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  • Research article
  • Open Access
  • Open Peer Review

Physical inactivity, gender and culture in Arab countries: a systematic assessment of the literature

  • 1,
  • 1Email author,
  • 1 and
  • 1, 2
BMC Public Health201818:639

https://doi.org/10.1186/s12889-018-5472-z

  • Received: 4 October 2017
  • Accepted: 17 April 2018
  • Published:
Open Peer Review reports

Abstract

Background

Physical inactivity is associated with excess weight and adverse health outcomes. We synthesize the evidence on physical inactivity and its social determinants in Arab countries, with special attention to gender and cultural context.

Methods

We searched MEDLINE, Popline, and SSCI for articles published between 2000 and 2016, assessing the prevalence of physical inactivity and its social determinants. We also included national survey reports on physical activity, and searched for analyses of the social context of physical activity.

Results

We found 172 articles meeting inclusion criteria. Standardized data are available from surveys by the World Health Organization for almost all countries, but journal articles show great variability in definitions, measurements and methodology. Prevalence of inactivity among adults and children/adolescents is high across countries, and is higher among women. Some determinants of physical inactivity in the region (age, gender, low education) are shared with other regions, but specific aspects of the cultural context of the region seem particularly discouraging of physical activity. We draw on social science studies to gain insights into why this is so.

Conclusions

Physical inactivity among Arab adults and children/adolescents is high. Studies using harmonized approaches, rigorous analytic techniques and a deeper examination of context are needed to design appropriate interventions.

Keywords

  • Physical activity
  • Social determinants
  • Gender
  • Culture
  • Arab countries

Background

Global increases in body mass index, raised blood pressure and cardiovascular disease have been attributed in part to the reduction in physical activity resulting from changes in the organization of labor and transportation, and to increases in sedentary behavior. The evidence on the magnitude of these changes and their consequences for health is well recognized. The World Health Organization (WHO) ranks physical inactivity as the fourth leading cause of global mortality, estimating that it results in 3.2 million deaths globally, mainly due to cardiovascular disease, diabetes, hypertension, and some cancers [16]. Analyses of the Global Burden of Disease estimate that insufficient physical activity accounts for an estimated 13.4 million disability adjusted life years (DALYs) related to ischemic heart disease, diabetes and stroke [7].

There are major variations in the prevalence of physical inactivity across regions and among countries. In the Arab region, alarming predictions have been made in light of very unfavorable combinations of risk factors related to body mass index, its determinants including physical activity, and its health consequences [810]. Some studies have compared indicators across countries [1115], but there have not been comprehensive assessments of the prevalence and determinants of physical inactivity across the Arab region. Yet, such regionally specific assessments are key to identify patterns and formulate interventions, and would be especially timely, given mounting evidence on the health effects of sedentary behaviour and physical inactivity, the growing awareness of the need for population interventions, and the urgency of scaling up policies and programs to increase physical activity in low and middle income countries [16]. In addition, there is a need to go beyond simplistic explanations of observed patterns in terms of religion or education.

Hence, this study was designed to review research on the subject, assess levels and variability in physical inactivity across countries and social groups, and gain insights into the extent to which social determinants, in particular those related to gender, could explain such unfavorable indicators. The diversity of indicators and measures in the region, and the difficulty of obtaining original survey data precluded the possibility of conducting a systematic review or meta-analysis. But we thought it was important to take stock of what was known about physical inactivity in the region and to review the explanations that are offered for observed levels, in order to identify patterns and to inform policies designed to increase physical activity.

The review proceeds as follows. We first present a summary of the evidence from studies published in peer-reviewed journals, including the availability and comparability of studies and the instruments used. Secondly, we provide a synthesis of prevalence levels based on the reports of surveys that have used standardized definitions and measurements. We then bring together the results of studies that examined the social determinants of physical activity, with special attention to those related to gender and cultural factors. Lastly we draw the implications of these results for research and policies.

Methods

Search strategy and inclusion criteria

We sought to retrieve research published in refereed journals and reports of surveys, and our approach was three-pronged. First, we searched for articles in refereed journals investigating physical inactivity in countries of the Arab region, published between January 2000 and January 2016, in MEDLINE, Popline and Social Sciences Citation Index (SSCI) databases. Various combinations of MeSH terms and key words were used, related to physical activity/ inactivity, sedentary lifestyle, exercise, sports, its prevalence, incidence, epidemiology, the burden it represents, and social or cultural factors. Details are shown in Additional file 1. Studies published in any language were retrieved. Two researchers conducted title and abstract screening, followed by full-text screening, checking to harmonize results regarding inclusion or exclusion; disagreements were discussed by the team as a whole and resolved. This was done according to the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) appraisal tool for systematic reviews [17]. In addition to the electronic search, we searched reference lists of the articles identified.

Sources were included if they fulfilled the following criteria: assessed physical activity or inactivity as an outcome or a determinant; were conducted among residents of Arab countries (the 22 countries of the Arab League: Algeria, Bahrain, Comoros, Djibouti, Egypt, Iraq, Jordan, Kingdom of Saudi Arabia (KSA), Kuwait, Lebanon, Libya, Mauritania, Morocco, Oman, Palestine, Qatar, Somalia, Sudan, Syria, Tunisia, United Arab Emirates (UAE), and Yemen); described the design and methods; reported on sample size; described how physical activity/inactivity was measured; reported on the prevalence of physical activity/inactivity. Multi-country studies were included if they presented data on at least one Arab country. Studies conducted exclusively on patients with a particular disease diagnosis, and studies conducted on Arabs residing outside the Arab region were excluded. To be included, articles needed to fulfill quality criteria informed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [18], including clear eligibility criteria for study selection, description of information sources, data and variables; we excluded studies that did not report on sample size, age range of study population, and those that presented unclear or inconsistent numbers.

