein at each meal (Gaytán González et al., 2020; Loenneke et al., 2016). Studies are now beginning to consider the protein sources consumed at specific times of the day in order to understand how to increase protein intake at each meal and improve protein distribution throughout the day in older adults (Smeuninx et al., 2020; Tieland et al., 2015). A study in the Netherlands reported that in community-dwelling older adults (mean age 77 years), protein was obtained mainly from plant-based protein sources at breakfast and the lunch meal, and animal-based protein sources at dinner (Tieland et al., 2015). However, such work has not yet been undertaken in NZ. In conclusion, further work is required regarding the role of obesity when investigating associations between muscle mass and muscle strength in older adults. It is also important to understand how older adults in New Zealand are consuming protein. This includes total protein intake, distribution of protein across the day and sources of protein (both across the day and at mealtimes). A greater understanding of how protein is consumed and associations with muscle strength adjusted appropriately for body composition is warranted. This knowledge will enable targeted nutrition education and interventions to be developed to help optimise protein intake in older adults. 25 1.2. Research objectives The aim of this research is to explore muscle strength, muscle mass, and dietary protein intake in community-dwelling older adults living in Auckland, NZ. Specific objectives are to: - Explore the role of obesity in the relationship between muscle mass and muscle strength in community-dwelling older adults living in NZ; - Investigate protein intake, distribution, and sources in community-dwelling older adults living in NZ; - Investigate muscle strength and its relationship with protein intake, sources, and different estimates of protein distribution throughout the day in community-dwelling older adults living in NZ. 1.3. Thesis outline This thesis includes six chapters – an introduction, literature review, three manuscripts, and a discussion chapter. As each manuscript is presented in the form of a journal article adapted from its published version, there may be some repetition throughout the thesis. Chapter one introduces the importance of the research topic in a global aging population. Previous literature and research gaps regarding muscle strength, muscle mass and dietary protein are identified, leading to the research aims and objectives. Chapter two provides a thorough review of all relevant evidence regarding muscle strength, muscle mass, and dietary protein intake, distribution, and sources in older adults. Chapter three, the first manuscript, examines the relationship between muscle mass and muscle strength, accounting for obesity in older adults living in Auckland, NZ. 26 Chapter four, the second manuscript, is a comprehensive investigation regarding protein intake, distribution, and sources in older adults living in Auckland, NZ. Chapter five, the third manuscript, explores associations between muscle strength and protein intake, sources, and distribution in older adults living in Auckland, NZ. Note that chapters three, four and five are participants from the same study population. Chapter six, discusses the findings of the three manuscripts, including their significance and relevance, the methodological strengths and limitations of the studies, and suggested future research on muscle strength, muscle mass, and dietary protein in older adults. This chapter ends with final conclusions regarding the research findings. 27 1.4. References American Geriatrics Society, British Geriatrics Society, & American Academy of Orthopaedic Surgeons Panel on Falls Prevention. (2001). Guideline for the prevention of falls in older persons. Journal of the American Geriatrics Society, 49(5), 664-672. Aoyama, S., Kim, H.-K., Hirooka, R., Tanaka, M., Shimoda, T., Chijiki, H., Kojima, S., Sasaki, K., Takahashi, K., Makino, S., Takizawa, M., Takahashi, M., Tahara, Y., Shimba, S., Shinohara, K., & Shibata, S. (2021). Distribution of dietary protein intake in daily meals influences skeletal muscle hypertrophy via the muscle clock. 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Falls in people aged 50 and over New Zealand Atlas of Healthcare Variation. 31 Houston, Nicklas, Ding, Harris, Tylavsky, Newman, Lee, J. S., Sahyoun, N. R., Visser, M., Kritchevsky, S. B., & Health, A. B. C. S. (2008). Dietary protein intake is associated with lean mass change in older, community-dwelling adults: the Health, Aging, and Body Composition (Health ABC) Study. American Journal of Clinical Nutrition, 87(1), 150-155. https://doi.org/10.1093/ajcn/87.1.150 Houston, D. K., Tooze, J. A., Garcia, K., Visser, M., Rubin, S., Harris, T. B., Newman, A. B., & Kritchevsky, S. B. (2017). Protein intake and mobility limitation in community-dwelling older adults: the Health ABC Study. Journal of the American Geriatrics Society, 65(8), 1705- 1711. https://doi.org/10.1111/jgs.14856 Hudson, J. L., Iii, R. E. B., & Campbell, W. W. (2020). Protein distribution and muscle-related outcomes: Does the evidence support the concept? Nutrients, 12(5). https://doi.org/10.3390/nu12051441 Hughes, V. A., Frontera, W. R., Wood, M., Evans, W. J., Dallal, G. E., Roubenoff, R., & Fiatarone Singh, M. A. (2001). Longitudinal muscle strength changes in older adults: influence of muscle mass, physical activity, and health. Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 56(5), B209-217. https://doi.org/10.1093/gerona/56.5.b209 Isanejad, M., Mursu, J., Sirola, J., Kroger, H., Rikkonen, T., Tuppurainen, M., & Erkkila, A. T. (2015). Association of protein intake with the change of lean mass among elderly women: The Osteoporosis Risk Factor and Prevention - Fracture Prevention Study (OSTPRE-FPS). Journal of Nutritional Science, 4, e41. https://doi.org/10.1017/jns.2015.31 Isanejad, M., Mursu, J., Sirola, J., Kröger, H., Rikkonen, T., Tuppurainen, M., & Erkkilä, A. T. (2016). Dietary protein intake is associated with better physical function and muscle strength among elderly women. British Journal of Nutrition, 115(7), 1281-1291. https://doi.org/10.1017/s000711451600012x Kim, I. Y., Schutzler, S., Schrader, A. M., Spencer, H. J., Azhar, G., Wolfe, R. R., & Ferrando, A. A. (2018). Protein intake distribution pattern does not affect anabolic response, lean body 32 mass, muscle strength or function over 8 weeks in older adults: A randomized-controlled trial. Clinical Nutrition, 37(2), 488-493. https://doi.org/10.1016/j.clnu.2017.02.020 Loenneke, J. P., Loprinzi, P. D., Murphy, C. H., & Phillips, S. M. (2016). Per meal dose and frequency of protein consumption is associated with lean mass and muscle performance. Clinical Nutrition, 35(6), 1506-1511. https://doi.org/10.1016/j.clnu.2016.04.002 Mamerow, M. M., Mettler, J. A., English, K. L., Casperson, S. L., Arentson-Lantz, E., Sheffield-Moore, M., Layman, D. K., & Paddon-Jones, D. (2014). Dietary protein distribution positively influences 24-h muscle protein synthesis in healthy adults. Journal of Nutrition, 144(6), 876-880. https://doi.org/10.3945/jn.113.185280 McLean, R. R., Mangano, K. M., Hannan, M. T., Kiel, D. P., & Sahni, S. (2016). Dietary protein intake is protective against loss of grip strength among older adults in the Framingham Offspring Cohort. Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 71(3), 356-361. https://doi.org/10.1093/gerona/glv184 Mendonça, N., Granic, A., Mathers, J. C., Hill, T. R., Siervo, M., Adamson, A. J., & Jagger, C. (2018). Prevalence and determinants of low protein intake in very old adults: insights from the Newcastle 85+ Study. European Journal of Nutrition, 57(8), 2713-2722. https://doi.org/10.1007/s00394-017-1537-5 Mishra, S., Goldman, J. D., Sahyoun, N. R., & Moshfegh, A. J. (2018). Association between dietary protein intake and grip strength among adults aged 51 years and over: What We Eat in America, National Health and Nutrition Examination Survey 2011-2014. PLoS One, 13(1), e0191368. https://doi.org/10.1371/journal.pone.0191368 Moore, D. R. (2014). Keeping older muscle “young” through dietary protein and physical activity. Advances in Nutrition, 5(5), 599S-607S. https://doi.org/10.3945/an.113.005405 Moore, D. R., Churchward-Venne, T. A., Witard, O., Breen, L., Burd, N. A., Tipton, K. D., & Phillips, S. M. (2015). Protein ingestion to stimulate myofibrillar protein synthesis requires 33 greater relative protein intakes in healthy older versus younger men. Journals of Gerontology: Series A, 70(1), 57-62. https://doi.org/10.1093/gerona/glu103 Moreland, B., Kakara, R., & Henry, A. (2020). Trends in nonfatal falls and fall-related injuries among adults aged ≥65 years - United States, 2012-2018. Morbidity and Mortality Weekly Report, 69(27), 875-881. https://doi.org/10.15585/mmwr.mm6927a5 Murton, A. J., Marimuthu, K., Mallinson, J. E., Selby, A. L., Smith, K., Rennie, M. J., & Greenhaff, P. L. (2015). 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British Journal of Community Nursing, 21(6), 305-309. https://doi.org/10.12968/bjcn.2016.21.6.305 Statistics New Zealand. (2020). National population projections: 2020(base)–2073. Retrieved 27 July 2022 from https://www.stats.govt.nz/information-releases/national-population- projections-2020base2073 35 Takahashi, J., Nishiyama, T., & Matsushima, Y. (2017). Does grip strength on the unaffected side of patients with hemiparetic stroke reflect the strength of other ipsilateral muscles? Journal of Physical Therapy Science, 29(1), 64-66. https://doi.org/10.1589/jpts.29.64 Ten Haaf, D. S. M., van Dongen, E. J. I., Nuijten, M. A. H., Eijsvogels, T. M. H., de Groot, L., & Hopman, M. T. E. (2018). Protein intake and distribution in relation to physical functioning and quality of life in community-dwelling elderly people: Acknowledging the role of physical activity. Nutrients, 10(4). https://doi.org/10.3390/nu10040506 Tieland, M., Borgonjen-Van den Berg, K. J., Van Loon, L. J., & de Groot, L. C. (2015). Dietary protein intake in Dutch elderly people: a focus on protein sources. Nutrients, 7(12), 9697-9706. https://doi.org/10.3390/nu7125496 van Vliet, S., Burd, N. A., & van Loon, L. J. C. (2015). The skeletal muscle anabolic response to plant- versus animal-based protein consumption. Journal of Nutrition, 145(9), 1981-1991. https://doi.org/10.3945/jn.114.204305 Volpi, E., Sheffield-Moore, M., Rasmussen, B. B., & Wolfe, R. R. (2001). Basal muscle amino acid kinetics and protein synthesis in healthy young and older men. Journal of the American Medical Association, 286(10), 1206-1212. https://doi.org/10.1001/jama.286.10.1206 Wan He, Goodkind, D., & Kowal, P. (2016). An aging world: 2015. U.S. Government Publishing Office, P95/16-91. https://doi.org/http://www.census.gov/content/dam/Census/library/publications/2016/demo/p 95-16-1.pdf Yang, Y., Churchward-Venne, T. A., Burd, N. A., Breen, L., Tarnopolsky, M. A., & Phillips, S. M. (2012). Myofibrillar protein synthesis following ingestion of soy protein isolate at rest and after resistance exercise in elderly men. Nutrition