Objectively quantified physical activity and sedentary behaviour in a young UAE population.

OBJECTIVES: There is a lack of public awareness of the importance of engaging in physical activity (PA) in the United Arab Emirates (UAE). Nearly 58% of the UAE adult population self-reports as being physically inactive although little accelerometer data currently exists. The aim of this study was to obtain the first dataset that objectively quantifies PA and sedentary behaviour (SB) in young UAE adults.
METHODS: This cross-sectional study recruited 140 university students. Body composition and accelerometry was assessed using a Tanita body composition analyser and ActiGraph accelerometer. Differences (p≤0.05) between gender (male vs female) and body mass index (normal vs overweight/obese) were determined using independent samples t-tests and χ2 tests for nominal variables.
RESULTS: Both males and females spent high amounts of time in SB, encompassing ~80% of waking hours. PA was primarily light intensity (14.1%), although males spent significantly greater time in moderate-to-vigorous intensity activity. Moreover, 50% of males compared with 76.6% of females were classified as sedentary/low active according to daily step counts.
CONCLUSION: Our data provide evidence of high levels of SB among young adults in the UAE with PA being predominantly light intensity, therefore, both PA and SB should be carefully monitored in this country. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Both young females and males in the United Arab Emirates typically spend over 12 hours/day being sedentary, representing over 80% of their waking day.

Many individuals exceeded the new recommended physical activity guidelines containing no minimum moderate-to vigorous activity bout lengths while very few individuals met the older obsolete physical activity guidelines requiring moderate-to-vigorous activity to be completed in at least 10 min bouts.

In terms of daily step count categories, more females versus males were classified as either ‘sedentary’ or ‘low active’.

Introduction

Non-communicable diseases are the leading causes of morbidity and mortality.1 Lifestyle factors, such as reduced physical activity (PA) and increased sedentary behaviour (SB), are inextricably linked to these diseases.2 PA involves any activities which raise energy expenditure >1.5 metabolic equivalent of tasks (METs).3 4 Adult PA recommendations advise ≥150 min/week of moderate-vigorous intensity PA (MVPA).5 Physically inactive individuals not meeting the PA recommendations have an elevated risk of disease.6 More recently, SB has been distinguished from physical inactivity, and is characterised by very low energy expenditure (<1.5 METs) involving sitting or lying.7 Although no definitive SB guidelines exist, evidence suggests SB is also an independent risk factor.8

Although physical inactivity is globally prevalent,9 there is a lack of public awareness on the benefits of PA in the United Arab Emirates (UAE). Nearly 58% of the UAE adult population are physically inactive,10 with adult overweight/obesity prevalence ~71%.11 Indeed, the UAE has seen huge economic and industrial growth accompanied by considerable lifestyle changes in the last decades.12 In 18–24 year olds, only 19.1% of males and 28.6% of females reported meeting PA recommendations.10 A meta-analysis in UAE adolescents who self-reported PA revealed that ~75% had little-to-no involvement in PA.13 Current studies which have investigated PA in the UAE have depended on questionnaires which may not fully capture PA.14 The main issue with self-reporting is often social desirability bias or sometimes recall bias that may result in over-reporting. Hence, using measurement tools such as accelerometers could generate estimates that are more accurate as they can record intensity and volume of PA, as well as SB and step counts.15

Therefore, this study aimed to use accelerometers to objectively quantify PA and SB in a young adult UAE population and explore differences in PA and SB between genders and body mass index (BMI) categories.

Methods

Participants

On obtaining ethical approval (IRB 296) and informed consent, a total of 140 students (63 males and 77 females) attending the American University of Sharjah volunteered to participate in this study. Eligibility criteria included: students aged ≥17 years old; no underlying medical conditions which may interfere with the study design (eg, ambulatory, cardiac or muscle issues); and being able to provide written informed consent. This cross-sectional study took place from September 2016 to March 2018 to account for seasonal variation in the UAE and included students from various ethnic backgrounds, primarily of Arab descent. There was no limit on gender or minority status.

Data collection

Participants had their body composition analysed using a segmental body composition analyser device (Tanita, Japan). Students then wore an ActiGraph accelerometer (wGT3X-BT, Pensacola, Florida, USA) around the waist on the right side, 24 hours/day for seven consecutive days. Monitors were removed for any water-based activity. Collected data were compiled and stratified based on gender and BMI.

