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Reference Walking Speeds for Healthy Young Adults in Qatar: Moderating Effect of Obesity and Physical Activity:

Reference Walking Speeds for Healthy Young Adults in Qatar: Moderating Effect of Obesity and... Walking speed (WS) is considered an important indicator for overall health. Despite this, there is a paucity of data relating to WS values in the Arab region. The present study aims to establish preferred (PWS) and maximal walking speeds (MWS) in young adults in Qatar and examine how gender, body mass index, and physical activity (PA) components influence WS. One hundred ninety-six healthy participants (age: 22 ± 2 years; 60% females) performed a standardized walking test on a flat 10-m pathway, completed the short form of the International PA Questionnaire, and had their height and weight measured. PWS and MWS were normalized for height (rPWS and rMWS). Results. Females demonstrated slower PWS, MWS, and rMWS compared to males. Moreover, MWS and rMWS were lower in obese participants compared to underweight, normal weight and overweight individuals. There was a significant positive relationship only between vigorous PA and rPWS and rMWS. This is the first study to establish reference WS values for healthy young adults in Qatar. Overall, we demonstrated that WS was lower compared to similar adults worldwide. The established healthy walking values can serve as reference for clinical evaluations within Qatar. Future PA guidelines and public health interventions should focus on WS values. Keywords gait speed, obesity, vigorous physical activity, public health, Arab culture Qatar, more than 50% of the population do not engage in Introduction regular PA (Qatar National Physical Activity Guidelines, Walking is the most common form of physical activity (PA), 2021). These high levels of physical inactivity are due to a and it can be performed at either light, moderate or vigorous multitude of factors including cultural, social and environ- intensity (Ciprandi et al., 2017). Walking speed (WS) is con- mental factors (i.e., hot, humid desert climate). Indeed, sidered a robust measure for assessing and monitoring func- 44% of Qatari females achieve <5,000 steps per day tional status and overall health (Studenski et al., 2011; (Sayegh et al., 2016); despite the on-going community- Verghese et al., 2011). WS is a valid, reliable, and sensitive based walking program (i.e., step into health), an interven- measure (Goldberg & Schepens, 2011; Rydwik et al., 2012); tion to increase PA levels utilizing wearable technologies. for tests performed in both clinical and research settings Subsequently, as well as the environment affecting PA lev- (Graham et al., 2008; Peel et al., 2013). WS has been shown els, it may also affect WS (Levine & Norenzayan, 1999). to be predictive of many health outcomes (Middleton et al., Although PWS and MWS have previously been related to 2015). A high preferred walking speed (PWS) may also be factors such as maximal strength of lower extremities associated with adults meeting the recommended levels of (Bohannon, 1997) or obesity (Fernández Menéndez et al., PA (Ciprandi et al., 2017). In addition, maximal walking 2019), it is unclear how components of PA influence WS speed (MWS) is increasingly being investigated as a valu- outcome measures in healthy young adults. Despite this, able measure for clinical assessment of mobility function (Middleton et al., 2016). Physical Education Department, College of Education, Qatar University, Gender- and age-stratified WS reference (i.e., norma- Doha, Qatar tive) values are established for healthy adults from differ- Research & Scientific Support Department, Aspetar Orthopaedic and ent countries around the world, as summarized in a meta- Sports Medicine Hospital, FIFA Medical Center of Excellence, Doha, Qatar analytical study (Bohannon & Williams Andrews, 2011). Corresponding Author: Ethnic background, geographic, socio-economic, and/or Lina Majed, Physical Education Department, College of Education, Qatar environmental factors all affect WS (Al-Obaidi et al., University, Building I10, Al-Tarfa Street, Doha 2713, Qatar. Email: lina.majed@qu.edu.qa 2003; Levine & Norenzayan, 1999). Within the state of Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open Table 1. Participants’ Physical Characteristics. Female (n = 119) Male (n = 77) Total (n = 196) Age (years) 22 (1.94) 22 (2.12) 22 (2.02) Height (m) 1.60 (0.07) 1.78 (0.07)** 1.67 (0.11) Weight (kg) 63.8 (16.8) 80.0 (17.9)** 70.2 (18.9) −2 Body mass index BMI (kg m ) 24.77 (6.15) 25.21 (5.35) 24.94 (5.84) BMI Category: % (n) Underweight (BMI < 18.5) 8% (9) 3% (2) 6% (11) Normal weight (BMI = 18.5–24.9) 55% (66) 53% (41) 55% (107) Overweight (BMI = 25–29.9) 18% (21) 29% (22) 22% (43) Obese (BMI ≥ 30) 19% (23) 16% (12) 18% (35) Note. Values are reported as mean (standard deviation) unless otherwise stated. **Significant difference between gender (p < .001). only three studies have examined walking behaviors in the participants between the age of 18 to 26 years were included Gulf and Arab regions, and all of them were limited due to in the study. Exclusion criteria were defined as any past or small sample sizes [i.e., 15 females and 15 males from present disease (e.g., metabolic or cardiovascular), health Kuwait (Al-Obaidi et al., 2003); 17 males from Tunisia condition (e.g., neuromuscular, skeletal or cognitive) or (Dhahbi et al., 2014); nine males and nine females from injury that might interfere with the ability to walk normally. Qatar (Majed et al., 2020)]. In the recent study from Qatar, Physical characteristics are presented in Table 1. Prior to data Majed et al. (2020) revealed lower walking speeds for their collection, all participants signed an informed consent Qatari and Arab sample as compared to international nor- according to the university’s code of practice and ethics and mative values referenced in the literature. Although the to the Declaration of Helsinki. An institutional review board later study has the merit to be the first to explore walking approval was received before the experiment (QU-IRB 856- behavior in Qatar, it has done so in a controlled laboratory E/17). All experimental testing took place outdoors in setting on a motorized treadmill. February (average temperature = 20°C to 25 °C, humid- Given that >70% of the Qatari population is either “over- ity = 60%−75%) on the university’s campus. weight” or “obese” (Qatar Biobank 2016-2017), it could be Initially, body mass scales (GS 28, Beurer, Germany) expected that WS will be significantly lower than in other and a stadiometer (MZ10017, ADE, Germany) were used countries, especially considering the lack of PA and environ- for anthropometric assessments that followed the standards mental challenges. Establishing reference WS values is the of the International Society for the Advancement of first step in developing public health interventions and