and Metabolism, 9(1), 57. https://doi.org/10.1186/1743-7075-9-57 36 Chapter Two – Literature review This chapter begins with describing the aging global population and the incidence of falls, which is linked to the rationale for the research focus on muscle strength in older adults. Due to the contradictory evidence on the relationship between muscle mass and muscle strength and associations with obesity, studies that examine the potential interaction of obesity within that relationship will be discussed in depth. Proteins are the most abundant component of muscle mass, however the muscle's ability to stimulate protein synthesis following protein ingestion decreases as we age and with obesity. Therefore, current evidence on the role of protein intake, distribution, and sources in overcoming age-related muscle protein synthesis impairment will be reviewed, as well as any controversies in the literature discussed. Gaps in the literature that investigate protein intake, distribution, and sources in both the New Zealand and global contexts are identified. Finally, an overview of the literature on protein intake, distribution, and sources, and their association with muscle mass and muscle strength in older adults is provided. 2.1. Search strategies Studies were identified through the following databases: Science Direct, PubMed, Google Scholar, and Scopus. Key concepts from the research questions were identified (Table 2. 1). Then search terms for each concept which identify controlled vocabulary and free text terms were created (McGowan et al., 2016). All terms within each concept were joined with OR. Finally, each concept was joined with another using AND. Papers were limited to those in English and published in full. To increase the search breadth, no additional filters for publication year or age group were applied. 37 Table 2. 1. Literature review search strategies Concept 1 Falls AND Concept 2 Muscle strength AND Concept 3 Older adults AND Concept 4 Muscle mass AND Concept 5 Obesity AND Concept 6 Protein intake Controlled vocabulary terms/ Subject terms (MeSH terms) Falls, injury Muscle strength, muscle weakness Aged, elderly Skeletal muscle, intramuscular lipid Adiposity Protein intake, protein distribution, protein sources 38 OR OR OR OR OR Free text terms/natural language terms (Synonyms, UK/US terminology, medical/laymen’s terms, acronyms/abbreviati on, more narrow search terms) Falls, injury, injuries, accident Muscle strength, muscle weakness, handgrip strength, knee extensor strength, quadriceps muscle, arm strength, leg strength, upper strength, lower strength, leg muscle power Aged, elderly, older, young-old, old-old, adults, senior, aging, ageing Muscle mass, lean mass (LM), lean body mass (LBM), fat-free mass (FFM), appendicular lean mass (ALM), appendicular skeletal muscle (ASM), skeletal muscle mass (SMM), appendicular skeletal muscle index (ASMI), muscle cross-sectional area (CSA) BMI, body fat percentage, fat mass, fat Protein intake, protein distribution, protein sources, protein recommendation, protein need, protein timing, protein quality, food sources of protein, animal protein, animal-based protein, plant protein, plant-based protein, vegetable protein, dairy-eggs protein Abbreviations: MeSH = Medical Subject Headings, BMI = Body Mass Index, UK = United Kingdom, US = United States. 39 2.2. Ageing and falls Population ageing is occurring worldwide, leading to a growing proportion of older adults (United Nations, 2019; Wan He et al., 2016). Previously, in 2015, the world population percentage for adults aged 65 and over was 8.5% (n = 617 million) (Wan He et al., 2016). According to the most recent United Nations World Population Prospects estimations, 9% (n = 703 million) of the world’s population consisted of people aged 65 years and older in 2019, and this proportion is expected to increase to 16% by 2050 (United Nations et al., 2019). The same trend is expected in New Zealand (NZ), a country of 4.9 million people. Currently, in 2020, 16% of New Zealand’s population is aged 65 or older, with women accounting for more than half (53.4%) (Statistics New Zealand, 2020). This percentage is expected to increase to more than 21% by the year 2048, and to more than 24% by 2073 (Crothers, 2021). One of the primary concerns with an ageing population is the incidence of falls and fall-related injuries (Health Quality & Safety Commission, 2016; Peel, 2011; Rubenstein & Josephson, 2002). An epidemiological review across different countries revealed that 20 to 33% of older adults (aged 65 years and over) in community settings experienced a fall once a year, and in the oldest group (85 years and older), up to 60% experienced a fall within a 12-month period (Peel, 2011). Recently, Moreland et al. (2020) examined trends in falls and fall-related injuries among older adults aged ≥ 65 years in the United States. They found that in 2018, 27.5% of older adults reported at least one fall in the past year, and 10.2% reported a fall-related injury. In NZ, there is a lack of studies reporting the prevalence of falls for older adults. However, it is clear that fall-related injuries are a public health concern for older adults. For example, data indicated that in New Zealand in 2016, the rate of one or more Accident Compensation Corporation (ACC) claims was for a fall-related injury. More specifically, the Health Quality and Safety Commission New Zealand reported “In 2016, 216,000 people aged 50 years and over had one or more ACC claims for a fall-related injury accepted” (Health Quality & Safety Commission, 2016). It was not stated how many claims were rejected. 