Measurements

The body composition analyser provided measures of weight, body fat and muscle mass. A cut-off value <25.0 kg/m2 was considered ‘normal’ BMI, 25.0–29.9 kg/m2 was considered ‘overweight’ while ≥30.0 kg/m2 was considered ‘obese’.16 The ActiGraph is an activity monitoring device that provides information on PA intensity and SB. ActiLife software V.6.13.3 (ActiGraph Manufacturing Technology, Florida, USA) was used to initialise and download data which captured raw acceleration data at 100 Hz. Data were analysed using 10 s epochs using the normal filter. Epoch lengths of 10 s rather than 60 s were used in order to more accurately capture PA and SB.17 Accelerometer data were analysed from 7:00 to 23:00 hours to minimise conflation between sleep time and actual SB time; an important issue in some studies.17 For inclusion in the analysis, participants needed to wear the ActiGraph≥600 min/day for four valid days including at least 1 weekend day.18 Wear time was identified and non wear time removed using the Choi 2011 algorithm.19 Derived accelerometer data included mean daily time and percentage time spent in different intensities (sedentary, light PA and MVPA), axis-1 counts per minute, peak 1 min step counts (ie, greatest number of steps per minute), daily step counts and daily wear time. Matthews sedentary cut-point and the Troiano Adult (2008) activity cut-point thresholds were used to establish the time spent in different intensities.20 21 Compliance with the new and older bout-based PA guidelines was also highlighted.22 Participants achieving ≥150 min MVPA/week, considering any bout length, met the new PA guidelines while those achieving ≥150 min MVPA/week in bout lengths ≥10 min met the bout-based PA guidelines.22 Daily step count categories included: <5000 steps (inactive); 5000–7499 steps (low active); 7500–9999 steps (somewhat active); 10 000–12499 steps (active) and ≥12 500 (highly active).23

Statistical analysis

Normality was assessed using skewness and kurtosis, with values within acceptable limits. The means and SD were calculated using SPSS V.25 (IBM) with the gender (male vs female) and BMI (normal vs overweight/obese) differences determined using independent samples t-tests for continuous variables and χ2 tests used for nominal variables (yes/no answers), with significance set at p≤0.05. Due to smaller numbers of participants being classified as overweight or obese versus having a normal BMI, a combined overweight/obese BMI group was used in analyses. All values are reported as mean (SD) or number (percentage).

Results

Body composition analysis

Seven females and eight males did not provide body composition data, leaving 70 females and 55 males for the related analyses in tables 1 and 2. Mean age was 20±1.4 years old and BMI was 22.7±4.6 kg/m2 for females and 25.3±6.3 kg/m2 for males (table 1). Males had significantly higher BMI and muscle mass, whereas females had significantly higher body fat percentage.

Table 1

The averaged body composition parameters compared between males and females as measured using the body composition analyser

Variables	Females	Males
Number of participants, n	70	55
Age, mean (SD)	20.1 (1.4)	19.9 (1.3)
Body mass (kg), mean (SD)	59.8 (13.1)*	81.1 (20.9)
BMI (kg/m2), mean (SD)	22.7 (4.6)*	25.3 (6.3)
Muscle mass (kg), mean (SD)	39.3 (5.1)*	61.6 (10.1)
Fat-free mass (kg), mean (SD)	41.3 (5.4)*	64.5 (10.6)
Fat mass (kg), mean (SD)	18.4 (9.0)	16.6 (11.6)
Fat percentage (%), mean (SD)	29.4 (7.9)*	18.8 (7.5)

*P≤0.05 between females versus males.

BMI, body mass index; kg, kilogram; kg/m2, kilogram per square metre; n, number; SD, standard deviation.

Gender comparison

One participant did not provide valid accelerometer data meaning 139 participants were analysed. Accelerometer wear time in both groups was almost 15.5 hour per day. There were no significant differences between gender for any of the SB and light PA parameters; females and males typically spent >12 hours/day being sedentary (>80% waking hours) while light PA was typically completed for >2 hours/day (>14% waking hours) (table 3). However, males had significantly higher mean percentage time in MVPA compared with females (5.5±2.4% vs 4.0±1.6%, p<0.001). The percentage of females meeting the new recommended PA guidelines was lower compared with males (83.1% vs 95.2%, p=0.03) but numbers achieving the new PA guidelines were still high. Few individuals met the bout-based PA guidelines (ie, 1% females vs 13% males). Males completed significantly more accelerometer counts per minute compared with females (297.5±110.9 vs 230.8±77.5) counts per minute; p<0.001), and 1540 higher daily steps (7840±2853 steps in males vs 6300±1722 steps in females; p<0.001). For daily step categories, 76.6% females vs 50.0% males were classified as sedentary or low active.

