Latent profiles of physical behaviour and their impact on physical fitness and function of Portuguese older adults

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Magalhães, Fátima Baptista, Eduardo B. Cruz, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4485059/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Exploring individuals’ patterns of physical activity and sedentary behaviour can reveal profiles that could differently impact health outcomes and benefit targeted interventions. This study aimed to identify latent profiles of physical behaviour in older adults and examine their association with physical fitness and function outcomes. The sample included 1095 participants (765 females) from the Portuguese physical activity and sports monitoring system. Latent profiles of physical behaviour were identified based on the percentage of waking time spent in sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity (MVPA) assessed by accelerometery. Physical fitness was assessed by Senior Fitness Test Battery, and physical function was evaluated through the 12-item Composite Physical Function questionnaire. Associations between the profiles of physical behaviour and physical fitness and function outcomes were examined using generalized linear models adjusted for age. Three profiles of physical behaviour were identified: "active", "intermediate", and "sedentary" for both sexes. Participants with “active" or "intermediate" profiles exhibited the most favourable physical fitness and functional outcomes, while those with a "sedentary" profile showed the poorest results. Our findings suggest that a more balanced behaviour between physical activity and sedentary behaviour throughout the waking day appears to provide physical fitness and functional benefits, even if MVPA are not fully met. This is important for older adults who may struggle to comply fully with MVPA guidelines but could maintain or improve their physical fitness and function with a more active behaviour through the reduction of sedentary behaviour and inclusion of light physical activity. physical activity sedentary behaviour ageing mobility health Figures Figure 1 Introduction Maintaining physical fitness and function is a crucial objective for older adults as it contributes to the preservation of physical independence(Billot et al. 2020 ). However, as individuals age, they commonly experience a gradual decline in physical fitness components, such as cardiorespiratory and muscular endurance, muscular strength and power, flexibility, agility, and overall physical function, which encompasses the ability to perform activities of daily living (ADLs)(Payette et al. 2011 ). Nonetheless, the rates of decline in physical fitness and function can vary among individuals of the same age due to a range of factors, including lifestyles such as the time spent in physical activity and sedentary pursuits(Harridge and Lazarus 2017 ; Pettee Gabriel et al. 2017 ; Cunningham et al. 2020 ; Moreno-Agostino et al. 2020 ). Several observational(Syue et al. 2022 ) and experimental(Liu and Latham 2009 ; Zhang et al. 2020 ) investigations have reported that older adults who engage in higher levels of physical activity exhibit better physical fitness and function when compared to those who are less active. Despite the well-documented benefits of physical activity, a large number of older adults are physically inactive, meaning they do not meet the recommended levels of physical activity guidelines(Magalhães et al. 2023 ). Actually, with ageing, both women and men tend to become less active and increase their time spent in sedentary behaviour(Magalhães et al. 2023 ) which has detrimental effects on physical fitness and function(Gilchrist et al. 2022 ). The evidence regarding the detrimental effects of sedentary behaviour has led to an update in the World Health Organization (WHO) physical activity recommendations. Currently, the guidelines emphasize the importance of older adults not only engaging in moderate-to-vigorous physical activity (MVPA) but also reducing sedentary time and replacing it with physical activity of any intensity, including light intensity(Bull et al. 2020 ), which also seems to provide important health benefits(Chastin et al. 2019 ; Bull et al. 2020 ). This update on WHO, as well as in other national guidelines(Ross et al. 2020 ) has expanded the perspective on physical behaviour for a more holistic view. Recognizing the intricate interplay between sedentary behaviour and physical activity across all spectrums of intensity becomes crucial, as all these variables contribute to energy expenditure throughout the waking day. Also, this is particularly important given the growing body of evidence suggesting that combinations of these behaviours can have varying effects on a range of health outcomes (McGregor et al. 2018 ; Mcgregor et al. 2021 ). However, to date, most studies analysing associations of physical activity of different intensities and or sedentary behaviour with health outcomes, including physical fitness and function, have used variable-centred approaches as the main form of analysis (Migueles et al. 2022 ). Although this type of approach is suitable for describing associations between variables, it falls in capturing individuals’ patterns and the complex combined effects that may exist among these variables. Moreover, a recent consensus statement on analytical approaches to assess associations with accelerometer-determined physical behaviours has emphasised the need for studies consider the interplay among these physical behaviours, moving away from focusing solely on sedentary behaviour or physical activity intensities as individual variables(Migueles et al. 2022 ). In this context, a person-oriented approach, such as latent profile analysis offers a promising alternative methodology focusing on identifying subgroups of individuals characterized by similar patterns across a set of variables(Bauer 2022 ). By identifying subgroups with specific behaviour patterns, we can explore how these behaviours contribute to health outcomes. This approach allows for a more nuanced understanding of the complexity of human physical behaviour and can inform more targeted and personalized interventions or policies. Therefore, this study aims to (1) identify profiles of physical activity and sedentary behaviour in older adults and (2) explore the association of those profiles with markers of physical fitness and function. Methods Participants Cross-sectional data from the Portuguese physical activity and sports monitoring system collected between 2017 and 2018 was used. A detailed description of the data collection process can be found in a previous publication(Magalhães et al. 2023 ). In brief, participants were recruited from community senior (social) centers, public and private institutions, sports clubs, and social/sports events. In this report, we included only older adults ( > = 65 years) with complete and valid accelerometry data, (n = 1095, 765 females). Written informed consent was obtained from participants. The study was approved by the Ethics Committee of the Faculty of Human Kinetics, University of Lisbon (number: 25/2020). Physical fitness and function Physical fitness was assessed through the Senior Fitness Test Battery(Rikli and Jones 1999 ) which consists of a set of six functional fitness tests validated to determine physiological parameters that support physical mobility and independence in older adults. The 30-s chair-stand, arm-curl, chair sit-and-reach, back-scratch, 8-ft up-and-go, and 6-min walk tests were used to measure lower and upper body strength, lower and upper body flexibility, agility, and functional endurance, respectively. A detailed description of each of the tests can be found elsewhere(Rikli and Jones 1999 ). Furthermore, we evaluated muscle strength through handgrip, which has been indicated as a diagnostic tool for sarcopenia, the age-related decline in skeletal muscle mass and function (Cruz-Jentoft et al. 2019 ). Physical function, instead, was assessed subjectively by the 12-item Composite Physical Function (CPF) scale (Rikli and Jones 1998 , 2013 ). This self-report questionnaire was designed to assess an individual's physical function across a range of abilities, including basic ADLs (e.g., dressing oneself), instrumental ADLs (e.g., housework), and advanced activities (e.g. more vigorous exercise activities). The questionnaire consists of 12 items, each answered on a 3-category scale (0 = cannot do, 1 = can do with help, 2 = can do independently). The total score across all items provides an overall measure of the individual's physical function level. Physical Activity and Sedentary Behaviour Time spent in sedentary behaviour, light physical activity (light PA) and MVPA were evaluated by accelerometry (min day − 1 ). Participants were asked to wear an accelerometer (either the Actigraph, model GT3X or the GT1M (Pensacola, Florida) on the right hip, near the iliac crest for 7 consecutive days, including at least 2 weekdays and 1 weekend days. The devices were taken off only when the participants were sleeping or engaging in water-based activities. Accelerometry movement counts were collected in raw mode with a 100 Hz frequency and posteriorly downloaded into 15-s epochs (Actilife v.6.9.1). Physical activity intensities and sedentary behaviour cut points, wear time, and non-wear time validation criteria were defined according to Troiano et al.(Troiano et al. 2008 ). For latent profile analysis and to adjust for inter-participant variability in accelerometer wear time, physical activity and sedentary behaviour were expressed as a percentage of wear time (calculated as minutes spent in each intensity (min/day) / average wear-times (min/day) x 100). Statistical Analysis Latent profile analysis was employed to identify subgroups of participants who shared similar profiles of physical behaviour. The analysis was conducted using the snowRMM module, version 5.5.7 (Seol 2023 ), of Jamovi software (version 2.3.28). Separate models were fitted for males and females, with the average percentage of time spent on sedentary behaviour, light PA, and MVPA per day serving as the variables. We initially fitted latent profile models for 2–6 profiles, with varying variances and covariances fixed to 0. To determine the optimal number of profiles, we considered a combination of model fit indices (i.e., a collection of statistics that quantify the degree of data-model fit), interpretability, and theoretical relevance. Since the fit indices may continue to improve as more profiles are extracted, especially in larger samples, we created elbow plots that represented the gains associated with additional profiles and identified the point at which the improvement in model fit plateaued. We then examined the interpretability and theoretical relevance of the resulting profiles. To assess whether the resulting physical behaviour profiles were significant predictors of each measure of physical fitness and function, generalized linear models (GzLM) were used. For continuous dependent variables, linear models with an identity link function or linear inverse models with a log link function were used, while Poisson models with a log link function were used for dependent count variables. These models were chosen based on the nature and distribution of the dependent variables and the model’s fit indices (i.e. AIC and BIC) as well as on the model’s residual distribution. Age was included as a covariate. Marginal means were estimated to examine the expected values of the dependent variables for each profile of physical behaviour adjusted for age. The significance level was set at p < 0.05. Results Physical Behaviour Profiles The elbow plots, representing the fit indices of the model solutions, indicated that the improvement in fit reaches a plateau at three profiles of physical behaviour for both females and males (see supplementary material). The values of the fit indices for the consecutive latent profile model solutions (ranging from 2 to 6) are also available in the supplementary material). The theoretical foundation for the three profiles was supported by distinct patterns of physical behaviour, which exhibited meaningful differences between the profiles. The identified profiles of physical behaviour are presented in Figure 1 (a) for females and (b) for males and were labelled as “active”, “intermediate” and “sedentary”. * Figure 1* Active. Participants with an "active" profile (females, n=304 and males, n=111) were characterised by a relatively low percentage of sedentary behaviour (50.1% for females and 49.1% for males) and high percentages of light PA (46.4% for females and 45.8% for males) and MVPA (3.5% for females and 5.1% for males) when compared to participants of “intermediate” and “sedentary” profiles. The proportion of participants' total physical activity and sedentary behaviour with this profile was more balanced. Also, among individuals in this profile, 52.3% of females and 67.6% of males met the recommended levels of MVPA (21.4 min/day). Intermediate. Participants with an "intermediate" profile (females, n=288 and males, n=146) were characterised by a relatively higher percentage of time spent in sedentary behaviour (65.6% for females and 66.4% for males) and lower percentages of time spent in light PA (32.9% for females and 31% for males) and MVPA (around 1.5% for females and 2.6% for males) when compared with participants of the “active” profile. Only 17.36% of the females and 39.73% of the males with “intermediate” profiles met the recommended levels of MVPA. Sedentary . Participants with a "sedentary" profile (females, n=173 and males, n=73) were characterised by a relatively very high percentage of time spent in sedentary behaviour (79.9% for females and 79.8% for males) and very low percentages of time spent in light PA (20% for females and 19.9% for males) and MVPA (0.2% for both females and males) when compared with remained profiles. None of the participants of this profile met the recommended levels of MVPA. Table 1 presents characteristics and the values of physical activity and sedentary behaviour in minutes per day for females and males according to the profiles of physical behaviour. Females with “active” profiles were the youngest, followed by those with “intermediate” profiles, who were older than the “active” group but younger than the “sedentary” group, which encompassed the oldest females. In males, there were no differences in age between the 'active' and 'intermediate' groups. However, the 'sedentary' group was characterized by the oldest individuals when contrasted with the 'active' and 