40 Falls cause physical injuries as well as serious social and psychological consequences such as fear of recurring falls, social isolation, and depression, the cost of which are difficult to estimate (Hadjistavropoulos et al., 2011; Zijlstra et al., 2007). Healthcare costs for physical fall-related injuries such as contusions, lacerations, dislocations, hip fractures, and traumatic brain injuries, on the other hand can be estimated (Garrett, 2008; Stevens & Sogolow, 2005; Thompson et al., 2006). A study that estimated the community-based costs associated with minor falls in older adults in New Zealand found that the mean cost per fall was NZD$422 (Garrett, 2008). A higher cost of $600 per fall in New Zealand has been estimated in 2011 (de Raad, 2012). Of all the physical injuries, hip fractures are the most common injury resulting from falls, and also represent the costliest injury for New Zealand’s ageing population (Robertson & Campbell, 2012). In New Zealand, a hip fracture with three weeks in hospital costs $47,000, and a hip fracture with complications and discharge to an aged residential care facility costs $135,000 (de Raad, 2012). Because all these estimations are over 10 years old, costs will have certainly risen since they were calculated. There is a wealth of evidence on risk factors for falls (Barker et al., 2009; Hendriks et al., 2008; Rubenstein, 2006). A review of 16 studies indicated that the most common locomotor system and physiological (intrinsic) risk factors that contribute to falls were related to muscle weakness (Rubenstein, 2006). In addition, sarcopenia which is a consequence of ageing and is associated with insulin resistance, type 2 diabetes, and metabolic syndrome further increases the risk of cardiovascular disease and stroke in older adults (Chung et al., 2013). These conditions limit older adult’s capacity to engage in physical activity, leading to further declines in muscle strength and an increase in the rate of falls in older adults. The predicted number of New Zealanders who are likely to live to older age will place a significant burden on future fall-related injuries and healthcare costs. Hence, this emphasises the need to prioritise further research that addresses muscle weakness in older adults. 41 2.3. Muscle strength in older adults Muscle weakness, also known as dynapenia, is a loss of muscle strength that occurs with age and is not caused by a neurological or muscular disease (Clark & Manini, 2012). Strength can be defined as the maximum force exerted by a muscle (Buchner et al., 1992). Muscle strength tends to peak between the second and third decades of life and then significantly decline (Figure 2. 1). The rate of decline is higher with advanced age, menopause, decreased intensity and duration of physical activity, the presence of chronic diseases, and certain lifestyle factors such as smoking (Kalyani et al., 2014; Kehayias et al., 1997; Marcell, 2003; Shah et al., 2022). Additionally, the timing of muscle strength loss varies by anatomical location, with lower extremity muscle loss occurring later than upper extremity muscle loss (Buckley et al., 2018; Burr, 1997). Figure 2. 1. Declining quadriceps muscle strength in adults. Data from Al-Abdulwahab (1999). 0 50 100 150 200 250 300 350 400 20-29 30-39 40-49 50-59 60-69 70-79 80-89 Q ua dr ic ep s m us cl e st re ng th (N ew to n) Age (years) Left Right 42 2.3.1 Assessment of muscle strength There are a few methods to assess muscle strength. These include handgrip (isometric strength), knee flexion/extension (isotonic strength), and peak torque (isokinetic strength) (Roberts et al., 2011). Handgrip strength is a simple measurement of muscle strength that is commonly used to predict overall muscle strength (Ekstrand et al., 2015; Takahashi et al., 2017) and will be focussed on within this literature review. It is used for screening older adults with low muscle strength in the diagnosis of frailty (Dudzińska-Griszek et al., 2017), sarcopenia (Cruz-Jentoft et al., 2010) and malnutrition (Zhang et al., 2017). Low handgrip strength has also been associated with higher hospital readmission, increased risk of fractures, reduced physical functioning, and increased risk of falls (Bohannon, 2008; Ibrahim et al., 2018). There are several protocols for measuring handgrip strength (Balogun et al., 1991; Firrell & Crain, 1996; Incel et al., 2002; O'Driscoll et al., 1992; Roberts et al., 2011), but the protocol by Roberts et al. (2011) is the most comprehensive and evidence-based. They recommend using a calibrated Jamar dynamometer with the handle in the second position. The individual being tested sits with his or her forearm and wrist in a neutral position supported by an armrest, his or her elbow flexed 90 degrees, and his or her shoulder at 0 degrees abduction / flexion. Three measurements must be taken for each hand, beginning with the right and alternating right/left. The Foundation for the National Institutes of Health Sarcopenia Project (FNIH), Asian Working Group for Sarcopenia (AWGS), European Working Group on Sarcopenia in Older People (EWGSOP) and Sarcopenia Definition and Outcomes Consortium (SDOC) have produced consensus statements on cut-off values for low muscle strength using handgrip strength measurements (Table 2. 2). Because muscle strength adjusted BMI has been proposed as the ideal marker for muscle strength (Keevil et al., 2015; Kim et al., 2019; Kim et al., 2017; Tang et al., 2018; Villareal et al., 2004), the FNIH also propose using BMI-handgrip strength cut-off values of < 1.001 in men and < 0.56 in women (Cawthon et al., 2014). 