PA Kinanthropometry (ISAK) (Marfell-Jones et al., 2012). guidelines within the state of Qatar, particularly important Participants’ body mass and height were assessed while they given that the Qatar National Physical Activity Guidelines were barefoot and wearing minimal clothing. Measurements (2021) does not contain any information regarding the WS or were taken by trained research assistants that are ISAK certi- step cadence necessary to elicit positive health benefits. fied (level 1). Secondly, participants performed a standard- Therefore, the primary aim of the present study was to estab- ized walking test consisting of six walking trials on a 14 -m lish reference values for PWS and MWS in young male and non-slippery pathway marked by cones as visual targets female adults in Qatar, and examine the relationship between demonstrating its beginning and end (Middleton et al., 2015). WS and gender, body mass index (BMI) and PA. We hypoth- Two meters on each end of the pathway were dedicated for esized that (1) WS would be lower in the present sample as acceleration and deceleration phases for accurate speed mea- compared to international norms, (2) WS would be lower in surement (Middleton et al., 2015). A stopwatch served to obese participants as compared to normal weight subjects, determine the time needed to cross the intermediate 10 -m, (3) WS would be positively correlated to components of PA thus allowing for appropriate acceleration and deceleration due to their significant association with peripheral muscle phases (Middleton et al., 2015). The use of a marked walk- strength and functional capacity (Vardar-Yagli et al., 2015). way and a stopwatch have been shown to be valid and reli- able for WS testing (Adell et al., 2013; Castell et al., 2013; Puthoff & Saskowski, 2013), in particular pertaining to clini- Methods cal feasibility (Middleton et al., 2015). Participants were A total of 196 participants (age: 22 ± 2 years; 60% females) asked to walk at their PWS for three trials and at their maxi- were randomly recruited on Qatar University’s campus mal MWS for three additional trials. The following instruc- (Doha) from the student body to participate in the study. tions were provided for each condition respectively, “walk at Qatar University is the only public university in Qatar and your most comfortable pace” and “walk as fast as possible the biggest academic institution in the country. Only healthy and safely, but without running.” A demonstration was given Majed et al. 3 prior to the first trial. All trials were separated with a 20-sec- MWS, rMWS) between gender and BMI. The least squares ond rest interval. The time required to cover the intermediate mean test provided pairwise comparisons between the fixed 10-m was recorded. For the walking test, participants were effects. Normality and homogeneity of variance of the resid- wearing their usual comfortable clothing and footwear (i.e., uals were checked using quantile-quantile plots, and scatter no sandals, heels or traditional clothing such as abaya or plots respectively, and deemed plausible in each instance. thobe). Finally, PA levels were assessed using the self- The relationship between PA (walking, moderate, vigorous administered short form of the International Physical Activity and sedentary minutes) and each WS (PWS, rPWS, MWS, Questionnaire (IPAQ-SF) that was not only validated in rMWS) was assessed using a random coefficient model. Chi comparison to other self-reported physical activity question- square (χ ) tests were used to examine the association naires across 12 countries (Craig et al., 2003), but also between gender, BMI, and whether participants met the PA against the gold-standard doubly labeled water (Maddison guidelines, and WS (PWS, rPWS, MWS, rMWS). Cramer’s et al., 2007). Each participant was given a printed copy of the V was obtained in order to determine the strength of the asso- IPAQ-SF questionnaire and was asked to complete it while ciation, with the following criteria applied 0.00 to <0.10 seated as a last step of their participation. negligible association, 0.10 to <0.20 weak association, 0.20 Body mass index (BMI) was calculated as the ratio to <0.40 moderate association, 0.40 to <0.60 relatively between body mass (kg) and height squared (m ). A BMI cat- strong association, 0.60 to <0.80 strong association, 0.80 to egory was assigned to each participant following the World 1.00 very strong association (Rea & Parker, 2014). Data is −1 Health Organization classification (Table 1). WS (cm s ) reported as mean (±standard deviation) unless otherwise was calculated as the ratio between the covered distance (i.e., stated. Significance was accepted as p ≤ .05. 1,000 cm) and the mean time (in seconds) required to cover the distance. Relative PWS (rPWS) and MWS (rMWS) were Results calculated as the ratio of the mean speed of the three respec- tive trials and the individual body height (m). This measure Males were on average 16 kg heavier [t = 6.423, p < .001] used in a previous study limits the effect of height on WS and 0.18 m taller [t = 17.264, p < .001] than females. There (Al-Obaidi et al., 2003). were no differences for age or BMI (p ≥ .71). The percentage Data from IPAQ-SF was cleaned, outliers were removed of participants in each BMI category is presented in Table 1. and truncation rules applied according the IPAQ guidelines. Additionally, on average males completed more vigorous PA The variables used for this study were the reported time per (t = 2.466, p = .02) and walking (t = 4.287, p < .001), and 302 298 −1 week (minutes week ) spent in walking (low-intensity), had higher total EE (t = 4.418, p < .001) compared to moderate-intensity PA, vigorous-intensity PA, and sitting females. Results showed that 90% of females and 81% of (i.e., sedentary behavior). Weekly total energy expenditure males met the PA guidelines (i.e., ≥150 minutes of moderate −1 (MET-min week ) was calculated as the sum of weekly or vigorous PA per week). More details on PA levels are energy expenditure for each type of activity. This was com- shown in Table 2. puted as the product of the time spent per week (min- There was a significant main effect of gender for PWS −1 utes week ) in each activity and the corresponding multiple (f = 6.76, p = .01), MWS (f = 46.07, p < .001), and rMWS of the resting metabolic rate (MET-min), using 3.3 MET-min (f = 12.07, p = .001), and of BMI for MWS (f = 10.69, p < .001) for walking, 4 MET-min for moderate PA, and 8 MET-min and rMWS (f = 9.55, p < .001). Females demonstrated slower −1 for vigorous PA (Ainsworth et al., 2000). The resulting value PWS (f = 6.76, p = .01, 95% CI = −10 to −10 cm s ), MWS −1 −1 (MET-min week ) that corresponds to that of a 60 kg person (f = 46.0, p < .001, 95% CI = −20 to −40 cm s ), and rMWS −1 was then multiplied by each participant’s body weight and (f = 12.1, p = .001, 95% CI = −4 to −14 cm s ) compared to −1 divided by 60 to convert it into kcal