'intermediate' groups. Regarding body mass, no differences were observed among females’ profiles of physical behaviour. However, females with a 'sedentary' profile were shorter and had a higher BMI than females with an 'active' profile. In males, no differences were observed among the profiles of physical behaviour in terms of body mass, height, and BMI. *Table 1* Physical Fitness and Function For females, GzLM analysis revealed that physical behaviour profiles predicted most physical fitness and function outcomes, except for handgrip strength. The estimated parameters corrected to age are presented in Table 2 for females and males. In brief, females with an “active” or “intermediate” profile showed better physical fitness and function when compared to those categorized as "sedentary". There were no differences in physical fitness between females with “active” and “intermediate” profiles, except for the functional endurance (i.e. 6-minute walk) and CPF-score, in which the “active” group demonstrated superior results. In detail, for lower body strength, females with “active” and “intermediate” profile performed on average, 1.38 and 1.36 times more chair stand repetitions within a 30-second interval, respectively, when compared to those with a ‘sedentary' profile. In absolute values, females with "active" and "intermediate" profiles perform an average of 14.18 and 13.94 chair stand repetitions in 30 seconds, respectively, while those with a "sedentary" profile perform only 10.28 repetitions in the same duration (see estimate marginal means in Table 3). Regarding upper body strength, females with an “active” profile performed 1.32 times more arm curl repetitions in 30 seconds, than females with a “sedentary” profile. Likewise, those with an 'intermediate' profile performed 1.28 times more arm curl repetitions in 30 seconds, than their 'sedentary' counterparts. This translates to an average of 17.07 and 16.55 arm curl repetitions in 30 seconds for females with "active" and "intermediate" profiles, respectively, while females with "sedentary" profiles achieved an average of 12.92 repetitions in the same time frame. Also, females with an ‘active' or ‘intermediate' profile demonstrated higher flexibility in both the upper and lower body. More precisely, they displayed 10.11 and 9.48 centimetres of additional flexibility in the upper body (i.e., back scratch), respectively, in contrast to those classified as 'sedentary.' In the lower body (i.e., chair sit and reach), the estimated differences amounted to 7.56 and 6.68 centimetres of increased flexibility for ‘active’ and ‘intermediate’ females, respectively. In terms of agility, females with “active” and “intermediate” profiles were expected to complete the agility test faster, with mean completion times of 7.14 and 7.46 seconds, respectively, whereas “sedentary” females took longer, with a mean completion time of 12.55 seconds. Regarding functional endurance, females with an “active” profile walked 57 meters farther in 6 minutes compared to those with an “intermediate” profile, and 179.5 meters farther compared to those with a “sedentary” profile. Females with an “intermediate” profile instead, walked 122.45 meters farther compared to those with a “sedentary” profile. Finally, concerning CPF scores, there were differences among the three profiles with “active” females showing higher expected scores, which translate into better physical function, averaging 19.38 points, followed by 17.55 points for the “intermediate” group and only 13.66 points for the “sedentary” group. For males, physical behaviour profiles predicted all measures of physical fitness and function, including handgrip strength. In brief, males with an 'active' or 'intermediate' profile exhibited better values in all measures when compared to their 'sedentary' counterparts. Furthermore, there were no differences in the values of physical fitness and function for all measures between the 'active' and 'intermediate' groups. In specific, males with 'active' and 'intermediate' profiles demonstrated, on average, 3.47 Kg and 4.52 Kg higher values of handgrip strength than the 'sedentary' group, respectively. In terms of lower body strength, males with 'active' and 'intermediate' profiles achieved, on average, 1.42 times more chair stand repetitions within a 30-second interval compared to those in the 'sedentary' cohort. This translates to an average of 15.1 chair stand repetitions for 'active' and 'intermediate' individuals, in contrast to 10.6 repetitions for 'sedentary' individuals. Concerning upper body strength, males with 'active' and “intermediate” profiles performed 1.37 and 1.31 times more arm curl repetitions in 30 seconds, respectively, than males categorized as “sedentary”. These values correspond to an average of 18.91 and 17.99 arm curl repetitions in 30 seconds, for 'active' and 'intermediate’ groups respectively, while those with a 'sedentary' profile performed only 13.75 repetitions in the same duration. When assessing flexibility, males with 'active' and 'intermediate' profiles exhibited superior flexibility. They demonstrated additional increases of 5.37 and 7.98 centimetres in the upper body, and 10.76 and 7.73 centimetres in the lower body, respectively, compared to individuals with “sedentary” profiles.' In terms of agility, males with 'active' and 'intermediate' profiles completed the agility test faster, with mean completion times of 6.44 and 6.28 seconds, while males with a 'sedentary' profile took longer, with a mean completion time of 10.33 seconds. Concerning functional endurance, males with an 'active' and 'intermediate' profile walked 166.48 and 181.67 meters farther in 6 minutes, respectively, compared to those with a 'sedentary' profile. Finally, concerning CPF scores, individuals with 'active' and 'intermediate' profiles showed scores of 21.60 and 20.85, respectively, demonstrating higher levels of physical function compared to 'sedentary' individuals, who exhibited the lowest CPF scores, with an average score of 15.04. *Table 2 and Table 3** The main effects of physical behaviour profiles on each measure of physical fitness and function are also illustrated separately for females and males in the supplementary material. Discussion This study aimed to identify profiles of physical behaviour in older adults using latent profile analysis and examine their impact on physical fitness and functional outcomes. Three distinct profiles, named "active," "intermediate," and "sedentary," were identified for characterizing physical behaviour in both females and males. Individuals with an "active" or "intermediate" profile demonstrated the most favourable physical fitness and functional outcomes, while those with a "sedentary” profile exhibited the poorest results. Individuals classified as having an "active" profile had a more balanced distribution of physical activity and sedentary behaviour during their waking hours, spending roughly 50% of their time on each. In contrast, participants classified as having an "intermediate" profile spent approximately 65% of their time in sedentary behaviour and 35% in physical activity, while those having a "sedentary" profile spent approximately 80% of their time in sedentary behaviour and only 20% in physical activity. Moreover, across all groups, the majority of time spent engaging in physical activity was in light intensity while also dedicating a small percentage of their time to MVPA. This characteristic is consistent with previous studies that reported light PA as the most common type of activity among older adults, contributing considerably to their overall physical activity while MVPA only accounts for a small proportion(Magalhães et al. 2023 ). The profiles of physical behaviour identified in our study present a more comprehensive portrayal of an individual's physical activity and sedentary behaviour. They consider the combined effects of the range of physical activity intensities and sedentary behaviour which collectively constitute the spectrum of waking daily energy expenditure. This consideration is pivotal because patterns revealed within profiles may have differing impacts on health outcomes providing valuable insights in terms of public health. Moreover, in terms of intervention, by identifying different subgroups of individuals with specific behaviour patterns, more targeted interventions can be developed to address the specific needs of each subgroup. Regarding physical fitness and function, our analysis showed that individuals with "active" or “intermediate" profiles exhibited better outcomes than those with “sedentary” profiles, although only 52.30% of females and 67.57% of males with an “active” profile and 17.36 of females and 39.73% of males with an “intermediate” profile met the recommended guidelines for MVPA. Specifically, females with “active” and “intermediate” profiles had higher lower limb muscle strength, increased flexibility, higher endurance levels, and better CPF scores than individuals with a “sedentary” profile, except for handgrip strength, where no differences were observed among the three groups. In turn, males of both the “active” and “intermediate” groups had better values in all measures compared to the “sedentary” group. Interestingly, for both, females and males, the “intermediate” group, which exhibited a higher percentage of sedentary behaviour and a lower percentage of light and MVPA than the “active” group, did not demonstrate statistical differences in all outcomes with the “active” group, except for endurance levels and CPF score in females, when the “active” group has better results. This finding suggests that older adults who spent slightly more than half of the day in sedentary behaviour (around 66%) but incorporate physical activity into their daily routines, even at lower intensities, may have some benefits in their physical fitness and function as they age, even if they do not engage in enough MVPA. This is especially relevant for older adults who may be frail and vulnerable, as meeting the guidelines for MVPA may not be feasible. Moreover, this finding goes against the growing body of research suggesting that reducing sedentary behaviour and replacing it with physical activity, even light PA, can provide health benefits(Buman et al. 2010 ; Benatti and Ried-Larsen 2015 ). Specifically, evidence from ‘replacement’ studies(Lai et al. 2023 ) (ie, isotemporal substitution) indicates that reallocating sedentary behaviour to light PA may provide beneficial changes in physical function outcomes (Lerma et al. 2018 ; Del Pozo-Cruz et al. 2022 ; Gilchrist et al. 2022 ). The participants in our study with "sedentary" profiles were, on average, older than those with "active” and “intermediate” profiles, and none of them met the recommended levels of MVPA, which is 21.4 minutes or more per day. This observation aligns with previous studies that indicate older adults are more prone to adopting a sedentary lifestyle and are less inclined to adhere to physical activity recommendations, with this trend becoming more pronounced as age increases (Harvey et al. 2013 ). However, despite the "sedentary" group being on average older, our analysis showed that this group presented lower levels of physical fitness and functioning than those with "active" and "intermediate" profiles, regardless of age. This underlines that although ageing can contribute to a decline in physical function, prolonged periods of sedentary behaviour combined with low levels of physical activity may worsen or accelerate this process, potentially affecting an individual's ability to carry out daily activities and compromising their independence earlier in life. However, longitudinal studies are necessary to confirm this finding. Although our analysis revealed that individuals with a profile classified as "active" or "intermediate" demonstrated higher levels of physical fitness and function when compared to those categorized as “sedentary”, it's important to note that not all of them meet the recommended fitness standards associated with independent function in later years develop by Rikli and Jones (Rikli and Jones 2013 ). These standards were established to determine the fitness level necessary for each 5-year age interval to maintain physical independence until age 90 and beyond, despite the expected age-related declines. For example, among individuals with a profile characterized as "active," only 77.9% of females and 67.6% of males achieved healthy upper body strength cut points, and 70.7% and 64.1% met the health values for lower body strength, respectively. This percentage was slightly lower for those with an "intermediate" profile, with 68.1% of females and 66.7% of males meeting the recommended values for upper body strength, and 64.4 and 66.7 meeting the standards for lower body strength, respectively. When considering other measures of physical fitness, the percentage of individuals with “active” or “intermediate” profiles meeting the expected health benchmarks dropped to as low as 50%. This implies that, despite their relatively better performance, there may still be room for improvement in their physical fitness. Regarding the participants with a “sedentary” profile, more than 90% of both, females and males showed risk values for aerobic endurance assessed by 6 min of walk or values for agility, assessed by 8-ft up-and-go (Rikli and Jones 2013 ). According to physical function scores assessed using the CPF scale, around 74% of “sedentary” females and 61% of males may be at risk of losing physical independence.