43 Based on the consensus statement of the Australian and New Zealand Society for Sarcopenia and Frailty Research (ANZSSFR), clinicians and researchers in Australia and New Zealand are recommended to use the cut-off values for low handgrip strength proposed by the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), with the cut-off now at < 16 kg for women and < 27 kg for men (Cruz-Jentoft et al., 2019; Daly et al., 2022). However, EWGSOP2 has not provided threshold values for BMI-handgrip strength. Table 2. 2. Consensus statements on cut-off values for determining low muscle strength in older adults. Working group Cut-off points by sex Females Males European Working Group on Sarcopenia in Older People (EWSSOP) (Cruz-Jentoft et al., 2010) < 20 kg < 30 kg Foundation for the National Institutes of Health Sarcopenia Project (FNIH) (Studenski et al., 2014) < 16 kg < 26 kg Asian Working Group for Sarcopenia (AWGS) (Chen et al., 2014) < 18 kg < 26 kg European Working Group on Sarcopenia in Older People (EWSSOP2) (Cruz-Jentoft et al., 2019) < 16 kg < 27 kg Sarcopenia Definition and Outcomes Consortium (SDOC) (Bhasin et al., 2020) < 20 kg < 35.5 kg 44 2.3.2. Prevalence of low muscle strength Using the EWGSOP2 cut-off values (< 16 kg for women and < 27 kg for men), a nationally representative sample of Brazilians aged 65 years and older revealed a 28.2% prevalence of low muscle strength (Borges et al., 2020). Other studies, which used the older cut-off values defined by the EWGSOP (< 20 kg for women and < 30 kg for men), found the prevalence of low muscle strength to be 33.9% among Mexicans aged 50 years and older (Rodríguez-García et al., 2018), 22.5% among Europeans aged 70 years and older (Bertoni et al., 2018), 44% in Americans aged 65 years and older (Duchowny et al., 2018), and 71% in community-dwelling New Zealanders aged 75 years and older (Chatindiara et al., 2019). Different cut-off values used in the literature make it difficult to compare studies. However, low muscle strength in older adults appears to be a global issue. 2.4. Muscle strength and muscle mass in older adults 2.4.1. Muscle mass, protein, and ageing Muscle is the most abundant tissue in the human body (40 to 50% of total body weight) (Karagounis & Hawley, 2010) and includes skeletal, smooth, and cardiac muscle. Muscle mass is the limb lean mass that covers the limb bones and is surrounded by limb fat. In this review, the terms skeletal muscle mass (SMM), appendicular skeletal mass (ASM), appendicular lean mass (ALM), fat-free mass (FFM), lean mass (LM) and muscle area, all refer to muscle mass. Lean mass is increased, decreased, and maintained through the regulation of the net protein balance between muscle protein synthesis (anabolic) (MPS) and muscle protein breakdown (catabolic) (MPB) (Bennet et al., 1979; Bohé et al., 2003; Bohé et al., 2001; Fujita, 2007). A significant increase in MPS and/or a decrease in MPB, such that the net protein balance remains positive, results in lean mass accretion (Bennet et al., 1979; Bohé et al., 2003; Bohé et al., 2001; Burd et al., 2011; Fujita et al., 2007). 45 Protein ingestion stimulates the process of MPS. Protein is a macronutrient composed of various amino acids, that can be found in both plant (e.g., soy, rice, peas, oats, wheat, legumes, beans and nuts) and animal-based foods (i.e., meat, dairy and eggs). Protease enzymes break down foods into short strings of amino acids (peptides) and single amino acids. This process starts in the stomach and progresses to the small intestine, where amino acids are absorbed into the bloodstream and used for protein synthesis (Cuthbertson et al., 2005; Fry et al., 2011; Groen et al., 2015; Pennings et al., 2011; Volpi et al., 2003). With ageing, MPS stimulation after protein ingestion decreases (Colley et al., 2011; Cuthbertson et al., 2005; Katsanos et al., 2005, 2006; Paddon-Jones et al., 2004; Volpi et al., 2001). Cuthbertson et al. (2005) was the first to demonstrate that basal MPB rates were similar between younger and older people, but MPS in older adults was less responsive to the ingestion of protein (anabolic resistance). This anabolic resistance to protein was subsequently confirmed by others (Katsanos et al., 2005, 2006; Paddon-Jones et al., 2004). The aetiology of anabolic resistance with ageing is not entirely understood but is proposed to be mediated by impairments in several physiological processes (Boirie et al., 1997; Burd et al., 2013; Dickinson et al., 2013; Rasmussen et al., 2006; Timmerman et al., 2010; Volpi et al., 1999). A reduced rate of amino acid absorption into the bloodstream and/or a greater retention of amino acids in the stomach and the small intestine may limit the availability of amino acids for MPS (Boirie et al., 1997; Volpi et al., 1999). In addition, a decline in amino acid transporters, that mediate transfer of amino acids into and out of cells, may limit the delivery of amino acids to the muscle and the uptake of amino acids by the muscle (Dickinson et al., 2013; Rasmussen et al., 2006; Timmerman et al., 2010). The aged-anabolic impairment to protein results in muscle mass decline in older adults. A decrease in skeletal muscle mass of one to two percent per year has been observed in men and women (Kehayias et al., 1997; Marcell, 2003). In older adults aged 70 to 79 years, Goodpaster et al. (2006) observed that the loss of leg lean mass was about 1% per year, regardless of sex or ethnicity. 