Secondly, we retrieved the reports of surveys on physical activity conducted by international organizations in collaboration with country partners; these surveys generally use standardized instruments and the two main sources are the World Health Organization (WHO) surveys on non-communicable disease risk factors (STEPS) which include modules on physical activity among adults; and the Global School-based Student Health Surveys (GSHS) which measure activity among adolescents. We present results separately for studies based on national surveys using standardized definitions and measures, and whose results represent comparable and higher-quality estimates.

A third part of the review was to retrieve data from sources that considered physical inactivity in relation to social factors such as age, marriage, education, employment, residence, and those that examined cultural and social barriers to physical activity. We sought to gain insights into the socio-cultural context of physical activity, and to explain the patterns that emerged from the analysis of the quantifiable data. We extracted notes and themes from those sources that included qualitative information, and provide a critical synthesis of main findings. Thus, this review draws both on rigorous quantitative analyses and a narrative synthesis of qualitative studies.

Data extraction and analysis

Citations from search results of databases were imported into the reference manager EndNote and duplicates removed. We used the open-source Open Data Kit (ODK) (https://ona.io/) to create the data entry protocol. The data extracted for each study included: (1) article identification (title, author/s, publication year, journal, country/ies of study); (2) research design, setting, sample size, study population, gender, and age; (3) definition of physical activity/inactivity, instrument used, reported prevalence; and, (4) demographic, economic, lifestyle and social correlates of physical inactivity. In addition, we retrieved themes from those studies that examined the social context of physical activity and provided information about gender and cultural differences.

We retrieved the most recent data from STEPS and GSHS surveys. For countries where no published reports were available, we retrieved any data available from the WHO website.

Regarding the outcome variable, because of the diversity of definitions and measures of physical activity, we found that the most consistent way to report the results was to use physical inactivity, which refers to not engaging in any physical activity and/or being in the lowest category of physical activity, however physical activity was defined in the study. This is consistent with other studies that have reviewed physical activity across the world [13].

We present results separately for adults and for children/adolescents. We defined as adults those respondents aged 18 or older, or those who were categorized as adults in the articles; younger respondents were categorized as children/adolescents. In the discussion, we build on the narrative synthesis of qualitative studies.

Results

The evidence on physical inactivity

Sources and quality of data

Our search retrieved 1,228 articles, of which 172 met the inclusion criteria. Figure 1 provides a flow chart of the review’s inclusion and exclusion process. The included articles referred to a total of 157 datasets: 149 from studies conducted in a single country and 8 conducted as part of multi-country studies; the results of multi-country studies are counted once for each individual country. Some articles were based on the same datasets, including six articles based on STEPS and GSHS surveys. Only 16/143 journal articles reported on surveys using nationally representative samples; qualitative data were retrieved from five qualitative studies and from four mixed methods studies.
Fig. 1
Fig. 1

Flow chart of the review’s inclusion and exclusion process

All STEPS and GSHS, and 125/157 journal articles include both men/boys and women/girls. GSHS surveys (usually on adolescents 13-15) have been conducted in all but four countries of the region (Bahrain, Comoros, KSA, and Somalia). STEPS surveys usually include adults aged 25-64. Age categories in journal articles are more diverse. 12 countries had both STEPS and GSHS surveys. Unlike GSHS, not all STEPS were based on nationally representative samples (exceptions were Algeria, Mauritania, Oman and Sudan). Additional results about the prevalence of physical inactivity and its determinants are available from journal articles that used the World Health Surveys (WHS) as data sources. STEPS are based on household surveys and GSHS on school populations, while the settings in journal articles included schools (28%), health facilities (27%), households (16%), and universities (15%).

Table 1 shows disparities in the available evidence: for some countries there are very few studies (Algeria, Comoros, Djibouti, Iraq, Somalia, Sudan and Yemen), while for others many more sources are available (for example 40 for Saudi Arabia). There is also a variability in sample size, with most studies in the range of 200-2000 and a few large studies including several thousand respondents.
Table 1

The evidence on physical activity in Arab Countries: studies, sample sizes and instruments

Country

Total number of studies

Data from Reports/Factsheetsa

Data from Journal Articles

Studies (#)

Sample size/range

Single country studies (#)

Multi-country studies (#)

Sample size/range

Nationally representative studies (#)

Instruments usedb,c

Algeria

4

2 [116, 117]

4102 – 4532

1 [118]

1 [15]

293 – 4698d

-

Locally Validated Questionnaire [15]

Bahrain

4

1 [119]

1769

4 [82, 120122]

0

142 – 2013

1 [122]

WHO Heart and Health Questionnaire [120]

Comoros

3

1 [123]

5556

0

2 [12, 13]

1492 – 212021d

-

IPAQ [12, 13]

Djibouti

1e

1 [124]

1777

0

1 [11, 58]

829 – 882

1 [58]

PACE+ [11, 58]

Egypt

12e

2 [125, 126]

2568 – 5300

7 [34, 46, 74, 127130]

4 [11, 21, 58, 131, 132]

188 – 3271

1 [58]

IPAQ [131] PACE+ [11, 58]

Iraq

3

2 [133, 134]

2038 – 4120

1 [135]