(Rikli and Jones 2013 ) Another observation was that muscle strength assessed by handgrip did not reveal differences between the groups of females. This is critical because of the approach to assessing sarcopenia, which is identified in both sexes when handgrip strength is decreased (< 16 kg for females and < 27 kg for males)(Cruz-Jentoft et al. 2019 ). According to our results, a more or less active profile does not appear to be decisive for handgrip strength in females. In fact, muscle weakness expressed through the handgrip strength seems to be more prevalent in males than in females (Lima et al. 2022 ). Lastly, it is important to acknowledge the limitations of our study, particularly its cross-sectional design, which restricts our ability to establish a causal relationship between physical behaviour profiles with physical fitness and function. However, the study's main strength lies in its adoption of a person-centred approach, which complements previous traditional variable-centred approaches focused on identifying relationships between variables. Through the use of latent profile analysis, it became possible to characterize individuals more holistically in terms of their behaviours. This methodology offers a more integrated and comprehensive understanding of physical behaviours, revealing the intricate interplay among various intensities of physical activity and sedentary behaviour. For instance, the time individuals allocate to specific intensities of physical activity, such MVPA, reflects adjustments in the time spent in other activity intensities as well as in sedentary behaviour. This interconnectedness fosters a deeper appreciation of the multifaceted dynamics of physical behaviour and its effects on overall health. Conclusion Incorporating a more balanced behaviour between physical activity and sedentary behaviour throughout the waking day appears to provide physical fitness and functional benefits, even if MVPA are not fully met. This is particularly important for older adults who may struggle to comply fully with MVPA guidelines but could maintain or improve their physical fitness and function with a more active behaviour through the reduction of sedentary behaviour and inclusion of light physical activity. Declarations Acknowledgments This study was supported by the Portuguese Foundation for Science and Technology (FCT) within the Unit I&D 472 (grant number UIDB/00447/2020). Vera Zymbal was also supported by the FCT, DOI 10.54499/CEECINST/00036/2021/CP2776/CT0002 (https://doi.org/10.54499/CEECINST/00036/2021/CP2776/CT0002) Authors’ contribution Vera Zymbal: Conceptualization, Methodology, Formal Analysis, Investigation, Writing - Original Draft. João P. Magalhães: Conceptualization, Investigation, Writing - Review & Editing. Fátima Baptista : Conceptualization, Writing - Review & Editing. Eduardo B. Cruz : Conceptualization, Writing - Review & Editing. Gil B. Rosa: Investigation and Data Curation. Luís B. Sardinha: Conceptualization, Writing - Review & Editing. All authors All authors read and approved the final manuscript. Competing Interests The authors have no competing interests to declare that are relevant to the content of this article. Funding This study was supported by the Portuguese Foundation for Science and Technology (FCT) within the Unit I&D 472 (grant number UIDB/00447/2020). Vera Zymbal was also supported by the FCT, DOI 10.54499/CEECINST/00036/2021/CP2776/CT0002 (https://doi.org/10.54499/CEECINST/00036/2021/CP2776/CT0002) Compliance with Ethical Standards This study was approved by the Ethics Committee of the Faculty of Human Kinetics of the University of Lisbon (number: 25/2020). Written informed consent was obtained from participants. Data availability statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References Bauer J (2022) A Primer to Latent Profile and Latent Class Analysis. In: Professional and Practice-based Learning Benatti FB, Ried-Larsen M (2015) The Effects of Breaking up Prolonged Sitting Time: A Review of Experimental Studies. Med Sci Sports Exerc 47:2053–2061. https://doi.org/10.1249/MSS.0000000000000654 Billot M, Calvani R, Urtamo A, et al (2020) Preserving Mobility in Older Adults with Physical Frailty and Sarcopenia: Opportunities, Challenges, and Recommendations for Physical Activity Interventions. https://doi.org/10.2147/CIA.S253535 Bull FC, Al-Ansari SS, Biddle S, et al (2020) World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med 54:1451. https://doi.org/10.1136/BJSPORTS-2020-102955 Buman MP, Hekler EB, Haskell WL, et al (2010) Objective Light-Intensity Physical Activity Associations With Rated Health in Older Adults. Am J Epidemiol 172:1155. https://doi.org/10.1093/AJE/KWQ249 Chastin SFM, De Craemer M, De Cocker K, et al (2019) How does light-intensity physical activity associate with adult cardiometabolic health and mortality? Systematic review with meta-analysis of experimental and observational studies. Br J Sports Med 53:370–376. https://doi.org/10.1136/BJSPORTS-2017-097563 Cruz-Jentoft AJ, Bahat G, Bauer J, et al (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48:16. https://doi.org/10.1093/AGEING/AFY169 Cunningham C, O’ Sullivan R, Caserotti P, Tully MA (2020) Consequences of physical inactivity in older adults: A systematic review of reviews and meta-analyses. Scand J Med Sci Sports 30:816–827. https://doi.org/10.1111/SMS.13616 Del Pozo-Cruz J, Irazusta J, Rodriguez-Larrad A, et al (2022) Replacing Sedentary Behavior With Physical Activity of Different Intensities: Implications for Physical Function, Muscle Function, and Disability in Octogenarians Living in Long-Term Care Facilities. J Phys Act Health 19:329–338. https://doi.org/10.1123/JPAH.2021-0186 Gilchrist SC, Bennett A, Judd SE, et al (2022) Sedentary Behavior and Physical Functioning in Middle-Age and Older Adults Living in the United States: The Reasons for Geographic and Racial Differences in Stroke Study. Med Sci Sports Exerc 54:1897–1903. https://doi.org/10.1249/MSS.0000000000002983 Harridge SDR, Lazarus NR (2017) Physical activity, aging, and physiological function. Physiology 32:152–161. https://doi.org/10.1152/PHYSIOL.00029.2016/ASSET/IMAGES/LARGE/PHY0021703720003.JPEG Harvey JA, Chastin SFM, Skelton DA (2013) Prevalence of Sedentary Behavior in Older Adults: A Systematic Review. Int J Environ Res Public Health 10:6645. https://doi.org/10.3390/IJERPH10126645 Lai TF, Liao Y, Hsueh MC, et al (2023) Effect of isotemporal substitution of sedentary behavior with different intensities of physical activity on the muscle function of older adults in the context of a medical center. BMC Geriatr 23:. https://doi.org/10.1186/S12877-023-03819-Z Lerma NL, Cho CC, Swartz AM, et al (2018) Isotemporal Substitution of Sedentary Behavior and Physical Activity on Function. Med Sci Sports Exerc 50:792. https://doi.org/10.1249/MSS.0000000000001491 Lima AB de, Henrinques-Neto D, Ribeiro G dos S, et al (2022) Muscle Weakness and Walking Slowness for the Identification of Sarcopenia in the Older Adults from Northern Brazil: A Cross-Sectional Study. International Journal of Environmental Research and Public Health 2022, Vol 19, Page 9297 19:9297. https://doi.org/10.3390/IJERPH19159297 Liu CJ, Latham NK (2009) Progressive resistance strength training for improving physical function in older adults. Cochrane Database of Systematic Reviews. https://doi.org/10.1002/14651858.CD002759.PUB2/INFORMATION/EN Magalhães JP, Hetherington-Rauth M, Rosa GB, et al (2023) Physical Activity and Sedentary Behavior in the Portuguese Population: What Has Changed from 2008 to 2018? Med Sci Sports Exerc McGregor DE, Carson V, Palarea-Albaladejo J, et al (2018) Compositional Analysis of the Associations between 24-h Movement Behaviours and Health Indicators among Adults and Older Adults from the Canadian Health Measure Survey. Int J Environ Res Public Health 15:. https://doi.org/10.3390/IJERPH15081779 Mcgregor DE, Palarea-Albaladejo J, Dall PM, et al (2021) Compositional analysis of the association between mortality and 24-hour movement behaviour from NHANES. Eur J Prev Cardiol 28:791–798. https://doi.org/10.1177/2047487319867783 Migueles JH, Aadland E, Andersen LB, et al (2022) GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies. Br J Sports Med 56:376–384. https://doi.org/10.1136/BJSPORTS-2020-103604 Moreno-Agostino D, Daskalopoulou C, Wu YT, et al (2020) The impact of physical activity on healthy ageing trajectories: evidence from eight cohort studies. Int J Behav Nutr Phys Act 17:. https://doi.org/10.1186/S12966-020-00995-8 Payette H, Gueye NR, Gaudreau P, et al (2011) Trajectories of Physical Function Decline and Psychological Functioning: The Québec Longitudinal Study on Nutrition and Successful Aging (NuAge). The Journals of Gerontology: Series B 66B:i82–i90. https://doi.org/10.1093/GERONB/GBQ085 Pettee Gabriel K, Sternfeld B, Colvin A, et al (2017) Physical activity trajectories during midlife and subsequent risk of physical functioning decline in late mid-life: The Study of Women’s Health Across the Nation (SWAN). Prev Med (Baltim) 105:287. https://doi.org/10.1016/J.YPMED.2017.10.005 Rikli RE, Jones CJ (1999) Functional Fitness Normative Scores for Community-Residing Older Adults, Ages 60-94. J Aging Phys Act 7:162–181. https://doi.org/10.1123/JAPA.7.2.162 Rikli RE, Jones CJ (2013) Development and Validation of Criterion-Referenced Clinically Relevant Fitness Standards for Maintaining Physical Independence in Later Years. Gerontologist 53:255–267. https://doi.org/10.1093/GERONT/GNS071 Rikli RE, Jones CJ (1998) The Reliability and Validity of a 6-Minute Walk Test as a Measure of Physical Endurance in Older Adults. J Aging Phys Act 6:363–375. https://doi.org/10.1123/JAPA.6.4.363 Ross R, Chaput JP, Giangregorio LM, et al (2020) Canadian 24-Hour Movement Guidelines for Adults aged 18-64 years and Adults aged 65 years or older: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab 45:S57–S102. https://doi.org/10.1139/APNM-2020-0467 Seol H (2023) snowRMM: Rasch Mixture, LCA, and Test Equating Analysis. (Version 5.5.7)[jamovi module].URL https://github.com/hyunsooseol/snowRMM. Syue SH, Yang HF, Wang CW, et al (2022) The Associations between Physical Activity, Functional Fitness, and Life Satisfaction among Community-Dwelling Older Adults. Int J Environ Res Public Health 19:. https://doi.org/10.3390/IJERPH19138043 Troiano RP, Berrigan D, Dodd KW, et al (2008) Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 40:181–188. https://doi.org/10.1249/MSS.0B013E31815A51B3 Zhang Y, Zhang Y, Du S, et al (2020) Exercise interventions for improving physical function, daily living activities and quality of life in community-dwelling frail older adults: A systematic review and meta-analysis of randomized controlled trials. Geriatr Nurs (Minneap) 41:261–273. https://doi.org/10.1016/J.GERINURSE.2019.10.006 Tables Table 1 - Participants' characteristics and values of physical activity and sedentary behaviour variables in minutes per day for females and males according to the profiles of physical behaviour. "Active" “Intermediate" "Sedentary" Females Mean SE 95% IC Mean SE 95% IC Mean SE 95% IC Age (yrs) 71.55 b,c 0.351 70.86 72.23 75.17 a,c 0.360 74.46 75.88 81.76 a,b 0.465 80.84 82.67 BMI (Kg/m 2 ) 28.02 c 0.253 27.53 28.52 28.75 0.260 28.24 29.26 29.23 a 0.335 28.57 29.89 Body mass (Kg) 65.95 0.644 64.69 67.22 67.35 0.662 66.05 68.65 66.80 0.854 65.12 68.48 Body height (cm) 153.40 c 0.367 152.68 154.12 152.99 c 0.377 152.25 153.73 151.08 a,b 0.486 150.12 152.03 Sedentary behaviour (min-d -1 ) 393.84 b,c 2.97 388.01 399.67 518.02 a,c 3.04 512.04 523.99 620.78 a,b 4.01 612.91 628.65 Light PA (min-d -1 ) 367.46 b,c 3.14 361.29 373.64 259.35 a,c 3.22 253.03 265.67 165.55 a,b 4.24 157.22 173.88 MVPA (min-d -1 ) 27.48 b,c 0.94 25.64 29.32 11.42 a,c 0.96 9.54 13.30 2.46 a,b 1.26 -0.027 4.94 Males Age (yrs) 73.26 c 0.628 72.02 74.50 74.90 c 0.548 73.83 75.98 80.77 a,b 0.775 79.24 82.29 BMI (Kg/m 2 ) 27.58 0.394 26.80 28.35 27.40 0.343 26.73 28.08 28.07 0.486 27.12 29.03 Body mass (Kg) 76.33 1.247 73.87 78.78 75.91 1.088 73.77 78.05 75.53 1.538 72.50 78.55 Body height (cm) 166.21 0.632 164.97 167.45 166.19 0.551 165.11 167.28 163.95 0.779 162.42 165.48 Sedentary behaviour (min-d -1 ) 385.69 b,c 4.953 375.94 395.43 524.58 a,c 4.245 516.23 532.93 624.62 a,b 6.077 612.67 636.58 Light PA (min-d -1 ) 365.31 b,c 5.127 355.22 375.39 245.73 a,c 4.394 237.09 254.37 163.58 a,b 6.291 151.20 175.95 MVPA (min-d -1 ) 40.54 b,c 2.226 36.16 44.91 21.22 a,c 1.907 17.47 24.97 3.33 a,b 2.731 -2.04 8.70 BMI, body mass index; PA, physical activity, MVPA, moderate-to-vigorous physical activity. Table 2. Physical fitness and function estimated parameters, standard errors, and p-values from the generalised linear models for females and males according to profiles of physical behaviour. Females Males β SE p β SE p Handgrip Active - Intermediate 0.229 0.499 0.646 -1.048 1.179 0.375 Active – Sedentary 1.144 0.662 0.085 3.469 1.520 0.023 Intermediate -Sedentary 0.914 0.609 0.134 4.517 1.403 0.001 Exp (β) Exp (β) Chair Stand Active - Intermediate 1.017 0.024 0.472 1.003 0.034 0.922 Active – Sedentary 1.379 0.048 <0.001 1.424 0.072 <0.001 Intermediate -Sedentary 1.356 0.045 <0.001 1.419 0.068 <0.001 Exp (β) Exp (β) Arm Curl Active - Intermediate 1.031 0.022 0.154 1.051 0.032 0.102 Active – Sedentary 1.321 0.041 <0.001 1.375 0.061 <0.001 Intermediate -Sedentary 1.281 0.038 <0.001 1.308 0.055 <0.001 β β Back Scratch Active - Intermediate 0.631 1.089 0.562 -2.615 1.795 0.146 Active – Sedentary 10.113 1.472 <0.001 5.368 2.349 0.023 Intermediate -Sedentary 9.482 1.353 <0.001 7.982 2.189 <0.001 β β Chair Sit and Reach Active - Intermediate 0.882 1.177 0.454 3.031 1.848 0.102 Active – Sedentary 7.563 1.542 <0.001 10.756 2.358 <0.001 Intermediate -Sedentary 6.681 1.415 <0.001 7.725 2.216 <0.001 Exp (β) Exp (β) 8-Foot Up and Go Active - Intermediate 0.957 0.037 0.255 1.027 0.045 0.546 Active – Sedentary 0.569 0.035 <0.001 0.624 0.043 <0.001 Intermediate -Sedentary 0.595 0.035 <0.001 0.607 0.040 <0.001 β β 6-Minute Walk Active - Intermediate 57.073 10.146 <0.001 -15.198 16.901 0.369 Active – Sedentary 179.521 13.238 <0.001 166.477 21.872 <0.001 Intermediate -Sedentary 122.449 12.205 <0.001 181.675 20.506 <0.001 β β CPF -Score Active - Intermediate 1.827 0.468 <0.001 0.747 0.639 0.243 Active – Sedentary 5.720 0.592 <0.001 6.556 0.791 <0.001 Intermediate -Sedentary 3.893 0.537 <0.001 5.809 0.735 <0.001 All models were adjusted to age. Table 3. Estimate marginal means, standard errors, and 95% confidence intervals of physical fitness and function outcomes, for females and males according to the profiles of physical behaviour. “Active" "Intermediate" "Sedentary" Females Mean SE 95% CI Mean SE 95% CI Mean SE 95% CI Handgrip (kg) 21.43 0.36 20.72 22.14 21.20 0.35 20.52 21.88 20.29 0.50 19.31 21.27 Chair Stand (rep/30 sec) 14.18 c 0.24 13.71 14.66 13.94 c 0.24 13.48 14.41 10.28 a,b 0.29 9.73 10.86 Arm Curl (rep/30 sec) 17.07 c 0.26 16.56 17.60 16.55 c 0.26 16.06 17.06 12.92 a,b 0.32 12.31 13.57 Back Scratch (cm) -12.47 c 0.79 -14.01 -10.92 -13.10 c 0.75 -14.58 -11.61 -22.58 a,b 1.12 -24.78 -20.38 Chair Sit and Reach (cm) -2.21 c 0.85 -3.88 -0.55 -3.10 c 0.82 -4.71 -1.48 -9.78 a,b 1.14 -12.02 -7.53 8 Foot Up-and -go (sec) 7.14 c 0.20 6.76 7.55 7.46 c 0.21 7.06 7.89 12.55 ab 0.65 11.35 13.89 6 Minute Walk (m/6 min) 450.11 b,c 7.31 435.75 464.46 393.03 a,c 7.09 379.11 406.96 270.59 a,b 9.86 251.22 289.95 CPF – score (score) 19.38 b,c 0.35 18.70 20.06 17.55 ,c 0.32 16.92 18.18 13.66 a,b 0.43 12.82 14.49 Males Handgrip (kg) 34.04 c 0.91 32.25 35.82 35.08c 0.77 33.57 36.60 30.57 a,b 1.15 28.30 32.83 Chair Stand (rep/30 sec) 15.11 c 0.39 14.36 15.89 15.06 c 0.35 14.39 15.75 10.61 a,b 0.44 9.79 11.51 Arm Curl (rep/30 sec) 18.91 c 0.43 18.08 19.77 17.99 c 0.37 17.27 18.74 13.75 a,b 0.49 12.81 14.75 Back Scratch (cm) -20.73 1.37 -23.43 -18.04 -18.12 c 1.18 -20.44 -15.80 -26.10 b 1.82 -29.68 -22.52 Chair Sit and Reach (cm) -5.41 c 1.39 -8.15 -2.66 -8.44 c 1.24 -10.87 -6.00 -16.16 a,b 1.81 -19.72 -12.61 8 Foot Up-and -go (sec) 6.44 c 0.22 6.03 6.88 6.28 c 0.19 5.92 6.65 10.33 ab 0.59 9.24 11.56 6 Minute Walk (m/6 min) 478.82 c 12.79 453.64 503.99 494.01 c 11.27 471.84 516.19 312.34 a,b 16.81 279.25 345.42 CPF - score 21.60 c 0.49 20.63 22.56 20.85 c 0.42 20.02 21.68 15.04 a,b 0.59 13.88 16.20 All models were adjusted to age. ᵃ difference from "active" profile b difference from "intermediate" profile c difference from "sedentary" profile Additional Declarations No competing interests reported. 