Table 3

The averaged PA and SB parameters compared between males and females as measured using the accelerometer

Variables	Females	Males*
Number of participants, n	77	62
Time in SB (min/day), mean (SD)	758.9 (49.8)	745.1 (69.6)
Time in light PA (min/day), mean (SD)	130.0 (34.8)	131.2 (38.2)
Time in MVPA (min/day), mean (SD)	37.1 (14.7)†	50.9 (22.0)
% time spent in SB, mean (SD)	82.0 (4.6)	80.3 (5.3)
% time spent in light PA, mean (SD)	14.0 (3.7)	14.2 (4.0)
% time spent in MVPA, mean (SD)	4.0 (1.6)†	5.5 (2.4)
Number meeting new PA guidelines (no MVPA bouts), n(%)	64 (83.1)†	59 (95.2)
Time in ≥10 min MVPA bouts (min/day), mean (SD)	5.3 (6.1)†	9.2 (10.9)
Number meeting bout-based PA guidelines (≥10 min MVPA bouts), n(%)	1 (1.3)†	8 (12.9)
Axis-1 counts per minute, mean (SD)	230.8 (77.5)†	297.5 (110.9)
Peak 1 min step counts, mean (SD)	135.0 (15.6)	135.3 (19.9)
Daily step counts, mean (SD)	6300 (1722)†	7840 (2853)
Daily step count categories†;
Sedentary, n(%)	16 (20.8)	9 (14.5)
Low active, n(%)	43 (55.8)	22 (35.5)
Somewhat active, n(%)	17 (22.1)	16 (24.2)
Active, n(%)	1 (1.3)	11 (17.7)
Highly active, n(%)	0 (0.0)	5 (8.1)
Wear time (min/day), mean (SD)	926.0 (35.1)	927.2 (52.4)

*One male participant did not provide valid accelerometer data meaning 62 male participants were analysed for their accelerometer data.

†P≤0.05 between females versus males.

MVPA, moderate-vigorous physical activity; n, number; PA, physical activity; SB, sedentary behaviour; SD, standard deviation.

BMI category comparison

Accelerometer wear time in both groups was almost 15.5 hour per day. There were no significant differences for most PA and SB parameters (table 2). However, percentage time in SB was significantly higher in the normal BMI versus overweight/obese participants (82.1±4.9% vs 80.2±5.0%; p=0.04) and accelerometer counts per minute were significantly lower in the normal weight versus overweight/obese participants (243.3±99.3 vs 283.8±101.1 counts per minute; p=0.04). There were no significant differences between BMI categories for participants achieving the ‘somewhat active’ step count classification (ie, ≥7500 daily steps).

Table 2

The averaged PA and SB parameters compared between normal and overweight/obese BMI subgroups

Variables	NormalBMI group*	Overweight/obeseBMI group
Number of participants, n	85	39
BMI (kg/m²), mean (SD)	21.1 (2.4)†	29.9 (5.7)
Fat percentage (%), mean (SD)	23.0 (7.8)†	29.3 (10.5)
Time in SB (min/day), mean (SD)	761.8 (56.7)	740.4 (66.0)
Time in light PA (min/day), mean (SD)	124.8 (34.8)	136.7 (38.4)
Time in MVPA (min/day), mean (SD)	40.7 (20.3)	46.2 (18.7)
% time spent in SB, mean (SD)	82.1 (4.9)†	80.2 (5.0)
% time spent in light PA, mean (SD)	13.4 (3.7)	14.8 (4.0)
% time spent in MVPA, mean (SD)	4.4 (2.2)	5.0 (2.1)
Number meeting new PA guidelines (no MVPA bouts), n(%)	72 (84.7)	36 (92.3)
Time in ≥10 min MVPA bouts (min/day), mean (SD)	6.7 (8.3)	7.2 (10.1)
Number meeting bout-based PA guidelines (≥10 min MVPA bouts), n(%)	5 (5.9)	3 (7.7)
Axis-1 counts per minute, mean (SD)	243.3 (99.3)†	283.8 (101.1)
Peak 1 min step counts, mean (SD)	134.9 (17.7)	134.7 (17.8)
Daily step counts, mean (SD)	6738 (2377)	7005 (2469)
Daily step count categories:
Sedentary, n(%)	17 (20.0)
Low active, n(%)	40 (47.1)
Somewhat active, n(%)	19 (22.4)
Active, n(%)	7 (8.2)
Highly active, n(%)	2 (2.4)	2 (5.1)
Wear time (min/day), mean (SD)	927.3 (38.2)	923.2 (56.4)