week , as recommended males. Moreover, MWS and rMWS were lower in obese par- by the IPAQ guidelines for data processing and analysis. ticipants compared to underweight (p = .02, 95% CI = −2 to −1 −1 Statistical analyses were performed using the Statistical −33 cm s and p = .009, 95% CI = −3 to −21 cm s respec- −1 Package for the Social Sciences (SPSS) version 26 (IBM, tively), normal weight (p < .001, 95% CI = −17 to −29 cm s , −1 SPSS Inc, Chicago, IL, USA). GraphPad Prism 8 (GraphPad and p < .001, 95% CI = −9 to −19 cm s respectively) and −1 Software, CA, USA) was used to create Figure 1. Normality overweight (p < .001, 95% CI = −1 to −29 cm s and p = .001, −1 of the descriptives was verified using the Shapiro-Wilk test. 95% CI = −4 to −16 cm s respectively) individuals. There Descriptive analyses were performed for age and anthropo- was a significant relationship between vigorous minutes of metric measures (i.e., height, body mass and BMI) and PA PA and rPWS (p = .05) and rMWS (p = .001). Participants variables (i.e., walking, moderate- and vigorous-PA and sit- who engaged in more minutes of vigorous PA had a faster ting) for male and females separately. Independent t-tests rPWS and rMWS. Additionally, there was no association were used to analyze differences in physical characteristics between whether participants met the PA guidelines and 2 2 between males and females. Linear mixed models were used rPWS (χ = 0.49, V = 1.0) or rMWS (χ = 0.49, V = 1.0). to determine differences in walking speeds (PWS, rPWS, Individual data is shown in Figure 1. 4 SAGE Open Figure 1. Walking speeds for males and females, and by BMI category. Note. MWS = maximal walking speed; PWS = preferred walking speed; rMWS = relative maximal walking speed; rPWS = relative preferred walking speed; UW = underweight; NW = normal weight; OW = overweight; OB = obese. Table 2. Physical Activity Results From the IPAQ-SF. −1 Time spent per week (minutes week ) Total EE −1 Walk Mod PA Vig PA Sit (kcal week ) Females 150 (60–420) 120 (0–240) 0 (0–180) 360 (180–480) 1,769 (743–3,588) Males 300 (150–840) 90 (0–240) 120 (0–360) 420 (300–480) 4,875 (2,410–7,409) Total 210 (77–420) 90 (0–240) 0 (0–240) 360 (240–480) 2,555 (1,129–5,326) Note. Data are presented as median (interquartile range). Mod and Vig PA = moderate and vigorous physical activity; Total EE = weekly total energy expenditure. Majed et al. 5 −1 Table 3. Preferred Walking Speed (PWS, cm s ) Reference Values in Healthy Young Adults (20–29 Years) Worldwide Compared to Young Female (n = 119) and Male (n = 77) Adults From Qatar (18–26 Years). Stratified results by age (20–29 years) n Mean PWS (SD) Difference with Qatar Males Tunisia (Dhahbi et al., 2014) 18 120.0 (7.00) 11.06 Kuwait (Al-Obaidi et al., 2003) 15 121.7 (19.9) 9.36 Italy (Ble et al., 2005) 27 131.1 (19.7) −0.04 France (Delval et al., 2006) 11 135.3 (9.3) −4.24 USA (Goble et al., 2003) 20 138.0 (16.0) −6.94 USA (Bohannon, 1997) 15 139.3 (15.3) −8.24 Australia (Studenski et al., 2011) 10 141.0 (12.6) −9.94 Israel (Laufer, 2003) 14 146.5 (18.5) −15.44 UK (Button et al., 2005) 17 147.4 (13.6) −16.34 Females Kuwait Al-Obaidi et al. (2003) 15 108.2 (14.6) 14.86 Italy Ble et al. (2005) 24 126.6 (21.5) −3.54 USA Rogers et al. (2005) 10 135.0 (15.9) −11.94 Australia Lord et al. (1996) 21 138.0 (16.0) −14.94 USA Hansen et al. (2004) 12 137.0 (22.0) −13.94 USA Hollman et al. (2007) 10 138.7 (12.6) −15.64 USA Bohannon (1997) 22 140.7 (17.5) −17.64 Israel Laufer (2003) 15 144.5 (16.6) −21.44 UK Button et al. (2005) 22 144.8 (25.1) −21.74 UK Busse et al. (2006) 15 149.9 (18.9) −26.84 As cited in Bohannon and Williams Andrews (2011). the present study, males demonstrated greater engagement in Discussion vigorous PA and walking, and had higher total EE compared The present study is the first to establish normative values to females. Caution should be taken when interpreting these for WS in healthy young adults in Qatar. The main findings findings, given that both PA and body composition (i.e., indicated lower PWS for the present sample as compared to BMI) were not directly and/or objectively quantified in the global norms, and lower MWS for obese individuals com- present study. Future research employing objective and pared to all other BMI categories (Figure 1), partially sup- direct measures of PA (e.g., accelerometer and wearable porting hypotheses (1) and (2). Furthermore, participants technology), body composition (e.g., waist circumference, who engaged in more minutes of vigorous PA had a faster skinfolds) and strength measures, would be required in order rPWS and rMWS, accepting hypothesis (3). to ascertain the differences in PWS between males and On average, PWS in the present study was lower for females. −1 males (123.06 ± 21.30 cm s ) and particularly for females MWS is typically utilized and measured in older adults −1 (131.06 ± 13.83 cm s ) compared to worldwide data (please (Bohannon & Wang, 2019; Ng et al., 2013; Rantanen et al., refer to Table 3 for direct comparisons). Conversely, PWS 1998). While a very limited number of studies have exam- was higher for both males and females only when compared ined MWS in young adults worldwide, no studies have done to values reported from the Gulf Peninsula [i.e., Kuwait so in the Gulf Peninsula or Arab regions, making the com- (Al-Obaidi et al., 2003)] and Arab regions [i.e., Tunisia parison of data problematic. The MWS of males −1 −1 (Dhahbi et al., 2014)] (Table 3). Meta-analytical data showed (200.66 ± 32.87 cm s ) and females (170.01 ± 23.11 cm s ) −1 a global average difference in PWS of 1.70 cm s between in the present study were slightly higher (i.e., 8%) in com- males and females in their 20 seconds (Bohannon & Williams parison to normative values reported in a recent study from Andrews, 2011), while in the present study there was a the USA on adults (80 males and 179 females) of a similar −1 greater magnitude in gender difference (i.e., 8.0 cm s ), age range (Bohannon & Wang, 2019). Interestingly, in a which is in agreement with healthy young Kuwaiti (Al-Obaidi 1997 study investigating walking speed reference values in et al., 2003). These results may be partially explained by dif- the USA, Bohannon found MWS values that were about ferences in body composition, engagement in PA, or maxi- 37% to 57% faster for males and females respectively, as mal lower limb strength (Bohannon, 1997). Despite there compared to the recently reported values. Although both being no differences in BMI between males and females in studies present discrepancies in the sample size and the 6 SAGE Open protocol used to assess walking speed, the large difference in schools and workplaces within the state of Qatar, to establish MWS over the 22-year period might possibly reflect changes gender- and age-stratified normative values. Additionally, PA in other related factors in the community such as those was not measured objectively, and was only determined from related to obesity or fitness levels. Indeed, only the female the IPAQ-SF. Future studies should employ accelerometers sample in the 2019 study had a higher average BMI (i.e., and/or other wearable technologies to accurately quantify PA, −2 27.78 kg m ) as compared to that of the 1997 study (i.e., and provide additional variables such as step count, and −2 21.85 kg m ). In the present study, obese participants showed cadence. Furthermore, direct quantification of body composi- lower MWS compared to all other BMI categories in the tion should be employed in future studies, as BMI, utilized in present study (Figure 1). This finding supports previous the present study, does not provide information on the distribu- studies (Fernández Menéndez et al., 2019; Liu & Yang, tion or type of tissue (i.e., lean muscle mass or adipose tissue). 