0

200

-

-

Jordan

15e

2 [136, 137]

2197 – 3654

12 [61, 64, 70, 72, 80, 81, 138143]

2 [11, 15, 58]

209 – 8791

3 [58, 138, 141]

PACE+ [11, 58] ATLS [140]

Locally Validated Questionnaire [15]

KSA

48

1 [144]

3547

46 [19, 20, 2427, 36, 38, 41, 42, 44, 48, 5154, 65, 66, 68, 69, 73, 93, 96, 98, 99, 103, 107, 145167]

1 [12]

30 – 197681

3 [38, 157, 167]

ATLS [24, 42, 66, 98, 99, 167]

Barriers to Being Active Quiz: CDC website [44]

CDC Adolescent Health Survey [27]

Electronic Pedometer [19, 20]

GPAQ [36, 54, 107, 150]

IPAQ [12, 26, 69, 93, 157] KPAS [25]

WHO stepwise questionnaire [166]

YRBSS and GSHS Questionnaires [167]

Kuwait

15

2 [94, 168]

2280 – 3637

12 [37, 49, 79, 97, 169177]

1 [15]

224 – 38611

3 [169171]

The Exercise Pattern Questionnaire [172]

Locally Validated Questionnaire [15]

Lebanon

13e

2 [178, 179]

1982 – 2286

13 [22, 29, 30, 35, 57, 59, 63, 114, 180186]

0

83 – 2608

5 [35, 181, 182, 185, 186]

IPAQ: 2 used a shorter version [35, 181, 182]

Self-reported Weekly Activity Checklist [59]

Libya

5e

2 [187, 188]

2242 – 3590

2 [56, 189]

2 [11, 15, 58]

383 – 1300

1 [58]

Locally Validated Questionnaire [15]

Mauritania

4

2 [190, 191]

2063 – 2600

0

2 [12, 13]

2726 – 212021f

-

IPAQ [12, 13]

Morocco

6e

1 [192]

2924

5 [38, 61, 62, 75, 84, 85, 105, 193]

1 [11, 58]

239 – 2891

1 [58]

IPAQ [39]

PACE+ [11, 58]

Oman

7e

2 [94, 194]

1373 –3468

5 [33, 71, 195197]

2 [11, 58, 198]

10 – 5409

2 [58, 195]

GPAQ [33] GSHS Questionnaire [197]

IPAQ [196] LASA Physical Activity Questionnaire [197]

PACE+ [11, 58]

WHO Health Behavior in School Children [196]

Palestine

11

2 [126, 199, 200]

1908 – 6957

8 [55, 77, 86, 100, 201204]

1 [15]

16 – 8885

1 [202]

MESA [204]

Locally Validated Questionnaire [15]

Qatar

10e

2 [205, 206]

2021 – 2496

9 [23, 40, 207214]

0

340 – 2467

1 [214]

GPAQ [214]

Somalia

1

0

-

1 [215]

0

173

-

-

Sudan

3

2 [216, 217]

1573 – 2211

1 [218]

0

1200

-

-

Syria

4

1 [219]

3102

2 [92, 220, 221]

1 [15]

1168-2037

-

Locally Validated Questionnaire [15]

Tunisia

12e

1 [222]

2870

9 [31, 32, 43, 76, 223228]

4 [1113, 58, 131]

10 – 17789

2 [43, 223]

IPAQ [12, 13, 228], (including 1 short version) PACE+ [11]

Locally Validated questionnaire [31, 43, 223, 224]

UAE

15e

1 [229]

2581

11 [28, 45, 47, 67, 78, 83, 96, 230233]

4 [1113, 15, 58]

20 – 9918

1 [58]

Health Promoting Lifestyle Profile [47]

IPAQ: 3 used shorter version [12, 13, 78, 83]

PACE+ [11, 58]

Locally Validated Questionnaire [15]

Yemen

1e

1 [234]

1175

0

1 [11]

568

1 [11]

PACE+ [11]

aWHO-STEPS and GSHS used GPAQ and PACE+ respectively to assess physical inactivity

bThis column indicates whether some studies used internationally or locally standardized/validated instruments, with the reference number in brackets; where not indicated, the assessment of physical activity was either not specified or based on a single question

cATLS: Arab Teens Lifestyle Study – GSHS: Global School-based Student Health survey – IPAQ: International Physical Activity Questionnaire – KPAS: Kaiser Physical Activity Survey –LASA: Longitudinal Aging Study Amsterdam – MESA: Multi-Ethnic Study of Atherosclerosis questionnaire – PACE+: Patient-Centered Assessment and Counseling for Exercise Plus Nutrition – YRBSS: The Youth Risk Behavior Surveillance System

dFor multi-country studies where the information on sample size was not available for each country, we included the pooled sample size.

eA number of journal articles are based on WHO surveys (STEPS and GSHS)

STEPS and GSHS use standardized instruments, namely the Global Physical Activity Questionnaire (GPAQ) and the Patient-Centered Assessment and Counseling for Exercise Plus Nutrition (PACE+) respectively, but only 38/143 journal articles referred to studies that used validated instruments. About half of these used internationally validated tools, such as the International Physical Activity Questionnaire (IPAQ), the GPAQ or the PACE+; others used regionally or nationally validated questionnaires. Two studies used electronic pedometers [19, 20]. The majority of studies (112/157) simply used respondents’ reports. Only five studies followed the WHO’s recommendations regarding the multi-dimensional categorization of physical activity into work, active transportation, household and family, and leisure-time activities; the questionnaires that follow this recommendation include the long version of IPAQ, the GPAQ, and the Kaiser Physical Activity Survey (KPAS).