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Magalhães","email":"","orcid":"","institution":"CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"João","middleName":"P.","lastName":"Magalhães","suffix":""},{"id":313583966,"identity":"add285cb-a62f-4c4d-aae6-b5e09263b2aa","order_by":2,"name":"Fátima Baptista","email":"","orcid":"","institution":"CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Fátima","middleName":"","lastName":"Baptista","suffix":""},{"id":313583967,"identity":"c49948ae-cc5b-4b26-b087-aa7410e3383f","order_by":3,"name":"Eduardo B. Cruz","email":"","orcid":"","institution":"Instituto Politécnico de Setúbal, Escola Superior de Saúde","correspondingAuthor":false,"prefix":"","firstName":"Eduardo","middleName":"B.","lastName":"Cruz","suffix":""},{"id":313583968,"identity":"71538d51-a4c8-47ba-b14a-1c0b1dcba9c9","order_by":4,"name":"Gil B. Rosa","email":"","orcid":"","institution":"CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Gil","middleName":"B.","lastName":"Rosa","suffix":""},{"id":313583969,"identity":"09d2b437-a1fb-44a6-9df4-44653d7a37f8","order_by":5,"name":"Luís B. Sardinha","email":"","orcid":"","institution":"CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Luís","middleName":"B.","lastName":"Sardinha","suffix":""}],"badges":[],"createdAt":"2024-05-27 12:36:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4485059/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4485059/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59048363,"identity":"fef94d68-5342-4991-b76f-146aaabf3987","added_by":"auto","created_at":"2024-06-25 19:27:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25205,"visible":true,"origin":"","legend":"\u003cp\u003eProfiles of physical behaviour for (a) females and (b) males.\u003c/p\u003e\n\u003cp\u003ePA, physical activity, MVPA, moderate-to-vigorous physical activity.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4485059/v1/0cfb51a314cc7e5d1ade555b.png"},{"id":59726329,"identity":"1e88d7b3-a972-4fdc-b072-a28417d42dcd","added_by":"auto","created_at":"2024-07-05 10:59:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1003553,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4485059/v1/1199b4df-6f7e-487f-98e2-ba80978e109d.pdf"},{"id":59048365,"identity":"210436bc-e0ae-46e4-ad61-6ec50b0b62cc","added_by":"auto","created_at":"2024-06-25 19:27:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":331531,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4485059/v1/35dab16d15c651b6b05ab4d3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Latent profiles of physical behaviour and their impact on physical fitness and function of Portuguese older adults","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMaintaining physical fitness and function is a crucial objective for older adults as it contributes to the preservation of physical independence(Billot et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, as individuals age, they commonly experience a gradual decline in physical fitness components, such as cardiorespiratory and muscular endurance, muscular strength and power, flexibility, agility, and overall physical function, which encompasses the ability to perform activities of daily living (ADLs)(Payette et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Nonetheless, the rates of decline in physical fitness and function can vary among individuals of the same age due to a range of factors, including lifestyles such as the time spent in physical activity and sedentary pursuits(Harridge and Lazarus \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Pettee Gabriel et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cunningham et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Moreno-Agostino et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral observational(Syue et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and experimental(Liu and Latham \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) investigations have reported that older adults who engage in higher levels of physical activity exhibit better physical fitness and function when compared to those who are less active. Despite the well-documented benefits of physical activity, a large number of older adults are physically inactive, meaning they do not meet the recommended levels of physical activity guidelines(Magalh\u0026atilde;es et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Actually, with ageing, both women and men tend to become less active and increase their time spent in sedentary behaviour(Magalh\u0026atilde;es et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) which has detrimental effects on physical fitness and function(Gilchrist et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe evidence regarding the detrimental effects of sedentary behaviour has led to an update in the World Health Organization (WHO) physical activity recommendations. Currently, the guidelines emphasize the importance of older adults not only engaging in moderate-to-vigorous physical activity (MVPA) but also reducing sedentary time and replacing it with physical activity of any intensity, including light intensity(Bull et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which also seems to provide important health benefits(Chastin et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bull et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This update on WHO, as well as in other national guidelines(Ross et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) has expanded the perspective on physical behaviour for a more holistic view.\u003c/p\u003e \u003cp\u003eRecognizing the intricate interplay between sedentary behaviour and physical activity across all spectrums of intensity becomes crucial, as all these variables contribute to energy expenditure throughout the waking day. Also, this is particularly important given the growing body of evidence suggesting that combinations of these behaviours can have varying effects on a range of health outcomes (McGregor et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mcgregor et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, to date, most studies analysing associations of physical activity of different intensities and or sedentary behaviour with health outcomes, including physical fitness and function, have used variable-centred approaches as the main form of analysis (Migueles et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although this type of approach is suitable for describing associations between variables, it falls in capturing individuals\u0026rsquo; patterns and the complex combined effects that may exist among these variables. Moreover, a recent consensus statement on analytical approaches to assess associations with accelerometer-determined physical behaviours has emphasised the need for studies consider the interplay among these physical behaviours, moving away from focusing solely on sedentary behaviour or physical activity intensities as individual variables(Migueles et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this context, a person-oriented approach, such as latent profile analysis offers a promising alternative methodology focusing on identifying subgroups of individuals characterized by similar patterns across a set of variables(Bauer \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). By identifying subgroups with specific behaviour patterns, we can explore how these behaviours contribute to health outcomes. This approach allows for a more nuanced understanding of the complexity of human physical behaviour and can inform more targeted and personalized interventions or policies. Therefore, this study aims to (1) identify profiles of physical activity and sedentary behaviour in older adults and (2) explore the association of those profiles with markers of physical fitness and function.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eCross-sectional data from the Portuguese physical activity and sports monitoring system collected between 2017 and 2018 was used. A detailed description of the data collection process can be found in a previous publication(Magalh\u0026atilde;es et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In brief, participants were recruited from community senior (social) centers, public and private institutions, sports clubs, and social/sports events. In this report, we included only older adults (\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;65 years) with complete and valid accelerometry data, (n\u0026thinsp;=\u0026thinsp;1095, 765 females). Written informed consent was obtained from participants. The study was approved by the Ethics Committee of the Faculty of Human Kinetics, University of Lisbon (number: 25/2020).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePhysical fitness and function\u003c/h2\u003e \u003cp\u003ePhysical fitness was assessed through the Senior Fitness Test Battery(Rikli and Jones \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) which consists of a set of six functional fitness tests validated to determine physiological parameters that support physical mobility and independence in older adults. The 30-s chair-stand, arm-curl, chair sit-and-reach, back-scratch, 8-ft up-and-go, and 6-min walk tests were used to measure lower and upper body strength, lower and upper body flexibility, agility, and functional endurance, respectively. A detailed description of each of the tests can be found elsewhere(Rikli and Jones \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Furthermore, we evaluated muscle strength through handgrip, which has been indicated as a diagnostic tool for sarcopenia, the age-related decline in skeletal muscle mass and function (Cruz-Jentoft et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Physical function, instead, was assessed subjectively by the 12-item Composite Physical Function (CPF) scale (Rikli and Jones \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1998\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This self-report questionnaire was designed to assess an individual's physical function across a range of abilities, including basic ADLs (e.g., dressing oneself), instrumental ADLs (e.g., housework), and advanced activities (e.g. more vigorous exercise activities). The questionnaire consists of 12 items, each answered on a 3-category scale (0\u0026thinsp;=\u0026thinsp;cannot do, 1\u0026thinsp;=\u0026thinsp;can do with help, 2\u0026thinsp;=\u0026thinsp;can do independently). The total score across all items provides an overall measure of the individual's physical function level.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePhysical Activity and Sedentary Behaviour\u003c/h2\u003e \u003cp\u003eTime spent in sedentary behaviour, light physical activity (light PA) and MVPA were evaluated by accelerometry (min day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Participants were asked to wear an accelerometer (either the Actigraph, model GT3X or the GT1M (Pensacola, Florida) on the right hip, near the iliac crest for 7 consecutive days, including at least 2 weekdays and 1 weekend days. The devices were taken off only when the participants were sleeping or engaging in water-based activities. Accelerometry movement counts were collected in raw mode with a 100 Hz frequency and posteriorly downloaded into 15-s epochs (Actilife v.6.9.1). Physical activity intensities and sedentary behaviour cut points, wear time, and non-wear time validation criteria were defined according to Troiano et al.(Troiano et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). For latent profile analysis and to adjust for inter-participant variability in accelerometer wear time, physical activity and sedentary behaviour were expressed as a percentage of wear time (calculated as minutes spent in each intensity (min/day) / average wear-times (min/day) x 100).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eLatent profile analysis was employed to identify subgroups of participants who shared similar profiles of physical behaviour. The analysis was conducted using the snowRMM module, version 5.5.7 (Seol \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), of Jamovi software (version 2.3.28). Separate models were fitted for males and females, with the average percentage of time spent on sedentary behaviour, light PA, and MVPA per day serving as the variables. We initially fitted latent profile models for 2\u0026ndash;6 profiles, with varying variances and covariances fixed to 0. To determine the optimal number of profiles, we considered a combination of model fit indices (i.e., a collection of statistics that quantify the degree of data-model fit), interpretability, and theoretical relevance. Since the fit indices may continue to improve as more profiles are extracted, especially in larger samples, we created elbow plots that represented the gains associated with additional profiles and identified the point at which the improvement in model fit plateaued. We then examined the interpretability and theoretical relevance of the resulting profiles. To assess whether the resulting physical behaviour profiles were significant predictors of each measure of physical fitness and function, generalized linear models (GzLM) were used. For continuous dependent variables, linear models with an identity link function or linear inverse models with a log link function were used, while Poisson models with a log link function were used for dependent count variables. These models were chosen based on the nature and distribution of the dependent variables and the model\u0026rsquo;s fit indices (i.e. AIC and BIC) as well as on the model\u0026rsquo;s residual distribution. Age was included as a covariate. Marginal means were estimated to examine the expected values of the dependent variables for each profile of physical behaviour adjusted for age. The significance level was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePhysical Behaviour Profiles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe elbow plots, representing the fit indices of the model solutions, indicated that the improvement in fit reaches a plateau at three profiles of physical behaviour for both females and males (see supplementary material). The values of the fit indices for the consecutive latent profile model solutions (ranging from 2 to 6) are also available in the supplementary material). The theoretical foundation for the three profiles was supported by distinct patterns of physical behaviour, which exhibited meaningful differences between the profiles. The identified profiles of physical behaviour are presented in Figure 1 (a) for females and (b) for males and were labelled as \u0026ldquo;active\u0026rdquo;, \u0026ldquo;intermediate\u0026rdquo; and \u0026ldquo;sedentary\u0026rdquo;.