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. 2020 May 31;2020:6134362. doi: 10.1155/2020/6134362

Table 1.

Descriptive characteristics of studies included in this review.

Authors, country Study population (sample size) Study design Anthropometric used Criteria Prevalence of obesity Risk factors
Al-Lahham et al. [18], Palestine Schoolchildren (N = 1320) Cross-sectional BMI percentiles CDC 15.7% Urban residence and high waist circumferences
Golshevsky et al. [30], Australia Children (N = 343) Cross-sectional BMI percentiles CDC No prevalence Watching television, obstructive sleep and sleep apnea
Gokosmanoglu et al. [26], Turkey Adolescent (N = 750) Cross-sectional BMI WHO 4% Irregular physical exercise, family history of obesity and consuming pastry foods
Chomba et al. [39], Tanzania Schoolchildren (N = 451) Cross-sectional BMI percentile WHO 12.6% Being a girl, random sleeping time and random eating habit
Baratin et al. [40], Ghanaians Adults (N = 5898) Cross-sectional BMI WHO No prevalence Negative life events and stress at work place
Baalwa et al. [10], Uganda Adults (N = 683) Cross-sectional BMI WHO 2.3% Urban residence, alcohol consumption, smoking, physical inactiveness, using vehicle for transport and richness
Addo et al. [14], Ghana Adults (N = 180) Cross-sectional BMI WHO 17.8% Being physically inactive, consumption of alcohol, being married, female, older age
Karki et al. [41], Nepal Schoolchildren (N = 575) Cross sectional BMI for age-sex WHO 7.1% Children mothers' high education level, having professional mother, consuming energy-dense food, having sedentary behaviors
Ganle et al. [11], Ghana School children (N = 285) Cross-sectional BMI WHO 21.2% Being aged 11–16, family high education level and consumption of fizzy drinks
Firouzbakht et al. [17], Iran Female (N = 680) Cross-sectional BMI WHO 51.2% Weak structural social capital
Adom et al. [9], Africa Children (N = 89468) Systematic review and meta-analysis WHO/CDC/IOTF 6.1%, 6.9%, 4% Urban residence and learning in private school
Al Kibria et al. [6], India Women (N = 647, 168) Cross-sectional BMI WHO 5.1% Older age, ever-pregnant, ever married, being muslims, high education level, wealthy and urban residence
Al-Raddadi et al. [7], Saudi Arabia Adult (N = 1419) Cross-sectional BMI WHO 34.8% No factor identified
Narciso et al. [15] Adolescent (N = ) Systematic review Genetic factors and socioeconomic factors
Sagbo et al. [27], Togo Adolescent (N = 634) Cross-sectional BMI IOTF 1.9% Watching television, medium dietary diversity score
Hu et al. [20], China Adult (N = 15364) Cross-sectional BMI WHO 7.9% Urban residence