Prevalence of physical inactivity

Tables 2 and 3 present the prevalence of physical inactivity among adults; Table 2 summarizes data from WHO-STEPS surveys and Table 3 presents results of journal articles. Among adults, the prevalence of physical inactivity defined as performing less than 600 MET-minute per week, exceeded 40% in all Arab countries except for Comoros (21%), Egypt (32%) Jordan (5%); it reached 68% in KSA (national) and 87% in Sudan (subnational).
Table 2

Prevalence of physical inactivity among adults based on data from WHO-STEPS surveys

Countrya

Year of study

Age range

Sample size

Prevalence of Physical inactivity

National samples

 Comoros

2011

25-64

5556

20.1

 Egypt

2011-2012

15-64

5300

32.1

 Jordan

2007

18+

3654

5.2

 Iraq

2015

18+

4120

47.0

 Kuwait

2014

18-69

4391

62.6

 Libya

2009

25-64

3590

43.9

 Lebanon

2008

25-64

1982

45.8

 Palestine

2010-2011

15-64

6957

46.5

 Qatar

2012

18-64

2496

45.9

 Saudi Arabia

2005

25-64

3547

67.6

Subnational samples

 Algeria

2003

25-64

4102

40.7

 Mauritania

2006

25-64

1971b

51.3

 Sudan

2005-2006

25-64

1573

86.8

aFor Bahrain and Oman, surveys were available but no total physical inactivity prevalence could be retrieved; specific prevalence of work, transportation, and leisure time were 71.9%, 63.9%, and 57.1%., respectively for Bahrain and 6.4%, 30.1%, and 53.8% for Oman

bSample size was calculated for age group (25-64) from numbers provided in the report

Table 3

Prevalence of physical inactivity among adults based on findings from published literature

Country

First author, year (year of study)

Source

Definition

Instrument

Prevalence (%)

Age range

Sample size

National samples

 Comoros

Guthold, 2008 (2002-2003)

World Health Survey

<600 MET-minutes/week

IPAQ

2.7

18-69

1492

 Jordan

Zindah, 2008 (2004)

Behavioral Risk Factor Surveillance System

Not engaging in moderate activity (resulting in light sweating, small increases in breathing or heart rate.

NA

51.8

18+

710

 Kuwait

Ahmed, 2013 (2002-2009)

National Nutrition Surveillance Data

No deliberate non-work related exercise outside the home such as walking, running or cycling

NA

68.4

20+

32811

Al-Zenki, 2012 (2008-2009)

NA

Neither moderately nor very activea

NA

77.1

20+

765

Alarouj, 2013 (NA)

NA

Neither moderate nor vigorous physical activitya

NA

63.0

20-65

1970

 KSA

Al-Baghli, 2008 (2004-2005)

NA

No physical activity or mild physical activity (ordinary housework, walking)

NA

79.2

30+

197681

Al-Nozha, 2007 (1995-2000)

Coronary Artery Disease in Saudis Study (CADISS)

<600 MET-minutes/week

NA

96.1

30-70

17395

Memish, 2014 (2013)

Saudi Health Information Survey

Neither moderate nor vigorous physical activitya

IPAQ

69.1

15+

10735

 Lebanon

Farah, 2015 (2013-2014)

NA

Neither moderate-intensity physical activity for at least 150 min per week or vigorous intensity physical activity for 75 min at least per week

NA

76.0

40+

1515

Tohme, 2005 (2003-2004)

NA

Less than 30 min of physical exercise

NA

40.3

30+

954

 Mauritania

Guthold, 2008 (2002-2003)

World Health Survey

<600 MET-minutes/week

IPAQ

61.9

18-49

1492

 Morocco

El Rhazi, 2011 (2008)

NA

Less than 30 min per day

 

38.7

18+

2620

Najdi, 2011 (2008)

NA

<3METs

IPAQ

16.5

18-99

2613

 Palestine

Baron-Epel, 2005 (2002-2003)

KAP and EUROCHIS&

Exercising less than once per week for at least 20 consecutive minutesb

NA

62.8

21+

1826c

 Tunisia

Guthold, 2008 (2002-2003)

World Health Survey

<600 MET-minutes/week

IPAQ

14.6

18-69

4332

 UAE

Guthold, 2008 (2002-2003)

World Health Survey

<600 MET-minutes/week

IPAQ

43.2

18-69

1104

Subnational samplesd

 Bahrain

Al-Mahroos, 2001 (NA)

NA

<1 km walking

WHO Heart and Health Questionnaire

77.5

40-69

2013

Hamadeh, 2000 (NA)

NA

No exercise

NA

89.1

30-79

516

 Egypt

Abolfotouh, 2007 (2002-2003)

NA

No non-vigorous physical activity for at least 20 minutes or 3 times per week

NA

33.8

17-25

600

Kamel, 2013 (2010-2011)

NA

NA

NA

63.8

60+

340

Mahfouz, 2014 (2011)

NA

No exercise

NA

78.3

NA

300

 Jordan

Centers for Disease, Control, Prevention, 2003 (2002)

Jordan Behavioral Risk Factor Survey

Less than having moderate: activity that caused light sweating and small increases in heart rate or breathing for 30 minutes

NA

47.4

18+

8791

Mohannad, 2008 (2002)

NA

No activity that caused light sweating and small increases in heart rate or breathing