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e* Figure 1*\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eActive.\u003c/em\u003e\u003c/strong\u003e Participants with an \u0026quot;active\u0026quot; profile (females, n=304 and males, n=111) were characterised by a relatively low percentage of sedentary behaviour (50.1% for females and 49.1% for males) and high percentages of light PA (46.4% for females and 45.8% for males) and MVPA (3.5% for females and 5.1% for males) when compared to participants of \u0026ldquo;intermediate\u0026rdquo; and \u0026ldquo;sedentary\u0026rdquo; profiles. The proportion of participants\u0026apos; total physical activity and sedentary behaviour with this profile was more balanced. Also, among individuals in this profile, 52.3% of females and 67.6% of males met the recommended levels of MVPA (21.4 min/day).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIntermediate.\u003c/em\u003e\u003c/strong\u003e Participants with an \u0026quot;intermediate\u0026quot; profile (females, n=288 and males, n=146) were characterised by a relatively higher percentage of time spent in sedentary behaviour (65.6% for females and 66.4% for males) and lower percentages of time spent in light PA (32.9% for females and 31% for males) and MVPA (around 1.5% for females and 2.6% for males) when compared with participants of the \u0026ldquo;active\u0026rdquo; profile. Only 17.36% of the females and 39.73% of the males with \u0026ldquo;intermediate\u0026rdquo; profiles met the recommended levels of MVPA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSedentary\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eParticipants with a \u0026quot;sedentary\u0026quot; profile (females, n=173 and males, n=73) were characterised by a relatively very high percentage of time spent in sedentary behaviour (79.9% for females and 79.8% for males) and very low percentages of time spent in light PA (20% for females and 19.9% for males) and MVPA (0.2% for both females and males) when compared with remained profiles. None of the participants of this profile met the recommended levels of MVPA.\u003c/p\u003e\n\u003cp\u003eTable 1 presents characteristics and the values of physical activity and sedentary behaviour in minutes per day for females and males according to the profiles of physical behaviour. Females with \u0026ldquo;active\u0026rdquo; profiles were the youngest, followed by those with \u0026ldquo;intermediate\u0026rdquo; profiles, who were older than the \u0026ldquo;active\u0026rdquo; group but younger than the \u0026ldquo;sedentary\u0026rdquo; group, which encompassed the oldest females. In males, there were no differences in age between the \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; groups. However, the \u0026apos;sedentary\u0026apos; group was characterized by the oldest individuals when contrasted with the \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; groups. Regarding body mass, no differences were observed among females\u0026rsquo; profiles of physical behaviour. However, females with a \u0026apos;sedentary\u0026apos; profile were shorter and had a higher BMI than females with an \u0026apos;active\u0026apos; profile. In males, no differences were observed among the profiles of physical behaviour in terms of body mass, height, and BMI.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e*Table 1*\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysical Fitness and Function\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor females, GzLM\u0026nbsp;analysis revealed that physical behaviour profiles predicted most physical fitness and function outcomes, except for handgrip strength. The estimated parameters corrected to age are presented in Table 2 for females and males. \u0026nbsp;In brief, females with an \u0026ldquo;active\u0026rdquo; or \u0026ldquo;intermediate\u0026rdquo; profile showed better physical fitness and function when compared to those categorized as \u0026quot;sedentary\u0026quot;. There were no differences in physical fitness between females with \u0026ldquo;active\u0026rdquo; and \u0026ldquo;intermediate\u0026rdquo; profiles, except for the functional endurance (i.e. 6-minute walk) and CPF-score, in which the \u0026ldquo;active\u0026rdquo; group demonstrated superior results. In detail, for lower body strength, females with \u0026ldquo;active\u0026rdquo; and \u0026ldquo;intermediate\u0026rdquo; profile performed on average, 1.38 and 1.36 times more chair stand repetitions within a 30-second interval, respectively, when compared to those with a \u0026lsquo;sedentary\u0026apos; profile. In absolute values, females with \u0026quot;active\u0026quot; and \u0026quot;intermediate\u0026quot; profiles perform an average of 14.18 and 13.94 chair stand repetitions in 30 seconds, respectively, while those with a \u0026quot;sedentary\u0026quot; profile perform only 10.28 repetitions in the same duration (see estimate marginal means in Table 3). Regarding upper body strength, females with an \u0026ldquo;active\u0026rdquo; profile performed 1.32 times more arm curl repetitions in 30 seconds, than females with a \u0026ldquo;sedentary\u0026rdquo; profile. Likewise, those with an \u0026apos;intermediate\u0026apos; profile performed 1.28 times more arm curl repetitions in 30 seconds, than their \u0026apos;sedentary\u0026apos; counterparts. This translates to an average of 17.07 and 16.55 arm curl repetitions in 30 seconds for females with \u0026quot;active\u0026quot; and \u0026quot;intermediate\u0026quot; profiles, respectively, while females with \u0026quot;sedentary\u0026quot; profiles achieved an average of 12.92 repetitions in the same time frame. Also, females with an \u0026lsquo;active\u0026apos; or \u0026lsquo;intermediate\u0026apos; profile demonstrated higher flexibility in both the upper and lower body. More precisely, they displayed 10.11 and 9.48 centimetres of additional flexibility in the upper body (i.e., back scratch), respectively, in contrast to those classified as \u0026apos;sedentary.\u0026apos; In the lower body (i.e., chair sit and reach), the estimated differences amounted to 7.56 and 6.68 centimetres of increased flexibility for \u0026lsquo;active\u0026rsquo; and \u0026lsquo;intermediate\u0026rsquo; females, respectively. In terms of agility, females with \u0026ldquo;active\u0026rdquo; and \u0026ldquo;intermediate\u0026rdquo; profiles were expected to complete the agility test faster, with mean completion times of 7.14 and 7.46 seconds, respectively, whereas \u0026ldquo;sedentary\u0026rdquo; females took longer, with a mean completion time of 12.55 seconds. Regarding functional endurance, females with an \u0026ldquo;active\u0026rdquo; profile walked 57 meters farther in 6 minutes compared to those with an \u0026ldquo;intermediate\u0026rdquo; profile, and 179.5 meters farther compared to those with a \u0026ldquo;sedentary\u0026rdquo; profile. Females with an \u0026ldquo;intermediate\u0026rdquo; profile instead, walked 122.45 meters farther compared to those with a \u0026ldquo;sedentary\u0026rdquo; profile. \u0026nbsp;Finally, concerning CPF scores, there were differences among the three profiles with \u0026ldquo;active\u0026rdquo; females showing higher expected scores, which translate into better physical function, averaging 19.38 points, followed by 17.55 points for the \u0026ldquo;intermediate\u0026rdquo; group and only 13.66 points for the \u0026ldquo;sedentary\u0026rdquo; group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor males, physical behaviour profiles predicted all measures of physical fitness and function, including handgrip strength. In brief, males with an \u0026apos;active\u0026apos; or \u0026apos;intermediate\u0026apos; profile exhibited better values in all measures when compared to their \u0026apos;sedentary\u0026apos; counterparts. Furthermore, there were no differences in the values of physical fitness and function for all measures between the \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; groups. In specific, males with \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; profiles demonstrated, on average, 3.47 Kg and 4.52 Kg higher values of handgrip strength than the \u0026apos;sedentary\u0026apos; group, respectively. In terms of lower body strength, males with \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; profiles achieved, on average, 1.42 times more chair stand repetitions within a 30-second interval compared to those in the \u0026apos;sedentary\u0026apos; cohort. This translates to an average of 15.1 chair stand repetitions for \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; individuals, in contrast to 10.6 repetitions for \u0026apos;sedentary\u0026apos; individuals. Concerning upper body strength, males with \u0026apos;active\u0026apos; and \u0026ldquo;intermediate\u0026rdquo; profiles performed 1.37 and 1.31 times more arm curl repetitions in 30 seconds, respectively, than males categorized as \u0026ldquo;sedentary\u0026rdquo;. These values correspond to an average of 18.91 and 17.99 arm curl repetitions in 30 seconds, for \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026rsquo; groups respectively, while those with a \u0026apos;sedentary\u0026apos; profile performed only 13.75 repetitions in the same duration. When assessing flexibility, males with \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; profiles exhibited superior flexibility. They demonstrated additional increases of 5.37 and 7.98 centimetres in the upper body, and 10.76 and 7.73 centimetres in the lower body, respectively, compared to individuals with \u0026ldquo;sedentary\u0026rdquo; profiles.\u0026apos; In terms of agility, males with \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; profiles completed the agility test faster, with mean completion times of 6.44 and 6.28 seconds, while males with a \u0026apos;sedentary\u0026apos; profile took longer, with a mean completion time of 10.33 seconds. Concerning functional endurance, males with an \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; profile walked 166.48 and 181.67 meters farther in 6 minutes, respectively, compared to those with a \u0026apos;sedentary\u0026apos; profile. Finally, concerning CPF scores, individuals with \u0026apos;active\u0026apos; and \u0026apos;intermediate\u0026apos; profiles showed scores of 21.60 and 20.85, respectively, demonstrating higher levels of physical function compared to \u0026apos;sedentary\u0026apos; individuals, who exhibited the lowest CPF scores, with an average score of 15.04.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e*Table 2 and Table 3**\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe main effects of physical behaviour profiles on each measure of physical fitness and function are also illustrated separately for females and males in the supplementary material.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to identify profiles of physical behaviour in older adults using latent profile analysis and examine their impact on physical fitness and functional outcomes. Three distinct profiles, named \"active,\" \"intermediate,\" and \"sedentary,\" were identified for characterizing physical behaviour in both females and males. Individuals with an \"active\" or \"intermediate\" profile demonstrated the most favourable physical fitness and functional outcomes, while those with a \"sedentary\u0026rdquo; profile exhibited the poorest results.\u003c/p\u003e \u003cp\u003eIndividuals classified as having an \"active\" profile had a more balanced distribution of physical activity and sedentary behaviour during their waking hours, spending roughly 50% of their time on each. In contrast, participants classified as having an \"intermediate\" profile spent approximately 65% of their time in sedentary behaviour and 35% in physical activity, while those having a \"sedentary\" profile spent approximately 80% of their time in sedentary behaviour and only 20% in physical activity. Moreover, across all groups, the majority of time spent engaging in physical activity was in light intensity while also dedicating a small percentage of their time to MVPA. This characteristic is consistent with previous studies that reported light PA as the most common type of activity among older adults, contributing considerably to their overall physical activity while MVPA only accounts for a small proportion(Magalh\u0026atilde;es et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The profiles of physical behaviour identified in our study present a more comprehensive portrayal of an individual's physical activity and sedentary behaviour. They consider the combined effects of the range of physical activity intensities and sedentary behaviour which collectively constitute the spectrum of waking daily energy expenditure. This consideration is pivotal because patterns revealed within profiles may have differing impacts on health outcomes providing valuable insights in terms of public health. Moreover, in terms of intervention, by identifying different subgroups of individuals with specific behaviour patterns, more targeted interventions can be developed to address the specific needs of each subgroup.