2017), indicating that obese adults prefer to walk slower pos- Nevertheless, compared to previous research from other coun- sibly in an effort to decrease the energy expenditure and tries (Table 3) and from Qatar (Majed et al., 2020), the sample increase comfort. The slower walking speed found in obese size was larger, and the simple walking test employed can be individuals is expected to reduce the energy expenditure, easily replicated in a clinical setting, which are considered as joint loads (DeVita & Hortobágyi, 2003), mechanical work strengths of the current study. (Malatesta et al., 2009), and/or ground reaction forces (Browning & Kram, 2007) resulting from the additional Conclusions mass carried against gravity. Conversely, some studies found Establishing WS reference values can facilitate clinical that people with obesity walk at similar speeds than normal- comparisons for rehabilitation and functional assessment. weight individuals (Browning & Kram, 2005; Rosso et al., Moreover, reference values are an important first step in 2019). Variation in findings are presently unclear. However, developing public health interventions and PA guidelines given that MWS (i.e., step cadence) has been linked to mor- within the state of Qatar, particularly essential given that bidity and mortality, and that >70% of Qatari adults are the first edition of the Qatar NPAG does not contain any overweight or obese, it is essential to establish age- and gen- information regarding the WS or step cadence necessary to der-stratified WS across the state of Qatar, as this is the first elicit positive health benefits. Both gender and obesity step to improving the Qatar NPAG, and developing public appear to affect MWS and PWS. Walking is the most popu- health interventions. lar form of exercise, and is a culturally and socially accept- Slower PWS and MWS in the present study and existing able form of exercise in the current population. Subsequently, data within the Arab region, compared to worldwide data, it is important that future research establishes gender- and may be due to geographic, environmental, and/or cultural age-stratified WS normative values across the state of factors (Levine & Norenzayan, 1999). Cities with the slow- Qatar, and provides specific public health recommenda- est WS were more likely to have warm climates and empha- tions and interventions related to WS (i.e., step cadence, size collectivistic culture. Additionally, MWS was found to step count), to improve the existing community-based pro- correlate with maximal lower limb strength in disabled grams. Additionally, in a community setting, both values women (Rantanen et al., 1998) and in healthy young adults provide valuable information regarding, for example, safe (Bohannon, 1997). Given that 83% of the Qatari population crossing of streets where safety margins of signal timings participate in little or no PA, and maximal lower limb strength can be optimized for pedestrians. is likely associated with PA, this could partially explain the findings. In support of this postulation, the present study Acknowledgments showed that participants who engaged in greater amounts of vigorous PA had higher PWS and MWS. However, causal The authors are grateful to Mohammad Prince, Bahaa Aboghaba, Aya Sewefy, Dhoha Abdelrahman, Somaia Gabr, and Rana Marzuq inference cannot be made at this stage. Further research for their help in the data collection and to all participants who vol- examining the exact mechanisms related to MWS would unteered in the study. need to be performed. Nevertheless, this study highlights the importance of utilizing walking outcome measures at a pop- Declaration of Conflicting Interests ulation level to improve the NPAG and future public health interventions across the state of Qatar. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Caution must be taken when interpreting these results, as the sample was homogeneous (i.e., from the university cam- pus only), and therefore, these results may not be representa- Funding tive of the Qatari population as a whole. The authors speculate The author(s) disclosed receipt of the following financial support that those who volunteered for the study were the more “health for the research, authorship, and/or publication of this article: This conscious” individuals from the university. Future studies work was supported by a Qatar University (http://www.qu.edu.qa) should measure WS, step cadence and step count across all grant [QUST-1-CAS-2018-21] received by LM. The funders had Majed et al. 7 no role in study design, data collection and analysis, decision to Busse, M. E., Wiles, C. M., & van Deursen, R. W. (2006). Community publish, or preparation of the manuscript. The findings achieved walking activity in neurological disorders with leg weakness. herein are solely the responsibility of the authors. Open access Journal of Neurology, Neurosurgery, and Psychiatry, 77(3), funding was provided by the Qatar National Library. 359–362. https://doi.org/10.1136/jnnp.2005.074294 Button, K., Van Deursen, R., & Price, P. (2005). Measurement of func- tional recovery in individuals with acute anterior cruciate ligament Ethics Statement rupture. British Journal of Sports Medicine, 39(11), 866–871. The study was approved by Qatar University’s Institutional Review Castell, M. V., Sánchez, M., Julián, R., Queipo, R., Martín, S., & Board (IRB) with the following approval number: QU-IRB 856- Otero, Á. (2013). Frailty prevalence and slow walking speed in E/17. A written informed consent was obtained from all participants persons age 65 and older: Implications for primary care. BMC prior to the start of the study. Family Practice, 14, 86. https://doi.org/10.1186/1471-2296-14-86 Ciprandi, D., Bertozzi, F., Zago, M., Ferreira, C. L. P., Boari, ORCID iD G., Sforza, C., & Galvani, C. (2017). Study of the associa- Lina Majed https://orcid.org/0000-0003-0945-8344 tion between gait variability and physical activity. European Review of Aging and Physical Activity, 14, 19. https://doi. org/10.1186/s11556-017-0188-0 References Craig, C. L., Marshall, A. L., Sjöström, M., Bauman, A. E., Booth, Adell, E., Wehmhörner, S., & Rydwik, E. (2013). The test-retest M. L., Ainsworth, B. 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Relationship of clinic- siveness of gait speed, five times sit to stand, and hand grip based gait speed measurement to limitations in community- strength for patients in cardiac rehabilitation. Cardiopulmonary based activities in older adults. Archives of Physical Medicine Physical Therapy Journal, 24(1), 31–37. https://www.ncbi. and Rehabilitation, 92(5), 844–846. https://doi.org/10.1016/j. nlm.nih.gov/pubmed/23754937 apmr.2010.12.030 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png SAGE Open SAGE