46 Similarly, Frontera et al. (2000) reported a reduction in muscle cross-sectional area of 1.4% per year in older adults after 50 years. This was also confirmed by von Haehling et al. (2010), who identified a loss of muscle mass of 1 to 2% per year after the age of 50. 2.4.2. Assessment and prevalence of low muscle mass Body composition assessment is an important tool for the identification of common nutrition- related conditions and provides valuable information about responses to intervention. However, quantifiable and clinically meaningful changes in body composition take time to occur; therefore, there is a need for multiple assessments over time and this is determined based on the individual, the intervention, and the goals to be achieved. There are a wide range of methods to quantify muscle mass, which require assumptions with variable degrees of accuracy. Total body counting (using radioactive potassium), and neutron activation are two direct measurements of muscle mass available to the researcher/clinician. Fat-free mass can be estimated using the amount of naturally radioactive potassium 40 (40K) in the body, assuming a constant concentration of potassium in FFM (Ellis, 2000). Currently, the only available detectors which can measure radioactive potassium are in the United States, which precludes its use in research outside of US. Neutron activation quantifies the body nitrogen to predict the amount of protein in the body to further analyse components of FFM. This method has been reported to be highly accurate, however it involves high levels of neutron radiation exposure and therefore has not been used in large-scale population research (Haas et al., 2007). Indirect measures include anthropometric (limb circumference measurement), dual-energy X- ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound are used to measure muscle mass (Cohn et al., 1983; Heymsfield et al., 1982; Heymsfield et al., 1990; Reeves et al., 2004). Anthropometric measures are vulnerable to error and therefore are not recommended for routine use in muscle mass assessment (Cruz-Jentoft et al., 2010). 47 Computed tomography and MRI are considered gold standard for skeletal muscle mass estimation in research, mainly because of their precision in separating fat from other soft tissues (Cruz-Jentoft et al., 2010). However, CT scans utilise radiation and the high cost of both CT and MRI scans limits their use (Chien et al., 2008). Ultrasound has been proposed as a simple alternative for measuring skeletal muscle mass in clinical practice, but it is not standardised and does not yet have validated cut-off values for determining low muscle mass (Perkisas et al., 2021; Stringer & Wilson, 2018). Bioelectrical impedance analysis is portable, inexpensive, easy to use, and can be used for both bedridden and ambulatory patients (Jung et al., 2020). However, the appendicular lean mass equations are both population and device-specific, which limits its accuracy (Gonzalez et al., 2018). The most common method of estimating skeletal muscle mass used in both clinical and research settings is DXA. It has the advantages of being able to distinguish fat, bone mineral, and lean tissues with good precision, and minimal radiation exposure (Cruz-Jentoft et al., 2010). However, DXA instruments are relatively expensive and are not portable, which may limit their use in large epidemiological studies (Cruz-Jentoft et al., 2010). Heymsfield et al. (1990) first demonstrated that using DXA, the calculation of skeletal muscle mass (SMM), appendicular skeletal mass (ASM), or appendicular lean mass (ALM) as the sum of limb lean mass (LM) minus the sum of limb fat and bone mass was a highly accurate method of quantifying human skeletal muscle mass, while being safe and accessible. To determine the cut-off value for low muscle mass, Baumgartner et al. (1998) proposed controlling SMM, ASM, or ALM for height squared to calculate an index of relative skeletal muscle mass, because of the strong relationship between muscle mass and height. They determined that cut- off values for low muscle mass (ASM/height2) were < 7.26 kg/m2 for men and < 5.45 kg/m2 for women. Different definitions and cut-off values for low muscle mass have been developed for DXA and BIA measurements, making it difficult to compare studies. However, the ANZSSFR, recommend clinicians and researchers in Australia and New Zealand use the cut-off values for low muscle mass revised by the EWGSOP2 to be ASM/height2 < 7 kg/m2 for men and < 5.5 kg/m2 for women (Cruz-Jentoft et al., 2019; Daly et al., 2022). 48 Table 2. 3 compares studies investigating the prevalence of low muscle mass in adults and older adults living in developed countries. A common finding is that low muscle mass is highly prevalent in older people and that it worsens with age. Table 2. 