\u003c/p\u003e \u003cp\u003e Regarding physical fitness and function, our analysis showed that individuals with \"active\" or \u0026ldquo;intermediate\" profiles exhibited better outcomes than those with \u0026ldquo;sedentary\u0026rdquo; profiles, although only 52.30% of females and 67.57% of males with an \u0026ldquo;active\u0026rdquo; profile and 17.36 of females and 39.73% of males with an \u0026ldquo;intermediate\u0026rdquo; profile met the recommended guidelines for MVPA. Specifically, females with \u0026ldquo;active\u0026rdquo; and \u0026ldquo;intermediate\u0026rdquo; profiles had higher lower limb muscle strength, increased flexibility, higher endurance levels, and better CPF scores than individuals with a \u0026ldquo;sedentary\u0026rdquo; profile, except for handgrip strength, where no differences were observed among the three groups. In turn, males of both the \u0026ldquo;active\u0026rdquo; and \u0026ldquo;intermediate\u0026rdquo; groups had better values in all measures compared to the \u0026ldquo;sedentary\u0026rdquo; group. Interestingly, for both, females and males, the \u0026ldquo;intermediate\u0026rdquo; group, which exhibited a higher percentage of sedentary behaviour and a lower percentage of light and MVPA than the \u0026ldquo;active\u0026rdquo; group, did not demonstrate statistical differences in all outcomes with the \u0026ldquo;active\u0026rdquo; group, except for endurance levels and CPF score in females, when the \u0026ldquo;active\u0026rdquo; group has better results. This finding suggests that older adults who spent slightly more than half of the day in sedentary behaviour (around 66%) but incorporate physical activity into their daily routines, even at lower intensities, may have some benefits in their physical fitness and function as they age, even if they do not engage in enough MVPA. This is especially relevant for older adults who may be frail and vulnerable, as meeting the guidelines for MVPA may not be feasible. Moreover, this finding goes against the growing body of research suggesting that reducing sedentary behaviour and replacing it with physical activity, even light PA, can provide health benefits(Buman et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Benatti and Ried-Larsen \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Specifically, evidence from \u0026lsquo;replacement\u0026rsquo; studies(Lai et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) (ie, isotemporal substitution) indicates that reallocating sedentary behaviour to light PA may provide beneficial changes in physical function outcomes (Lerma et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Del Pozo-Cruz et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gilchrist et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe participants in our study with \"sedentary\" profiles were, on average, older than those with \"active\u0026rdquo; and \u0026ldquo;intermediate\u0026rdquo; profiles, and none of them met the recommended levels of MVPA, which is 21.4 minutes or more per day. This observation aligns with previous studies that indicate older adults are more prone to adopting a sedentary lifestyle and are less inclined to adhere to physical activity recommendations, with this trend becoming more pronounced as age increases (Harvey et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, despite the \"sedentary\" group being on average older, our analysis showed that this group presented lower levels of physical fitness and functioning than those with \"active\" and \"intermediate\" profiles, regardless of age. This underlines that although ageing can contribute to a decline in physical function, prolonged periods of sedentary behaviour combined with low levels of physical activity may worsen or accelerate this process, potentially affecting an individual's ability to carry out daily activities and compromising their independence earlier in life. However, longitudinal studies are necessary to confirm this finding.\u003c/p\u003e \u003cp\u003eAlthough our analysis revealed that individuals with a profile classified as \"active\" or \"intermediate\" demonstrated higher levels of physical fitness and function when compared to those categorized as \u0026ldquo;sedentary\u0026rdquo;, it's important to note that not all of them meet the recommended fitness standards associated with independent function in later years develop by Rikli and Jones (Rikli and Jones \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These standards were established to determine the fitness level necessary for each 5-year age interval to maintain physical independence until age 90 and beyond, despite the expected age-related declines. For example, among individuals with a profile characterized as \"active,\" only 77.9% of females and 67.6% of males achieved healthy upper body strength cut points, and 70.7% and 64.1% met the health values for lower body strength, respectively. This percentage was slightly lower for those with an \"intermediate\" profile, with 68.1% of females and 66.7% of males meeting the recommended values for upper body strength, and 64.4 and 66.7 meeting the standards for lower body strength, respectively. When considering other measures of physical fitness, the percentage of individuals with \u0026ldquo;active\u0026rdquo; or \u0026ldquo;intermediate\u0026rdquo; profiles meeting the expected health benchmarks dropped to as low as 50%. This implies that, despite their relatively better performance, there may still be room for improvement in their physical fitness. Regarding the participants with a \u0026ldquo;sedentary\u0026rdquo; profile, more than 90% of both, females and males showed risk values for aerobic endurance assessed by 6 min of walk or values for agility, assessed by 8-ft up-and-go (Rikli and Jones \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). According to physical function scores assessed using the CPF scale, around 74% of \u0026ldquo;sedentary\u0026rdquo; females and 61% of males may be at risk of losing physical independence.(Rikli and Jones \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) Another observation was that muscle strength assessed by handgrip did not reveal differences between the groups of females. This is critical because of the approach to assessing sarcopenia, which is identified in both sexes when handgrip strength is decreased (\u0026lt;\u0026thinsp;16 kg for females and \u0026lt;\u0026thinsp;27 kg for males)(Cruz-Jentoft et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). According to our results, a more or less active profile does not appear to be decisive for handgrip strength in females. In fact, muscle weakness expressed through the handgrip strength seems to be more prevalent in males than in females (Lima et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLastly, it is important to acknowledge the limitations of our study, particularly its cross-sectional design, which restricts our ability to establish a causal relationship between physical behaviour profiles with physical fitness and function. However, the study's main strength lies in its adoption of a person-centred approach, which complements previous traditional variable-centred approaches focused on identifying relationships between variables. Through the use of latent profile analysis, it became possible to characterize individuals more holistically in terms of their behaviours. This methodology offers a more integrated and comprehensive understanding of physical behaviours, revealing the intricate interplay among various intensities of physical activity and sedentary behaviour. For instance, the time individuals allocate to specific intensities of physical activity, such MVPA, reflects adjustments in the time spent in other activity intensities as well as in sedentary behaviour. This interconnectedness fosters a deeper appreciation of the multifaceted dynamics of physical behaviour and its effects on overall health.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIncorporating a more balanced behaviour between physical activity and sedentary behaviour throughout the waking day appears to provide physical fitness and functional benefits, even if MVPA are not fully met. This is particularly important for older adults who may struggle to comply fully with MVPA guidelines but could maintain or improve their physical fitness and function with a more active behaviour through the reduction of sedentary behaviour and inclusion of light physical activity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Portuguese Foundation for Science and Technology (FCT) within the Unit I\u0026amp;D 472 (grant number UIDB/00447/2020). Vera Zymbal was also supported by the FCT, DOI 10.54499/CEECINST/00036/2021/CP2776/CT0002 (https://doi.org/10.54499/CEECINST/00036/2021/CP2776/CT0002)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVera Zymbal:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Formal Analysis, Investigation, Writing - Original Draft. \u003cstrong\u003eJo\u0026atilde;o P. Magalh\u0026atilde;es:\u003c/strong\u003e Conceptualization, Investigation, Writing - Review \u0026amp; Editing. \u003cstrong\u003eF\u0026aacute;tima Baptista\u003c/strong\u003e: Conceptualization, Writing - Review \u0026amp; Editing. \u003cstrong\u003eEduardo B. Cruz\u003c/strong\u003e: Conceptualization, Writing - Review \u0026amp; Editing. \u003cstrong\u003eGil B. Rosa:\u003c/strong\u003e Investigation and Data Curation. \u003cstrong\u003eLu\u0026iacute;s B. Sardinha:\u003c/strong\u003e Conceptualization, Writing - Review \u0026amp; Editing. All authors All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Portuguese Foundation for Science and Technology (FCT) within the Unit I\u0026amp;D 472 (grant number UIDB/00447/2020). Vera Zymbal was also supported by the FCT, DOI 10.54499/CEECINST/00036/2021/CP2776/CT0002 (https://doi.org/10.54499/CEECINST/00036/2021/CP2776/CT0002)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the Faculty of Human Kinetics of the University of Lisbon (number: 25/2020). Written informed consent was obtained from participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBauer J (2022) A Primer to Latent Profile and Latent Class Analysis. In: Professional and Practice-based Learning\u003c/li\u003e\n \u003cli\u003eBenatti FB, Ried-Larsen M (2015) The Effects of Breaking up Prolonged Sitting Time: A Review of Experimental Studies. Med Sci Sports Exerc 47:2053\u0026ndash;2061. https://doi.org/10.1249/MSS.0000000000000654\u003c/li\u003e\n \u003cli\u003eBillot M, Calvani R, Urtamo A, et al (2020) Preserving Mobility in Older Adults with Physical Frailty and Sarcopenia: Opportunities, Challenges, and Recommendations for Physical Activity Interventions. https://doi.org/10.2147/CIA.S253535\u003c/li\u003e\n \u003cli\u003eBull FC, Al-Ansari SS, Biddle S, et al (2020) World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med 54:1451. https://doi.org/10.1136/BJSPORTS-2020-102955\u003c/li\u003e\n \u003cli\u003eBuman MP, Hekler EB, Haskell WL, et al (2010) Objective Light-Intensity Physical Activity Associations With Rated Health in Older Adults. Am J Epidemiol 172:1155. https://doi.org/10.1093/AJE/KWQ249\u003c/li\u003e\n \u003cli\u003eChastin SFM, De Craemer M, De Cocker K, et al (2019) How does light-intensity physical activity associate with adult cardiometabolic health and mortality? Systematic review with meta-analysis of experimental and observational studies. Br J Sports Med 53:370\u0026ndash;376. https://doi.org/10.1136/BJSPORTS-2017-097563\u003c/li\u003e\n \u003cli\u003eCruz-Jentoft AJ, Bahat G, Bauer J, et al (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48:16. https://doi.org/10.1093/AGEING/AFY169\u003c/li\u003e\n \u003cli\u003eCunningham C, O\u0026rsquo; Sullivan R, Caserotti P, Tully MA (2020) Consequences of physical inactivity in older adults: A systematic review of reviews and meta-analyses. Scand J Med Sci Sports 30:816\u0026ndash;827. https://doi.org/10.1111/SMS.13616\u003c/li\u003e\n \u003cli\u003eDel Pozo-Cruz J, Irazusta J, Rodriguez-Larrad A, et al (2022) Replacing Sedentary Behavior With Physical Activity of Different Intensities: Implications for Physical Function, Muscle Function, and Disability in Octogenarians Living in Long-Term Care Facilities. J Phys Act Health 19:329\u0026ndash;338. https://doi.org/10.1123/JPAH.2021-0186\u003c/li\u003e\n \u003cli\u003eGilchrist SC, Bennett A, Judd SE, et al (2022) Sedentary Behavior and Physical Functioning in Middle-Age and Older Adults Living in the United States: The Reasons for Geographic and Racial Differences in Stroke Study. Med Sci Sports Exerc 54:1897\u0026ndash;1903. https://doi.org/10.1249/MSS.0000000000002983\u003c/li\u003e\n \u003cli\u003eHarridge SDR, Lazarus NR (2017) Physical activity, aging, and physiological function. Physiology 32:152\u0026ndash;161. https://doi.org/10.1152/PHYSIOL.00029.2016/ASSET/IMAGES/LARGE/PHY0021703720003.JPEG\u003c/li\u003e\n \u003cli\u003eHarvey JA, Chastin SFM, Skelton DA (2013) Prevalence of Sedentary Behavior in Older Adults: A Systematic Review. Int J Environ Res Public Health 10:6645. https://doi.org/10.3390/IJERPH10126645\u003c/li\u003e\n \u003cli\u003eLai TF, Liao Y, Hsueh MC, et al (2023) Effect of isotemporal substitution of sedentary behavior with different intensities of physical activity on the muscle function of older adults in the context of a medical center. BMC Geriatr 23:. https://doi.org/10.1186/S12877-023-03819-Z\u003c/li\u003e\n \u003cli\u003eLerma NL, Cho CC, Swartz AM, et al (2018) Isotemporal Substitution of Sedentary Behavior and Physical Activity on Function. Med Sci Sports Exerc 50:792. https://doi.org/10.1249/MSS.0000000000001491\u003c/li\u003e\n \u003cli\u003eLima AB de, Henrinques-Neto D, Ribeiro G dos S, et al (2022) Muscle Weakness and Walking Slowness for the Identification of Sarcopenia in the Older Adults from Northern Brazil: A Cross-Sectional Study. International Journal of Environmental Research and Public Health 2022, Vol 19, Page 9297 19:9297. https://doi.org/10.3390/IJERPH19159297\u003c/li\u003e\n \u003cli\u003eLiu CJ, Latham NK (2009) Progressive resistance strength training for improving physical function in older adults. Cochrane Database of Systematic Reviews. https://doi.org/10.1002/14651858.CD002759.PUB2/INFORMATION/EN\u003c/li\u003e\n \u003cli\u003eMagalh\u0026atilde;es JP, Hetherington-Rauth M, Rosa GB, et al (2023) Physical Activity and Sedentary Behavior in the Portuguese Population: What Has Changed from 2008 to 2018? Med Sci Sports Exerc\u003c/li\u003e\n \u003cli\u003eMcGregor DE, Carson V, Palarea-Albaladejo J, et al (2018) Compositional Analysis of the Associations between 24-h Movement Behaviours and Health Indicators among Adults and Older Adults from the Canadian Health Measure Survey. Int J Environ Res Public Health 15:. https://doi.org/10.3390/IJERPH15081779\u003c/li\u003e\n \u003cli\u003eMcgregor DE, Palarea-Albaladejo J, Dall PM, et al (2021) Compositional analysis of the association between mortality and 24-hour movement behaviour from NHANES. Eur J Prev Cardiol 28:791\u0026ndash;798. https://doi.org/10.1177/2047487319867783\u003c/li\u003e\n \u003cli\u003eMigueles JH, Aadland E, Andersen LB, et al (2022) GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies. Br J Sports Med 56:376\u0026ndash;384. https://doi.org/10.1136/BJSPORTS-2020-103604\u003c/li\u003e\n \u003cli\u003eMoreno-Agostino D, Daskalopoulou C, Wu YT, et al (2020) The impact of physical activity on healthy ageing trajectories: evidence from eight cohort studies. Int J Behav Nutr Phys Act 17:. https://doi.org/10.1186/S12966-020-00995-8\u003c/li\u003e\n \u003cli\u003ePayette H, Gueye NR, Gaudreau P, et al (2011) Trajectories of Physical Function Decline and Psychological Functioning: The Qu\u0026eacute;bec Longitudinal Study on Nutrition and Successful Aging (NuAge). The Journals of Gerontology: Series B 66B:i82\u0026ndash;i90. https://doi.org/10.1093/GERONB/GBQ085\u003c/li\u003e\n \u003cli\u003ePettee Gabriel K, Sternfeld B, Colvin A, et al (2017) Physical activity trajectories during midlife and subsequent risk of physical functioning decline in late mid-life: The Study of Women\u0026rsquo;s Health Across the Nation (SWAN). Prev Med (Baltim) 105:287. https://doi.org/10.1016/J.YPMED.2017.10.005\u003c/li\u003e\n \u003cli\u003eRikli RE, Jones CJ (1999) Functional Fitness Normative Scores for Community-Residing Older Adults, Ages 60-94. J Aging Phys Act 7:162\u0026ndash;181. https://doi.org/10.1123/JAPA.7.2.162\u003c/li\u003e\n \u003cli\u003eRikli RE, Jones CJ (2013) Development and Validation of Criterion-Referenced Clinically Relevant Fitness Standards for Maintaining Physical Independence in Later Years. Gerontologist 53:255\u0026ndash;267. https://doi.org/10.1093/GERONT/GNS071\u003c/li\u003e\n \u003cli\u003eRikli RE, Jones CJ (1998) The Reliability and Validity of a 6-Minute Walk Test as a Measure of Physical Endurance in Older Adults. J Aging Phys Act 6:363\u0026ndash;375. https://doi.org/10.1123/JAPA.6.4.363\u003c/li\u003e\n \u003cli\u003eRoss R, Chaput JP, Giangregorio LM, et al (2020) Canadian 24-Hour Movement Guidelines for Adults aged 18-64 years and Adults aged 65 years or older: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab 45:S57\u0026ndash;S102. https://doi.org/10.1139/APNM-2020-0467\u003c/li\u003e\n \u003cli\u003eSeol H (2023) snowRMM: Rasch Mixture, LCA, and Test Equating Analysis. (Version 5.5.7)[jamovi module].URL https://github.com/hyunsooseol/snowRMM.