NA

58.7

40+

3083

Kulwicki, 2001 (NA)

NA

No exercise

NA

22.5

17-93

209

Madanat, 2006 (2003)

NA

<30 mins of physical activity/week

NA

81.5

Mean: 21.1

431

 KSA

Almurshed, 2009 (2003-2004)

NA

No exercise

NA

52.0

30+

50

Al-Quaiz, 2009 (2007)

NA

Not practicing in any regular sport and leisure time physical activity

CDC web site questionnaire

82.4

15-80

450

Al-Senany, 2015 (NA)

NA

Less than one hour weekly activity

NA

69.0

60-90

55

Amin, 2011 (NA)

NA

<600 MET-minutes/week

GPAQ

48.0

18-64

2176

Amin, 2014 (NA)

NA

<30 minutes /≥ 5 days/week

GPAQe

80.0

18-78

2127

Awadalla, 2004 (2012-2013)

NA

Neither vigorous: >6 METs nor moderate: 3-6 METs

IPAQ (short form)

58.0

17-25

1257

Garawi, 2015 (2004-2005)

NA

<600 MET-minutes/week

GPAQ

67.0

15-64

4758

 Kuwait

Naser Al-Isa, 2011 (NA)f

NA

Not engaging in regular physical activity

NA

45.0

NA

787

 Lebanon

Al-Tannir, 2008 (2007)

NA

Less than 3 days/week

NA

44.5

18+

346

Musharrafieh, 2008 (2001)

NA

Physical exercise for <0.5 h/week

NA

73.6

Mean: 21.0

2013

Tamim, 2003 (2000-2001)

NA

<3 hours/week

NA

64.3

Mean: 21.0

1964

 Mauritania

Guthold, 2008 (2002-2003)

World Health Survey

<600 MET-minutes/week

IPAQ

61.9

18-49

2726

 Palestine

Abdul-Rahim, 2003 (NA)

NA

Occupation-related sedentary-light PA for men AND no exercise for women

NA

56.2

30-65

936

Abu-Mourad, 2008 (2005)

NA

No home exercise or sports

NA

78.0

18+

956

 Qatar

Al-Nakeeb, 2015 (NA)

NA

<840 MET-min/week

NA

50. 8g

Mean= 21.2

732

Bener, 2004 (2003)

NA

Not walking, cycling at least 30 minutes/day

NA

55.3

25-65

1208

 Somalia

Ali, 2015 (2013)

NA

<2 hours/week

NA

33.5

18-29

173

 Syria

Al Ali, 2011 (2006)

2nd Aleppo Household Survey

Less than 15 mins/ week of sport or brisk walking

NA

82.3

25+

1168

 Tunisia

Maatoug, 2009 (2009)

NA

<150 mins/week of moderate level of physical activity

Oxford Health Alliance Community Intervention for Health Project

44.4

Mean: 37.9

1880

 UAE

Abdulle, 2006 (2001-2005)

NA

Less than one hour, <3 times per week

NA

39.4

20-75

424h

McIlvenny, 2000 (NA)

NA

No regular exercise

NA

54.0

18-94

254

Sabri, 2004 (2001-2002)

NA

< 1 hour/week) of sport

NA

47.5

20-65

436

aDefinition of physical activity not specified

bIt includes: walking, running, swimming playing ball games or any other sports activities (combined every day and nearly every day with once or twice a week)

cPrevalence rate for Arabs only

dOne study conducted in Libya by Salam (2012) was excluded from the prevalence table; it includes adolescents and youth (17-24 years) and the prevalence was 65.0%

eCombined Global Physical Activity Questionnaire (GPAQ) version 2.0 with a modified show card based on World Health Organization STEPs survey

fKuwaiti college students

gOnly Qatari students

hOnly normotensives

Among the 102 journal articles on adults, 48 reported on prevalence among both men and women. In most countries, inactivity exceeded 40%; a few studies found lower inactivity, including nationally representative studies in Comoros (3%), Morocco (17%), and Tunisia (15%), and subnational studies in Egypt and Somalia (34%) and Jordan (23%).

Physical inactivity among children/adolescents is presented in Tables 4 and 5, based on GSHS reports (Table 4) and journal articles (Table 5). Prevalence of physical inactivity, defined in GSHS as <60 minutes per day on 5 or more days during the past seven days, is very high, with a low of 65% in Lebanon and a high of 91% in Egypt. Journal articles report similarly high levels of inactivity (>60%) except in KSA (45%) and Tunisia (29%), with smaller studies showing a wide variation within and among countries.
Table 4

Prevalence of physical inactivity among children/adolescents using data from Global School-based Student Health Surveys (GSHS)a

Country

Year of study

Age range

Sample size

Total prevalence of physical inactivity

Definition: < 60 mins per day on five or more days during the past seven days

 Iraq

2012

13-15

2038

80.0

 Lebanon

2011

13-15

2286

65.4

 Mauritania

2010

13-15

2063

83.7

 Morocco

2010

13-15

2924

82.6

 Palestine (Gaza Strip)

2010

13-15

2677

75.8

 Palestine (West Bank)

2010

13-15

1908

81.7

 Qatar

2011

13-15

2021

85.0

 Sudan

2012

13-15

2211

89.0

 Syria

2010

13-15

3102

84.9

 UAE

2010

13-15

2581

72.5

Definition: < 60 mins per day on all 7 days during the past 7 days

 Djibouti

2007

13-15

1777

85.1

 Egypt

2006

13-15

5249

90.6

 Jordan

2007

13-15

2197

85.6

 Kuwait

2015

13-17

3637

84.4

 Libya

2007

13-15

2242

83.9

 Oman

2015

13-17

3468

88.3

 Tunisia

2008

13-15

2870

81.5

 Yemen

2008

13-15

1175

84.8

aAll based on nationally representative samples

Table 5

Prevalence of physical inactivity among children/adolescents using data from journal articles