Reference Walking Speeds for Healthy Young Adults in Qatar: Moderating Effect of Obesity and Physical Activity:

SAGE Open , Volume 12 (1): 1 – Mar 2, 2022

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Abstract

Walking speed (WS) is considered an important indicator for overall health. Despite this, there is a paucity of data relating to WS values in the Arab region. The present study aims to establish preferred (PWS) and maximal walking speeds (MWS) in young adults in Qatar and examine how gender, body mass index, and physical activity (PA) components influence WS. One hundred ninety-six healthy participants (age: 22 ± 2 years; 60% females) performed a standardized walking test on a flat 10-m pathway, completed the short form of the International PA Questionnaire, and had their height and weight measured. PWS and MWS were normalized for height (rPWS and rMWS). Results. Females demonstrated slower PWS, MWS, and rMWS compared to males. Moreover, MWS and rMWS were lower in obese participants compared to underweight, normal weight and overweight individuals. There was a significant positive relationship only between vigorous PA and rPWS and rMWS. This is the first study to establish reference WS values for healthy young adults in Qatar. Overall, we demonstrated that WS was lower compared to similar adults worldwide. The established healthy walking values can serve as reference for clinical evaluations within Qatar. Future PA guidelines and public health interventions should focus on WS values. Keywords gait speed, obesity, vigorous physical activity, public health, Arab culture Qatar, more than 50% of the population do not engage in Introduction regular PA (Qatar National Physical Activity Guidelines, Walking is the most common form of physical activity (PA), 2021). These high levels of physical inactivity are due to a and it can be performed at either light, moderate or vigorous multitude of factors including cultural, social and environ- intensity (Ciprandi et al., 2017). Walking speed (WS) is con- mental factors (i.e., hot, humid desert climate). Indeed, sidered a robust measure for assessing and monitoring func- 44% of Qatari females achieve <5,000 steps per day tional status and overall health (Studenski et al., 2011; (Sayegh et al., 2016); despite the on-going community- Verghese et al., 2011). WS is a valid, reliable, and sensitive based walking program (i.e., step into health), an interven- measure (Goldberg & Schepens, 2011; Rydwik et al., 2012); tion to increase PA levels utilizing wearable technologies. for tests performed in both clinical and research settings Subsequently, as well as the environment affecting PA lev- (Graham et al., 2008; Peel et al., 2013). WS has been shown els, it may also affect WS (Levine & Norenzayan, 1999). to be predictive of many health outcomes (Middleton et al., Although PWS and MWS have previously been related to 2015). A high preferred walking speed (PWS) may also be factors such as maximal strength of lower extremities associated with adults meeting the recommended levels of (Bohannon, 1997) or obesity (Fernández Menéndez et al., PA (Ciprandi et al., 2017). In addition, maximal walking 2019), it is unclear how components of PA influence WS speed (MWS) is increasingly being investigated as a valu- outcome measures in healthy young adults. Despite this, able measure for clinical assessment of mobility function (Middleton et al., 2016). Physical Education Department, College of Education, Qatar University, Gender- and age-stratified WS reference (i.e., norma- Doha, Qatar tive) values are established for healthy adults from differ- Research & Scientific Support Department, Aspetar Orthopaedic and ent countries around the world, as summarized in a meta- Sports Medicine Hospital, FIFA Medical Center of Excellence, Doha, Qatar analytical study (Bohannon & Williams Andrews, 2011). Corresponding Author: Ethnic background, geographic, socio-economic, and/or Lina Majed, Physical Education Department, College of Education, Qatar environmental factors all affect WS (Al-Obaidi et al., University, Building I10, Al-Tarfa Street, Doha 2713, Qatar. Email: lina.majed@qu.edu.qa 2003; Levine & Norenzayan, 1999). Within the state of Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open Table 1. Participants’ Physical Characteristics. Female (n = 119) Male (n = 77) Total (n = 196) Age (years) 22 (1.94) 22 (2.12) 22 (2.02) Height (m) 1.60 (0.07) 1.78 (0.07)** 1.67 (0.11) Weight (kg) 63.8 (16.8) 80.0 (17.9)** 70.2 (18.9) −2 Body mass index BMI (kg m ) 24.77 (6.15) 25.21 (5.35) 24.94 (5.84) BMI Category: % (n) Underweight (BMI < 18.5) 8% (9) 3% (2) 6% (11) Normal weight (BMI = 18.5–24.9) 55% (66) 53% (41) 55% (107) Overweight (BMI = 25–29.9) 18% (21) 29% (22) 22% (43) Obese (BMI ≥ 30) 19% (23) 16% (12) 18% (35) Note. Values are reported as mean (standard deviation) unless otherwise stated. **Significant difference between gender (p < .001). only three studies have examined walking behaviors in the participants between the age of 18 to 26 years were included Gulf and Arab regions, and all of them were limited due to in the study. Exclusion criteria were defined as any past or small sample sizes [i.e., 15 females and 15 males from present disease (e.g., metabolic or cardiovascular), health Kuwait (Al-Obaidi et al., 2003); 17 males from Tunisia condition (e.g., neuromuscular, skeletal or cognitive) or (Dhahbi et al., 2014); nine males and nine females from injury that might interfere with the ability to walk normally. Qatar (Majed et al., 2020)]. In the recent study from Qatar, Physical characteristics are presented in Table 1. Prior to data Majed et al. (2020) revealed lower walking speeds for their collection, all participants signed an informed consent Qatari and Arab sample as compared to international nor- according to the university’s code of practice and ethics and mative values referenced in the literature. Although the to the Declaration of Helsinki. An institutional review board later study has the merit to be the first to explore walking approval was received before the experiment (QU-IRB 856- behavior in Qatar, it has done so in a controlled laboratory E/17). All experimental testing took place outdoors in setting on a motorized treadmill. February (average temperature = 20°C to 25 °C, humid- Given