\u003c/li\u003e\n \u003cli\u003eSyue SH, Yang HF, Wang CW, et al (2022) The Associations between Physical Activity, Functional Fitness, and Life Satisfaction among Community-Dwelling Older Adults. Int J Environ Res Public Health 19:. https://doi.org/10.3390/IJERPH19138043\u003c/li\u003e\n \u003cli\u003eTroiano RP, Berrigan D, Dodd KW, et al (2008) Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 40:181\u0026ndash;188. https://doi.org/10.1249/MSS.0B013E31815A51B3\u003c/li\u003e\n \u003cli\u003eZhang Y, Zhang Y, Du S, et al (2020) Exercise interventions for improving physical function, daily living activities and quality of life in community-dwelling frail older adults: A systematic review and meta-analysis of randomized controlled trials. Geriatr Nurs (Minneap) 41:261\u0026ndash;273. https://doi.org/10.1016/J.GERINURSE.2019.10.006\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 - Participants\u0026apos; characteristics and values of physical activity and sedentary behaviour variables in minutes per day for females and males according to the profiles of physical behaviour.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026quot;Active\u0026quot;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ldquo;Intermediate\u0026quot;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026quot;Sedentary\u0026quot;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eFemales\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% IC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% IC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% IC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge (yrs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e71.55 \u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.17\u003cstrong\u003e\u003csup\u003ea,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e74.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e81.76\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.02 \u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBody mass (Kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e67.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBody height (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e153.40 \u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e152.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e154.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e152.99\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e152.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e153.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e151.08\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e150.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e152.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSedentary behaviour (min-d\u003csup\u003e-1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e393.84 \u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e388.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e399.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e518.02\u003cstrong\u003e\u003csup\u003ea,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e512.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e523.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e620.78\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e612.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e628.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLight PA (min-d\u003csup\u003e-1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e367.46 \u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e361.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e373.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e259.35\u003cstrong\u003e\u003csup\u003ea,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e253.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e265.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e165.55\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e157.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e173.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMVPA (min-d\u003csup\u003e-1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.48 \u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.42\u003cstrong\u003e\u003csup\u003ea,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.46\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eMales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge (yrs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e73.26\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e74.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74.90\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e80.77\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBody mass (Kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e76.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBody height (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e166.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e164.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e167.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e166.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e165.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e167.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e163.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e162.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e165.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSedentary behaviour (min-d\u003csup\u003e-1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e385.69\u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e375.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e395.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e524.58\u003cstrong\u003e\u003csup\u003ea,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e516.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e532.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e624.62\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e612.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e636.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLight PA (min-d\u003csup\u003e-1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e365.31\u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e355.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e375.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e245.73\u003cstrong\u003e\u003csup\u003ea,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e237.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e254.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e163.58\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e151.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e175.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMVPA (min-d\u003csup\u003e-1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40.54\u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.22\u003cstrong\u003e\u003csup\u003ea,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.33\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eBMI, body mass index; PA, physical activity, MVPA, moderate-to-vigorous physical activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Physical fitness and function estimated parameters, standard errors, and p-values from the generalised linear models for females and males according to profiles of physical behaviour.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"664\" style=\"margin-right: calc(20%); width: 80%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.234939759036145%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.94578313253012%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.05421686746988%\" colspan=\"3\" valign=\"top\" style=\"width: 26.1648%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.35542168674699%\" colspan=\"3\" valign=\"top\" style=\"width: 21.4493%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003eHandgrip\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive - Intermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e-1.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive \u0026ndash; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e3.469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eIntermediate -Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e4.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp (\u0026beta;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp (\u0026beta;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003eChair Stand\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive - Intermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e0.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive \u0026ndash; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eIntermediate -Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp (\u0026beta;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp (\u0026beta;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003eArm Curl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive - Intermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive \u0026ndash; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eIntermediate -Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003eBack Scratch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive - Intermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e0.562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e-2.615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive \u0026ndash; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e10.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e5.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e2.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eIntermediate -Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e9.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e7.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e2.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003eChair Sit and Reach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive - Intermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e0.454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e3.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive \u0026ndash; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e7.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e10.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e2.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eIntermediate -Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e6.681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e1.415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e7.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e2.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp (\u0026beta;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp (\u0026beta;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e8-Foot Up and Go\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive - Intermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive \u0026ndash; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eIntermediate -Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e6-Minute Walk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive - Intermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e57.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e10.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e-15.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e16.901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.369\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive \u0026ndash; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e179.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e13.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e166.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e21.872\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eIntermediate -Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e122.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e12.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e181.675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e20.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003eCPF -Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive - Intermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e1.827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eActive \u0026ndash; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e5.720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e6.556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.203007518796994%\" valign=\"top\" style=\"width: 20.8731%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.909774436090224%\" valign=\"top\" style=\"width: 23.5189%;\"\u003e\n \u003cp\u003eIntermediate -Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e3.