Country

First author, year

Source

Definition

Questionnaire used

Prevalence (%)

Age range

Sample size

National samples

 Bahrain

Musaiger, 2014 (2006–2007)

NA

<5days/week of playing sport

NA

72.1

15-18

735

 Egypt

Salazar-Martinez, 2006 (1997)

NA

Not engaged in sports

NA

62.3

11-19

1502

 KSA

AlBuhairan, 2015 (NA)

NA

Complete absence of exercise

YRBSS and the GSHS Questionnairesa

45.2

Mean: 15.8

12575

 Oman

Afifi, 2006 (2004)

NA

Engaging in physical activities <once per week, apart from school physical education

27-item Child Depression Inventory

66.3

14-20

5409

 Palestine

Al Sabbah, 2007 (2003–2004)

Health Behavior in School-aged Children Survey

< 60 minutes/day, <5/7 days per week

WHO international HBSC questionnaire

80.0

12-18

8885

 Tunisia

Nouira, 2014 (2009-2010)

NA

NA

Oxford Health Alliance for community intervention for health

88.1

12-14

3987

Aounallah-Skhiri, 2012 2005

NA

< 3 Mets

Locally validated questionnaire

29.4

15-19

2870

Subnational sampleb

 Algeria

Abbes, 2016 (2010-2011)

NA

Not engaged in sports

NA

92.8

6-11

293

 Egypt

Shady, 2015 (NS)

NA

< 4 hours/week

NA

65.5

9-11

200

 Jordan

Haddad, 2009 (NA)

NA

Not very physically nor moderately active

modified Adolescent Wellness Appraisal (AWA)

4.0

12-17

530

 KSA

Al-Hazzaa, 2011 (2009-2010)

Arab Teens Lifestyle Study

<1680 METs-min/week

ATLS

61.9

15-19

2908

Al-Muhaimeed, 2015 (2012)

NA

Not engaging in sports

NA

27.3

6-10

601

Al-Mutairi, 2015 (2013)

NA

No regular exercise

NA

31.9

15-22

426

Al-Othman, 2012 (2010)

NA

NAc

NA

15.7

6-17

331

Mahfouz, 2011 (2008)

NA

Less than 30 mins of physical exercise during the previous week

CDC Adolescent Health Survey Questionnaire

34.3

11-19

1869

 Kuwait

Shehab, 2005 (NA)

NA

Only performing normal daily routine with some recreational activities or walking slowly and doing no structured exercise

NA

71.3

10-18

400

 Lebanon

Nasreddine, 2014 (2009)

NA

Based on weekly frequency: Neverd

NA

32.6

Mean: 13.06

868

 Palestine

Jildeh, 2011 (2002-2003)

The Health Behavior for School-Aged Children Project (HBSC)

<5 days a week

First Palestinian National Health and Nutrition Survey Questionnaire (2000)

77.6

11-16

314

Arar, 2009 (NA)

NA

No extra-curricular (EC) physical activities

NA

43.3

9-11

180

 Sudan

Moukhyer, 2008 (2001)

NA

Not engaging in sports activities

NA

33.4

10-19

1200

aGSHS: Global School-based Student Health survey – YRBSS: The Youth Risk Behavior Surveillance System

bOne study conducted in Lebanon by Shediac-Riskallah (2001) was excluded from the prevalence table as it includes youth (16+ years)

cModerate intensity activities included: playground activities, brisk walking, dancing, and bicycle riding. Higher intensity activities included: ball games, jumping rope, active games involving running and chasing, and swimming

dFrequency and type of activities performed along with duration (number of minutes per week)

Gender differences in physical inactivity

Where physical activity was reported among men/boys and women/girls, we calculated the M/F ratio of the prevalence of physical inactivity. Figures 2 and 3 show gender ratios among adults and children/adolescents respectively. Overall, the prevalence of inactivity was higher among women/girls in all but 9 studies (8 adults and 1 children/adolescents).
Fig. 2
Fig. 2

Gender differences in prevalence of physical inactivity among adults

Fig. 3
Fig. 3

Gender differences in prevalence of physical inactivity among children/adolescents

Socio-demographic and lifestyle determinants

Data from 41 articles about sociodemographic determinants of inactivity were analyzed and results are summarized in Table 6. Inactivity increased with age (18/24 studies), being married (7/10 studies), and urban residence (5/5 studies); it decreased with increased education (14/20 studies) and employment (6/8 studies); parity was positively associated with inactivity in one study. For other sociodemographic determinants, reported associations were inconsistent.
Table 6

Factors associated with physical inactivity in Arab countries

 

Statistical association with physical inactivity

Positive

Negative

Other associations

Agea

[13, 29, 35, 36, 38, 39, 69, 73, 83, 92, 100, 135, 143, 153, 176, 218, 221, 231]

[44, 71, 142]

U shape [63, 202]

Curvilinear [41]

Marital status

[29, 37, 38, 41, 105, 181, 232]

[42, 79, 221]

 

Educational levela,b

[35, 54]

[30, 33, 38, 41, 42, 46, 92, 100, 148, 150, 171, 218, 231, 232]