that >70% of the Qatari population is either “over- ity = 60%−75%) on the university’s campus. weight” or “obese” (Qatar Biobank 2016-2017), it could be Initially, body mass scales (GS 28, Beurer, Germany) expected that WS will be significantly lower than in other and a stadiometer (MZ10017, ADE, Germany) were used countries, especially considering the lack of PA and environ- for anthropometric assessments that followed the standards mental challenges. Establishing reference WS values is the of the International Society for the Advancement of first step in developing public health interventions and PA Kinanthropometry (ISAK) (Marfell-Jones et al., 2012). guidelines within the state of Qatar, particularly important Participants’ body mass and height were assessed while they given that the Qatar National Physical Activity Guidelines were barefoot and wearing minimal clothing. Measurements (2021) does not contain any information regarding the WS or were taken by trained research assistants that are ISAK certi- step cadence necessary to elicit positive health benefits. fied (level 1). Secondly, participants performed a standard- Therefore, the primary aim of the present study was to estab- ized walking test consisting of six walking trials on a 14 -m lish reference values for PWS and MWS in young male and non-slippery pathway marked by cones as visual targets female adults in Qatar, and examine the relationship between demonstrating its beginning and end (Middleton et al., 2015). WS and gender, body mass index (BMI) and PA. We hypoth- Two meters on each end of the pathway were dedicated for esized that (1) WS would be lower in the present sample as acceleration and deceleration phases for accurate speed mea- compared to international norms, (2) WS would be lower in surement (Middleton et al., 2015). A stopwatch served to obese participants as compared to normal weight subjects, determine the time needed to cross the intermediate 10 -m, (3) WS would be positively correlated to components of PA thus allowing for appropriate acceleration and deceleration due to their significant association with peripheral muscle phases (Middleton et al., 2015). The use of a marked walk- strength and functional capacity (Vardar-Yagli et al., 2015). way and a stopwatch have been shown to be valid and reli- able for WS testing (Adell et al., 2013; Castell et al., 2013; Puthoff & Saskowski, 2013), in particular pertaining to clini- Methods cal feasibility (Middleton et al., 2015). Participants were A total of 196 participants (age: 22 ± 2 years; 60% females) asked to walk at their PWS for three trials and at their maxi- were randomly recruited on Qatar University’s campus mal MWS for three additional trials. The following instruc- (Doha) from the student body to participate in the study. tions were provided for each condition respectively, “walk at Qatar University is the only public university in Qatar and your most comfortable pace” and “walk as fast as possible the biggest academic institution in the country. Only healthy and safely, but without running.” A demonstration was given Majed et al. 3 prior to the first trial. All trials were separated with a 20-sec- MWS, rMWS) between gender and BMI. The least squares ond rest interval. The time required to cover the intermediate mean test provided pairwise comparisons between the fixed 10-m was recorded. For the walking test, participants were effects. Normality and homogeneity of variance of the resid- wearing their usual comfortable clothing and footwear (i.e., uals were checked using quantile-quantile plots, and scatter no sandals, heels or traditional clothing such as abaya or plots respectively, and deemed plausible in each instance. thobe). Finally, PA levels were assessed using the self- The relationship between PA (walking, moderate, vigorous administered short form of the International Physical Activity and sedentary minutes) and each WS (PWS, rPWS, MWS, Questionnaire (IPAQ-SF) that was not only validated in rMWS) was assessed using a random coefficient model. Chi comparison to other self-reported physical activity question- square (χ ) tests were used to examine the association naires across 12 countries (Craig et al., 2003), but also between gender, BMI, and whether participants met the PA against the gold-standard doubly labeled water (Maddison guidelines, and WS (PWS, rPWS, MWS, rMWS). Cramer’s et al., 2007). Each participant was given a printed copy of the V was obtained in order to determine the strength of the asso- IPAQ-SF questionnaire and was asked to complete it while ciation, with the following criteria applied 0.00 to <0.10 seated as a last step of their participation. negligible association, 0.10 to <0.20 weak association, 0.20 Body mass index (BMI) was calculated as the ratio to <0.40 moderate association, 0.40 to <0.60 relatively between body mass (kg) and height squared (m ). A BMI cat- strong association, 0.60 to <0.80 strong association, 0.80 to egory was assigned to each participant following the World 1.00 very strong association (Rea & Parker, 2014). Data is −1 Health Organization classification (Table 1). WS (cm s ) reported as mean (±standard deviation) unless otherwise was calculated as the ratio between the covered distance (i.e., stated. Significance was accepted as p ≤ .05. 1,000 cm) and the mean time (in seconds) required to cover the distance. Relative PWS (rPWS) and MWS (rMWS) were Results calculated as the ratio of the mean speed of the three respec- tive trials and the individual body height (m). This measure Males were on average 16 kg heavier [t = 6.423, p < .001] used in a previous study limits the effect of height on WS and 0.18 m taller [t = 17.264, p < .001] than females. There (Al-Obaidi et al., 2003). were no differences for age or BMI (p ≥ .71). The percentage Data from IPAQ-SF was cleaned, outliers were removed of participants in each BMI category is presented in Table 1. and truncation rules applied according the IPAQ guidelines. Additionally, on average males completed more vigorous PA The variables used for this study were the reported time per (t = 2.466, p = .02) and walking (t = 4.287, p < .001), and 302 298 −1 week (minutes week ) spent in walking (low-intensity), had higher total EE (t = 4.418, p < .001) compared to moderate-intensity PA, vigorous-intensity PA, and sitting females. Results showed that 90% of females and 81% of (i.e., sedentary behavior). Weekly total energy expenditure males met the PA guidelines (i.e., ≥150 minutes of moderate −1 (MET-min week ) was calculated as the sum of weekly or vigorous PA per week). More details on PA levels are energy expenditure for each type of activity. This was com- shown in Table 2. puted as the product of the time spent per week (min- There was a significant main effect of gender for PWS −1 utes week ) in each activity and the corresponding multiple (f = 6.76, p = .01), MWS (f = 46.07, p < .001), and rMWS of the resting metabolic rate (MET-min), using 3.3 MET-min (f = 12.07, p = .001), and of BMI for MWS (f = 10.69, p < .001) for walking, 4 MET-min for moderate PA, and 8 MET-min and rMWS (f = 9.55, p < .001). Females demonstrated slower −1 for vigorous PA (Ainsworth et al., 2000). The resulting value PWS (f = 6.76, p = .01, 95% CI = −10 to −10 cm s ), MWS −1 −1 (MET-min week ) that corresponds to that of a 60 kg person (f = 46.0, p < .001, 95% CI = −20 to −40 cm s ), and rMWS −1 was then multiplied by each participant’s body weight and (f = 12.1, p = .001, 95% CI = −4 to −14 cm s ) compared to −1 divided by 60 to convert it into kcal week , as recommended males. Moreover, MWS and rMWS were lower in obese par- by the IPAQ guidelines for data processing and analysis. ticipants compared to underweight (p = .02, 95% CI = −2 to −1 −1 Statistical analyses were performed using the Statistical −33 cm s and p = .009, 95% CI = −3 to −21 cm s respec- −1 Package for the Social Sciences (SPSS) version 26 (IBM, tively), normal weight (p < .001, 95% CI = −17 to −29 cm s , −1 SPSS Inc, Chicago, IL, USA). GraphPad Prism 8 (GraphPad and p < .001, 95% CI = −9 to −19 cm s respectively) and −1 Software, CA, USA) was used to create Figure 1. Normality overweight (p < .001, 95% CI = −1 to −29 cm s and p = .001, −1 of the descriptives was verified using the Shapiro-Wilk test. 95% CI = −4 to −16 cm s respectively) individuals. There Descriptive analyses were performed for age and anthropo- was a significant relationship between vigorous minutes of metric measures (i.e., height, body mass and BMI) and PA PA and rPWS (p = .05) and rMWS (p = .001). Participants variables (i.e., walking, moderate- and vigorous-PA and sit- who engaged in more minutes of vigorous PA had a faster ting) for male and females separately. Independent t-tests rPWS and rMWS. Additionally, there was no association were used to analyze differences in physical characteristics between whether participants met the PA guidelines and 2 2 between males and females. Linear mixed models were used rPWS (χ = 0.49, V = 1.0) or rMWS (χ = 0.49, V = 1.0). to determine differences in walking speeds (PWS, rPWS, Individual data is shown in Figure 1. 4 SAGE Open Figure 1. Walking speeds for males and females, and by BMI category. Note. MWS = maximal walking speed; PWS = preferred walking speed; rMWS = relative maximal walking speed; rPWS = relative preferred walking speed; UW = underweight; NW = normal weight; OW = overweight; OB = obese. Table 2. Physical Activity Results From the IPAQ-SF. −1 Time spent per week (minutes week ) Total EE −1 Walk Mod PA Vig PA Sit (kcal week ) Females 150 (60–420) 120 (0–240) 0 (0–180) 360 (180–480) 1,769 (743–3,588) Males 300 (150–840) 90 (0–240) 120 (0–360) 420 (300–480) 4,875 (2,410–7,409) Total 210 (77–420) 90 (0–240) 0 (0–240) 360 (240–480) 2,555 (1,129–5,326) Note. Data are presented as median (interquartile range). Mod and Vig PA = moderate and vigorous physical activity; Total EE = weekly total energy expenditure. Majed et al. 5 −1 Table 3. Preferred Walking Speed (PWS, cm s ) Reference Values in Healthy Young Adults (20–29 Years) Worldwide Compared to Young Female (n = 119) and Male (n = 77) Adults From Qatar (18–26 Years). Stratified results by age (20–29 years) n Mean PWS (SD) Difference with Qatar Males Tunisia (Dhahbi et al., 2014) 18 120.0 (7.00) 11.06 Kuwait (Al-Obaidi et al., 2003) 15 121.7 (19.9) 9.36 Italy (Ble et al., 2005) 27 131.1 (19.7) −0.04 France (Delval et al., 2006) 11 135.3 (9.3) −4.24 USA (Goble et al., 2003) 20 138.0 (16.0) −6.94 USA (Bohannon, 1997) 15 139.3 (15.3) −8.24 Australia (Studenski et al., 2011) 10 141.0 (12.6) −9.94 Israel (Laufer, 2003) 14 146.5 (18.5) −15.44 UK (Button et al., 2005) 17 147.4 (13.6) −16.34 Females Kuwait Al-Obaidi et al. (2003) 15 108.2 (14.6) 14.86 Italy Ble et al. (2005) 24 126.6 (21.5) −3.54 USA Rogers et al. (2005) 10 135.0 (15.9) −11.94 Australia Lord et al. (1996) 21 138.0 (16.0) −14.94 USA Hansen et al. (2004) 12 137.0 (22.0) −13.94 USA Hollman et al. (2007) 10 138.7 (12.6) −15.64 USA Bohannon (1997) 22 140.7 (17.5) −17.64 Israel Laufer (2003) 15 144.5 (16.6) −21.44 UK Button et al. (2005) 22 144.8 (25.1) −21.74 UK Busse et al. (2006) 15 149.9 (18.9) −26.84 As cited in Bohannon and Williams Andrews (2011). the present study, males demonstrated greater engagement in Discussion vigorous PA and walking, and had higher total EE compared The present study is the first to establish normative values to females. Caution should be taken when interpreting these for WS in healthy young adults in Qatar. The main findings findings, given that both PA and body composition (i.e., indicated lower PWS for the present sample as compared to BMI) were not directly and/or objectively quantified in the global norms, and lower MWS for obese individuals com- present study. Future research employing objective and pared to all other BMI categories (Figure 1), partially sup- direct measures of PA (e.g., accelerometer and wearable porting hypotheses (1) and (2). Furthermore, participants technology), body composition (e.g., waist circumference, who engaged in more minutes of vigorous PA had a faster skinfolds) and strength measures, would be required in order rPWS and rMWS, accepting hypothesis (3). to ascertain the differences in PWS between males and On average, PWS in the present study was lower for females. −1 males (123.06 ± 21.30 cm s ) and particularly for females MWS is typically utilized and measured in older adults −1 (131.06 ± 13.83 cm s ) compared to worldwide data (please (Bohannon & Wang, 2019; Ng et al., 2013; Rantanen et al., refer to Table 3 for direct comparisons). Conversely, PWS 1998). While a very limited number of studies have exam- was higher for both males and females only when compared ined MWS in young adults worldwide, no studies have done to values reported from the Gulf Peninsula [i.e., Kuwait so in the Gulf Peninsula or Arab regions, making the com- (Al-Obaidi et al., 2003)] and Arab regions [i.e., Tunisia parison of data problematic. The MWS of males −1 −1 (Dhahbi et al., 2014)] (Table 3). Meta-analytical data showed (200.66 ± 32.87 cm s ) and females (170.01 ± 23.11 cm s ) −1 a global average difference in PWS of 1.70 cm s between in the present study were slightly higher (i.e., 8%) in com- males and females in their 20 seconds (Bohannon & Williams parison to normative values reported in a recent study from Andrews, 2011), while in the present study there was a the USA on adults (80 males and 179 females) of a similar −1 greater magnitude in gender difference (i.e., 8.0 cm s ), age range (Bohannon & Wang, 2019). Interestingly, in a which is in agreement with healthy young Kuwaiti (Al-Obaidi 1997 study investigating walking speed reference values in et al., 2003). These results may be partially explained by dif- the USA, Bohannon found MWS values that were about ferences in body composition, engagement in PA, or maxi- 37% to 57% faster for males and females respectively, as