3. Prevalence of low muscle mass in older adults: a comparison of different definitions and cut-off values. Author et al. (years) Country Muscle mass assessment method Muscle mass calculation and cut-off values Sex N Age (years) Prevalence Baumgartner et al. (1998) Mexico DXA ALM/ht2 male ≤ 7.26 kg/m2 female ≤ 5.45 k/m2 Male and female 883 61 to 70 71 to 80 ≥ 80 13% 24% 50% Morley et al. (2001) US DXA ALM /ht2 male ≤ 7.26 kg/m2 female ≤ 5.45 k/m2 Male and female 199 < 70 ≥ 80 12% 30% Janssen et al. (2002) Canada BIA Ratio of muscle mass/total body mass male ≤ 31.5% female ≤ 22.1% Male Female 2224 2278 ≥ 60 ≥ 60 7% 10% Newman (2003) US DXA ALM /ht2 male ≤ 7.23 kg/m2 female ≤ 5.67 kg/m2 Male Female 1435 1549 70 to 79 20% 20% Waters et al. (2010) New Zealand DXA ASM index male < 7.2 kg/m2 female < 5.4 kg/m2 Male Female 183 56 to 93 4% 12% Kim et al. (2012) Korea DXA ASM/weight Class I Class II Male Female 4486 5999 ≥ 20 9.7% 11.8% Abbreviations: ALM = appendicular lean mass; ASM = appendicular skeletal mass; ht = height; DXA = dual-energy X-ray absorptiometry; BIA = bioelectrical impedance analysis; Class I was from 1 to 2 SD below the mean for young adults and Class II was below 2 SD. 49 2.4.3. Relationship between muscle mass and muscle strength Cross-sectional studies have shown that muscle mass and muscle strength are positively correlated (Barbat-Artigas, Plouffe, et al., 2013; Beliaeff et al., 2008; Chen et al., 2013; Hayashida et al., 2014; Reed et al., 1991). Age and sex seem to interact with the relationship between muscle mass and muscle strength, leading to a weaker degree of association when classified by sex and age groups (Table 2. 4). Due to the limitations of these cross-sectional studies in detecting causality, only associations can be described. In the Health, Aging and Body Composition study, Newman et al. (2003) reported that lower muscle strength in older men and women aged 70 to 79 years was predominantly due to lower muscle mass. Similarly, Frontera et al. (2000) found that quantitative loss of muscle mass was a major contributor to the decline in muscle strength seen in men of advanced age (initial mean age 65 years). These studies suggest that efforts to maintain muscle mass may have a significant impact on maintaining strength in older adults. However, several studies have shown that changes in muscle mass explain only a small portion (~5%) of the changes in strength in older adults (Goodpaster et al., 2006; Hughes et al., 2001). Also, there is evidence that older adults may have low muscle strength despite maintaining or increasing muscle mass and the reverse is also true (Alemán-Mateo et al., 2014; Park et al., 2006; Raue et al., 2009). As previously stated, the aged-anabolic impairment to ingested protein is the most important factor influencing muscle loss in older adults (Colley et al., 2011; Fujita, 2007; Volpi et al., 2001). Obesity in older adults is also known to impair the responsiveness of MPS to protein ingestion (Beals et al., 2018; Guillet et al., 2009; Murton et al., 2015). This weakened MPS is likely to increase intramuscular lipid content (or poor muscle quality), body fat percentage (%BF) and decline in muscle oxidative capacity (Gallagher et al., 2000; Goodpaster et al., 2006; Hughes et al., 2002; Jacobs et al., 2014). Lipids which accumulate within the muscle cell potentially playing a role in the development of insulin resistance, which is associated accelerated peripheral inflammation and functional deficits in skeletal muscle (Consitt et al., 2009). These conditions are associated with both lower muscle strength and muscle mass in older adults (Goodpaster et al., 2001; Visser et al., 2005). 50 Also, obesity classified using BMI limits the degree of association to which higher muscle mass translates into greater muscle strength. Chen et al. (2013) found that obese older adults (BMI ≥ 30 kg/m2) had lower strength than non-obese older adults with the same muscle mass. Thus, obesity may interact with the relationship between muscle mass and muscle strength, leading to different degrees of association. Table 2. 4. Cross-sectional studies investigating the relationship between muscle mass and muscle strength in older adults. Author et al. (years) Country Sex N Age (years) Key findings Reed et al. (1991) US Male and female 218 65+ Midarm muscle area (MAMA) was correlated with upper arm strength (r = 0.68). By sex, correlation between MAMA and arm muscle strength was lower in both groups (r = 0.36 for males; r = 0.23 for females). Midthigh muscle area was correlated with thigh muscle strength (r = 0.37 for males; r = 0.19 for females) Beliaeff et al. (2008) Canada Male and female 904 65 to 84 In both legs and arms, muscle mass was correlated with muscle strength (r = 0.21 for legs; r = 0.49 for arms) Chen et al. (2013) US Male and female 2647 50+ Correlation between muscle mass and isokinetic quadriceps strength after adjusting for age and sex was 0.365 Barbat-Artigas, Plouffe, et al. (2013) Canada Female 1219 75+ Muscle mass was positively, but weakly associated with muscle strength (r values ranged from 0.16 to 0.22) Hayashida et al. (2014) Japan Male and female 318 65+ Leg muscle mass was correlated with knee extension strength (r = 0.33 in males; r = 0.22 in females). Appendicular muscle mass was correlated with knee extension strength (r = 0.34 in males; r = 0.23 in females) 51 2.5. Protein intake, distribution, sources, and muscle protein synthesis 2.5.1. Protein intake, recommendations, and muscle protein synthesis in older adults Protein recommendations for older adults refer to the amount of protein that is necessary to maintain the balance between MPS and MPB (Joint FAO/WHO/UNU Expert Consultation, 2007; National Health and Medical Research Council Australian Government Department of Health and Ageing, 2006). Recommendations of protein are given as either the Estimated Average Requirement (EAR) or the Recommended Dietary Intake (RDI) (note that the US/Canadian term is Recommended Dietary Allowance (RDA), and in the UK is Recommended Nutrient Intake (RNI)) (Department of Health Panel on Dietary Reference Values, 1991; National Academy of Sciences, 2005). The EAR is the average daily nutrient intake level estimated to meet the needs of half of the healthy individuals