No effect [34, 69, 93]

Employmenta

[54, 150]

[30, 33, 36, 92, 183, 232]

 

SESa,c

[12, 35, 46, 75, 105, 232]

[42, 44, 54, 92, 181]

U shape [83]

Urban residence

[35, 36, 43, 77, 150]

  

Consuming fruits/vegetables

 

[33]

 

Smokinga

[2932]

[225]

 

Alcohol

[30]

  

Screen timed

[2128]

  

Overweight/ Obesitye

[22, 24, 29, 33, 35, 3739]

[30, 4042]

No effect [43]

Chronic medical conditionsa

[29, 3436]

  

Parity

[107]

  

aThe direction of the association between physical inactivity and some variables was not specified in other studies: age [15, 93, 140, 147, 161], educational level [39, 151], employment [29, 37], SES [26, 31, 34, 39, 140], smoking [30], overweight/obesity [15], and chronic medical conditions [28]

bEducation categorized as iliterate, primary, intermediate, secondary,and university

cSocio-economic status (SES): SES score, resources, income, housing type, wealth, Human Development Index, schooling type, domestic help, car ownership

dScreen time: Television viewing, computer using, video gaming

eThe association between underweight and physical inactivity was mentioned in one study and showed a positive association

Several studies found associations between physical inactivity and lifestyle factors. Predictably, screen time was positively associated with physical inactivity in all eight studies that examined this factor [2128]. Smoking and alcohol were positively associated with physical inactivity [2932], while consuming fruits and vegetables was negatively correlated [33]. Four studies found a positive association between physical inactivity and chronic medical conditions [29, 3436].

The studies we reviewed did not report consistent associations between obesity and physical inactivity: 8/13 found a positive association [22, 24, 29, 33, 35, 3739], four reported the reverse [30, 4042] and one showed no effect [43].

Barriers to Physical activity

We examined the subset of studies that investigated barriers to exercise. Some reported reasons were shared with other parts of the world, while others were specific to the Arab region. It is clear that the hot climate of the Arabian Peninsula and Gulf countries limits outdoor physical activity to relatively short seasons and requires special indoor facilities [13, 38, 4452]. In addition in most countries, the built environment, inadequate public transportation systems, and lack of spaces for walkers or joggers discourage exercise [15, 20, 26, 31, 38, 42, 46, 47, 5368]. As in other studies, time constraints were mentioned as barriers [15, 26, 28, 30, 31, 4042, 46, 52, 54, 67, 6973], in addition to insufficient motivation or interest [25, 26, 34, 44, 46, 54, 71, 73], other priorities [26], and lack of skills [26, 44].

A particularity of the region is the lack of encouragement for physical activity by many parents, who appear to favor educational and spiritual activities over physical activities for their children. Lack of support for physical activity is also noted among friends, peers, and even teachers, in studies conducted in Saudi Arabia, Egypt, and Jordan [15, 20, 2426, 30, 42, 46, 5355, 64, 66, 68, 71, 74]. Another regionally specific factor relates to gender constraints: even where fitness facilities are available, as is the case in the more affluent countries of the region, accessibility is a problem, particularly for women.

Lower physical activity among women has been attributed to gender norms, including conservative dress that is not suitable for physical activity, the need for women to be chaperoned in public spaces, and the paucity of gender-segregated fitness facilities [15, 28, 62, 64, 67, 71, 75, 76]. In addition, cultural values put a premium on comfort for both genders, physical exertion is avoided, and public spaces such as streets are not considered appropriate for physical activity. Thus, both general norms and gender norms converge to discourage physical activity [15, 27, 31, 41, 4547, 54, 60, 6264, 67, 74, 75, 7786].

Discussion

The diversity of definitions and methods among studies published in journals and the fact that only 43/157 studies used validated instruments hampers comparisons of the prevalence and correlates of physical activity, and it is possible that some of the differences we found are artifactual. Using inactivity instead of activity improves the comparability, but it is clear that harmonizing definitions and measurements and considering the multi-dimensional aspects of physical activity would improve the evidence for the region.

Despite these limitations, it is possible to discern some patterns. The results of this review indicate that throughout the region, levels of physical inactivity are very high. Inactivity among adults is 40% or higher in all but five of the fifteen countries with nationally representative surveys; studies with smaller samples suggest even higher levels of inactivity (>60%). Among children and adolescents, inactivity is alarmingly high, around 80% in all national surveys except Tunisia.

High inactivity among children and adolescents is documented in other regions [87, 88] and is a worldwide problem, but the levels of adult inactivity we found in this review compare very unfavorably with those of other regions. Inactivity levels in Europe, the western Pacific, Africa, and southeast Asia are considerably lower (25%, 34%, 28% and 17% respectively [8890]); they are even lower in South-East Asia and Africa (15% and 21% respectively); the Americas have lower or similar inactivity levels [8890]. These high levels of inactivity indicate that social circumstances in many countries of the region do not seem to encourage physical activity. Some comparative analyses across countries in the Arab region and outside it have reported that Muslim countries were more likely to be physically inactive, and seemed to suggest that religion constitutes an obstacle to physical activity [91]. This however is not consistent with the diverse interpretations of religious doctrine in the region, and the fact that there are no grounds for arguing that Islamic doctrine is antithetical to exercise. In addition, there is no evidence linking religious observance to lower activity. The one study that compared Muslims and non-Muslims, conducted in Syria, found no significant differences in physical activity between Muslim Syrians and Syrians belonging to other religious groups [92]. Such research highlights the complex interplay among the multiple factors that hinder physical activity.