*One participant did not provide valid accelerometer data meaning 85 participants with normal BMI were analysed for their accelerometer data.

†P≤0.05 between normal BMI and overweight/obese BMI groups.

BMI, body mass index; kg/m2, kilogram per square metre; MVPA, moderate-vigorous physical activity; n, number; PA, physical activity; SB, sedentary behaviour;SD, standard deviation.

Discussion

The main findings indicate that regardless of gender and BMI category, many young adults in the UAE are sedentary for ~80% of waking hours while most PA was light intensity. These SB levels are much higher than a suggested maximum of 7 hours/day.24 Although there are no clear SB guidelines, this proportion of the day spent being sedentary is much higher than recorded in other studies: 55% among American adults,20 69% among Canadian adults25 and 61% among Nigerian university students.26 Compliance with PA guidelines varied greatly depending on the recommendations used and this is certainly an important issue for future studies to consider when assessing compliance with PA guidelines. Many met the new PA guidelines which recommend ≥150 min MVPA/week accumulated in any bout length while few met the now obsolete bout-based PA guidelines which additionally required MVPA to be completed in ≥10 min bouts. This makes comparison with previous research difficult. Previous findings from Gulf Cooperation Council countries reported that only 40% of males and 27% of females achieved the bout-based PA recommendations.27 Another study found significantly less Emirati girls engaged in MVPA compared with Emirati males (53%–63% vs 77%–81%).28 Research incorporating females from the UAE University found 48.5% reported not participating in any PA while 47.1% participated in mild PA.29 It is plausible that the desert climate does not support outdoor PA engagement for much of the year. Additionally, the dusty nature of the UAE means high prevalence of respiratory conditions among adolescents,30 which can discourage exercise and being outdoors.

Males had higher daily steps than females with 41.9% of males compared with 23.4% of females being classified as at least somewhat active (ie, ≥7500 steps/day); levels known to be beneficial for health.22 Cultural and societal barriers negatively affect PA engagement in females more so than males. These include the need to preserve modesty, a lack of peer role models and family support, along with increased wealth resulting in the proliferation of household helpers, contributing to decreased PA opportunities.31

Limitations and strengths

Limitations include using a cross-sectional design which incorporated a sub-population of young UAE adults attending university. Additionally, potential covariates such as quality of life, socioeconomic status and aerobic fitness were not collected. This would have facilitated linear regression analyses to identify variables associated with PA and SB in this population. There may be possible selection bias with generally healthier students and possibly more sports-orientated students keen to volunteer. Although common non-wear criteria and cut-points were used, using 100 Hz (most studies record accelerometry using 30 Hz) and the additional methods which had to be applied to separate waking hours from sleep time may affect the comparability of our data to previously published studies. Study strengths include being the first objectively quantified PA and SB dataset within the UAE and obtaining data in a way to account for possible seasonal variation in the UAE.

Conclusion

Our data highlight high levels of SB among young adults in the UAE with PA being predominantly light intensity, therefore, both PA and SB should be carefully monitored across different cohorts in this country. Young UAE females seem to be undertaking less MVPA and daily step counts compared with young UAE males, highlighting the need for researchers and healthcare professionals to develop specific interventions encouraging higher intensity activity in young UAE females. The large discrepancy between those meeting the new PA guidelines compared with those meeting the older bout-based PA guidelines is extremely important for future studies to consider when comparing their adherence data to previous research. Multiple factors may have contributed to these findings meaning the relationships between sociodemographic, cultural and environmental factors need to be more fully understood in order to design effective interventions in this population.