in a given life stage and gender group. The RDI is an estimate of the minimum daily average dietary intake level that meets the nutrient requirements of 97 or 98% of healthy individuals in a given life stage and gender group (Joint FAO/WHO/UNU Expert Consultation, 2007). The RDA for protein has been established by many health agencies, including the World Health Organisation (WHO) and the European Food Safety Authority (EFSA) as 0.8 grams per kilogram of body weight (g/kg) of good quality protein for healthy adult men and for healthy non-pregnant women of all ages (EFSA Panel on Dietetic Products Nutrition, 2012; Joint FAO/WHO/UNU Expert Consultation, 2007). However, a meta-analysis demonstrated that the median daily protein requirement for older adults was higher than for younger adults (0.9 g/kg BW for females and 1.1 g/kg BW for males) (Rand et al., 2003). Also, Campbell et al. (2001) reported that an intake of 0.8 g/kg BW in men and women aged 55 to 77 years over 14 weeks resulted in metabolic and physiological adaptation to the dietary intake, suggesting that 0.8 g/kg BW was insufficient to meet their protein requirements. Based on these findings, in 2006, the Australia and New Zealand Nutrient Reference Values (NRVs) provided a RDI for protein for older adults (aged 70+ years) that was higher than for younger adults (aged between 19 and 70 years) (Table 2. 5). In 2015, Japan established a recommendation of 0.9 g/kg BW, which is higher than 0.8 g/kg BW/day (Tsuboyama-Kasaoka et al., 2013). 52 Table 2. 5. Nutrient Reference Values for protein for adults and older adults in Australia and New Zealand (National Health and Medical Research Council Australian Government Department of Health and Ageing, 2006). Age EAR (g/kg BW) RDI (g/kg BW) RDI (g/day) Men 19 to 70 years 0.68 0.84 64 More than 70 years 0.86 1.07 81 Women 19 to 70 years 0.60 0.75 46 More than 70 years 0.75 0.94 57 Abbreviations: EAR = Estimated Average Requirement, RDI = Recommended Dietary Intake, BW = body weight. All the above protein recommendations are based on a short-term net protein balance protocol (EFSA Panel on Dietetic Products Nutrition, 2012; Joint FAO/WHO/UNU Expert Consultation, 2007; National Health and Medical Research Council Australian Government Department of Health and Ageing, 2006). The net protein balance measurement is based on the concept that protein is the most nitrogen-containing substance in the body. As a result, nitrogen gain or loss from the body corresponds to nitrogen gain or loss from protein. This method has several limitations, including the difficulty of quantifying all routes of nitrogen intake and loss and standardising research methods for addressing nitrogen balance studies. Because of these constraints, protein requirements are likely to be underestimated (Bauer et al., 2013; Gaffney- Stomberg et al., 2009). In addition, Morse et al. (2001) demonstrated that shorter-term nitrogen balance protocols are insufficient to establish the RDA for protein of older women aged 70 years and older. The indicator amino acid oxidation (IAAO) method has emerged as a new method of investigating protein requirements (Elango et al., 2008, 2012). This method assumes that when the amount of one essential or indispensable dietary amino acid (IDAA) is insufficient for protein synthesis, all other excess IDAAs, including the indicator amino acid, will be used as an energy substrate, and thereby oxidised. 53 A study using this method to estimate protein requirements in older adults, suggests that the RDA for protein in men and women over 65 years of age should be increased to 1.2 g/kg BW/day (Rafii et al., 2015). More specifically, Courtney-Martin et al. (2016) estimated an RDA of 1.2 g/kg BW/day for men aged 66 to 79 years, 1.2 g/kg BW/day for women aged 80 to 87 years, and 1.3 g/kg BW/day for women aged 65 to 85 years. In recent years, several research experts have recommended that older adults should consume protein at a rate of 1.0 to 1.2 g/kg BW/day. At a Workshop on Protein Requirements in the Elderly, members of the European Society for Clinical Nutrition and Metabolism presented and debated the latest research studies on preserving muscle performance in the older adults. They recommend adults over the age of 65 years consume at least 1.0 to 1.2 g protein per kg per day (Deutz et al., 2014). Similarly, the PROT-AGE study group (representing the European Union Geriatric Medicine Society, the International Association of Gerontology and Geriatrics, the International Academy on Nutrition and Aging, and the Australian and New Zealand Society for Geriatric Medicine) recommended an average daily intake of 1.0 to 1.2 g/kg BW/day in healthy older adults (Bauer et al., 2013). Furthermore, Moore and Soeters (2015) observed that 0.4 g/kg BW/meal over three meals, equating to 1.2 g/kg/day, resulted in a maximal simulation of MPS in older adults. 2.5.2. Protein distribution and muscle protein synthesis in older adults The maximum stimulation rate for MPS in older adults has been observed at a protein intake of 30 g per meal or 0.4 g/kg BW per meal (Moore & Soeters, 2015; Paddon-Jones & Rasmussen, 2009). Paddon-Jones and Rasmussen (2009) observed that 30 g of protein per meal was sufficient to maximally stimulate muscle protein synthesis and giving a dose higher than this did not further increase MPS simulation. Similarly, Moore and Soeters (2015) found that maximal MPS was achieved at 0.4 g/kg BW per meal in older adults. Therefore, it was hypothesised that three meals per day, with a regular protein intake o