Physical and social barriers to exercise have been amply documented in multiple Arab countries: the hot weather discourages walking and exertion outdoors; an unfriendly built environment hinders exercise and promotes a car culture; physical exertion is associated with lower status occupations; a premium is placed on comfort; all these contribute to devaluing and discouraging exercise. That parental preferences favor spiritual and educational, over physical activities, and social gatherings are the main leisure activity further contributes to reducing physical activity and encouraging sedentarity [93, 94].

The combination of physical obstacles and low valuations translates into insufficient interest and motivation to exercise, which are documented in multiple countries [20, 46, 52, 68, 90]. A number of studies [24, 40, 71, 74, 95101] bring out the clustering of health risks within the studied populations, whereby physical activity is one among a set of lifestyle factors that may include energy dense foods, sweet drinks, sedentariness, and unsafe driving. This suggests that lack of knowledge about healthy behaviors in general contributes to inactivity, and emphasizes the role of social activities that are focused on sedentarity and unhealthy snacking. Interestingly, studies [72] that have probed into perceptions of health behaviors have found these to be limited to hygiene, rest and diet, but not physical activity. Thus a combination of material and cultural factors translates into barriers to physical activity at multiple levels and to a lack of awareness and motivation among the population.

A striking result of this analysis is the consistency of gender differences in physical inactivity: in nearly all (45/53) studies conducted among adults and (31/32) among children/adolescents, prevalence of inactivity was higher among women/girls. While traditional religious norms have been reported to potentially define acceptable behaviors for women and preclude exercising, careful qualitative research [76, 102] shows that these are not insurmountable obstacles. Studies show that some women athletes negotiate their involvement in sports even as they continue to wear Islamic clothing, and that decisions to exercise are influenced by new ideas about healthy lifestyles disseminated by professionals. In addition, some studies [103] suggest that ideas about physical activity can become more positive, and that cultural barriers can be overcome when adequate facilities are available.

Studies on ideas about the body report preferences for heavier shapes, especially for men [104] and ethnographic research indicates that there is a normalization of weight gain with increasing age and with maternal status among women [105, 106]. Such notions of the body likely translate into a lack of motivation to exercise and maintain optimal weight across the life cycle for both sexes, and women are vulnerable to weight gain with successive pregnancies. Women's marginalization in segregated societies [107] further pushes them towards a lifestyle centered on hospitality, excessive food consumption and sedentariness. But research also indicates that ideal body shapes can change as a result of exposure to media, as younger women in several countries of the region seem to have adopted thinner body shape preferences [108]. Ideas about exercise can also be transformed by initiatives that provide information about the link between health and exercise, activities that involve women in sports, and efforts to change societal valuations of exertion—and of women [109].

Some initiatives, inspired by those in other regions [110] are underway: policies have been formulated in Oman and Qatar; healthy lifestyles including exercise have been promoted in Morocco, Bahrain and Palestine [111]; some have reported success in improving physical activity in Dubai [89], and Oman [112], while others, such as school-based interventions [113, 114] in Lebanon and Tunisia did not report improvements in physical activity or reductions in screen time. A closer examination of these interventions’ successes and failures can provide useful lessons for future efforts.

Conclusions

The high levels of inactivity in the region call for considerable efforts to tackle the material and socio-cultural aspects of the cultural context that discourage physical activity. Multi-sectoral efforts are needed, including collaborations among ministries of health, sports, youth and education, as well as wider collaborations that involve sectors such as transport, environment and urban planning [16, 111, 115].

Abbreviations

ATLS: 

Arab Teens Lifestyle Study

DALYs: 

Disability Adjusted Life Years

GPAQ: 

Global Physical Activity Questionnaire

GSHS: 

Global School-based Student Health Surveys

IPAQ: 

International Physical Activity Questionnaire

KPAS: 

Kaiser Physical Activity Survey

KSA: 

Kingdom of Saudi Arabia

LASA: 

Longitudinal Aging Study Amsterdam

MESA: 

Multi-Ethnic Study of Atherosclerosis questionnaire

ODK: 

Open Data Kit

PACE+: 

Patient-Centered Assessment and Counseling for Exercise Plus Nutrition

PRISMA: 

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

SSCI: 

Social Sciences Citation Index

UAE: 

United Arab Emirates

WHO STEPS: 

World Health Organization STEPwise approach to Surveillance

WHO: 

World Health Organization

WHS: 

World Health Surveys

YRBSS: 

The Youth Risk Behavior Surveillance System

Declarations

Acknowledgements

This work was funded in part by a grant (106981–001) from the International Development Research Centre (IDRC) in Canada. The funder had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

We would like to thank Dr. Regina Guthold of the World Health Organization, for her constructive comments on a previous draft of the manuscript, and Zeina Jamaluddine for assisting with the preparation of the data extraction protocol.

Funding

This work was funded by a grant (106981–001) from the International Development Research Centre (IDRC) in Canada. The funder had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Availability of data and materials

Data were extracted from published sources. Data sharing not applicable.

Authors’ contributions

ES drafted the paper and conducted data screening, extraction, analysis and interpretation; CA conducted the search and data screening; CA and HG supervised the work and contributed to data analysis, interpretation and writing. CMO designed the analysis, supervised the work and critically reviewed the paper. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, P.O. Box 11-0236/EPHD, Riad El Solh, Beirut, Lebanon
(2)
Institute for Advanced Study, Aix-Marseille University, Marseille, France

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