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.3786%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\" style=\"width: 9.4076%;\"\u003e\n \u003cp\u003e5.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.270676691729323%\" valign=\"top\" style=\"width: 8.2316%;\"\u003e\n \u003cp\u003e0.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\" style=\"width: 8.6726%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAll models were adjusted to age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Estimate marginal means, standard errors, and 95% confidence intervals of physical fitness and function outcomes, for females and males according to the profiles of physical behaviour.\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.207729468599034%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ldquo;Active\u0026quot;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.207729468599034%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026quot;Intermediate\u0026quot;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.932367149758456%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026quot;Sedentary\u0026quot;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.62726176115802%\"\u003e\n \u003cp\u003e\u003cem\u003eFemales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.323281061519904%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.428226779252111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.545235223160434%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.202653799758746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.428226779252111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.545235223160434%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.047044632086852%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.428226779252111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.424607961399277%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eHandgrip (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e21.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e20.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e22.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e21.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e20.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e21.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e20.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e19.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e21.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eChair Stand (rep/30 sec)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e14.18\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e13.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e14.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e13.94\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e13.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e14.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e10.28\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e9.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e10.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eArm Curl (rep/30 sec)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e17.07\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e16.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e17.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e16.55\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e16.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e17.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e12.92\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e12.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e13.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eBack Scratch (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e-12.47\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-14.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-10.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e-13.10\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-14.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-11.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e-22.58\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-24.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-20.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eChair Sit and Reach (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e-2.21\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e-3.10\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e-9.78\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-12.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-7.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003e8 Foot Up-and -go (sec)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e7.14\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e6.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e7.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e7.46\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e7.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e7.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e12.55\u003cstrong\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e11.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e13.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003e6 Minute Walk (m/6 min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e450.11\u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e7.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e435.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e464.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e393.03\u003cstrong\u003e\u003csup\u003ea,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e7.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e379.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e406.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e270.59\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e9.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e251.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e289.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eCPF \u0026ndash; score (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e19.38\u003cstrong\u003e\u003csup\u003eb,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e18.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e20.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e17.55\u003cstrong\u003e\u003csup\u003e,c\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e16.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e18.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e13.66\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e12.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e14.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e\u003cem\u003eMales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.207729468599034%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.207729468599034%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.932367149758456%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eHandgrip (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e34.04\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e32.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e35.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e35.08c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e33.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e36.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e30.57\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e28.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e32.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eChair Stand (rep/30 sec)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e15.11\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e14.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e15.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e15.06\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e14.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e15.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e10.61\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e9.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e11.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eArm Curl (rep/30 sec)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e18.91\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e18.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e19.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e17.99\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e17.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e18.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e13.75\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e12.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e14.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eBack Scratch (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e-20.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-23.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-18.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e-18.12\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-20.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e-15.80\u003c/p\u003e\n \u003c/td\u003e\n 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\u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003e8 Foot Up-and -go (sec)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e6.44\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e6.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e6.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e6.28\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e5.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e6.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e10.33\u003cstrong\u003e\u003csup\u003eab\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e9.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e11.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003e6 Minute Walk (m/6 min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e478.82\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e12.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e453.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e503.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e494.01\u003cstrong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e11.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e471.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e516.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e312.34\u003cstrong\u003e\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e16.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e279.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e345.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.602409638554217%\"\u003e\n \u003cp\u003eCPF - score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.313253012048193%\"\u003e\n \u003cp\u003e21.60\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e20.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e22.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.19277108433735%\"\u003e\n \u003cp\u003e20.85\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e20.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e21.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.036144578313253%\"\u003e\n \u003cp\u003e15.04\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.421686746987952%\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e13.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.265060240963855%\"\u003e\n \u003cp\u003e16.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;All models were adjusted to age.\u003c/p\u003e\n\u003cp\u003eᵃ difference from \u0026quot;active\u0026quot; profile \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e difference from \u0026quot;intermediate\u0026quot; profile\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e difference from \u0026quot;sedentary\u0026quot; profile\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"physical activity, sedentary behaviour, ageing, mobility, health","lastPublishedDoi":"10.21203/rs.3.rs-4485059/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4485059/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eExploring individuals\u0026rsquo; patterns of physical activity and sedentary behaviour can reveal profiles that could differently impact health outcomes and benefit targeted interventions. This study aimed to identify latent profiles of physical behaviour in older adults and examine their association with physical fitness and function outcomes. The sample included 1095 participants (765 females) from the Portuguese physical activity and sports monitoring system. Latent profiles of physical behaviour were identified based on the percentage of waking time spent in sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity (MVPA) assessed by accelerometery. Physical fitness was assessed by Senior Fitness Test Battery, and physical function was evaluated through the 12-item Composite Physical Function questionnaire. Associations between the profiles of physical behaviour and physical fitness and function outcomes were examined using generalized linear models adjusted for age. Three profiles of physical behaviour were identified: \"active\", \"intermediate\", and \"sedentary\" for both sexes. Participants with \u0026ldquo;active\" or \"intermediate\" profiles exhibited the most favourable physical fitness and functional outcomes, while those with a \"sedentary\" profile showed the poorest results. Our findings suggest that a more balanced behaviour between physical activity and sedentary behaviour throughout the waking day appears to provide physical fitness and functional benefits, even if MVPA are not fully met. This is important for older adults who may struggle to comply fully with MVPA guidelines but could maintain or improve their physical fitness and function with a more active behaviour through the reduction of sedentary behaviour and inclusion of light physical activity.\u003c/p\u003e","manuscriptTitle":"Latent profiles of physical behaviour and their impact on physical fitness and function of Portuguese older adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-25 19:27:46","doi":"10.21203/rs.3.rs-4485059/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8027966a-5220-4c3c-ad03-f49a135dff12","owner":[],"postedDate":"June 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-05T10:51:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-25 19:27:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4485059","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4485059","identity":"rs-4485059","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}