mal lower limb strength (Bohannon, 1997). Despite there compared to the recently reported values. Although both being no differences in BMI between males and females in studies present discrepancies in the sample size and the 6 SAGE Open protocol used to assess walking speed, the large difference in schools and workplaces within the state of Qatar, to establish MWS over the 22-year period might possibly reflect changes gender- and age-stratified normative values. Additionally, PA in other related factors in the community such as those was not measured objectively, and was only determined from related to obesity or fitness levels. Indeed, only the female the IPAQ-SF. Future studies should employ accelerometers sample in the 2019 study had a higher average BMI (i.e., and/or other wearable technologies to accurately quantify PA, −2 27.78 kg m ) as compared to that of the 1997 study (i.e., and provide additional variables such as step count, and −2 21.85 kg m ). In the present study, obese participants showed cadence. Furthermore, direct quantification of body composi- lower MWS compared to all other BMI categories in the tion should be employed in future studies, as BMI, utilized in present study (Figure 1). This finding supports previous the present study, does not provide information on the distribu- studies (Fernández Menéndez et al., 2019; Liu & Yang, tion or type of tissue (i.e., lean muscle mass or adipose tissue). 2017), indicating that obese adults prefer to walk slower pos- Nevertheless, compared to previous research from other coun- sibly in an effort to decrease the energy expenditure and tries (Table 3) and from Qatar (Majed et al., 2020), the sample increase comfort. The slower walking speed found in obese size was larger, and the simple walking test employed can be individuals is expected to reduce the energy expenditure, easily replicated in a clinical setting, which are considered as joint loads (DeVita & Hortobágyi, 2003), mechanical work strengths of the current study. (Malatesta et al., 2009), and/or ground reaction forces (Browning & Kram, 2007) resulting from the additional Conclusions mass carried against gravity. Conversely, some studies found Establishing WS reference values can facilitate clinical that people with obesity walk at similar speeds than normal- comparisons for rehabilitation and functional assessment. weight individuals (Browning & Kram, 2005; Rosso et al., Moreover, reference values are an important first step in 2019). Variation in findings are presently unclear. However, developing public health interventions and PA guidelines given that MWS (i.e., step cadence) has been linked to mor- within the state of Qatar, particularly essential given that bidity and mortality, and that >70% of Qatari adults are the first edition of the Qatar NPAG does not contain any overweight or obese, it is essential to establish age- and gen- information regarding the WS or step cadence necessary to der-stratified WS across the state of Qatar, as this is the first elicit positive health benefits. Both gender and obesity step to improving the Qatar NPAG, and developing public appear to affect MWS and PWS. Walking is the most popu- health interventions. lar form of exercise, and is a culturally and socially accept- Slower PWS and MWS in the present study and existing able form of exercise in the current population. Subsequently, data within the Arab region, compared to worldwide data, it is important that future research establishes gender- and may be due to geographic, environmental, and/or cultural age-stratified WS normative values across the state of factors (Levine & Norenzayan, 1999). Cities with the slow- Qatar, and provides specific public health recommenda- est WS were more likely to have warm climates and empha- tions and interventions related to WS (i.e., step cadence, size collectivistic culture. Additionally, MWS was found to step count), to improve the existing community-based pro- correlate with maximal lower limb strength in disabled grams. Additionally, in a community setting, both values women (Rantanen et al., 1998) and in healthy young adults provide valuable information regarding, for example, safe (Bohannon, 1997). Given that 83% of the Qatari population crossing of streets where safety margins of signal timings participate in little or no PA, and maximal lower limb strength can be optimized for pedestrians. is likely associated with PA, this could partially explain the findings. In support of this postulation, the present study Acknowledgments showed that participants who engaged in greater amounts of vigorous PA had higher PWS and MWS. However, causal The authors are grateful to Mohammad Prince, Bahaa Aboghaba, Aya Sewefy, Dhoha Abdelrahman, Somaia Gabr, and Rana Marzuq inference cannot be made at this stage. Further research for their help in the data collection and to all participants who vol- examining the exact mechanisms related to MWS would unteered in the study. need to be performed. Nevertheless, this study highlights the importance of utilizing walking outcome measures at a pop- Declaration of Conflicting Interests ulation level to improve the NPAG and future public health interventions across the state of Qatar. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Caution must be taken when interpreting these results, as the sample was homogeneous (i.e., from the university cam- pus only), and therefore, these results may not be representa- Funding tive of the Qatari population as a whole. The authors speculate The author(s) disclosed receipt of the following financial support that those who volunteered for the study were the more “health for the research, authorship, and/or publication of this article: This conscious” individuals from the university. Future studies work was supported by a Qatar University (http://www.qu.edu.qa) should measure WS, step cadence and step count across all grant [QUST-1-CAS-2018-21] received by LM. The funders had Majed et al. 7 no role in study design, data collection and analysis, decision to Busse, M. E., Wiles, C. M., & van Deursen, R. W. (2006). Community publish, or preparation of the manuscript. The findings achieved walking activity in neurological disorders with leg weakness. herein are solely the responsibility of the authors. Open access Journal of Neurology, Neurosurgery, and Psychiatry, 77(3), funding was provided by the Qatar National Library. 359–362. https://doi.org/10.1136/jnnp.2005.074294 Button, K., Van Deursen, R., & Price, P. (2005). Measurement of func- tional recovery in individuals with acute anterior cruciate ligament Ethics Statement rupture. British Journal of Sports Medicine, 39(11), 866–871. The study was approved by Qatar University’s Institutional Review Castell, M. 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Journal

SAGE OpenSAGE

Published: Mar 2, 2022

Keywords: gait speed; obesity; vigorous physical activity; public health; Arab culture

References